| n_samples | confidence | feature_proportion | n_clusters | result |
|---|---|---|---|---|
| 169 | 0.001 | 0.100332 | 1 | 0.828650 |
| Name | Type | Lower bound | Upper bound | Values | Type |
|---|---|---|---|---|---|
| n_samples | range | 100 | 1000 | int | |
| confidence | choice | 0.001, 0.005, | |||
| 0.01, 0.025, | |||||
| 0.05, 0.1, | |||||
| 0.25 | |||||
| feature_propo… | range | 0 | 0.2 | float | |
| n_clusters | range | 1 | 4 | int |
| Failed | Succeeded | Running | Total |
|---|---|---|---|
| 263 | 228 | 11 | 502 |
trial_index,arm_name,trial_status,generation_method,result,n_samples,confidence,feature_proportion,n_clusters 0,0_0,COMPLETED,Sobol,0.841681424800347466330663337430,697,0.010000000000000000208166817117,0.054493993520736694335937500000,2 1,1_0,COMPLETED,Sobol,0.851505329635446228664363843563,531,0.050000000000000002775557561563,0.089709608070552351866133733438,3 2,2_0,COMPLETED,Sobol,0.848598255755672159494906736654,165,0.050000000000000002775557561563,0.133431331813335413150056751874,1 3,3_0,COMPLETED,Sobol,0.841714839442643802946975029045,970,0.005000000000000000104083408559,0.180374011769890790768400279376,1 4,4_0,COMPLETED,Sobol,0.841848498011828816345314407954,164,0.001000000000000000020816681712,0.050916207581758500533286593281,2 5,5_0,COMPLETED,Sobol,0.844855815818491673319101664674,880,0.250000000000000000000000000000,0.032522250898182392120361328125,4 6,6_0,COMPLETED,Sobol,0.841013131954422399338966442883,156,0.010000000000000000208166817117,0.064752514474093914031982421875,1 7,7_0,COMPLETED,Sobol,0.849333377886189788696924551914,743,0.005000000000000000104083408559,0.050803099945187571440108342813,4 8,8_0,COMPLETED,Sobol,0.847562401844488277902200934477,401,0.010000000000000000208166817117,0.017815119586884975433349609375,3 9,9_0,COMPLETED,Sobol,0.849433621813078465478952239209,612,0.050000000000000002775557561563,0.028564392961561681921756061797,4 10,10_0,COMPLETED,Sobol,0.861228990543656203193734199886,267,0.050000000000000002775557561563,0.136976843513548385278255636877,3 11,11_0,COMPLETED,Sobol,0.842483376215457546720699610887,903,0.001000000000000000020816681712,0.168821467645466349871696820628,4 12,12_0,COMPLETED,Sobol,0.841982156581013829743653786863,545,0.010000000000000000208166817117,0.014081121794879436839864617070,1 13,13_0,COMPLETED,Sobol,0.850736792862632373868336799205,129,0.005000000000000000104083408559,0.124128070846199992094405217813,4 14,14_0,COMPLETED,Sobol,0.848330938617302132698227978835,269,0.005000000000000000104083408559,0.022765718959271909194175265156,3 15,15_0,COMPLETED,Sobol,0.838941424132054636153554838529,218,0.001000000000000000020816681712,0.153062728978693496362240011877,1 16,16_0,COMPLETED,Sobol,0.843151669061382724734698967950,916,0.050000000000000002775557561563,0.003580087795853614807128906250,3 17,17_0,COMPLETED,Sobol,0.843218498345975175922717426147,701,0.010000000000000000208166817117,0.053518407605588437514487765156,2 18,18_0,COMPLETED,Sobol,0.848097036121228331495558450115,187,0.010000000000000000208166817117,0.168143008649349223748714621252,4 19,19_0,COMPLETED,Sobol,0.844388010826344070913762607233,856,0.005000000000000000104083408559,0.150274576433002959863216574377,2 20,20_0,COMPLETED,BoTorch,0.842048985865606280931672245060,281,0.001000000000000000020816681712,0.095511931688158177577996355012,1 21,21_0,COMPLETED,BoTorch,0.843920205834196579530726012308,462,0.001000000000000000020816681712,0.168500437375803557848996661050,1 22,22_0,COMPLETED,BoTorch,0.850436061081966121477648812288,100,0.001000000000000000020816681712,0.116121120229294508274797692593,1 23,23_0,COMPLETED,BoTorch,0.850436061081966121477648812288,100,0.001000000000000000020816681712,0.049297150296263164692689429103,1 24,24_0,COMPLETED,BoTorch,0.850436061081966121477648812288,100,0.001000000000000000020816681712,0.196277381682319645994638790398,1 25,25_0,COMPLETED,BoTorch,0.846125572225749356114476995572,514,0.001000000000000000020816681712,0.111283680291679329399379128063,1 26,26_0,FAILED,BoTorch,,1000,0.100000000000000005551115123126,0.000000000000000000000000000000,1 27,27_0,COMPLETED,BoTorch,0.838172887359240781357527794171,1000,0.001000000000000000020816681712,0.078333816082492915833235258560,1 28,28_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,1 29,29_0,FAILED,BoTorch,,100,0.001000000000000000020816681712,0.000000000000000000000000000000,1 30,30_0,COMPLETED,BoTorch,0.844454840110936633124083527946,411,0.001000000000000000020816681712,0.200000000000000011102230246252,1 31,31_0,COMPLETED,BoTorch,0.842483376215457546720699610887,1000,0.025000000000000001387778780781,0.082678555004395748451173631111,1 32,32_0,FAILED,BoTorch,,543,0.250000000000000000000000000000,0.000000000000000000000000000000,1 33,33_0,COMPLETED,BoTorch,0.836101179536873018172116189817,1000,0.050000000000000002775557561563,0.200000000000000011102230246252,1 34,34_0,COMPLETED,BoTorch,0.845290206168342939108129030501,100,0.001000000000000000020816681712,0.200000000000000011102230246252,2 35,35_0,COMPLETED,BoTorch,0.842884351923012697938020210131,1000,0.250000000000000000000000000000,0.116724986725779869556340884174,1 36,36_0,COMPLETED,BoTorch,0.844621913322417872116432135954,917,0.100000000000000005551115123126,0.039491857602488959766429132969,1 37,37_0,COMPLETED,BoTorch,0.840411668393089783535288006533,1000,0.001000000000000000020816681712,0.022693055889432149629936219526,2 38,38_0,FAILED,BoTorch,,100,0.100000000000000005551115123126,0.000000000000000000000000000000,1 39,39_0,COMPLETED,BoTorch,0.846559962575600621903504361399,491,0.001000000000000000020816681712,0.134851359300241835370570697705,1 40,40_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,2 41,41_0,COMPLETED,BoTorch,0.842249473719383856540332544682,391,0.001000000000000000020816681712,0.088530554386544446643370065431,1 42,42_0,FAILED,BoTorch,,626,0.250000000000000000000000000000,0.000000000000000000000000000000,1 43,29_0,FAILED,BoTorch,,100,0.001000000000000000020816681712,0.000000000000000000000000000000,1 44,44_0,COMPLETED,BoTorch,0.836836301667390647374134005076,988,0.050000000000000002775557561563,0.200000000000000011102230246252,2 45,45_0,COMPLETED,BoTorch,0.850135329301299869086960825371,236,0.005000000000000000104083408559,0.163511983093401397360011628734,1 46,46_0,COMPLETED,BoTorch,0.843118254419086499140689738852,947,0.001000000000000000020816681712,0.044674076127555001347602114947,1 47,47_0,COMPLETED,BoTorch,0.840612156246867359143948306155,1000,0.001000000000000000020816681712,0.150188058050470196747028239770,2 48,48_0,COMPLETED,BoTorch,0.842483376215457546720699610887,1000,0.025000000000000001387778780781,0.200000000000000011102230246252,1 49,28_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,1 50,50_0,COMPLETED,BoTorch,0.837972399505463316771169957065,1000,0.100000000000000005551115123126,0.200000000000000011102230246252,1 51,51_0,COMPLETED,BoTorch,0.843886791191900353936716783210,938,0.050000000000000002775557561563,0.200000000000000011102230246252,1 52,52_0,COMPLETED,BoTorch,0.842349717646272644344662694493,239,0.001000000000000000020816681712,0.196681510834082223793117805144,2 53,53_0,COMPLETED,BoTorch,0.847094596852340675496861877036,948,0.100000000000000005551115123126,0.200000000000000011102230246252,1 54,54_0,COMPLETED,BoTorch,0.837972399505463316771169957065,1000,0.100000000000000005551115123126,0.161267362247732248814457989283,1 55,28_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,1 56,56_0,FAILED,BoTorch,,1000,0.005000000000000000104083408559,0.000000000000000000000000000000,1 57,57_0,COMPLETED,BoTorch,0.841948741938717493127342095249,1000,0.010000000000000000208166817117,0.122306006176385206885015577427,3 58,58_0,COMPLETED,BoTorch,0.838172887359240781357527794171,1000,0.001000000000000000020816681712,0.164751269798091320994970487845,1 59,59_0,COMPLETED,BoTorch,0.838039228790055767959188415261,1000,0.001000000000000000020816681712,0.200000000000000011102230246252,3 60,60_0,COMPLETED,BoTorch,0.849299963243893452080612860300,219,0.005000000000000000104083408559,0.093164711561329383027185713217,1 61,61_0,COMPLETED,BoTorch,0.841414107661977439533984579612,929,0.001000000000000000020816681712,0.001804314210812638617775771621,1 62,62_0,FAILED,BoTorch,,922,0.001000000000000000020816681712,0.000000000000000000000000000000,1 63,63_0,FAILED,BoTorch,,680,0.010000000000000000208166817117,0.000000000000000000000000000000,1 64,64_0,COMPLETED,BoTorch,0.840511912319978682361920618860,1000,0.005000000000000000104083408559,0.199963376911347967546106474401,3 65,65_0,COMPLETED,BoTorch,0.844822401176195447725092435576,1000,0.050000000000000002775557561563,0.136985669248943897624570809057,2 66,66_0,COMPLETED,BoTorch,0.842717278711531347923369139608,1000,0.100000000000000005551115123126,0.200000000000000011102230246252,3 67,67_0,COMPLETED,BoTorch,0.839877034116349729941930490895,1000,0.010000000000000000208166817117,0.120525135066867267186196954754,2 68,68_0,COMPLETED,BoTorch,0.840812644100644934752608605777,1000,0.250000000000000000000000000000,0.200000000000000011102230246252,2 69,69_0,COMPLETED,BoTorch,0.841514351588866227338314729423,1000,0.025000000000000001387778780781,0.196387355196368795784422900397,2 70,70_0,COMPLETED,BoTorch,0.839877034116349729941930490895,1000,0.010000000000000000208166817117,0.036178118103656724258154753215,2 71,71_0,COMPLETED,BoTorch,0.837671667724797064380481970147,1000,0.001000000000000000020816681712,0.041099193598007593974941187298,3 72,72_0,COMPLETED,BoTorch,0.841480936946570001744305500324,1000,0.025000000000000001387778780781,0.200000000000000011102230246252,3 73,73_0,COMPLETED,BoTorch,0.842550205500050108931020531600,1000,0.050000000000000002775557561563,0.137913496287657311167862417278,3 74,74_0,COMPLETED,BoTorch,0.840812644100644934752608605777,1000,0.250000000000000000000000000000,0.156104640761024149320235210325,3 75,75_0,FAILED,BoTorch,,759,0.001000000000000000020816681712,0.000000000000000000000000000000,1 76,76_0,COMPLETED,BoTorch,0.842683864069235122329359910509,1000,0.100000000000000005551115123126,0.132336088654343403403501611137,2 77,77_0,FAILED,BoTorch,,798,0.001000000000000000020816681712,0.000000000000000000000000000000,2 78,78_0,COMPLETED,BoTorch,0.840411668393089783535288006533,1000,0.001000000000000000020816681712,0.200000000000000011102230246252,2 79,79_0,COMPLETED,BoTorch,0.838172887359240781357527794171,1000,0.001000000000000000020816681712,0.200000000000000011102230246252,1 80,80_0,FAILED,BoTorch,,613,0.001000000000000000020816681712,0.000000000000000000000000000000,1 81,81_0,COMPLETED,BoTorch,0.840612156246867359143948306155,1000,0.001000000000000000020816681712,0.095136665646274654051239849650,2 82,82_0,FAILED,BoTorch,,643,0.050000000000000002775557561563,0.000000000000000000000000000000,1 83,83_0,COMPLETED,BoTorch,0.842216059077087519924020853068,1000,0.025000000000000001387778780781,0.200000000000000011102230246252,4 84,84_0,COMPLETED,BoTorch,0.842149229792495068736002394871,853,0.001000000000000000020816681712,0.200000000000000011102230246252,2 85,85_0,FAILED,BoTorch,,1000,0.010000000000000000208166817117,0.000000000000000000000000000000,1 86,86_0,COMPLETED,BoTorch,0.839542887693387251957233274879,1000,0.005000000000000000104083408559,0.125480464875883351849594760097,1 87,87_0,COMPLETED,BoTorch,0.838172887359240781357527794171,1000,0.001000000000000000020816681712,0.120728018491730412775631009481,1 88,88_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,4 89,89_0,COMPLETED,BoTorch,0.839108497343535875145903446537,1000,0.001000000000000000020816681712,0.111585437177154703225490095519,3 90,90_0,FAILED,BoTorch,,736,0.001000000000000000020816681712,0.000000000000000000000000000000,1 91,91_0,FAILED,BoTorch,,742,0.025000000000000001387778780781,0.000000000000000000000000000000,1 92,92_0,COMPLETED,BoTorch,0.840946302669829948150947984686,1000,0.001000000000000000020816681712,0.102829485131717024426478701571,4 93,93_0,FAILED,BoTorch,,1000,0.005000000000000000104083408559,0.000000000000000000000000000000,3 94,94_0,FAILED,BoTorch,,1000,0.005000000000000000104083408559,0.000000000000000000000000000000,2 95,95_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,3 96,96_0,COMPLETED,BoTorch,0.840612156246867359143948306155,1000,0.001000000000000000020816681712,0.200000000000000011102230246252,4 97,97_0,FAILED,BoTorch,,639,0.001000000000000000020816681712,0.000000000000000000000000000000,1 98,98_0,FAILED,BoTorch,,1000,0.005000000000000000104083408559,0.000000000000000000000000000000,4 99,99_0,COMPLETED,BoTorch,0.836869716309686872968143234175,1000,0.001000000000000000020816681712,0.157408464426212507669688989154,4 100,100_0,COMPLETED,BoTorch,0.841915327296421267533332866151,1000,0.025000000000000001387778780781,0.121584838410418255572054135882,4 101,101_0,RUNNING,BoTorch,,990,0.050000000000000002775557561563,0.200000000000000011102230246252,1 102,102_0,COMPLETED,BoTorch,0.842416546930865095532681152690,977,0.050000000000000002775557561563,0.200000000000000011102230246252,2 103,103_0,COMPLETED,BoTorch,0.842282888361680082134341773781,978,0.025000000000000001387778780781,0.200000000000000011102230246252,2 104,104_0,COMPLETED,BoTorch,0.841881912654125041939323637052,977,0.050000000000000002775557561563,0.200000000000000011102230246252,3 105,105_0,FAILED,BoTorch,,987,0.001000000000000000020816681712,0.000000000000000000000000000000,3 106,106_0,COMPLETED,BoTorch,0.846727035787081860895852969406,985,0.001000000000000000020816681712,0.200000000000000011102230246252,4 107,107_0,COMPLETED,BoTorch,0.837671667724797064380481970147,987,0.050000000000000002775557561563,0.200000000000000011102230246252,1 108,108_0,COMPLETED,BoTorch,0.845256791526046713514119801403,974,0.010000000000000000208166817117,0.035122731151610186994815876460,2 109,88_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,4 110,110_0,COMPLETED,BoTorch,0.839977278043238517746260640706,978,0.100000000000000005551115123126,0.200000000000000011102230246252,2 111,111_0,COMPLETED,BoTorch,0.844488254753232858718092757044,974,0.025000000000000001387778780781,0.112830492604275980927930334019,3 112,112_0,COMPLETED,BoTorch,0.844755571891602885514771514863,981,0.001000000000000000020816681712,0.200000000000000011102230246252,3 113,113_0,COMPLETED,BoTorch,0.852507768904333884663060416642,670,0.010000000000000000208166817117,0.065467168958601135164698803237,2 114,114_0,COMPLETED,BoTorch,0.849868012162929842290282067552,973,0.005000000000000000104083408559,0.200000000000000011102230246252,3 115,115_0,COMPLETED,BoTorch,0.847061182210044449902852647938,677,0.010000000000000000208166817117,0.064885476415393231186534706012,1 116,116_0,COMPLETED,BoTorch,0.842015571223310055337663015962,202,0.001000000000000000020816681712,0.200000000000000011102230246252,1 117,117_0,COMPLETED,BoTorch,0.837170448090353236381133683608,899,0.001000000000000000020816681712,0.145199366594284118292534913053,1 118,118_0,COMPLETED,BoTorch,0.840779229458348709158599376678,332,0.001000000000000000020816681712,0.101228831414884881678695194296,1 119,98_0,FAILED,BoTorch,,1000,0.005000000000000000104083408559,0.000000000000000000000000000000,4 120,120_0,COMPLETED,BoTorch,0.842850937280716472344010981033,909,0.010000000000000000208166817117,0.104310504741430179476147088735,1 121,121_0,COMPLETED,BoTorch,0.838774350920573397161206230521,889,0.001000000000000000020816681712,0.009651100271967950894325127820,1 122,122_0,COMPLETED,BoTorch,0.842282888361680082134341773781,662,0.001000000000000000020816681712,0.083601222593334148514010450981,1 123,123_0,FAILED,BoTorch,,573,0.001000000000000000020816681712,0.000000000000000000000000000000,1 124,124_0,FAILED,BoTorch,,902,0.005000000000000000104083408559,0.000000000000000000000000000000,4 125,125_0,FAILED,BoTorch,,900,0.010000000000000000208166817117,0.000000000000000000000000000000,1 126,126_0,COMPLETED,BoTorch,0.851572158920038790874684764276,680,0.005000000000000000104083408559,0.200000000000000011102230246252,1 127,127_0,COMPLETED,BoTorch,0.838540448424499595958536701801,920,0.005000000000000000104083408559,0.200000000000000011102230246252,1 128,128_0,COMPLETED,BoTorch,0.845925084371971780505816695950,319,0.001000000000000000020816681712,0.200000000000000011102230246252,1 129,88_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,4 130,130_0,COMPLETED,BoTorch,0.838607277709092158168857622513,1000,0.001000000000000000020816681712,0.050536297826837009439238102004,4 131,131_0,COMPLETED,BoTorch,0.840812644100644934752608605777,1000,0.250000000000000000000000000000,0.200000000000000011102230246252,4 132,132_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,4 133,133_0,COMPLETED,BoTorch,0.840812644100644934752608605777,1000,0.250000000000000000000000000000,0.082610991424067137245401681866,4 134,134_0,FAILED,BoTorch,,682,0.001000000000000000020816681712,0.000000000000000000000000000000,1 135,135_0,FAILED,BoTorch,,1000,0.010000000000000000208166817117,0.000000000000000000000000000000,4 136,136_0,COMPLETED,BoTorch,0.842884351923012697938020210131,1000,0.250000000000000000000000000000,0.200000000000000011102230246252,1 137,137_0,FAILED,BoTorch,,653,0.250000000000000000000000000000,0.000000000000000000000000000000,1 138,131_0,COMPLETED,BoTorch,0.840812644100644934752608605777,1000,0.250000000000000000000000000000,0.200000000000000011102230246252,4 139,139_0,FAILED,BoTorch,,412,0.001000000000000000020816681712,0.000000000000000000000000000000,1 140,140_0,COMPLETED,BoTorch,0.845524108664416740310798559221,800,0.001000000000000000020816681712,0.031895402522216786955766565370,1 141,88_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,4 142,142_0,FAILED,BoTorch,,648,0.001000000000000000020816681712,0.000000000000000000000000000000,1 143,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1 144,144_0,FAILED,BoTorch,,744,0.001000000000000000020816681712,0.000000000000000000000000000000,1 145,145_0,FAILED,BoTorch,,944,0.001000000000000000020816681712,0.000000000000000000000000000000,3 146,28_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,1 147,147_0,COMPLETED,BoTorch,0.843385571557456525937368496670,827,0.250000000000000000000000000000,0.200000000000000011102230246252,4 148,135_0,FAILED,BoTorch,,1000,0.010000000000000000208166817117,0.000000000000000000000000000000,4 149,149_0,FAILED,BoTorch,,483,0.001000000000000000020816681712,0.000000000000000000000000000000,1 150,88_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,4 151,95_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,3 152,152_0,FAILED,BoTorch,,421,0.001000000000000000020816681712,0.000000000000000000000000000000,1 153,153_0,FAILED,BoTorch,,852,0.001000000000000000020816681712,0.000000000000000000000000000000,2 154,154_0,FAILED,BoTorch,,679,0.250000000000000000000000000000,0.000000000000000000000000000000,1 155,155_0,FAILED,BoTorch,,490,0.250000000000000000000000000000,0.000000000000000000000000000000,1 156,88_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,4 157,157_0,FAILED,BoTorch,,419,0.001000000000000000020816681712,0.000000000000000000000000000000,1 158,28_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,1 159,135_0,FAILED,BoTorch,,1000,0.010000000000000000208166817117,0.000000000000000000000000000000,4 160,160_0,COMPLETED,BoTorch,0.838674106993684609356876080710,1000,0.001000000000000000020816681712,0.079668850794297974005075957393,3 161,161_0,COMPLETED,BoTorch,0.843218498345975175922717426147,1000,0.005000000000000000104083408559,0.031497912163918916073068743344,4 162,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1 163,163_0,FAILED,BoTorch,,454,0.001000000000000000020816681712,0.000000000000000000000000000000,2 164,132_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,4 165,165_0,RUNNING,BoTorch,,1000,0.250000000000000000000000000000,0.140743753073893668181781890780,4 166,166_0,FAILED,BoTorch,,965,0.025000000000000001387778780781,0.000000000000000000000000000000,3 167,93_0,FAILED,BoTorch,,1000,0.005000000000000000104083408559,0.000000000000000000000000000000,3 168,168_0,FAILED,BoTorch,,1000,0.025000000000000001387778780781,0.000000000000000000000000000000,4 169,135_0,FAILED,BoTorch,,1000,0.010000000000000000208166817117,0.000000000000000000000000000000,4 170,95_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,3 171,98_0,FAILED,BoTorch,,1000,0.005000000000000000104083408559,0.000000000000000000000000000000,4 172,172_0,COMPLETED,BoTorch,0.843719717980419003922065712686,1000,0.010000000000000000208166817117,0.072570910156620455078169129592,4 173,173_0,COMPLETED,BoTorch,0.842683864069235122329359910509,1000,0.010000000000000000208166817117,0.200000000000000011102230246252,1 174,28_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,1 175,152_0,FAILED,BoTorch,,421,0.001000000000000000020816681712,0.000000000000000000000000000000,1 176,88_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,4 177,177_0,FAILED,BoTorch,,100,0.250000000000000000000000000000,0.000000000000000000000000000000,1 178,95_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,3 179,179_0,FAILED,BoTorch,,640,0.250000000000000000000000000000,0.000000000000000000000000000000,1 180,180_0,FAILED,BoTorch,,510,0.001000000000000000020816681712,0.000000000000000000000000000000,1 181,181_0,COMPLETED,BoTorch,0.838172887359240781357527794171,1000,0.001000000000000000020816681712,0.145277293813302343927773563337,1 182,132_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,4 183,88_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,4 184,184_0,COMPLETED,BoTorch,0.840612156246867359143948306155,1000,0.001000000000000000020816681712,0.079814653597244183957926111361,2 185,185_0,FAILED,BoTorch,,465,0.250000000000000000000000000000,0.000000000000000000000000000000,1 186,186_0,FAILED,BoTorch,,224,0.250000000000000000000000000000,0.000000000000000000000000000000,1 187,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1 188,188_0,COMPLETED,BoTorch,0.841748254084940028540984258143,1000,0.001000000000000000020816681712,0.058638395449828718819507145099,4 189,189_0,FAILED,BoTorch,,246,0.250000000000000000000000000000,0.000000000000000000000000000000,1 190,190_0,FAILED,BoTorch,,408,0.001000000000000000020816681712,0.000000000000000000000000000000,1 191,88_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,4 192,132_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,4 193,193_0,FAILED,BoTorch,,670,0.250000000000000000000000000000,0.000000000000000000000000000000,1 194,194_0,FAILED,BoTorch,,455,0.001000000000000000020816681712,0.000000000000000000000000000000,1 195,28_0,RUNNING,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,1 196,196_0,FAILED,BoTorch,,559,0.001000000000000000020816681712,0.000000000000000000000000000000,1 197,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1 198,198_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,3 199,95_0,RUNNING,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,3 200,200_0,FAILED,BoTorch,,424,0.001000000000000000020816681712,0.000000000000000000000000000000,1 201,177_0,FAILED,BoTorch,,100,0.250000000000000000000000000000,0.000000000000000000000000000000,1 202,40_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,2 203,85_0,FAILED,BoTorch,,1000,0.010000000000000000208166817117,0.000000000000000000000000000000,1 204,204_0,FAILED,BoTorch,,353,0.001000000000000000020816681712,0.000000000000000000000000000000,1 205,205_0,COMPLETED,BoTorch,0.858522404517659598610634930083,356,0.250000000000000000000000000000,0.010170518095815836087658645681,1 206,206_0,FAILED,BoTorch,,407,0.250000000000000000000000000000,0.000000000000000000000000000000,1 207,207_0,FAILED,BoTorch,,403,0.001000000000000000020816681712,0.000000000000000000000000000000,1 208,88_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,4 209,209_0,FAILED,BoTorch,,416,0.001000000000000000020816681712,0.000000000000000000000000000000,1 210,95_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,3 211,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1 212,198_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,3 213,132_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,4 214,214_0,FAILED,BoTorch,,1000,0.050000000000000002775557561563,0.000000000000000000000000000000,1 215,215_0,FAILED,BoTorch,,719,0.250000000000000000000000000000,0.000000000000000000000000000000,1 216,216_0,COMPLETED,BoTorch,0.846626791860193073091522819595,812,0.250000000000000000000000000000,0.200000000000000011102230246252,1 217,217_0,FAILED,BoTorch,,806,0.250000000000000000000000000000,0.000000000000000000000000000000,1 218,218_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,2 219,219_0,COMPLETED,BoTorch,0.846125572225749356114476995572,551,0.010000000000000000208166817117,0.021834769656869645881869246296,1 220,220_0,COMPLETED,BoTorch,0.845423864737527952506468409410,742,0.250000000000000000000000000000,0.148382318208447216978385085895,1 221,221_0,COMPLETED,BoTorch,0.839977278043238517746260640706,911,0.001000000000000000020816681712,0.190363033361253264352797032188,1 222,222_0,COMPLETED,BoTorch,0.840278009823904881159251090139,904,0.001000000000000000020816681712,0.072089437293909916504297541451,2 223,223_0,COMPLETED,BoTorch,0.842683864069235122329359910509,888,0.001000000000000000020816681712,0.200000000000000011102230246252,1 224,224_0,COMPLETED,BoTorch,0.839442643766498464152903125068,904,0.001000000000000000020816681712,0.049333454538326923510815902318,1 225,225_0,COMPLETED,BoTorch,0.842784107996123910133690060320,893,0.001000000000000000020816681712,0.200000000000000011102230246252,2 226,226_0,COMPLETED,BoTorch,0.838440204497610919176509014505,915,0.001000000000000000020816681712,0.200000000000000011102230246252,2 227,227_0,COMPLETED,BoTorch,0.840445083035386120151599698147,354,0.001000000000000000020816681712,0.022174112886802592459201122210,1 228,228_0,COMPLETED,BoTorch,0.842583620142346445547332223214,355,0.001000000000000000020816681712,0.200000000000000011102230246252,1 229,229_0,COMPLETED,BoTorch,0.840511912319978682361920618860,988,0.001000000000000000020816681712,0.142672710143254860559736130199,1 230,230_0,COMPLETED,BoTorch,0.850135329301299869086960825371,349,0.001000000000000000020816681712,0.015762747529365114806942926862,2 231,231_0,COMPLETED,BoTorch,0.842583620142346445547332223214,981,0.250000000000000000000000000000,0.200000000000000011102230246252,3 232,232_0,COMPLETED,BoTorch,0.839609716977979703145251733076,901,0.005000000000000000104083408559,0.091054695575964281206715611461,2 233,233_0,COMPLETED,BoTorch,0.847929962909747092503209842107,353,0.005000000000000000104083408559,0.140399676928489897109741946224,1 234,234_0,COMPLETED,BoTorch,0.840278009823904881159251090139,930,0.001000000000000000020816681712,0.200000000000000011102230246252,1 235,235_0,FAILED,BoTorch,,333,0.001000000000000000020816681712,0.000000000000000000000000000000,3 236,236_0,COMPLETED,BoTorch,0.844321181541751619725744149036,921,0.005000000000000000104083408559,0.200000000000000011102230246252,3 237,237_0,FAILED,BoTorch,,358,0.001000000000000000020816681712,0.000000000000000000000000000000,3 238,56_0,FAILED,BoTorch,,1000,0.005000000000000000104083408559,0.000000000000000000000000000000,1 239,239_0,FAILED,BoTorch,,869,0.001000000000000000020816681712,0.000000000000000000000000000000,1 240,240_0,COMPLETED,BoTorch,0.842182644434791294330011623970,974,0.250000000000000000000000000000,0.127576543277154758060376593676,4 241,241_0,COMPLETED,BoTorch,0.841146790523607412737305821793,920,0.001000000000000000020816681712,0.144808163674682910393443080466,1 242,242_0,FAILED,BoTorch,,713,0.025000000000000001387778780781,0.000000000000000000000000000000,1 243,243_0,COMPLETED,BoTorch,0.842784107996123910133690060320,348,0.001000000000000000020816681712,0.055481838679636158451202732067,4 244,244_0,COMPLETED,BoTorch,0.843185083703678950328708197048,899,0.025000000000000001387778780781,0.200000000000000011102230246252,4 245,245_0,FAILED,BoTorch,,644,0.001000000000000000020816681712,0.000000000000000000000000000000,1 246,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1 247,88_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,4 248,248_0,COMPLETED,BoTorch,0.840411668393089783535288006533,1000,0.001000000000000000020816681712,0.120948394532869235584726652633,2 249,249_0,COMPLETED,BoTorch,0.845323620810639164702138259599,690,0.250000000000000000000000000000,0.200000000000000011102230246252,4 250,132_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,4 251,132_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,4 252,252_0,FAILED,BoTorch,,1000,0.050000000000000002775557561563,0.000000000000000000000000000000,4 253,56_0,FAILED,BoTorch,,1000,0.005000000000000000104083408559,0.000000000000000000000000000000,1 254,254_0,FAILED,BoTorch,,717,0.001000000000000000020816681712,0.000000000000000000000000000000,1 255,255_0,FAILED,BoTorch,,924,0.005000000000000000104083408559,0.000000000000000000000000000000,1 256,256_0,FAILED,BoTorch,,832,0.025000000000000001387778780781,0.000000000000000000000000000000,1 257,132_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,4 258,258_0,FAILED,BoTorch,,1000,0.100000000000000005551115123126,0.000000000000000000000000000000,4 259,88_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,4 260,260_0,FAILED,BoTorch,,953,0.001000000000000000020816681712,0.000000000000000000000000000000,3 261,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1 262,262_0,COMPLETED,BoTorch,0.840812644100644934752608605777,1000,0.250000000000000000000000000000,0.155225728258488848698704032358,2 263,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1 264,264_0,FAILED,BoTorch,,523,0.001000000000000000020816681712,0.000000000000000000000000000000,1 265,56_0,FAILED,BoTorch,,1000,0.005000000000000000104083408559,0.000000000000000000000000000000,1 266,132_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,4 267,252_0,FAILED,BoTorch,,1000,0.050000000000000002775557561563,0.000000000000000000000000000000,4 268,260_0,FAILED,BoTorch,,953,0.001000000000000000020816681712,0.000000000000000000000000000000,3 269,269_0,COMPLETED,BoTorch,0.844020449761085256312753699603,901,0.050000000000000002775557561563,0.007906343953206008620671063625,3 270,56_0,FAILED,BoTorch,,1000,0.005000000000000000104083408559,0.000000000000000000000000000000,1 271,271_0,FAILED,BoTorch,,991,0.100000000000000005551115123126,0.000000000000000000000000000000,3 272,88_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,4 273,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1 274,274_0,FAILED,BoTorch,,632,0.001000000000000000020816681712,0.000000000000000000000000000000,1 275,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1 276,56_0,FAILED,BoTorch,,1000,0.005000000000000000104083408559,0.000000000000000000000000000000,1 277,277_0,FAILED,BoTorch,,893,0.005000000000000000104083408559,0.000000000000000000000000000000,1 278,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1 279,279_0,FAILED,BoTorch,,863,0.010000000000000000208166817117,0.000000000000000000000000000000,1 280,280_0,FAILED,BoTorch,,506,0.001000000000000000020816681712,0.000000000000000000000000000000,1 281,281_0,COMPLETED,BoTorch,0.853343134961740190647105919197,327,0.001000000000000000020816681712,0.200000000000000011102230246252,4 282,258_0,FAILED,BoTorch,,1000,0.100000000000000005551115123126,0.000000000000000000000000000000,4 283,132_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,4 284,284_0,FAILED,BoTorch,,643,0.001000000000000000020816681712,0.000000000000000000000000000000,1 285,285_0,FAILED,BoTorch,,538,0.001000000000000000020816681712,0.000000000000000000000000000000,4 286,286_0,FAILED,BoTorch,,560,0.001000000000000000020816681712,0.000000000000000000000000000000,1 287,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1 288,218_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,2 289,88_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,4 290,132_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,4 291,291_0,COMPLETED,BoTorch,0.844621913322417872116432135954,917,0.100000000000000005551115123126,0.039495576573283820709381330971,1 292,40_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,2 293,88_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,4 294,294_0,FAILED,BoTorch,,452,0.001000000000000000020816681712,0.000000000000000000000000000000,1 295,295_0,COMPLETED,BoTorch,0.840812644100644934752608605777,1000,0.250000000000000000000000000000,0.117482891287608026686939410865,3 296,296_0,COMPLETED,BoTorch,0.840812644100644934752608605777,1000,0.100000000000000005551115123126,0.200000000000000011102230246252,4 297,297_0,COMPLETED,BoTorch,0.843753132622715229516074941785,359,0.001000000000000000020816681712,0.024196096071949932393430060529,1 298,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1 299,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1 300,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1 301,301_0,COMPLETED,BoTorch,0.842182644434791294330011623970,1000,0.100000000000000005551115123126,0.118353408697022405293708402496,4 302,302_0,COMPLETED,BoTorch,0.840110936612423531144600019616,995,0.050000000000000002775557561563,0.200000000000000011102230246252,1 303,303_0,COMPLETED,BoTorch,0.837170448090353236381133683608,896,0.005000000000000000104083408559,0.013358932732360865106024938598,1 304,304_0,COMPLETED,BoTorch,0.845858255087379329317798237753,913,0.005000000000000000104083408559,0.200000000000000011102230246252,2 305,305_0,FAILED,BoTorch,,895,0.001000000000000000020816681712,0.000000000000000000000000000000,1 306,306_0,COMPLETED,BoTorch,0.842483376215457546720699610887,929,0.005000000000000000104083408559,0.200000000000000011102230246252,1 307,307_0,COMPLETED,BoTorch,0.840311424466201106753260319238,932,0.010000000000000000208166817117,0.200000000000000011102230246252,1 308,308_0,COMPLETED,BoTorch,0.838005814147759542365179186163,217,0.001000000000000000020816681712,0.200000000000000011102230246252,2 309,309_0,COMPLETED,BoTorch,0.838807765562869622755215459620,903,0.005000000000000000104083408559,0.200000000000000011102230246252,1 310,310_0,COMPLETED,BoTorch,0.841648010158051240736654108332,996,0.050000000000000002775557561563,0.200000000000000011102230246252,1 311,311_0,COMPLETED,BoTorch,0.842015571223310055337663015962,924,0.005000000000000000104083408559,0.200000000000000011102230246252,2 312,312_0,COMPLETED,BoTorch,0.837471179871019488771821670525,158,0.001000000000000000020816681712,0.008219790664827255136093420163,1 313,313_0,COMPLETED,BoTorch,0.837270692017241913163161370903,165,0.005000000000000000104083408559,0.140777008799616937251286685751,1 314,314_0,FAILED,BoTorch,,991,0.005000000000000000104083408559,0.000000000000000000000000000000,1 315,315_0,FAILED,BoTorch,,987,0.100000000000000005551115123126,0.000000000000000000000000000000,4 316,316_0,COMPLETED,BoTorch,0.843084839776790162524378047237,986,0.100000000000000005551115123126,0.184930903161941134760226645994,4 317,317_0,COMPLETED,BoTorch,0.830287031777324768810899513483,164,0.001000000000000000020816681712,0.084980383925100724806789287413,1 318,318_0,RUNNING,BoTorch,,165,0.005000000000000000104083408559,0.029829687685756223203270565136,1 319,319_0,COMPLETED,BoTorch,0.840445083035386120151599698147,159,0.001000000000000000020816681712,0.123440122463064183566672227244,1 320,320_0,FAILED,BoTorch,,885,0.005000000000000000104083408559,0.000000000000000000000000000000,1 321,321_0,COMPLETED,BoTorch,0.831356300330804987019917007274,168,0.001000000000000000020816681712,0.040692450743706837235080797655,1 322,322_0,FAILED,BoTorch,,874,0.001000000000000000020816681712,0.000000000000000000000000000000,3 323,323_0,COMPLETED,BoTorch,0.840511912319978682361920618860,175,0.001000000000000000020816681712,0.002339118748376654757098469517,1 324,324_0,FAILED,BoTorch,,723,0.025000000000000001387778780781,0.000000000000000000000000000000,1 325,325_0,COMPLETED,BoTorch,0.838005814147759542365179186163,156,0.005000000000000000104083408559,0.083567982087696418558309119362,1 326,326_0,FAILED,BoTorch,,861,0.001000000000000000020816681712,0.000000000000000000000000000000,4 327,327_0,COMPLETED,BoTorch,0.828649714304808382436817737471,169,0.001000000000000000020816681712,0.100332095958836395310775913003,1 328,328_0,FAILED,BoTorch,,886,0.005000000000000000104083408559,0.000000000000000000000000000000,2 329,329_0,FAILED,BoTorch,,716,0.050000000000000002775557561563,0.000000000000000000000000000000,2 330,330_0,FAILED,BoTorch,,730,0.010000000000000000208166817117,0.000000000000000000000000000000,1 331,331_0,COMPLETED,BoTorch,0.842216059077087519924020853068,986,0.100000000000000005551115123126,0.200000000000000011102230246252,1 332,332_0,FAILED,BoTorch,,877,0.010000000000000000208166817117,0.000000000000000000000000000000,1 333,333_0,COMPLETED,BoTorch,0.834363618137467843993704263994,172,0.001000000000000000020816681712,0.084898414484966266968513082247,1 334,334_0,FAILED,BoTorch,,873,0.001000000000000000020816681712,0.000000000000000000000000000000,3 335,335_0,COMPLETED,BoTorch,0.843786547265011566132386633399,889,0.005000000000000000104083408559,0.008676660294084570165806802322,3 336,336_0,COMPLETED,BoTorch,0.834363618137467843993704263994,172,0.001000000000000000020816681712,0.085852013275284078108740004609,1 337,337_0,FAILED,BoTorch,,872,0.005000000000000000104083408559,0.000000000000000000000000000000,2 338,338_0,FAILED,BoTorch,,711,0.001000000000000000020816681712,0.000000000000000000000000000000,1 339,339_0,FAILED,BoTorch,,863,0.025000000000000001387778780781,0.000000000000000000000000000000,1 340,340_0,FAILED,BoTorch,,875,0.001000000000000000020816681712,0.000000000000000000000000000000,4 341,341_0,FAILED,BoTorch,,871,0.010000000000000000208166817117,0.000000000000000000000000000000,2 342,342_0,FAILED,BoTorch,,897,0.001000000000000000020816681712,0.000000000000000000000000000000,4 343,343_0,COMPLETED,BoTorch,0.837571423797908276576151820336,171,0.001000000000000000020816681712,0.085041675570839858622207430017,1 344,344_0,FAILED,BoTorch,,852,0.050000000000000002775557561563,0.000000000000000000000000000000,1 345,345_0,FAILED,BoTorch,,871,0.025000000000000001387778780781,0.000000000000000000000000000000,1 346,346_0,FAILED,BoTorch,,859,0.001000000000000000020816681712,0.000000000000000000000000000000,1 347,347_0,COMPLETED,BoTorch,0.843686303338122778328056483588,933,0.100000000000000005551115123126,0.054333929002806674590786428780,1 348,332_0,FAILED,BoTorch,,877,0.010000000000000000208166817117,0.000000000000000000000000000000,1 349,349_0,COMPLETED,BoTorch,0.843251912988271401516726655245,851,0.025000000000000001387778780781,0.040025767910441205355009941513,1 350,350_0,COMPLETED,BoTorch,0.843385571557456525937368496670,831,0.025000000000000001387778780781,0.101709554600000778856738747891,1 351,338_0,FAILED,BoTorch,,711,0.001000000000000000020816681712,0.000000000000000000000000000000,1 352,352_0,COMPLETED,BoTorch,0.840912888027533611534636293072,853,0.025000000000000001387778780781,0.028619189780432263692233618713,1 353,353_0,FAILED,BoTorch,,873,0.005000000000000000104083408559,0.000000000000000000000000000000,1 354,354_0,FAILED,BoTorch,,732,0.010000000000000000208166817117,0.000000000000000000000000000000,1 355,355_0,RUNNING,BoTorch,,847,0.010000000000000000208166817117,0.110757259339255800800749796053,1 356,356_0,FAILED,BoTorch,,857,0.050000000000000002775557561563,0.000000000000000000000000000000,1 357,357_0,FAILED,BoTorch,,859,0.250000000000000000000000000000,0.000000000000000000000000000000,1 358,358_0,FAILED,BoTorch,,877,0.001000000000000000020816681712,0.000000000000000000000000000000,1 359,359_0,FAILED,BoTorch,,771,0.250000000000000000000000000000,0.000000000000000000000000000000,4 360,360_0,FAILED,BoTorch,,738,0.010000000000000000208166817117,0.000000000000000000000000000000,1 361,361_0,FAILED,BoTorch,,765,0.100000000000000005551115123126,0.000000000000000000000000000000,3 362,362_0,FAILED,BoTorch,,714,0.001000000000000000020816681712,0.000000000000000000000000000000,1 363,363_0,COMPLETED,BoTorch,0.842850937280716472344010981033,742,0.005000000000000000104083408559,0.055052424409314459907704986108,1 364,364_0,FAILED,BoTorch,,606,0.001000000000000000020816681712,0.000000000000000000000000000000,1 365,365_0,FAILED,BoTorch,,751,0.025000000000000001387778780781,0.000000000000000000000000000000,2 366,366_0,COMPLETED,BoTorch,0.861228990543656203193734199886,100,0.250000000000000000000000000000,0.200000000000000011102230246252,4 367,367_0,FAILED,BoTorch,,733,0.050000000000000002775557561563,0.000000000000000000000000000000,1 368,368_0,FAILED,BoTorch,,719,0.010000000000000000208166817117,0.000000000000000000000000000000,1 369,369_0,COMPLETED,BoTorch,0.846292645437230595106825603580,737,0.025000000000000001387778780781,0.038154239066357273357787960322,1 370,370_0,FAILED,BoTorch,,754,0.050000000000000002775557561563,0.000000000000000000000000000000,2 371,371_0,COMPLETED,BoTorch,0.861228990543656203193734199886,100,0.250000000000000000000000000000,0.200000000000000011102230246252,3 372,372_0,FAILED,BoTorch,,761,0.050000000000000002775557561563,0.000000000000000000000000000000,1 373,373_0,FAILED,BoTorch,,703,0.001000000000000000020816681712,0.000000000000000000000000000000,1 374,374_0,COMPLETED,BoTorch,0.834363618137467843993704263994,172,0.001000000000000000020816681712,0.090442087505985466200364442102,1 375,375_0,FAILED,BoTorch,,769,0.250000000000000000000000000000,0.000000000000000000000000000000,4 376,376_0,COMPLETED,BoTorch,0.845323620810639164702138259599,760,0.250000000000000000000000000000,0.071603655009983099843928755490,4 377,377_0,FAILED,BoTorch,,434,0.001000000000000000020816681712,0.000000000000000000000000000000,1 378,378_0,FAILED,BoTorch,,863,0.001000000000000000020816681712,0.000000000000000000000000000000,1 379,379_0,FAILED,BoTorch,,443,0.001000000000000000020816681712,0.000000000000000000000000000000,3 380,380_0,COMPLETED,BoTorch,0.844254352257159057515423228324,436,0.001000000000000000020816681712,0.000000000000000000298907180617,1 381,381_0,COMPLETED,BoTorch,0.849934841447522293478300525749,763,0.100000000000000005551115123126,0.035206496838175102559453932827,3 382,382_0,COMPLETED,BoTorch,0.846593377217896847497513590497,738,0.025000000000000001387778780781,0.036793639676769289426072617744,1 383,383_0,COMPLETED,BoTorch,0.850770207504928599462346028304,422,0.001000000000000000020816681712,0.044328048130094027667880141053,2 384,384_0,FAILED,BoTorch,,445,0.001000000000000000020816681712,0.000000000000000000000000000000,4 385,385_0,FAILED,BoTorch,,602,0.001000000000000000020816681712,0.000000000000000000000000000000,1 386,386_0,FAILED,BoTorch,,576,0.001000000000000000020816681712,0.000000000000000000000000000000,4 387,387_0,FAILED,BoTorch,,616,0.001000000000000000020816681712,0.000000000000000000000000000000,3 388,388_0,FAILED,BoTorch,,858,0.001000000000000000020816681712,0.000000000000000000000000000000,1 389,389_0,FAILED,BoTorch,,572,0.001000000000000000020816681712,0.000000000000000000000000000000,2 390,390_0,FAILED,BoTorch,,842,0.001000000000000000020816681712,0.000000000000000000000000000000,4 391,391_0,COMPLETED,BoTorch,0.851271427139372427461694314843,597,0.001000000000000000020816681712,0.031408823450167593083204309323,4 392,392_0,FAILED,BoTorch,,538,0.001000000000000000020816681712,0.000000000000000000000000000000,3 393,393_0,FAILED,BoTorch,,545,0.001000000000000000020816681712,0.000000000000000000000000000000,4 394,394_0,FAILED,BoTorch,,543,0.001000000000000000020816681712,0.000000000000000000000000000000,3 395,395_0,FAILED,BoTorch,,868,0.001000000000000000020816681712,0.000000000000000000000000000000,1 396,396_0,FAILED,BoTorch,,844,0.001000000000000000020816681712,0.000000000000000000000000000000,4 397,397_0,FAILED,BoTorch,,859,0.001000000000000000020816681712,0.000000000000000000000000000000,3 398,398_0,COMPLETED,BoTorch,0.845824840445082992701486546139,839,0.005000000000000000104083408559,0.068559442791628247282353925129,4 399,373_0,FAILED,BoTorch,,703,0.001000000000000000020816681712,0.000000000000000000000000000000,1 400,400_0,FAILED,BoTorch,,860,0.001000000000000000020816681712,0.000000000000000000000000000000,1 401,401_0,FAILED,BoTorch,,707,0.001000000000000000020816681712,0.000000000000000000000000000000,1 402,402_0,COMPLETED,BoTorch,0.854245330303739058841472342465,478,0.250000000000000000000000000000,0.200000000000000011102230246252,1 403,403_0,COMPLETED,BoTorch,0.843953620476492805124735241407,849,0.005000000000000000104083408559,0.044349552237808925747586386024,3 404,404_0,FAILED,BoTorch,,867,0.001000000000000000020816681712,0.000000000000000000000000000000,1 405,405_0,COMPLETED,BoTorch,0.844688742607010434326753056666,674,0.001000000000000000020816681712,0.009341796367090933472798752746,1 406,406_0,COMPLETED,BoTorch,0.847061182210044449902852647938,841,0.005000000000000000104083408559,0.068689304510479470833317350298,4 407,407_0,COMPLETED,BoTorch,0.846158986868045581708486224670,835,0.010000000000000000208166817117,0.200000000000000011102230246252,4 408,408_0,COMPLETED,BoTorch,0.844688742607010434326753056666,850,0.001000000000000000020816681712,0.067445689928380250788286787156,4 409,409_0,FAILED,BoTorch,,870,0.005000000000000000104083408559,0.000000000000000000000000000000,1 410,410_0,FAILED,BoTorch,,616,0.250000000000000000000000000000,0.000000000000000000000000000000,1 411,411_0,FAILED,BoTorch,,658,0.250000000000000000000000000000,0.000000000000000000000000000000,1 412,28_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,1 413,413_0,RUNNING,BoTorch,,977,0.001000000000000000020816681712,0.035353581424803895427722011391,1 414,414_0,FAILED,BoTorch,,688,0.250000000000000000000000000000,0.000000000000000000000000000000,1 415,415_0,FAILED,BoTorch,,647,0.250000000000000000000000000000,0.000000000000000000000000000000,1 416,416_0,RUNNING,BoTorch,,689,0.005000000000000000104083408559,0.088299343110396666389760866878,2 417,417_0,COMPLETED,BoTorch,0.851505329635446228664363843563,625,0.100000000000000005551115123126,0.046617598594046953663916355026,1 418,418_0,FAILED,BoTorch,,853,0.250000000000000000000000000000,0.000000000000000000000000000000,1 419,239_0,FAILED,BoTorch,,869,0.001000000000000000020816681712,0.000000000000000000000000000000,1 420,56_0,FAILED,BoTorch,,1000,0.005000000000000000104083408559,0.000000000000000000000000000000,1 421,421_0,FAILED,BoTorch,,870,0.001000000000000000020816681712,0.000000000000000000000000000000,1 422,422_0,FAILED,BoTorch,,878,0.005000000000000000104083408559,0.000000000000000000000000000000,1 423,423_0,COMPLETED,BoTorch,0.839576302335683477551242503978,997,0.001000000000000000020816681712,0.151175894104641828086244004226,2 424,424_0,COMPLETED,BoTorch,0.834363618137467843993704263994,172,0.001000000000000000020816681712,0.091518382375551154961357269713,1 425,28_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,1 426,426_0,COMPLETED,BoTorch,0.839576302335683477551242503978,896,0.001000000000000000020816681712,0.064976667097237081338612085801,1 427,427_0,FAILED,BoTorch,,882,0.010000000000000000208166817117,0.000000000000000000000000000000,1 428,428_0,COMPLETED,BoTorch,0.854746549938182886840820629004,166,0.010000000000000000208166817117,0.007916691422013058185291889401,2 429,400_0,FAILED,BoTorch,,860,0.001000000000000000020816681712,0.000000000000000000000000000000,1 430,421_0,FAILED,BoTorch,,870,0.001000000000000000020816681712,0.000000000000000000000000000000,1 431,418_0,FAILED,BoTorch,,853,0.250000000000000000000000000000,0.000000000000000000000000000000,1 432,432_0,FAILED,BoTorch,,871,0.005000000000000000104083408559,0.000000000000000000000000000000,1 433,433_0,FAILED,BoTorch,,849,0.250000000000000000000000000000,0.000000000000000000000000000000,1 434,434_0,FAILED,BoTorch,,862,0.001000000000000000020816681712,0.000000000000000000000000000000,1 435,435_0,COMPLETED,BoTorch,0.837571423797908276576151820336,171,0.001000000000000000020816681712,0.081554789913772227083477162068,1 436,436_0,COMPLETED,BoTorch,0.845256791526046713514119801403,847,0.010000000000000000208166817117,0.110796472013699159875343980275,1 437,437_0,COMPLETED,BoTorch,0.845256791526046713514119801403,846,0.005000000000000000104083408559,0.073481745543256329900039247605,1 438,438_0,COMPLETED,BoTorch,0.844621913322417872116432135954,846,0.010000000000000000208166817117,0.119762452563734994592792304502,1 439,378_0,FAILED,BoTorch,,863,0.001000000000000000020816681712,0.000000000000000000000000000000,1 440,440_0,FAILED,BoTorch,,951,0.250000000000000000000000000000,0.000000000000000000000000000000,4 441,441_0,COMPLETED,BoTorch,0.847027767567748224308843418839,474,0.001000000000000000020816681712,0.200000000000000011102230246252,4 442,442_0,FAILED,BoTorch,,859,0.050000000000000002775557561563,0.000000000000000000000000000000,1 443,443_0,COMPLETED,BoTorch,0.841280449092792426135645200702,823,0.050000000000000002775557561563,0.054795325065888779436651390142,1 444,444_0,FAILED,BoTorch,,485,0.001000000000000000020816681712,0.000000000000000000000000000000,4 445,445_0,FAILED,BoTorch,,850,0.250000000000000000000000000000,0.000000000000000000000000000000,1 446,446_0,FAILED,BoTorch,,817,0.100000000000000005551115123126,0.000000000000000000000000000000,1 447,447_0,COMPLETED,BoTorch,0.844388010826344070913762607233,791,0.025000000000000001387778780781,0.061686006754933277174135497489,1 448,448_0,FAILED,BoTorch,,865,0.250000000000000000000000000000,0.000000000000000000000000000000,1 449,449_0,COMPLETED,BoTorch,0.841213619808199974947626742505,913,0.250000000000000000000000000000,0.200000000000000011102230246252,4 450,450_0,COMPLETED,BoTorch,0.844521669395529084312101986143,826,0.100000000000000005551115123126,0.024479787667490447711227119498,1 451,451_0,COMPLETED,BoTorch,0.844889230460787898913110893773,872,0.100000000000000005551115123126,0.087459538912774192898069713920,1 452,452_0,COMPLETED,BoTorch,0.845490694022120514716789330123,874,0.250000000000000000000000000000,0.142505053436539269595684231717,1 453,453_0,COMPLETED,BoTorch,0.839843619474053504347921261797,906,0.100000000000000005551115123126,0.122111802412221512326162553563,4 454,454_0,COMPLETED,BoTorch,0.829318007150733449428514632018,170,0.001000000000000000020816681712,0.082511324772335595256755880200,1 455,455_0,FAILED,BoTorch,,948,0.250000000000000000000000000000,0.000000000000000000000000000000,4 456,456_0,FAILED,BoTorch,,872,0.001000000000000000020816681712,0.000000000000000000000000000000,2 457,457_0,COMPLETED,BoTorch,0.843853376549604017320405091596,937,0.250000000000000000000000000000,0.032865611685334965297311526911,4 458,458_0,FAILED,BoTorch,,440,0.250000000000000000000000000000,0.000000000000000000000000000000,4 459,459_0,COMPLETED,BoTorch,0.852507768904333884663060416642,483,0.250000000000000000000000000000,0.138543368017125051450122441565,2 460,132_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,4 461,461_0,RUNNING,BoTorch,,917,0.250000000000000000000000000000,0.101099448492499285889856253107,4 462,462_0,FAILED,BoTorch,,958,0.250000000000000000000000000000,0.000000000000000000000000000000,4 463,463_0,COMPLETED,BoTorch,0.855782403849366768433526431181,419,0.250000000000000000000000000000,0.200000000000000011102230246252,4 464,464_0,COMPLETED,BoTorch,0.848364353259598358292237207934,744,0.001000000000000000020816681712,0.154140333250431804668068025421,2 465,28_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,1 466,466_0,COMPLETED,BoTorch,0.838239716643833343567848714883,995,0.001000000000000000020816681712,0.039936804951470949998082460297,1 467,467_0,COMPLETED,BoTorch,0.836635813813613182787776167970,992,0.001000000000000000020816681712,0.145731579467055089027738290497,2 468,468_0,COMPLETED,BoTorch,0.843285327630567738133038346859,587,0.001000000000000000020816681712,0.200000000000000011102230246252,1 469,469_0,FAILED,BoTorch,,592,0.001000000000000000020816681712,0.000000000000000000000000000000,1 470,470_0,FAILED,BoTorch,,578,0.001000000000000000020816681712,0.000000000000000000000000000000,1 471,471_0,COMPLETED,BoTorch,0.844655327964714097710441365052,764,0.001000000000000000020816681712,0.200000000000000011102230246252,1 472,472_0,COMPLETED,BoTorch,0.842048985865606280931672245060,620,0.001000000000000000020816681712,0.059614754602420799711737231519,1 473,473_0,COMPLETED,BoTorch,0.847295084706118251105522176658,569,0.001000000000000000020816681712,0.076344581826440008343048759798,1 474,474_0,FAILED,BoTorch,,591,0.001000000000000000020816681712,0.000000000000000000000000000000,1 475,475_0,COMPLETED,BoTorch,0.844020449761085256312753699603,553,0.005000000000000000104083408559,0.016882991409375016494953669621,1 476,28_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,1 477,477_0,COMPLETED,BoTorch,0.844922645103084235529422585387,597,0.001000000000000000020816681712,0.138171192439053180933683506737,1 478,478_0,FAILED,BoTorch,,627,0.005000000000000000104083408559,0.000000000000000000000000000000,1 479,479_0,FAILED,BoTorch,,482,0.025000000000000001387778780781,0.000000000000000000000000000000,1 480,480_0,COMPLETED,BoTorch,0.848364353259598358292237207934,536,0.025000000000000001387778780781,0.093540873183005385227417605165,1 481,28_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,1 482,482_0,COMPLETED,BoTorch,0.840411668393089783535288006533,1000,0.001000000000000000020816681712,0.190977909933611328385794081441,2 483,79_0,COMPLETED,BoTorch,0.838172887359240781357527794171,1000,0.001000000000000000020816681712,0.200000000000000011102230246252,1 484,484_0,FAILED,BoTorch,,901,0.010000000000000000208166817117,0.000000000000000000000000000000,1 485,485_0,COMPLETED,BoTorch,0.843452400842048977125386954867,970,0.001000000000000000020816681712,0.054632609609757000479479671640,1 486,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1 487,487_0,FAILED,BoTorch,,933,0.001000000000000000020816681712,0.000000000000000000000000000000,4 488,56_0,FAILED,BoTorch,,1000,0.005000000000000000104083408559,0.000000000000000000000000000000,1 489,214_0,FAILED,BoTorch,,1000,0.050000000000000002775557561563,0.000000000000000000000000000000,1 490,490_0,COMPLETED,BoTorch,0.837504594513315714365830899624,901,0.010000000000000000208166817117,0.014863759215553230472184331745,1 491,491_0,FAILED,BoTorch,,934,0.001000000000000000020816681712,0.000000000000000000000000000000,4 492,492_0,FAILED,BoTorch,,1000,0.025000000000000001387778780781,0.000000000000000000000000000000,1 493,493_0,COMPLETED,BoTorch,0.842683864069235122329359910509,969,0.001000000000000000020816681712,0.041497825915564869048157703446,1 494,494_0,COMPLETED,BoTorch,0.845357035452935501318449951214,886,0.010000000000000000208166817117,0.050868498622799768194013836364,1 495,495_0,FAILED,BoTorch,,909,0.010000000000000000208166817117,0.000000000000000000000000000000,1 496,496_0,RUNNING,BoTorch,,1000,0.010000000000000000208166817117,0.089052782861047646845165104423,2 497,497_0,FAILED,BoTorch,,932,0.001000000000000000020816681712,0.000000000000000000000000000000,4 498,498_0,COMPLETED,BoTorch,0.838507033782203370364527472702,1000,0.001000000000000000020816681712,0.050592622158597444492755812462,4 499,499_0,COMPLETED,BoTorch,0.845524108664416740310798559221,842,0.010000000000000000208166817117,0.118382806633066620105587674061,1 500,500_0,COMPLETED,BoTorch,0.841079961239014961549287363596,980,0.001000000000000000020816681712,0.130073246876293596718809908452,2 501,501_0,RUNNING,BoTorch,,980,0.001000000000000000020816681712,0.130061492637200015742848790978,2
start_time,end_time,run_time,program_string,n_samples,confidence,feature_proportion,n_clusters,result,exit_code,signal,hostname,OO_Info_runtime,OO_Info_lpd 1727815916,1727815966,50,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 531 confidence 0.05 feature_proportion 0.08970960807055235 n_clusters 3,531,0.05,0.08970960807055235,3,0.8515053296354462,0,None,i7186,46,0.00018699347900403798 1727815925,1727815970,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 880 confidence 0.25 feature_proportion 0.03252225089818239 n_clusters 4,880,0.25,0.03252225089818239,4,0.8448558158184917,0,None,i7186,41,0.0004961568098534715 1727815916,1727815972,56,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 697 confidence 0.01 feature_proportion 0.054493993520736694 n_clusters 2,697,0.01,0.054493993520736694,2,0.8416814248003475,0,None,i7186,51,0.0005429879373141308 1727815926,1727815974,48,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 970 confidence 0.005 feature_proportion 0.1803740117698908 n_clusters 1,970,0.005,0.1803740117698908,1,0.8417148394426438,0,None,i7186,44,0.000696933967893302 1727815925,1727815981,56,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 165 confidence 0.05 feature_proportion 0.1334313318133354 n_clusters 1,165,0.05,0.1334313318133354,1,0.8485982557556722,0,None,i7186,52,0.00014518085963200115 1727815937,1727815983,46,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 612 confidence 0.05 feature_proportion 0.028564392961561682 n_clusters 4,612,0.05,0.028564392961561682,4,0.8494336218130785,0,None,i7181,42,0.0002564210593603856 1727815936,1727815986,50,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 267 confidence 0.05 feature_proportion 0.13697684351354839 n_clusters 3,267,0.05,0.13697684351354839,3,0.8612289905436562,0,None,i7181,45,-3.4096573771687094e-07 1727815936,1727815991,55,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 743 confidence 0.005 feature_proportion 0.05080309994518757 n_clusters 4,743,0.005,0.05080309994518757,4,0.8493333778861898,0,None,i7186,50,0.00033043368492962494 1727815937,1727815991,54,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 401 confidence 0.01 feature_proportion 0.017815119586884975 n_clusters 3,401,0.01,0.017815119586884975,3,0.8475624018444883,0,None,i7181,50,0.00022042884998658033 1727815925,1727815992,67,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 164 confidence 0.001 feature_proportion 0.0509162075817585 n_clusters 2,164,0.001,0.0509162075817585,2,0.8418484980118288,0,None,i7186,62,0.00028500724311510947 1727815937,1727815994,57,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 156 confidence 0.01 feature_proportion 0.06475251447409391 n_clusters 1,156,0.01,0.06475251447409391,1,0.8410131319544224,0,None,i7186,54,0.00025269823236542257 1727815955,1727816001,46,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 903 confidence 0.001 feature_proportion 0.16882146764546635 n_clusters 4,903,0.001,0.16882146764546635,4,0.8424833762154575,0,None,i7181,43,0.0006248538109399543 1727815955,1727816002,47,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 545 confidence 0.01 feature_proportion 0.014081121794879437 n_clusters 1,545,0.01,0.014081121794879437,1,0.8419821565810138,0,None,i7181,43,0.0004095071055881368 1727815955,1727816009,54,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 218 confidence 0.001 feature_proportion 0.1530627289786935 n_clusters 1,218,0.001,0.1530627289786935,1,0.8389414241320546,0,None,i7181,51,0.0003777553629085011 1727815955,1727816015,60,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 269 confidence 0.005 feature_proportion 0.02276571895927191 n_clusters 3,269,0.005,0.02276571895927191,3,0.8483309386173021,0,None,i7181,56,0.0001719740256847217 1727815955,1727816021,66,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 129 confidence 0.005 feature_proportion 0.12412807084619999 n_clusters 4,129,0.005,0.12412807084619999,4,0.8507367928626324,0,None,i7181,63,0.00010388314535667157 1727815972,1727816067,95,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 916 confidence 0.05 feature_proportion 0.003580087795853615 n_clusters 3,916,0.05,0.003580087795853615,3,0.8431516690613827,0,None,i7174,33,0.000583139402653985 1727815972,1727816070,98,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 856 confidence 0.005 feature_proportion 0.15027457643300296 n_clusters 2,856,0.005,0.15027457643300296,2,0.8443880108263441,0,None,i7174,36,0.0005432574102358752 1727815972,1727816070,98,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 701 confidence 0.01 feature_proportion 0.05351840760558844 n_clusters 2,701,0.01,0.05351840760558844,2,0.8432184983459752,0,None,i7174,37,0.00047396032099160596 1727815972,1727816084,112,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 187 confidence 0.01 feature_proportion 0.16814300864934922 n_clusters 4,187,0.01,0.16814300864934922,4,0.8480970361212283,0,None,i7174,50,0.00014755004969020113 1727816177,1727816182,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.1 feature_proportion 0 n_clusters 1,1000,0.1,0,1,None,1,None,i7186 1727816196,1727816200,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 100 confidence 0.001 feature_proportion 0 n_clusters 1,100,0.001,0,1,None,1,None,i7181 1727816195,1727816200,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1,1000,0.001,0,1,None,1,None,i7186 1727816196,1727816200,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 543 confidence 0.25 feature_proportion 0 n_clusters 1,543,0.25,0,1,None,1,None,i7181 1727816157,1727816219,62,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 281 confidence 0.001 feature_proportion 0.09551193168815818 n_clusters 1,281,0.001,0.09551193168815818,1,0.8420489858656063,0,None,i7186,58,0.0003196667446341654 1727816217,1727816220,3,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 100 confidence 0.1 feature_proportion 0 n_clusters 1,100,0.1,0,1,None,1,None,i7181 1727816165,1727816220,55,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 100 confidence 0.001 feature_proportion 0.11612112022929451 n_clusters 1,100,0.001,0.11612112022929451,1,0.8504360610819661,0,None,i7186,52,7.654559901907879e-05 1727816165,1727816222,57,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 462 confidence 0.001 feature_proportion 0.16850043737580356 n_clusters 1,462,0.001,0.16850043737580356,1,0.8439202058341966,0,None,i7186,53,0.00036827201509488677 1727816177,1727816232,55,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 100 confidence 0.001 feature_proportion 0.19627738168231965 n_clusters 1,100,0.001,0.19627738168231965,1,0.8504360610819661,0,None,i7186,52,7.654559901907879e-05 1727816177,1727816233,56,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 100 confidence 0.001 feature_proportion 0.049297150296263165 n_clusters 1,100,0.001,0.049297150296263165,1,0.8504360610819661,0,None,i7186,52,7.654559901907879e-05 1727816177,1727816233,56,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 514 confidence 0.001 feature_proportion 0.11128368029167933 n_clusters 1,514,0.001,0.11128368029167933,1,0.8461255722257494,0,None,i7186,53,0.0003512422864629512 1727816196,1727816239,43,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.025 feature_proportion 0.08267855500439575 n_clusters 1,1000,0.025,0.08267855500439575,1,0.8424833762154575,0,None,i7181,39,0.0006694862260070939 1727816196,1727816241,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.05 feature_proportion 0.2 n_clusters 1,1000,0.05,0.2,1,0.836101179536873,0,None,i7181,41,0.0009306596669178957 1727816195,1727816249,54,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0.07833381608249292 n_clusters 1,1000,0.001,0.07833381608249292,1,0.8381728873592408,0,None,i7186,50,0.0009222441273766169 1727816196,1727816250,54,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 411 confidence 0.001 feature_proportion 0.2 n_clusters 1,411,0.001,0.2,1,0.8444548401109366,0,None,i7181,50,0.0003106324154207338 1727816255,1727816258,3,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 100 confidence 0.001 feature_proportion 0 n_clusters 1,100,0.001,0,1,None,1,None,i7186 1727816255,1727816259,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 626 confidence 0.25 feature_proportion 0 n_clusters 1,626,0.25,0,1,None,1,None,i7186 1727816255,1727816260,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 2,1000,0.25,0,2,None,1,None,i7186 1727816217,1727816260,43,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 917 confidence 0.1 feature_proportion 0.03949185760248896 n_clusters 1,917,0.1,0.03949185760248896,1,0.8446219133224179,0,None,i7181,40,0.0005357121684270438 1727816217,1727816261,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0.11672498672577987 n_clusters 1,1000,0.25,0.11672498672577987,1,0.8428843519230127,0,None,i7181,40,0.0006551656650229844 1727816217,1727816264,47,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0.02269305588943215 n_clusters 2,1000,0.001,0.02269305588943215,2,0.8404116683930898,0,None,i7181,44,0.000771011931502459 1727816217,1727816271,54,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 491 confidence 0.001 feature_proportion 0.13485135930024184 n_clusters 1,491,0.001,0.13485135930024184,1,0.8465599625756006,0,None,i7181,50,0.0003333869992739911 1727816217,1727816282,65,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 100 confidence 0.001 feature_proportion 0.2 n_clusters 2,100,0.001,0.2,2,0.8452902061683429,0,None,i7186,62,0.00019203354669052126 1727816255,1727816312,57,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 391 confidence 0.001 feature_proportion 0.08853055438654445 n_clusters 1,391,0.001,0.08853055438654445,1,0.8422494737193839,0,None,i7186,53,0.00036499070815908464 1727816357,1727816362,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1,1000,0.001,0,1,None,1,None,i7186 1727816337,1727816388,51,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 988 confidence 0.05 feature_proportion 0.2 n_clusters 2,988,0.05,0.2,2,0.8368363016673906,0,None,i7186,47,0.0009034329213431697 1727816337,1727816392,55,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 236 confidence 0.005 feature_proportion 0.1635119830934014 n_clusters 1,236,0.005,0.1635119830934014,1,0.8501353293012999,0,None,i7186,51,0.00014407352262800507 1727816345,1727816395,50,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0.1501880580504702 n_clusters 2,1000,0.001,0.1501880580504702,2,0.8406121562468674,0,None,i7186,46,0.0007635864554366239 1727816345,1727816397,52,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 947 confidence 0.001 feature_proportion 0.044674076127555 n_clusters 1,947,0.001,0.044674076127555,1,0.8431182544190865,0,None,i7186,48,0.0006707680046136958 1727816357,1727816402,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.025 feature_proportion 0.2 n_clusters 1,1000,0.025,0.2,1,0.8424833762154575,0,None,i7186,41,0.0006694862260070939 1727816357,1727816403,46,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 938 confidence 0.05 feature_proportion 0.2 n_clusters 1,938,0.05,0.2,1,0.8438867911919004,0,None,i7186,42,0.0005780733117251978 1727816357,1727816403,46,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.1 feature_proportion 0.2 n_clusters 1,1000,0.1,0.2,1,0.8379723995054633,0,None,i7186,43,0.0008305925370783193 1727816375,1727816418,43,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 948 confidence 0.1 feature_proportion 0.2 n_clusters 1,948,0.1,0.2,1,0.8470945968523407,0,None,i7181,40,0.00047114645637718423 1727816375,1727816418,43,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.1 feature_proportion 0.16126736224773225 n_clusters 1,1000,0.1,0.16126736224773225,1,0.8379723995054633,0,None,i7181,40,0.0008305925370783193 1727816375,1727816437,62,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 239 confidence 0.001 feature_proportion 0.19668151083408222 n_clusters 2,239,0.001,0.19668151083408222,2,0.8423497176462726,0,None,i7186,59,0.0003094962770062892 1727816435,1727816440,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1,1000,0.001,0,1,None,1,None,i7186 1727816457,1727816462,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 1,1000,0.005,0,1,None,1,None,i7186 1727816465,1727816469,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 922 confidence 0.001 feature_proportion 0 n_clusters 1,922,0.001,0,1,None,1,None,i7186 1727816477,1727816481,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 680 confidence 0.01 feature_proportion 0 n_clusters 1,680,0.01,0,1,None,1,None,i7186 1727816457,1727816504,47,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.01 feature_proportion 0.1223060061763852 n_clusters 3,1000,0.01,0.1223060061763852,3,0.8419487419387175,0,None,i7186,43,0.0006885803073192387 1727816457,1727816509,52,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0.2 n_clusters 3,1000,0.001,0.2,3,0.8380392287900558,0,None,i7186,48,0.0008588800649481643 1727816457,1727816512,55,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0.16475126979809132 n_clusters 1,1000,0.001,0.16475126979809132,1,0.8381728873592408,0,None,i7186,51,0.0009222441273766169 1727816457,1727816512,55,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 219 confidence 0.005 feature_proportion 0.09316471156132938 n_clusters 1,219,0.005,0.09316471156132938,1,0.8492999632438935,0,None,i7186,51,0.00014727194197237963 1727816465,1727816517,52,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 929 confidence 0.001 feature_proportion 0.0018043142108126386 n_clusters 1,929,0.001,0.0018043142108126386,1,0.8414141076619774,0,None,i7186,48,0.0007338845511732875 1727816477,1727816527,50,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0.19996337691134797 n_clusters 3,1000,0.005,0.19996337691134797,3,0.8405119123199787,0,None,i7186,46,0.0007672991934695409 1727816555,1727816599,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.1 feature_proportion 0.2 n_clusters 3,1000,0.1,0.2,3,0.8427172787115313,0,None,i7186,41,0.0006611325654330295 1727816597,1727816601,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 759 confidence 0.001 feature_proportion 0 n_clusters 1,759,0.001,0,1,None,1,None,i7181 1727816555,1727816601,46,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.05 feature_proportion 0.1369856692489439 n_clusters 2,1000,0.05,0.1369856692489439,2,0.8448224011761954,0,None,i7186,42,0.0005859496202664576 1727816615,1727816620,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 798 confidence 0.001 feature_proportion 0 n_clusters 2,798,0.001,0,2,None,1,None,i7186 1727816577,1727816622,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0.2 n_clusters 2,1000,0.25,0.2,2,0.8408126441006449,0,None,i7186,41,0.0007291552301075473 1727816577,1727816623,46,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.025 feature_proportion 0.1963873551963688 n_clusters 2,1000,0.025,0.1963873551963688,2,0.8415143515888662,0,None,i7186,43,0.0007040942483853573 1727816577,1727816624,47,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.01 feature_proportion 0.036178118103656724 n_clusters 2,1000,0.01,0.036178118103656724,2,0.8398770341163497,0,None,i7186,43,0.0007625698724038016 1727816577,1727816625,48,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.01 feature_proportion 0.12052513506686727 n_clusters 2,1000,0.01,0.12052513506686727,2,0.8398770341163497,0,None,i7186,44,0.0007625698724038016 1727816585,1727816631,46,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.025 feature_proportion 0.2 n_clusters 3,1000,0.025,0.2,3,0.84148093694657,0,None,i7186,42,0.0007052876284673663 1727816585,1727816636,51,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0.041099193598007594 n_clusters 3,1000,0.001,0.041099193598007594,3,0.8376716677247971,0,None,i7186,46,0.0008724934377355268 1727816597,1727816638,41,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0.15610464076102415 n_clusters 3,1000,0.25,0.15610464076102415,3,0.8408126441006449,0,None,i7181,38,0.0007291552301075473 1727816597,1727816639,42,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.05 feature_proportion 0.1379134962876573 n_clusters 3,1000,0.05,0.1379134962876573,3,0.8425502055000501,0,None,i7181,39,0.0006670994658430758 1727816615,1727816660,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.1 feature_proportion 0.1323360886543434 n_clusters 2,1000,0.1,0.1323360886543434,2,0.8426838640692351,0,None,i7186,41,0.0006623259455150386 1727816697,1727816701,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 643 confidence 0.05 feature_proportion 0 n_clusters 1,643,0.05,0,1,None,1,None,i7186 1727816697,1727816701,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 613 confidence 0.001 feature_proportion 0 n_clusters 1,613,0.001,0,1,None,1,None,i7186 1727816705,1727816710,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.01 feature_proportion 0 n_clusters 1,1000,0.01,0,1,None,1,None,i7186 1727816675,1727816726,51,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0.2 n_clusters 2,1000,0.001,0.2,2,0.8404116683930898,0,None,i7186,47,0.000771011931502459 1727816675,1727816729,54,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0.2 n_clusters 1,1000,0.001,0.2,1,0.8381728873592408,0,None,i7186,50,0.0009222441273766169 1727816697,1727816743,46,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.025 feature_proportion 0.2 n_clusters 4,1000,0.025,0.2,4,0.8422160590770875,0,None,i7186,43,0.0006790332666631663 1727816697,1727816747,50,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0.09513666564627465 n_clusters 2,1000,0.001,0.09513666564627465,2,0.8406121562468674,0,None,i7186,46,0.0007635864554366239 1727816705,1727816762,57,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 853 confidence 0.001 feature_proportion 0.2 n_clusters 2,853,0.001,0.2,2,0.8421492297924951,0,None,i7186,53,0.0006814200268271843 1727816717,1727816765,48,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0.12548046487588335 n_clusters 1,1000,0.005,0.12548046487588335,1,0.8395428876933873,0,None,i7186,44,0.0008031889944544067 1727816717,1727816771,54,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0.12072801849173041 n_clusters 1,1000,0.001,0.12072801849173041,1,0.8381728873592408,0,None,i7186,50,0.0009222441273766169 1727816795,1727816800,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4,1000,0.001,0,4,None,1,None,i7186 1727816818,1727816822,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 736 confidence 0.001 feature_proportion 0 n_clusters 1,736,0.001,0,1,None,1,None,i7186 1727816825,1727816830,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 742 confidence 0.025 feature_proportion 0 n_clusters 1,742,0.025,0,1,None,1,None,i7186 1727816837,1727816842,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 2,1000,0.005,0,2,None,1,None,i7186 1727816837,1727816842,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 3,1000,0.005,0,3,None,1,None,i7186 1727816855,1727816860,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 639 confidence 0.001 feature_proportion 0 n_clusters 1,639,0.001,0,1,None,1,None,i7186 1727816856,1727816860,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 3,1000,0.001,0,3,None,1,None,i7186 1727816817,1727816869,52,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0.1115854371771547 n_clusters 3,1000,0.001,0.1115854371771547,3,0.8391084973435359,0,None,i7186,49,0.0008192775259303815 1727816825,1727816876,51,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0.10282948513171702 n_clusters 4,1000,0.001,0.10282948513171702,4,0.84094630266983,0,None,i7186,47,0.000751210661993567 1727816877,1727816882,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 4,1000,0.005,0,4,None,1,None,i7186 1727816856,1727816904,48,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0.2 n_clusters 4,1000,0.001,0.2,4,0.8406121562468674,0,None,i7186,44,0.0007363155105996015 1727816877,1727816921,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.025 feature_proportion 0.12158483841041826 n_clusters 4,1000,0.025,0.12158483841041826,4,0.8419153272964213,0,None,i7186,40,0.0006897736874012477 1727816877,1727816928,51,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0.1574084644262125 n_clusters 4,1000,0.001,0.1574084644262125,4,0.8368697163096869,0,None,i7186,47,0.0009021953419988641 1727817177,1727817182,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 987 confidence 0.001 feature_proportion 0 n_clusters 3,987,0.001,0,3,None,1,None,i7186 1727817156,1727817201,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 978 confidence 0.025 feature_proportion 0.2 n_clusters 2,978,0.025,0.2,2,0.8422828883616801,0,None,i7186,41,0.0006533138683440051 1727817156,1727817201,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 977 confidence 0.05 feature_proportion 0.2 n_clusters 2,977,0.05,0.2,2,0.8424165469308651,0,None,i7186,41,0.0006487049521652115 1727817197,1727817202,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4,1000,0.001,0,4,None,1,None,i7186 1727817156,1727817203,47,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 990 confidence 0.05 feature_proportion 0.2 n_clusters 1,990,0.05,0.2,1,0.8373375213018345,0,None,i7186,43,0.0008532667586364913 1727817177,1727817221,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 977 confidence 0.05 feature_proportion 0.2 n_clusters 3,977,0.05,0.2,3,0.841881912654125,0,None,i7186,41,0.0006671406168803858 1727817177,1727817229,52,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 985 confidence 0.001 feature_proportion 0.2 n_clusters 4,985,0.001,0.2,4,0.8467270357870819,0,None,i7186,49,0.0005371094354286794 1727817186,1727817231,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 987 confidence 0.05 feature_proportion 0.2 n_clusters 1,987,0.05,0.2,1,0.8376716677247971,0,None,i7181,41,0.0008413329578164008 1727817186,1727817231,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 974 confidence 0.01 feature_proportion 0.03512273115161019 n_clusters 2,974,0.01,0.03512273115161019,2,0.8452567915260467,0,None,i7181,41,0.00057043567920034 1727817216,1727817262,46,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 978 confidence 0.1 feature_proportion 0.2 n_clusters 2,978,0.1,0.2,2,0.8399772780432385,0,None,i7186,41,0.000732817672428196 1727817216,1727817266,50,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 974 confidence 0.025 feature_proportion 0.11283049260427598 n_clusters 3,974,0.025,0.11283049260427598,3,0.8444882547532329,0,None,i7186,46,0.000597883421086549 1727817216,1727817270,54,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 981 confidence 0.001 feature_proportion 0.2 n_clusters 3,981,0.001,0.2,3,0.8447555718916029,0,None,i7186,50,0.0006101266167427155 1727817237,1727817285,48,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 677 confidence 0.01 feature_proportion 0.06488547641539323 n_clusters 1,677,0.01,0.06488547641539323,1,0.8470611822100444,0,None,i7186,44,0.0003541952083402945 1727817237,1727817287,50,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 973 confidence 0.005 feature_proportion 0.2 n_clusters 3,973,0.005,0.2,3,0.8498680121629298,0,None,i7186,46,0.0004057492278830873 1727817237,1727817287,50,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 670 confidence 0.01 feature_proportion 0.06546716895860114 n_clusters 2,670,0.01,0.06546716895860114,2,0.8525077689043339,0,None,i7186,46,0.00021803054098305867 1727817437,1727817442,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 4,1000,0.005,0,4,None,1,None,i7186 1727817426,1727817477,51,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 899 confidence 0.001 feature_proportion 0.14519936659428412 n_clusters 1,899,0.001,0.14519936659428412,1,0.8371704480903532,0,None,i7186,48,0.0008592336590465375 1727817417,1727817478,61,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 202 confidence 0.001 feature_proportion 0.2 n_clusters 1,202,0.001,0.2,1,0.84201557122331,0,None,i7186,57,0.00032565117492112163 1727817477,1727817481,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 573 confidence 0.001 feature_proportion 0 n_clusters 1,573,0.001,0,1,None,1,None,i7186 1727817477,1727817482,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 902 confidence 0.005 feature_proportion 0 n_clusters 4,902,0.005,0,4,None,1,None,i7186 1727817478,1727817482,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 900 confidence 0.01 feature_proportion 0 n_clusters 1,900,0.01,0,1,None,1,None,i7181 1727817437,1727817501,64,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 332 confidence 0.001 feature_proportion 0.10122883141488488 n_clusters 1,332,0.001,0.10122883141488488,1,0.8407792294583487,0,None,i7186,60,0.0004260366892772412 1727817456,1727817506,50,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 889 confidence 0.001 feature_proportion 0.009651100271967951 n_clusters 1,889,0.001,0.009651100271967951,1,0.8387743509205734,0,None,i7186,46,0.0007742979180373391 1727817456,1727817506,50,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 909 confidence 0.01 feature_proportion 0.10431050474143018 n_clusters 1,909,0.01,0.10431050474143018,1,0.8428509372807165,0,None,i7186,46,0.0006337259745841315 1727817456,1727817509,53,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 662 confidence 0.001 feature_proportion 0.08360122259333415 n_clusters 1,662,0.001,0.08360122259333415,1,0.8422828883616801,0,None,i7186,49,0.0005120568157290851 1727817478,1727817528,50,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 680 confidence 0.005 feature_proportion 0.2 n_clusters 1,680,0.005,0.2,1,0.8515721589200388,0,None,i7181,47,0.0002691233352509121 1727817486,1727817537,51,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 920 confidence 0.005 feature_proportion 0.2 n_clusters 1,920,0.005,0.2,1,0.8385404484244996,0,None,i7186,47,0.0008103050756841645 1727817497,1727817557,60,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 319 confidence 0.001 feature_proportion 0.2 n_clusters 1,319,0.001,0.2,1,0.8459250843719718,0,None,i7186,57,0.00028875294663555513 1727817606,1727817611,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4,1000,0.001,0,4,None,1,None,i7186 1727817636,1727817641,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4,1000,0.25,0,4,None,1,None,i7186 1727817657,1727817661,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 682 confidence 0.001 feature_proportion 0 n_clusters 1,682,0.001,0,1,None,1,None,i7186 1727817657,1727817662,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.01 feature_proportion 0 n_clusters 4,1000,0.01,0,4,None,1,None,i7186 1727817617,1727817669,52,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0.05053629782683701 n_clusters 4,1000,0.001,0.05053629782683701,4,0.8386072777090922,0,None,i7186,48,0.0008378412160949667 1727817666,1727817670,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 653 confidence 0.25 feature_proportion 0 n_clusters 1,653,0.25,0,1,None,1,None,i7186 1727817636,1727817680,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0.2 n_clusters 4,1000,0.25,0.2,4,0.8408126441006449,0,None,i7186,40,0.0007291552301075473 1727817637,1727817682,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0.08261099142406714 n_clusters 4,1000,0.25,0.08261099142406714,4,0.8408126441006449,0,None,i7186,41,0.0007291552301075473 1727817696,1727817700,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 412 confidence 0.001 feature_proportion 0 n_clusters 1,412,0.001,0,1,None,1,None,i7186 1727817666,1727817711,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0.2 n_clusters 1,1000,0.25,0.2,1,0.8428843519230127,0,None,i7186,40,0.0006551656650229844 1727817677,1727817722,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0.2 n_clusters 4,1000,0.25,0.2,4,0.8408126441006449,0,None,i7186,41,0.0007291552301075473 1727817696,1727817745,49,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 800 confidence 0.001 feature_proportion 0.03189540252221679 n_clusters 1,800,0.001,0.03189540252221679,1,0.8455241086644167,0,None,i7186,44,0.00047590551149210577 1727817832,1727817837,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4,1000,0.001,0,4,None,1,None,i7186 1727817846,1727817851,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 648 confidence 0.001 feature_proportion 0 n_clusters 1,648,0.001,0,1,None,1,None,i7186 1727817872,1727817877,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 744 confidence 0.001 feature_proportion 0 n_clusters 1,744,0.001,0,1,None,1,None,i7186 1727817872,1727817877,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 944 confidence 0.001 feature_proportion 0 n_clusters 3,944,0.001,0,3,None,1,None,i7186 1727817872,1727817877,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1,1000,0.25,0,1,None,1,None,i7186 1727817892,1727817897,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1,1000,0.001,0,1,None,1,None,i7186 1727817908,1727817912,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 483 confidence 0.001 feature_proportion 0 n_clusters 1,483,0.001,0,1,None,1,None,i7186 1727817908,1727817913,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.01 feature_proportion 0 n_clusters 4,1000,0.01,0,4,None,1,None,i7186 1727817892,1727817936,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 827 confidence 0.25 feature_proportion 0.2 n_clusters 4,827,0.25,0.2,4,0.8433855715574565,0,None,i7186,40,0.0005098119710342789 1727817932,1727817936,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 421 confidence 0.001 feature_proportion 0 n_clusters 1,421,0.001,0,1,None,1,None,i7186 1727817932,1727817937,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 3,1000,0.001,0,3,None,1,None,i7186 1727817932,1727817937,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4,1000,0.001,0,4,None,1,None,i7186 1727817952,1727817956,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 679 confidence 0.25 feature_proportion 0 n_clusters 1,679,0.25,0,1,None,1,None,i7186 1727817952,1727817957,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 852 confidence 0.001 feature_proportion 0 n_clusters 2,852,0.001,0,2,None,1,None,i7186 1727817967,1727817971,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 490 confidence 0.25 feature_proportion 0 n_clusters 1,490,0.25,0,1,None,1,None,i7186 1727818130,1727818135,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4,1000,0.001,0,4,None,1,None,i7186 1727818147,1727818151,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 419 confidence 0.001 feature_proportion 0 n_clusters 1,419,0.001,0,1,None,1,None,i7186 1727818150,1727818155,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1,1000,0.001,0,1,None,1,None,i7186 1727818170,1727818175,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.01 feature_proportion 0 n_clusters 4,1000,0.01,0,4,None,1,None,i7186 1727818190,1727818195,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1,1000,0.25,0,1,None,1,None,i7186 1727818207,1727818211,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 454 confidence 0.001 feature_proportion 0 n_clusters 2,454,0.001,0,2,None,1,None,i7186 1727818207,1727818211,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4,1000,0.25,0,4,None,1,None,i7186 1727818170,1727818222,52,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0.07966885079429797 n_clusters 3,1000,0.001,0.07966885079429797,3,0.8386741069936846,0,None,i7186,48,0.0008353660574063553 1727818177,1727818222,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0.031497912163918916 n_clusters 4,1000,0.005,0.031497912163918916,4,0.8432184983459752,0,None,i7186,42,0.0006432318642028938 1727818230,1727818235,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 3,1000,0.005,0,3,None,1,None,i7186 1727818230,1727818235,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 965 confidence 0.025 feature_proportion 0 n_clusters 3,965,0.025,0,3,None,1,None,i7186 1727818250,1727818255,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.025 feature_proportion 0 n_clusters 4,1000,0.025,0,4,None,1,None,i7186 1727818267,1727818272,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.01 feature_proportion 0 n_clusters 4,1000,0.01,0,4,None,1,None,i7186 1727818267,1727818272,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 3,1000,0.001,0,3,None,1,None,i7186 1727818270,1727818275,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 4,1000,0.005,0,4,None,1,None,i7186 1727818230,1727818277,47,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0.14074375307389367 n_clusters 4,1000,0.25,0.14074375307389367,4,0.8408126441006449,0,None,i7186,42,0.0007291552301075473 1727818290,1727818335,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.01 feature_proportion 0.07257091015662046 n_clusters 4,1000,0.01,0.07257091015662046,4,0.843719717980419,0,None,i7186,41,0.0006253311629727572 1727818297,1727818345,48,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.01 feature_proportion 0.2 n_clusters 1,1000,0.01,0.2,1,0.8426838640692351,0,None,i7186,44,0.0006868565360896696 1727818447,1727818452,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1,1000,0.001,0,1,None,1,None,i7186 1727818470,1727818474,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 421 confidence 0.001 feature_proportion 0 n_clusters 1,421,0.001,0,1,None,1,None,i7186 1727818470,1727818475,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4,1000,0.001,0,4,None,1,None,i7186 1727818477,1727818480,3,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 100 confidence 0.25 feature_proportion 0 n_clusters 1,100,0.25,0,1,None,1,None,i7186 1727818490,1727818495,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 3,1000,0.001,0,3,None,1,None,i7186 1727818507,1727818511,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 510 confidence 0.001 feature_proportion 0 n_clusters 1,510,0.001,0,1,None,1,None,i7186 1727818507,1727818512,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 640 confidence 0.25 feature_proportion 0 n_clusters 1,640,0.25,0,1,None,1,None,i7186 1727818530,1727818535,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4,1000,0.25,0,4,None,1,None,i7186 1727818537,1727818542,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4,1000,0.001,0,4,None,1,None,i7186 1727818567,1727818571,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 224 confidence 0.25 feature_proportion 0 n_clusters 1,224,0.25,0,1,None,1,None,i7186 1727818567,1727818571,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 465 confidence 0.25 feature_proportion 0 n_clusters 1,465,0.25,0,1,None,1,None,i7186 1727818530,1727818585,55,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0.14527729381330234 n_clusters 1,1000,0.001,0.14527729381330234,1,0.8381728873592408,0,None,i7186,51,0.0009222441273766169 1727818590,1727818596,6,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1,1000,0.25,0,1,None,1,None,i7186 1727818550,1727818599,49,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0.07981465359724418 n_clusters 2,1000,0.001,0.07981465359724418,2,0.8406121562468674,0,None,i7186,45,0.0007635864554366239 1727818597,1727818601,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 246 confidence 0.25 feature_proportion 0 n_clusters 1,246,0.25,0,1,None,1,None,i7186 1727818590,1727818642,52,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0.05863839544982872 n_clusters 4,1000,0.001,0.05863839544982872,4,0.84174825408494,0,None,i7186,48,0.0007215087577302297 1727818777,1727818781,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 408 confidence 0.001 feature_proportion 0 n_clusters 1,408,0.001,0,1,None,1,None,i7186 1727818790,1727818795,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4,1000,0.001,0,4,None,1,None,i7186 1727818807,1727818812,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4,1000,0.25,0,4,None,1,None,i7186 1727818810,1727818814,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 670 confidence 0.25 feature_proportion 0 n_clusters 1,670,0.25,0,1,None,1,None,i7186 1727818830,1727818834,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 455 confidence 0.001 feature_proportion 0 n_clusters 1,455,0.001,0,1,None,1,None,i7186 1727818837,1727818842,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1,1000,0.001,0,1,None,1,None,i7186 1727818850,1727818854,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 559 confidence 0.001 feature_proportion 0 n_clusters 1,559,0.001,0,1,None,1,None,i7186 1727818867,1727818872,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 3,1000,0.25,0,3,None,1,None,i7186 1727818867,1727818872,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1,1000,0.25,0,1,None,1,None,i7186 1727818890,1727818894,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 424 confidence 0.001 feature_proportion 0 n_clusters 1,424,0.001,0,1,None,1,None,i7186 1727818890,1727818895,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 3,1000,0.001,0,3,None,1,None,i7186 1727818897,1727818900,3,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 100 confidence 0.25 feature_proportion 0 n_clusters 1,100,0.25,0,1,None,1,None,i7186 1727818910,1727818915,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 2,1000,0.25,0,2,None,1,None,i7186 1727818927,1727818932,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.01 feature_proportion 0 n_clusters 1,1000,0.01,0,1,None,1,None,i7186 1727818950,1727818954,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 353 confidence 0.001 feature_proportion 0 n_clusters 1,353,0.001,0,1,None,1,None,i7186 1727818958,1727818962,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 407 confidence 0.25 feature_proportion 0 n_clusters 1,407,0.25,0,1,None,1,None,i7186 1727818950,1727818997,47,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 356 confidence 0.25 feature_proportion 0.010170518095815836 n_clusters 1,356,0.25,0.010170518095815836,1,0.8585224045176596,0,None,i7186,43,3.5150467870085774e-05 1727819138,1727819143,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 403 confidence 0.001 feature_proportion 0 n_clusters 1,403,0.001,0,1,None,1,None,i7186 1727819144,1727819149,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4,1000,0.001,0,4,None,1,None,i7186 1727819164,1727819168,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 416 confidence 0.001 feature_proportion 0 n_clusters 1,416,0.001,0,1,None,1,None,i7186 1727819168,1727819172,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 3,1000,0.001,0,3,None,1,None,i7186 1727819184,1727819189,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1,1000,0.25,0,1,None,1,None,i7186 1727819198,1727819202,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 3,1000,0.25,0,3,None,1,None,i7186 1727819204,1727819209,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4,1000,0.25,0,4,None,1,None,i7186 1727819224,1727819229,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.05 feature_proportion 0 n_clusters 1,1000,0.05,0,1,None,1,None,i7186 1727819228,1727819232,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 719 confidence 0.25 feature_proportion 0 n_clusters 1,719,0.25,0,1,None,1,None,i7186 1727819258,1727819262,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 806 confidence 0.25 feature_proportion 0 n_clusters 1,806,0.25,0,1,None,1,None,i7186 1727819264,1727819269,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 2,1000,0.001,0,2,None,1,None,i7186 1727819244,1727819290,46,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 812 confidence 0.25 feature_proportion 0.2 n_clusters 1,812,0.25,0.2,1,0.8466267918601931,0,None,i7186,42,0.00042947643186656186 1727819287,1727819331,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 742 confidence 0.25 feature_proportion 0.14838231820844722 n_clusters 1,742,0.25,0.14838231820844722,1,0.845423864737528,0,None,i7186,40,0.00040525963605457055 1727819284,1727819334,50,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 551 confidence 0.01 feature_proportion 0.021834769656869646 n_clusters 1,551,0.01,0.021834769656869646,1,0.8461255722257494,0,None,i7186,46,0.0003283351808240631 1727819558,1727819615,57,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 911 confidence 0.001 feature_proportion 0.19036303336125326 n_clusters 1,911,0.001,0.19036303336125326,1,0.8399772780432385,0,None,i7186,51,0.0008173735577083725 1727819582,1727819632,50,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 888 confidence 0.001 feature_proportion 0.2 n_clusters 1,888,0.001,0.2,1,0.8426838640692351,0,None,i7186,46,0.0006394871198076235 1727819582,1727819632,50,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 904 confidence 0.001 feature_proportion 0.07208943729390992 n_clusters 2,904,0.001,0.07208943729390992,2,0.8402780098239049,0,None,i7186,46,0.0007224476110259105 1727819588,1727819639,51,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 904 confidence 0.001 feature_proportion 0.049333454538326924 n_clusters 1,904,0.001,0.049333454538326924,1,0.8394426437664985,0,None,i7186,48,0.0007780838134699193 1727819602,1727819662,60,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 893 confidence 0.001 feature_proportion 0.2 n_clusters 2,893,0.001,0.2,2,0.8427841079961239,0,None,i7186,56,0.0007094185595204739 1727819618,1727819670,52,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 915 confidence 0.001 feature_proportion 0.2 n_clusters 2,915,0.001,0.2,2,0.8384402044976109,0,None,i7186,49,0.0008138852159301917 1727819618,1727819679,61,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 354 confidence 0.001 feature_proportion 0.022174112886802592 n_clusters 1,354,0.001,0.022174112886802592,1,0.8404450830353861,0,None,i7186,57,0.0004156781501654028 1727819642,1727819695,53,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 988 confidence 0.001 feature_proportion 0.14267271014325486 n_clusters 1,988,0.001,0.14267271014325486,1,0.8405119123199787,0,None,i7186,49,0.0008286831289471042 1727819642,1727819704,62,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 355 confidence 0.001 feature_proportion 0.2 n_clusters 1,355,0.001,0.2,1,0.8425836201423464,0,None,i7186,57,0.00036559549806489887 1727819678,1727819722,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 981 confidence 0.25 feature_proportion 0.2 n_clusters 3,981,0.25,0.2,3,0.8425836201423464,0,None,i7186,41,0.0006429438069417186 1727819662,1727819725,63,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 349 confidence 0.001 feature_proportion 0.015762747529365115 n_clusters 2,349,0.001,0.015762747529365115,2,0.8501353293012999,0,None,i7186,59,0.00019810109361350695 1727819682,1727819732,50,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 901 confidence 0.005 feature_proportion 0.09105469557596428 n_clusters 2,901,0.005,0.09105469557596428,2,0.8396097169779797,0,None,i7186,46,0.0007454921919198784 1727819702,1727819760,58,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 353 confidence 0.005 feature_proportion 0.1403996769284899 n_clusters 1,353,0.005,0.1403996769284899,1,0.8479299629097471,0,None,i7186,55,0.0002509250496963994 1727819942,1727819946,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 333 confidence 0.001 feature_proportion 0 n_clusters 3,333,0.001,0,3,None,1,None,i7186 1727819948,1727819952,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 358 confidence 0.001 feature_proportion 0 n_clusters 3,358,0.001,0,3,None,1,None,i7186 1727819902,1727819959,57,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 930 confidence 0.001 feature_proportion 0.2 n_clusters 1,930,0.001,0.2,1,0.8402780098239049,0,None,i7186,48,0.0007759622488796817 1727819962,1727819967,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 1,1000,0.005,0,1,None,1,None,i7186 1727819978,1727819983,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 869 confidence 0.001 feature_proportion 0 n_clusters 1,869,0.001,0,1,None,1,None,i7186 1727819942,1727819991,49,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 921 confidence 0.005 feature_proportion 0.2 n_clusters 3,921,0.005,0.2,3,0.8443211815417516,0,None,i7186,45,0.0005830278966174014 1727820022,1727820027,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 713 confidence 0.025 feature_proportion 0 n_clusters 1,713,0.025,0,1,None,1,None,i7186 1727820002,1727820047,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 974 confidence 0.25 feature_proportion 0.12757654327715476 n_clusters 4,974,0.25,0.12757654327715476,4,0.8421826444347913,0,None,i7186,41,0.0006567705554781004 1727820002,1727820055,53,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 920 confidence 0.001 feature_proportion 0.1448081636746829 n_clusters 1,920,0.001,0.1448081636746829,1,0.8411467905236074,0,None,i7186,48,0.000743785185927733 1727820038,1727820083,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 899 confidence 0.025 feature_proportion 0.2 n_clusters 4,899,0.025,0.2,4,0.843185083703679,0,None,i7186,40,0.00056387208874929 1727820022,1727820098,76,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 348 confidence 0.001 feature_proportion 0.05548183867963616 n_clusters 4,348,0.001,0.05548183867963616,4,0.8427841079961239,0,None,i7186,72,0.00035470927976023693 1727820202,1727820210,8,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 644 confidence 0.001 feature_proportion 0 n_clusters 1,644,0.001,0,1,None,1,None,i7186 1727820218,1727820223,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1,1000,0.25,0,1,None,1,None,i7186 1727820242,1727820247,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4,1000,0.001,0,4,None,1,None,i7186 1727820278,1727820283,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4,1000,0.25,0,4,None,1,None,i7186 1727820282,1727820287,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4,1000,0.25,0,4,None,1,None,i7186 1727820248,1727820297,49,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0.12094839453286924 n_clusters 2,1000,0.001,0.12094839453286924,2,0.8404116683930898,0,None,i7186,45,0.000771011931502459 1727820302,1727820307,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.05 feature_proportion 0 n_clusters 4,1000,0.05,0,4,None,1,None,i7186 1727820262,1727820307,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 690 confidence 0.25 feature_proportion 0.2 n_clusters 4,690,0.25,0.2,4,0.8453236208106392,0,None,i7186,41,0.00037869927935754786 1727820322,1727820327,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 1,1000,0.005,0,1,None,1,None,i7186 1727820338,1727820344,6,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 717 confidence 0.001 feature_proportion 0 n_clusters 1,717,0.001,0,1,None,1,None,i7186 1727820342,1727820347,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 924 confidence 0.005 feature_proportion 0 n_clusters 1,924,0.005,0,1,None,1,None,i7186 1727820362,1727820367,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 832 confidence 0.025 feature_proportion 0 n_clusters 1,832,0.025,0,1,None,1,None,i7186 1727820562,1727820572,10,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4,1000,0.25,0,4,None,1,None,i7186 1727820578,1727820584,6,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.1 feature_proportion 0 n_clusters 4,1000,0.1,0,4,None,1,None,i7186 1727820602,1727820608,6,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4,1000,0.001,0,4,None,1,None,i7186 1727820608,1727820613,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 953 confidence 0.001 feature_proportion 0 n_clusters 3,953,0.001,0,3,None,1,None,i7186 1727820622,1727820629,7,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1,1000,0.25,0,1,None,1,None,i7186 1727820663,1727820667,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 523 confidence 0.001 feature_proportion 0 n_clusters 1,523,0.001,0,1,None,1,None,i7186 1727820663,1727820667,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1,1000,0.25,0,1,None,1,None,i7186 1727820639,1727820683,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0.15522572825848885 n_clusters 2,1000,0.25,0.15522572825848885,2,0.8408126441006449,0,None,i7186,41,0.0007291552301075473 1727820682,1727820687,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 1,1000,0.005,0,1,None,1,None,i7186 1727820699,1727820703,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4,1000,0.25,0,4,None,1,None,i7186 1727820723,1727820727,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 953 confidence 0.001 feature_proportion 0 n_clusters 3,953,0.001,0,3,None,1,None,i7186 1727820723,1727820728,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.05 feature_proportion 0 n_clusters 4,1000,0.05,0,4,None,1,None,i7186 1727820758,1727820763,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 1,1000,0.005,0,1,None,1,None,i7186 1727820763,1727820767,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 991 confidence 0.1 feature_proportion 0 n_clusters 3,991,0.1,0,3,None,1,None,i7186 1727820743,1727820787,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 901 confidence 0.05 feature_proportion 0.007906343953206009 n_clusters 3,901,0.05,0.007906343953206009,3,0.8440204497610853,0,None,i7186,41,0.0005551142187926103 1727820957,1727820962,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4,1000,0.001,0,4,None,1,None,i7186 1727820977,1727820982,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1,1000,0.25,0,1,None,1,None,i7186 1727820997,1727821001,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 632 confidence 0.001 feature_proportion 0 n_clusters 1,632,0.001,0,1,None,1,None,i7186 1727821017,1727821022,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1,1000,0.25,0,1,None,1,None,i7186 1727821029,1727821033,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 1,1000,0.005,0,1,None,1,None,i7186 1727821037,1727821041,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 893 confidence 0.005 feature_proportion 0 n_clusters 1,893,0.005,0,1,None,1,None,i7186 1727821057,1727821062,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1,1000,0.25,0,1,None,1,None,i7186 1727821077,1727821082,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 863 confidence 0.01 feature_proportion 0 n_clusters 1,863,0.01,0,1,None,1,None,i7186 1727821089,1727821093,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 506 confidence 0.001 feature_proportion 0 n_clusters 1,506,0.001,0,1,None,1,None,i7186 1727821117,1727821122,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.1 feature_proportion 0 n_clusters 4,1000,0.1,0,4,None,1,None,i7186 1727821137,1727821141,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 643 confidence 0.001 feature_proportion 0 n_clusters 1,643,0.001,0,1,None,1,None,i7186 1727821137,1727821142,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4,1000,0.25,0,4,None,1,None,i7186 1727821157,1727821161,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 538 confidence 0.001 feature_proportion 0 n_clusters 4,538,0.001,0,4,None,1,None,i7186 1727821097,1727821175,78,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 327 confidence 0.001 feature_proportion 0.2 n_clusters 4,327,0.001,0.2,4,0.8533431349617402,0,None,i7186,74,0.00015165106888299972 1727821177,1727821181,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 560 confidence 0.001 feature_proportion 0 n_clusters 1,560,0.001,0,1,None,1,None,i7186 1727821397,1727821402,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1,1000,0.25,0,1,None,1,None,i7186 1727821417,1727821422,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 2,1000,0.001,0,2,None,1,None,i7186 1727821437,1727821442,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4,1000,0.001,0,4,None,1,None,i7186 1727821449,1727821454,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4,1000,0.25,0,4,None,1,None,i7186 1727821477,1727821482,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 2,1000,0.25,0,2,None,1,None,i7186 1727821457,1727821500,43,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 917 confidence 0.1 feature_proportion 0.03949557657328382 n_clusters 1,917,0.1,0.03949557657328382,1,0.8446219133224179,0,None,i7186,40,0.0005357121684270438 1727821497,1727821502,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4,1000,0.001,0,4,None,1,None,i7186 1727821509,1727821513,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 452 confidence 0.001 feature_proportion 0 n_clusters 1,452,0.001,0,1,None,1,None,i7186 1727821569,1727821574,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1,1000,0.25,0,1,None,1,None,i7186 1727821537,1727821582,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0.11748289128760803 n_clusters 3,1000,0.25,0.11748289128760803,3,0.8408126441006449,0,None,i7186,41,0.0007291552301075473 1727821557,1727821601,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.1 feature_proportion 0.2 n_clusters 4,1000,0.1,0.2,4,0.8408126441006449,0,None,i7186,40,0.0007291552301075473 1727821597,1727821602,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1,1000,0.25,0,1,None,1,None,i7186 1727821597,1727821602,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1,1000,0.25,0,1,None,1,None,i7186 1727821557,1727821617,60,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 359 confidence 0.001 feature_proportion 0.024196096071949932 n_clusters 1,359,0.001,0.024196096071949932,1,0.8437531326227152,0,None,i7186,56,0.0003495171584188189 1727821617,1727821661,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.1 feature_proportion 0.1183534086970224 n_clusters 4,1000,0.1,0.1183534086970224,4,0.8421826444347913,0,None,i7186,40,0.0006802266467451753 1727821982,1727822027,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 995 confidence 0.05 feature_proportion 0.2 n_clusters 1,995,0.05,0.2,1,0.8401109366124235,0,None,i7186,42,0.0007542162118297383 1727822042,1727822047,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 895 confidence 0.001 feature_proportion 0 n_clusters 1,895,0.001,0,1,None,1,None,i7186 1727822002,1727822051,49,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 896 confidence 0.005 feature_proportion 0.013358932732360865 n_clusters 1,896,0.005,0.013358932732360865,1,0.8371704480903532,0,None,i7186,45,0.0008296049121828638 1727822019,1727822065,46,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 913 confidence 0.005 feature_proportion 0.2 n_clusters 2,913,0.005,0.2,2,0.8458582550873793,0,None,i7186,42,0.0005123578485425643 1727822042,1727822089,47,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 929 confidence 0.005 feature_proportion 0.2 n_clusters 1,929,0.005,0.2,1,0.8424833762154575,0,None,i7186,43,0.0006464004940758148 1727822062,1727822111,49,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 932 confidence 0.01 feature_proportion 0.2 n_clusters 1,932,0.01,0.2,1,0.8403114244662011,0,None,i7186,45,0.000747055931337684 1727822079,1727822143,64,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 217 confidence 0.001 feature_proportion 0.2 n_clusters 2,217,0.001,0.2,2,0.8380058141477595,0,None,i7186,60,0.0003686218475539157 1727822102,1727822152,50,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 903 confidence 0.005 feature_proportion 0.2 n_clusters 1,903,0.005,0.2,1,0.8388077655628696,0,None,i7186,46,0.0007731456889926408 1727822122,1727822169,47,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 996 confidence 0.05 feature_proportion 0.2 n_clusters 1,996,0.05,0.2,1,0.8416480101580512,0,None,i7186,43,0.0007052876284673654 1727822183,1727822188,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 991 confidence 0.005 feature_proportion 0 n_clusters 1,991,0.005,0,1,None,1,None,i7186 1727822140,1727822193,53,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 924 confidence 0.005 feature_proportion 0.2 n_clusters 2,924,0.005,0.2,2,0.84201557122331,0,None,i7186,50,0.0006861935471552205 1727822142,1727822201,59,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 158 confidence 0.001 feature_proportion 0.008219790664827255 n_clusters 1,158,0.001,0.008219790664827255,1,0.8374711798710195,0,None,i7186,55,0.0003712157917599491 1727822200,1727822204,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 987 confidence 0.1 feature_proportion 0 n_clusters 4,987,0.1,0,4,None,1,None,i7186 1727822162,1727822221,59,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 165 confidence 0.005 feature_proportion 0.14077700879961694 n_clusters 1,165,0.005,0.14077700879961694,1,0.8372706920172419,0,None,i7186,55,0.0003993049754402377 1727822222,1727822266,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 986 confidence 0.1 feature_proportion 0.18493090316194113 n_clusters 4,986,0.1,0.18493090316194113,4,0.8430848397767902,0,None,i7186,40,0.0006256603712712428 1727822582,1727822586,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 885 confidence 0.005 feature_proportion 0 n_clusters 1,885,0.005,0,1,None,1,None,i7186 1727822530,1727822591,61,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 164 confidence 0.001 feature_proportion 0.08498038392510072 n_clusters 1,164,0.001,0.08498038392510072,1,0.8302870317773248,0,None,i7186,57,0.0005428413818654633 1727822602,1727822607,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 874 confidence 0.001 feature_proportion 0 n_clusters 3,874,0.001,0,3,None,1,None,i7186 1727822560,1727822619,59,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 165 confidence 0.005 feature_proportion 0.029829687685756223 n_clusters 1,165,0.005,0.029829687685756223,1,0.8372706920172419,0,None,i7186,56,0.0003993049754402377 1727822560,1727822620,60,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 159 confidence 0.001 feature_proportion 0.12344012246306418 n_clusters 1,159,0.001,0.12344012246306418,1,0.8404450830353861,0,None,i7186,56,0.0003247485548167209 1727822642,1727822646,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 723 confidence 0.025 feature_proportion 0 n_clusters 1,723,0.025,0,1,None,1,None,i7186 1727822590,1727822650,60,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 168 confidence 0.001 feature_proportion 0.04069245074370684 n_clusters 1,168,0.001,0.04069245074370684,1,0.831356300330805,0,None,i7186,56,0.0005857390237813975 1727822620,1727822680,60,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 175 confidence 0.001 feature_proportion 0.0023391187483766548 n_clusters 1,175,0.001,0.0023391187483766548,1,0.8405119123199787,0,None,i7186,56,0.0003452846370612934 1727822680,1727822685,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 861 confidence 0.001 feature_proportion 0 n_clusters 4,861,0.001,0,4,None,1,None,i7186 1727822710,1727822714,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 886 confidence 0.005 feature_proportion 0 n_clusters 2,886,0.005,0,2,None,1,None,i7186 1727822662,1727822719,57,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 156 confidence 0.005 feature_proportion 0.08356798208769642 n_clusters 1,156,0.005,0.08356798208769642,1,0.8380058141477595,0,None,i7186,53,0.00032254411660967625 1727822722,1727822726,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 716 confidence 0.05 feature_proportion 0 n_clusters 2,716,0.05,0,2,None,1,None,i7186 1727822742,1727822748,6,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 730 confidence 0.01 feature_proportion 0 n_clusters 1,730,0.01,0,1,None,1,None,i7186 1727822702,1727822764,62,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 169 confidence 0.001 feature_proportion 0.1003320959588364 n_clusters 1,169,0.001,0.1003320959588364,1,0.8286497143048084,0,None,i7186,58,0.0005923504770699614 1727822762,1727822807,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 986 confidence 0.1 feature_proportion 0.2 n_clusters 1,986,0.1,0.2,1,0.8422160590770875,0,None,i7186,40,0.000655618326433402 1727823023,1727823037,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 873 confidence 0.001 feature_proportion 0 n_clusters 3,873,0.001,0,3,None,1,None,i7186 1727823023,1727823037,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 877 confidence 0.01 feature_proportion 0 n_clusters 1,877,0.01,0,1,None,1,None,i7186 1727823042,1727823047,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 872 confidence 0.005 feature_proportion 0 n_clusters 2,872,0.005,0,2,None,1,None,i7186 1727823070,1727823074,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 711 confidence 0.001 feature_proportion 0 n_clusters 1,711,0.001,0,1,None,1,None,i7186 1727823023,1727823080,57,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 889 confidence 0.005 feature_proportion 0.00867666029408457 n_clusters 3,889,0.005,0.00867666029408457,3,0.8437865472650116,0,None,i7186,43,0.0005626594606014417 1727823082,1727823087,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 863 confidence 0.025 feature_proportion 0 n_clusters 1,863,0.025,0,1,None,1,None,i7186 1727823023,1727823093,70,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 172 confidence 0.001 feature_proportion 0.08489841448496627 n_clusters 1,172,0.001,0.08489841448496627,1,0.8343636181374678,0,None,i7186,56,0.0004884613164761525 1727823040,1727823099,59,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 172 confidence 0.001 feature_proportion 0.08585201327528408 n_clusters 1,172,0.001,0.08585201327528408,1,0.8343636181374678,0,None,i7186,55,0.0004884613164761525 1727823122,1727823127,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 875 confidence 0.001 feature_proportion 0 n_clusters 4,875,0.001,0,4,None,1,None,i7186 1727823130,1727823134,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 871 confidence 0.01 feature_proportion 0 n_clusters 2,871,0.01,0,2,None,1,None,i7186 1727823142,1727823147,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 897 confidence 0.001 feature_proportion 0 n_clusters 4,897,0.001,0,4,None,1,None,i7186 1727823182,1727823187,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 852 confidence 0.05 feature_proportion 0 n_clusters 1,852,0.05,0,1,None,1,None,i7186 1727823203,1727823207,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 871 confidence 0.025 feature_proportion 0 n_clusters 1,871,0.025,0,1,None,1,None,i7186 1727823162,1727823222,60,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 171 confidence 0.001 feature_proportion 0.08504167557083986 n_clusters 1,171,0.001,0.08504167557083986,1,0.8375714237979083,0,None,i7186,56,0.00038157365718948357 1727823422,1727823427,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 859 confidence 0.001 feature_proportion 0 n_clusters 1,859,0.001,0,1,None,1,None,i7186 1727823460,1727823465,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 877 confidence 0.01 feature_proportion 0 n_clusters 1,877,0.01,0,1,None,1,None,i7186 1727823430,1727823475,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 933 confidence 0.1 feature_proportion 0.054333929002806675 n_clusters 1,933,0.1,0.054333929002806675,1,0.8436863033381228,0,None,i7186,41,0.0005847562401844485 1727823502,1727823506,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 711 confidence 0.001 feature_proportion 0 n_clusters 1,711,0.001,0,1,None,1,None,i7186 1727823462,1727823510,48,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 851 confidence 0.025 feature_proportion 0.040025767910441205 n_clusters 1,851,0.025,0.040025767910441205,1,0.8432519129882714,0,None,i7186,44,0.0005799057275930572 1727823482,1727823530,48,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 831 confidence 0.025 feature_proportion 0.10170955460000078 n_clusters 1,831,0.025,0.10170955460000078,1,0.8433855715574565,0,None,i7186,44,0.0005576068433187425 1727823542,1727823547,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 873 confidence 0.005 feature_proportion 0 n_clusters 1,873,0.005,0,1,None,1,None,i7186 1727823562,1727823567,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 732 confidence 0.01 feature_proportion 0 n_clusters 1,732,0.01,0,1,None,1,None,i7186 1727823520,1727823568,48,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 853 confidence 0.025 feature_proportion 0.028619189780432264 n_clusters 1,853,0.025,0.028619189780432264,1,0.8409128880275336,0,None,i7186,44,0.000655358145681373 1727823602,1727823607,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 857 confidence 0.05 feature_proportion 0 n_clusters 1,857,0.05,0,1,None,1,None,i7186 1727823622,1727823627,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 859 confidence 0.25 feature_proportion 0 n_clusters 1,859,0.25,0,1,None,1,None,i7186 1727823580,1727823630,50,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 847 confidence 0.01 feature_proportion 0.1107572593392558 n_clusters 1,847,0.01,0.1107572593392558,1,0.8452567915260467,0,None,i7186,45,0.0005152322263745005 1727823640,1727823645,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 877 confidence 0.001 feature_proportion 0 n_clusters 1,877,0.001,0,1,None,1,None,i7186 1727823851,1727823855,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 771 confidence 0.25 feature_proportion 0 n_clusters 4,771,0.25,0,4,None,1,None,i7186 1727823880,1727823885,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 738 confidence 0.01 feature_proportion 0 n_clusters 1,738,0.01,0,1,None,1,None,i7186 1727823903,1727823907,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 765 confidence 0.1 feature_proportion 0 n_clusters 3,765,0.1,0,3,None,1,None,i7186 1727823910,1727823915,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 714 confidence 0.001 feature_proportion 0 n_clusters 1,714,0.001,0,1,None,1,None,i7186 1727823963,1727823967,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 606 confidence 0.001 feature_proportion 0 n_clusters 1,606,0.001,0,1,None,1,None,i7186 1727823971,1727823975,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 751 confidence 0.025 feature_proportion 0 n_clusters 2,751,0.025,0,2,None,1,None,i7186 1727823940,1727823992,52,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 742 confidence 0.005 feature_proportion 0.05505242440931446 n_clusters 1,742,0.005,0.05505242440931446,1,0.8428509372807165,0,None,i7186,47,0.0005405309783217592 1727824003,1727824007,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 733 confidence 0.05 feature_proportion 0 n_clusters 1,733,0.05,0,1,None,1,None,i7186 1727823983,1727824027,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 100 confidence 0.25 feature_proportion 0.2 n_clusters 4,100,0.25,0.2,4,0.8612289905436562,0,None,i7186,40,-9.966979214140432e-05 1727824023,1727824027,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 719 confidence 0.01 feature_proportion 0 n_clusters 1,719,0.01,0,1,None,1,None,i7186 1727824083,1727824087,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 754 confidence 0.05 feature_proportion 0 n_clusters 2,754,0.05,0,2,None,1,None,i7186 1727824043,1727824088,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 737 confidence 0.025 feature_proportion 0.03815423906635727 n_clusters 1,737,0.025,0.03815423906635727,1,0.8462926454372306,0,None,i7186,42,0.0003930617133269904 1727824083,1727824127,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 100 confidence 0.25 feature_proportion 0.2 n_clusters 3,100,0.25,0.2,3,0.8612289905436562,0,None,i7186,40,-0.00010653100244276169 1727824334,1727824339,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 761 confidence 0.05 feature_proportion 0 n_clusters 1,761,0.05,0,1,None,1,None,i7186 1727824361,1727824365,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 703 confidence 0.001 feature_proportion 0 n_clusters 1,703,0.001,0,1,None,1,None,i7186 1727824414,1727824419,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 769 confidence 0.25 feature_proportion 0 n_clusters 4,769,0.25,0,4,None,1,None,i7186 1727824434,1727824438,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 434 confidence 0.001 feature_proportion 0 n_clusters 1,434,0.001,0,1,None,1,None,i7186 1727824391,1727824451,60,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 172 confidence 0.001 feature_proportion 0.09044208750598547 n_clusters 1,172,0.001,0.09044208750598547,1,0.8343636181374678,0,None,i7186,57,0.0004884613164761525 1727824451,1727824455,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 863 confidence 0.001 feature_proportion 0 n_clusters 1,863,0.001,0,1,None,1,None,i7186 1727824414,1727824458,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 760 confidence 0.25 feature_proportion 0.0716036550099831 n_clusters 4,760,0.25,0.0716036550099831,4,0.8453236208106392,0,None,i7186,40,0.0004185623613951845 1727824474,1727824478,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 443 confidence 0.001 feature_proportion 0 n_clusters 3,443,0.001,0,3,None,1,None,i7186 1727824494,1727824549,55,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 436 confidence 0.001 feature_proportion 2.9890718061719497e-19 n_clusters 1,436,0.001,0.0000000000000000003,1,0.8442543522571591,0,None,i7186,51,0.00033283604483327737 1727824514,1727824558,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 763 confidence 0.1 feature_proportion 0.0352064968381751 n_clusters 3,763,0.1,0.0352064968381751,3,0.8499348414475223,0,None,i7186,40,0.0002972144498982615 1727824534,1727824578,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 738 confidence 0.025 feature_proportion 0.03679363967676929 n_clusters 1,738,0.025,0.03679363967676929,1,0.8465933772178968,0,None,i7186,41,0.00038514771909893043 1727824554,1727824615,61,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 422 confidence 0.001 feature_proportion 0.04432804813009403 n_clusters 2,422,0.001,0.04432804813009403,2,0.8507702075049286,0,None,i7186,57,0.00021344455181076686 1727824751,1727824755,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 445 confidence 0.001 feature_proportion 0 n_clusters 4,445,0.001,0,4,None,1,None,i7186 1727824781,1727824785,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 602 confidence 0.001 feature_proportion 0 n_clusters 1,602,0.001,0,1,None,1,None,i7186 1727824794,1727824798,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 576 confidence 0.001 feature_proportion 0 n_clusters 4,576,0.001,0,4,None,1,None,i7186 1727824834,1727824838,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 616 confidence 0.001 feature_proportion 0 n_clusters 3,616,0.001,0,3,None,1,None,i7186 1727824841,1727824845,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 858 confidence 0.001 feature_proportion 0 n_clusters 1,858,0.001,0,1,None,1,None,i7186 1727824854,1727824858,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 572 confidence 0.001 feature_proportion 0 n_clusters 2,572,0.001,0,2,None,1,None,i7186 1727824894,1727824899,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 842 confidence 0.001 feature_proportion 0 n_clusters 4,842,0.001,0,4,None,1,None,i7186 1727824914,1727824918,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 538 confidence 0.001 feature_proportion 0 n_clusters 3,538,0.001,0,3,None,1,None,i7186 1727824934,1727824941,7,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 545 confidence 0.001 feature_proportion 0 n_clusters 4,545,0.001,0,4,None,1,None,i7186 1727824901,1727824958,57,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 597 confidence 0.001 feature_proportion 0.03140882345016759 n_clusters 4,597,0.001,0.03140882345016759,4,0.8512714271393724,0,None,i7186,54,0.00023708484295913686 1727824954,1727824959,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 543 confidence 0.001 feature_proportion 0 n_clusters 3,543,0.001,0,3,None,1,None,i7186 1727825231,1727825236,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 868 confidence 0.001 feature_proportion 0 n_clusters 1,868,0.001,0,1,None,1,None,i7186 1727825254,1727825259,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 844 confidence 0.001 feature_proportion 0 n_clusters 4,844,0.001,0,4,None,1,None,i7186 1727825274,1727825279,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 859 confidence 0.001 feature_proportion 0 n_clusters 3,859,0.001,0,3,None,1,None,i7186 1727825314,1727825318,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 703 confidence 0.001 feature_proportion 0 n_clusters 1,703,0.001,0,1,None,1,None,i7186 1727825292,1727825338,46,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 839 confidence 0.005 feature_proportion 0.06855944279162825 n_clusters 4,839,0.005,0.06855944279162825,4,0.845824840445083,0,None,i7186,42,0.0004530632381933289 1727825334,1727825339,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 860 confidence 0.001 feature_proportion 0 n_clusters 1,860,0.001,0,1,None,1,None,i7186 1727825351,1727825355,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 707 confidence 0.001 feature_proportion 0 n_clusters 1,707,0.001,0,1,None,1,None,i7186 1727825411,1727825415,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 867 confidence 0.001 feature_proportion 0 n_clusters 1,867,0.001,0,1,None,1,None,i7186 1727825374,1727825420,46,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 478 confidence 0.25 feature_proportion 0.2 n_clusters 1,478,0.25,0.2,1,0.8542453303037391,0,None,i7186,42,0.00011836712271046008 1727825394,1727825443,49,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 849 confidence 0.005 feature_proportion 0.044349552237808926 n_clusters 3,849,0.005,0.044349552237808926,3,0.8439536204764928,0,None,i7186,45,0.0005398553145988571 1727825434,1727825490,56,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 674 confidence 0.001 feature_proportion 0.009341796367090933 n_clusters 1,674,0.001,0.009341796367090933,1,0.8446887426070104,0,None,i7186,52,0.0004864778804895839 1727825454,1727825503,49,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 841 confidence 0.005 feature_proportion 0.06868930451047947 n_clusters 4,841,0.005,0.06868930451047947,4,0.8470611822100444,0,None,i7186,45,0.0004384406095235776 1727825474,1727825521,47,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 835 confidence 0.01 feature_proportion 0.2 n_clusters 4,835,0.01,0.2,4,0.8461589868680456,0,None,i7186,43,0.00045666677804880756 1727825494,1727825546,52,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 850 confidence 0.001 feature_proportion 0.06744568992838025 n_clusters 4,850,0.001,0.06744568992838025,4,0.8446887426070104,0,None,i7186,48,0.0005168827480201829 1727825714,1727825719,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 870 confidence 0.005 feature_proportion 0 n_clusters 1,870,0.005,0,1,None,1,None,i7186 1727825753,1727825757,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 616 confidence 0.25 feature_proportion 0 n_clusters 1,616,0.25,0,1,None,1,None,i7186 1727825771,1727825775,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 658 confidence 0.25 feature_proportion 0 n_clusters 1,658,0.25,0,1,None,1,None,i7186 1727825793,1727825798,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1,1000,0.001,0,1,None,1,None,i7186 1727825831,1727825835,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 688 confidence 0.25 feature_proportion 0 n_clusters 1,688,0.25,0,1,None,1,None,i7186 1727825853,1727825857,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 647 confidence 0.25 feature_proportion 0 n_clusters 1,647,0.25,0,1,None,1,None,i7186 1727825813,1727825866,53,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 977 confidence 0.001 feature_proportion 0.035353581424803895 n_clusters 1,977,0.001,0.035353581424803895,1,0.8441541083302704,0,None,i7186,49,0.0006829952885354363 1727825913,1727825917,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 853 confidence 0.25 feature_proportion 0 n_clusters 1,853,0.25,0,1,None,1,None,i7186 1727825873,1727825922,49,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 689 confidence 0.005 feature_proportion 0.08829934311039667 n_clusters 2,689,0.005,0.08829934311039667,2,0.846359474721823,0,None,i7186,45,0.0003717378955458282 1727825921,1727825925,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 869 confidence 0.001 feature_proportion 0 n_clusters 1,869,0.001,0,1,None,1,None,i7186 1727825891,1727825936,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 625 confidence 0.1 feature_proportion 0.046617598594046954 n_clusters 1,625,0.1,0.046617598594046954,1,0.8515053296354462,0,None,i7186,41,0.00021608135351577722 1727826131,1727826136,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 1,1000,0.005,0,1,None,1,None,i7186 1727826158,1727826163,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 870 confidence 0.001 feature_proportion 0 n_clusters 1,870,0.001,0,1,None,1,None,i7186 1727826178,1727826183,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 878 confidence 0.005 feature_proportion 0 n_clusters 1,878,0.005,0,1,None,1,None,i7186 1727826191,1727826241,50,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 997 confidence 0.001 feature_proportion 0.15117589410464183 n_clusters 2,997,0.001,0.15117589410464183,2,0.8395763023356835,0,None,i7186,46,0.000813089629208852 1727826238,1727826243,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1,1000,0.001,0,1,None,1,None,i7186 1727826218,1727826276,58,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 172 confidence 0.001 feature_proportion 0.09151838237555115 n_clusters 1,172,0.001,0.09151838237555115,1,0.8343636181374678,0,None,i7186,54,0.0004884613164761525 1727826278,1727826282,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 882 confidence 0.01 feature_proportion 0 n_clusters 1,882,0.01,0,1,None,1,None,i7186 1727826251,1727826302,51,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 896 confidence 0.001 feature_proportion 0.06497666709723708 n_clusters 1,896,0.001,0.06497666709723708,1,0.8395763023356835,0,None,i7186,47,0.0007733102931418831 1727826338,1727826343,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 860 confidence 0.001 feature_proportion 0 n_clusters 1,860,0.001,0,1,None,1,None,i7186 1727826298,1727826356,58,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 166 confidence 0.01 feature_proportion 0.007916691422013058 n_clusters 2,166,0.01,0.007916691422013058,2,0.8547465499381829,0,None,i7186,54,7.123561104915732e-05 1727826358,1727826363,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 870 confidence 0.001 feature_proportion 0 n_clusters 1,870,0.001,0,1,None,1,None,i7186 1727826371,1727826376,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 853 confidence 0.25 feature_proportion 0 n_clusters 1,853,0.25,0,1,None,1,None,i7186 1727826641,1727826646,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 862 confidence 0.001 feature_proportion 0 n_clusters 1,862,0.001,0,1,None,1,None,i7186 1727826630,1727826725,95,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 871 confidence 0.005 feature_proportion 0 n_clusters 1,871,0.005,0,1,None,1,None,i7181 1727826631,1727826725,94,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 849 confidence 0.25 feature_proportion 0 n_clusters 1,849,0.25,0,1,None,1,None,i7181 1727826671,1727826730,59,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 171 confidence 0.001 feature_proportion 0.08155478991377223 n_clusters 1,171,0.001,0.08155478991377223,1,0.8375714237979083,0,None,i7186,55,0.00038157365718948357 1727826691,1727826739,48,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 847 confidence 0.01 feature_proportion 0.11079647201369916 n_clusters 1,847,0.01,0.11079647201369916,1,0.8452567915260467,0,None,i7186,44,0.0005152322263745005 1727826701,1727826753,52,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 846 confidence 0.005 feature_proportion 0.07348174554325633 n_clusters 1,846,0.005,0.07348174554325633,1,0.8452567915260467,0,None,i7186,49,0.0005507654833658454 1727826751,1727826756,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 863 confidence 0.001 feature_proportion 0 n_clusters 1,863,0.001,0,1,None,1,None,i7186 1727826771,1727826776,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 951 confidence 0.25 feature_proportion 0 n_clusters 4,951,0.25,0,4,None,1,None,i7186 1727826731,1727826779,48,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 846 confidence 0.01 feature_proportion 0.119762452563735 n_clusters 1,846,0.01,0.119762452563735,1,0.8446219133224179,0,None,i7186,44,0.0005454131936098271 1727826821,1727826825,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 859 confidence 0.05 feature_proportion 0 n_clusters 1,859,0.05,0,1,None,1,None,i7186 1727826811,1727826873,62,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 474 confidence 0.001 feature_proportion 0.2 n_clusters 4,474,0.001,0.2,4,0.8470277675677482,0,None,i7186,58,0.00028982087705934766 1727826852,1727826896,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 823 confidence 0.05 feature_proportion 0.05479532506588878 n_clusters 1,823,0.05,0.05479532506588878,1,0.8412804490927924,0,None,i7186,41,0.0005867218073783464 1727827071,1727827075,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 485 confidence 0.001 feature_proportion 0 n_clusters 4,485,0.001,0,4,None,1,None,i7186 1727827091,1727827096,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 850 confidence 0.25 feature_proportion 0 n_clusters 1,850,0.25,0,1,None,1,None,i7186 1727827121,1727827126,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 817 confidence 0.1 feature_proportion 0 n_clusters 1,817,0.1,0,1,None,1,None,i7186 1727827171,1727827175,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 865 confidence 0.25 feature_proportion 0 n_clusters 1,865,0.25,0,1,None,1,None,i7186 1727827151,1727827197,46,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 791 confidence 0.025 feature_proportion 0.06168600675493328 n_clusters 1,791,0.025,0.06168600675493328,1,0.8443880108263441,0,None,i7186,42,0.0004811708490660609 1727827181,1727827224,43,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 913 confidence 0.25 feature_proportion 0.2 n_clusters 4,913,0.25,0.2,4,0.8412136198082,0,None,i7186,39,0.0006456571204985898 1727827211,1727827257,46,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 826 confidence 0.1 feature_proportion 0.024479787667490448 n_clusters 1,826,0.1,0.024479787667490448,1,0.8445216693955291,0,None,i7186,42,0.000491391798474327 1727827231,1727827274,43,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 872 confidence 0.1 feature_proportion 0.08745953891277419 n_clusters 1,872,0.1,0.08745953891277419,1,0.8448892304607879,0,None,i7186,39,0.0004951442449354031 1727827251,1727827294,43,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 874 confidence 0.25 feature_proportion 0.14250505343653927 n_clusters 1,874,0.25,0.14250505343653927,1,0.8454906940221205,0,None,i7186,39,0.00047691807641017404 1727827271,1727827315,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 906 confidence 0.1 feature_proportion 0.12211180241222151 n_clusters 4,906,0.1,0.12211180241222151,4,0.8398436194740535,0,None,i7186,40,0.0006682928459250843 1727827501,1727827505,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 948 confidence 0.25 feature_proportion 0 n_clusters 4,948,0.25,0,4,None,1,None,i7186 1727827511,1727827515,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 872 confidence 0.001 feature_proportion 0 n_clusters 2,872,0.001,0,2,None,1,None,i7186 1727827461,1727827521,60,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 170 confidence 0.001 feature_proportion 0.0825113247723356 n_clusters 1,170,0.001,0.0825113247723356,1,0.8293180071507334,0,None,i7186,56,0.0005801996980531414 1727827561,1727827565,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 440 confidence 0.25 feature_proportion 0 n_clusters 4,440,0.25,0,4,None,1,None,i7186 1727827541,1727827585,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 937 confidence 0.25 feature_proportion 0.032865611685334965 n_clusters 4,937,0.25,0.032865611685334965,4,0.843853376549604,0,None,i7186,41,0.0005791871331350728 1727827581,1727827624,43,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 483 confidence 0.25 feature_proportion 0.13854336801712505 n_clusters 2,483,0.25,0.13854336801712505,2,0.8525077689043339,0,None,i7186,39,0.00014535369398870578 1727827621,1727827626,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4,1000,0.25,0,4,None,1,None,i7186 1727827661,1727827665,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 958 confidence 0.25 feature_proportion 0 n_clusters 4,958,0.25,0,4,None,1,None,i7186 1727827631,1727827674,43,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 917 confidence 0.25 feature_proportion 0.10109944849249929 n_clusters 4,917,0.25,0.10109944849249929,4,0.8422160590770875,0,None,i7186,39,0.0006133203698893114 1727827681,1727827725,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 419 confidence 0.25 feature_proportion 0.2 n_clusters 4,419,0.25,0.2,4,0.8557824038493668,0,None,i7186,40,7.893603904767296e-05 1727827931,1727827936,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1,1000,0.001,0,1,None,1,None,i7186 1727827901,1727827957,56,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 744 confidence 0.001 feature_proportion 0.1541403332504318 n_clusters 2,744,0.001,0.1541403332504318,2,0.8483643532595984,0,None,i7186,51,0.0003898374934562992 1727827952,1727828002,50,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 995 confidence 0.001 feature_proportion 0.03993680495147095 n_clusters 1,995,0.001,0.03993680495147095,1,0.8382397166438333,0,None,i7186,46,0.0009195709559929166 1727827961,1727828011,50,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 992 confidence 0.001 feature_proportion 0.1457315794670551 n_clusters 2,992,0.001,0.1457315794670551,2,0.8366358138136132,0,None,i7186,46,0.0009108583974090039 1727828012,1727828016,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 592 confidence 0.001 feature_proportion 0 n_clusters 1,592,0.001,0,1,None,1,None,i7186 1727828032,1727828036,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 578 confidence 0.001 feature_proportion 0 n_clusters 1,578,0.001,0,1,None,1,None,i7186 1727827991,1727828040,49,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 587 confidence 0.001 feature_proportion 0.2 n_clusters 1,587,0.001,0.2,1,0.8432853276305677,0,None,i7186,45,0.00041729448635089583 1727828072,1727828120,48,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 764 confidence 0.001 feature_proportion 0.2 n_clusters 1,764,0.001,0.2,1,0.8446553279647141,0,None,i7186,44,0.00047353321654120304 1727828092,1727828144,52,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 620 confidence 0.001 feature_proportion 0.0596147546024208 n_clusters 1,620,0.001,0.0596147546024208,1,0.8420489858656063,0,None,i7186,48,0.0004917949917448698 1727828111,1727828162,51,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 569 confidence 0.001 feature_proportion 0.07634458182644001 n_clusters 1,569,0.001,0.07634458182644001,1,0.8472950847061183,0,None,i7186,47,0.000331759662798524 1727828278,1727828282,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 591 confidence 0.001 feature_proportion 0 n_clusters 1,591,0.001,0,1,None,1,None,i7186 1727828338,1727828343,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1,1000,0.001,0,1,None,1,None,i7186 1727828318,1727828367,49,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 553 confidence 0.005 feature_proportion 0.016882991409375016 n_clusters 1,553,0.005,0.016882991409375016,1,0.8440204497610853,0,None,i7186,45,0.0003740987126645852 1727828378,1727828382,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 627 confidence 0.005 feature_proportion 0 n_clusters 1,627,0.005,0,1,None,1,None,i7186 1727828358,1727828408,50,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 597 confidence 0.001 feature_proportion 0.13817119243905318 n_clusters 1,597,0.001,0.13817119243905318,1,0.8449226451030842,0,None,i7186,46,0.0003882463200136203 1727828411,1727828415,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 482 confidence 0.025 feature_proportion 0 n_clusters 1,482,0.025,0,1,None,1,None,i7186 1727828458,1727828463,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1,1000,0.001,0,1,None,1,None,i7186 1727828438,1727828485,47,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 536 confidence 0.025 feature_proportion 0.09354087318300539 n_clusters 1,536,0.025,0.09354087318300539,1,0.8483643532595984,0,None,i7186,43,0.0002522477898834877 1727828635,1727828684,49,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0.19097790993361133 n_clusters 2,1000,0.001,0.19097790993361133,2,0.8404116683930898,0,None,i7186,45,0.000771011931502459 1727828680,1727828684,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 901 confidence 0.01 feature_proportion 0 n_clusters 1,901,0.01,0,1,None,1,None,i7186 1727828660,1727828712,52,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0.2 n_clusters 1,1000,0.001,0.2,1,0.8381728873592408,0,None,i7186,48,0.0009222441273766169 1727828740,1727828745,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1,1000,0.25,0,1,None,1,None,i7186 1727828700,1727828750,50,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 970 confidence 0.001 feature_proportion 0.054632609609757 n_clusters 1,970,0.001,0.054632609609757,1,0.843452400842049,0,None,i7186,47,0.0006837149885233559 1727828760,1727828765,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 933 confidence 0.001 feature_proportion 0 n_clusters 4,933,0.001,0,4,None,1,None,i7186 1727828800,1727828805,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 1,1000,0.005,0,1,None,1,None,i7186 1727828820,1727828825,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.05 feature_proportion 0 n_clusters 1,1000,0.05,0,1,None,1,None,i7186 1727828860,1727828864,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 934 confidence 0.001 feature_proportion 0 n_clusters 4,934,0.001,0,4,None,1,None,i7186 1727828840,1727828890,50,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 901 confidence 0.01 feature_proportion 0.01486375921555323 n_clusters 1,901,0.01,0.01486375921555323,1,0.8375045945133157,0,None,i7186,46,0.000818082621735879 1727829058,1727829063,5,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.025 feature_proportion 0 n_clusters 1,1000,0.025,0,1,None,1,None,i7186 1727829131,1727829135,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 909 confidence 0.01 feature_proportion 0 n_clusters 1,909,0.01,0,1,None,1,None,i7186 1727829098,1727829148,50,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 969 confidence 0.001 feature_proportion 0.04149782591556487 n_clusters 1,969,0.001,0.04149782591556487,1,0.8426838640692351,0,None,i7186,46,0.0006868565360896696 1727829118,1727829162,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 886 confidence 0.01 feature_proportion 0.05086849862279977 n_clusters 1,886,0.01,0.05086849862279977,1,0.8453570354529355,0,None,i7186,41,0.0005119985513135729 1727829191,1727829195,4,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 932 confidence 0.001 feature_proportion 0 n_clusters 4,932,0.001,0,4,None,1,None,i7186 1727829158,1727829204,46,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.01 feature_proportion 0.08905278286104765 n_clusters 2,1000,0.01,0.08905278286104765,2,0.837805326293982,0,None,i7186,42,0.0008365594374883646 1727829218,1727829268,50,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0.050592622158597444 n_clusters 4,1000,0.001,0.050592622158597444,4,0.8385070337822034,0,None,i7186,46,0.0008415539541278837 1727829238,1727829287,49,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 842 confidence 0.01 feature_proportion 0.11838280663306662 n_clusters 1,842,0.01,0.11838280663306662,1,0.8455241086644167,0,None,i7186,45,0.0005066090928786932 1727829251,1727829300,49,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 980 confidence 0.001 feature_proportion 0.1300732468762936 n_clusters 2,980,0.001,0.1300732468762936,2,0.841079961239015,0,None,i7186,46,0.0007462603446163444
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2328959/2328959_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.1 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2328961/2328961_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2328962/2328962_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 100 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(100, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2328965/2328965_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 543 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(543, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2328971/2328971_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 100 confidence 0.1 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(100, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2328973/2328973_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2328975/2328975_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 626 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(626, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2328976/2328976_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 100 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(100, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2328982/2328982_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2328988/2328988_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2328989/2328989_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2328995/2328995_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 922 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(922, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2328996/2328996_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 680 confidence 0.01 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(680, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329009/2329009_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 759 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(759, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329011/2329011_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 798 confidence 0.001 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(798, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329014/2329014_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 613 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(613, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329016/2329016_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 643 confidence 0.05 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(643, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329019/2329019_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.01 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329026/2329026_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329034/2329034_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 736 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(736, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329037/2329037_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 742 confidence 0.025 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(742, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329039/2329039_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329040/2329040_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329048/2329048_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329056/2329056_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 639 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(639, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329062/2329062_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329099/2329099_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 987 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(987, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329103/2329103_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329113/2329113_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329117/2329117_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 573 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(573, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329118/2329118_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 902 confidence 0.005 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(902, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329119/2329119_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 900 confidence 0.01 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(900, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329123/2329123_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329126/2329126_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329128/2329128_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 682 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(682, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329129/2329129_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.01 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329131/2329131_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 653 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(653, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329133/2329133_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 412 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(412, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329135/2329135_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329136/2329136_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 648 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(648, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329137/2329137_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329138/2329138_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 744 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(744, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329139/2329139_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 944 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(944, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329140/2329140_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329142/2329142_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.01 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329143/2329143_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 483 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(483, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329144/2329144_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329145/2329145_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329146/2329146_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 421 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(421, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329148/2329148_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 679 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(679, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329147/2329147_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 852 confidence 0.001 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(852, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329149/2329149_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 490 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(490, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329150/2329150_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329151/2329151_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 419 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(419, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329152/2329152_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329153/2329153_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.01 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329156/2329156_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329157/2329157_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 454 confidence 0.001 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(454, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329158/2329158_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329160/2329160_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 965 confidence 0.025 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(965, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329161/2329161_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329163/2329163_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.025 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329164/2329164_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.01 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329165/2329165_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329166/2329166_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329169/2329169_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329170/2329170_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 421 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(421, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329171/2329171_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329172/2329172_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 100 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(100, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329173/2329173_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329174/2329174_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 640 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(640, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329175/2329175_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 510 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(510, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329177/2329177_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329178/2329178_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329180/2329180_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 465 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(465, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329181/2329181_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 224 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(224, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329182/2329182_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329184/2329184_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 246 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(246, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329185/2329185_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 408 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(408, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329186/2329186_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329187/2329187_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329188/2329188_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 670 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(670, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329189/2329189_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 455 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(455, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329191/2329191_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 559 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(559, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329192/2329192_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329193/2329193_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329195/2329195_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 424 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(424, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329196/2329196_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 100 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(100, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329197/2329197_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329198/2329198_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.01 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329199/2329199_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 353 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(353, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329201/2329201_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 407 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(407, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329202/2329202_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 403 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(403, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329203/2329203_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329204/2329204_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 416 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(416, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329205/2329205_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329206/2329206_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329207/2329207_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329208/2329208_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329209/2329209_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.05 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329210/2329210_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 719 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(719, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329212/2329212_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 806 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(806, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329213/2329213_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329230/2329230_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 333 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(333, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329232/2329232_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 358 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(358, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329233/2329233_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329234/2329234_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 869 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(869, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329237/2329237_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 713 confidence 0.025 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(713, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329241/2329241_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 644 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(644, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329242/2329242_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329243/2329243_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329246/2329246_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329247/2329247_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329248/2329248_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.05 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329249/2329249_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329250/2329250_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 717 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(717, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329251/2329251_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 924 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(924, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329252/2329252_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 832 confidence 0.025 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(832, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329253/2329253_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329254/2329254_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.1 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329255/2329255_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329256/2329256_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 953 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(953, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329257/2329257_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329259/2329259_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329260/2329260_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 523 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(523, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329261/2329261_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329262/2329262_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329263/2329263_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.05 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329264/2329264_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 953 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(953, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329266/2329266_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329267/2329267_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 991 confidence 0.1 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(991, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329268/2329268_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329269/2329269_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329270/2329270_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 632 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(632, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329271/2329271_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329272/2329272_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329273/2329273_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 893 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(893, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329274/2329274_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329275/2329275_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 863 confidence 0.01 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(863, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329276/2329276_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 506 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(506, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329278/2329278_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.1 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329279/2329279_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329280/2329280_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 643 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(643, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329281/2329281_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 538 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(538, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329282/2329282_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 560 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(560, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329283/2329283_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329284/2329284_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329285/2329285_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329286/2329286_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329288/2329288_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329289/2329289_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329290/2329290_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 452 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(452, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329294/2329294_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329295/2329295_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329296/2329296_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329301/2329301_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 895 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(895, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329310/2329310_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 991 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(991, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329311/2329311_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 987 confidence 0.1 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(987, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329316/2329316_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 885 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(885, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329318/2329318_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 874 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(874, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329320/2329320_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 723 confidence 0.025 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(723, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329322/2329322_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 861 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(861, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329324/2329324_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 886 confidence 0.005 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(886, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329325/2329325_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 716 confidence 0.05 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(716, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329326/2329326_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 730 confidence 0.01 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(730, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329328/2329328_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 877 confidence 0.01 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(877, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329330/2329330_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 873 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(873, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329333/2329333_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 872 confidence 0.005 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(872, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329334/2329334_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 711 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(711, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329335/2329335_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 863 confidence 0.025 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(863, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329336/2329336_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 875 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(875, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329337/2329337_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 871 confidence 0.01 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(871, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329338/2329338_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 897 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(897, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329340/2329340_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 852 confidence 0.05 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(852, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329341/2329341_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 871 confidence 0.025 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(871, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329342/2329342_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 859 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(859, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329344/2329344_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 877 confidence 0.01 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(877, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329347/2329347_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 711 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(711, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329349/2329349_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 873 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(873, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329350/2329350_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 732 confidence 0.01 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(732, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329352/2329352_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 857 confidence 0.05 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(857, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329353/2329353_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 859 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(859, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329354/2329354_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 877 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(877, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329355/2329355_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 771 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(771, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329356/2329356_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 738 confidence 0.01 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(738, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329357/2329357_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 765 confidence 0.1 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(765, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329358/2329358_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 714 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(714, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329360/2329360_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 606 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(606, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329361/2329361_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 751 confidence 0.025 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(751, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329363/2329363_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 733 confidence 0.05 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(733, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329364/2329364_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 719 confidence 0.01 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(719, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329366/2329366_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 754 confidence 0.05 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(754, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329368/2329368_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 761 confidence 0.05 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(761, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329369/2329369_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 703 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(703, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329371/2329371_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 769 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(769, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329373/2329373_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 434 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(434, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329374/2329374_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 863 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(863, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329375/2329375_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 443 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(443, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329380/2329380_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 445 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(445, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329381/2329381_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 602 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(602, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329382/2329382_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 576 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(576, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329383/2329383_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 616 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(616, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329384/2329384_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 858 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(858, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329385/2329385_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 572 confidence 0.001 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(572, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329386/2329386_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 842 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(842, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329388/2329388_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 538 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(538, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329389/2329389_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 545 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(545, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329390/2329390_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 543 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(543, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329391/2329391_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 868 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(868, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329392/2329392_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 844 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(844, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329393/2329393_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 859 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(859, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329395/2329395_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 703 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(703, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329396/2329396_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 860 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(860, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329397/2329397_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 707 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(707, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329400/2329400_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 867 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(867, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329405/2329405_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 870 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(870, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329406/2329406_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 616 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(616, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329407/2329407_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 658 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(658, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329408/2329408_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329410/2329410_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 688 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(688, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329411/2329411_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 647 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(647, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329414/2329414_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 853 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(853, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329415/2329415_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 869 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(869, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329416/2329416_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329417/2329417_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 870 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(870, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329418/2329418_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 878 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(878, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329421/2329421_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329423/2329423_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 882 confidence 0.01 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(882, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329425/2329425_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 860 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(860, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329426/2329426_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 870 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(870, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329427/2329427_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 853 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(853, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329548/2329548_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 862 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(862, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329525/2329525_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 871 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(871, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329536/2329536_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 849 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(849, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329595/2329595_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 863 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(863, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329596/2329596_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 951 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(951, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329598/2329598_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 859 confidence 0.05 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(859, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329600/2329600_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 485 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(485, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329601/2329601_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 850 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(850, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329602/2329602_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 817 confidence 0.1 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(817, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329604/2329604_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 865 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(865, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329611/2329611_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 948 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(948, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329612/2329612_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 872 confidence 0.001 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(872, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329614/2329614_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 440 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(440, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329616/2329616_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329618/2329618_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 958 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(958, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329621/2329621_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329625/2329625_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 592 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(592, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329626/2329626_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 578 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(578, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329630/2329630_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 591 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(591, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329632/2329632_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329634/2329634_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 627 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(627, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329635/2329635_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 482 confidence 0.025 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(482, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329637/2329637_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329640/2329640_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 901 confidence 0.01 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(901, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329642/2329642_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329643/2329643_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 933 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(933, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329644/2329644_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329645/2329645_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.05 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329647/2329647_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 934 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(934, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329648/2329648_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.025 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329651/2329651_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 909 confidence 0.01 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(909, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329653/2329653_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 932 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(932, 0)) while a minimum of 1
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This is a heatmap that visualizes the correlation between numerical columns in a dataset. The values represented in the heatmap show the strength and direction of relationships between different variables.
The heatmap uses a matrix to represent correlations between each pair of numerical columns. The calculation behind this is based on the concept of "correlation," which measures how strongly two variables are related. A correlation can be positive, negative, or zero:
The heatmap uses a color scale called "Viridis," which ranges from yellow to purple. Here's what the colors represent:
In the heatmap, each cell represents the correlation between two numerical columns. The color of the cell is determined by the correlation coefficient: from yellow for strong positive correlations, through green and blue for weaker correlations, to purple for strong negative correlations.
submitit INFO (2024-10-01 22:51:54,556) - Starting with JobEnvironment(job_id=2328933, hostname=i7186, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2024-10-01 22:51:54,558) - Loading pickle: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2328933/2328933_submitted.pkl
Parameters: {"n_samples": 697, "confidence": 0.01, "feature_proportion": 0.054493993520736694, "n_clusters": 2}
Debug-Infos:
========
DEBUG INFOS START:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 697 confidence 0.01 feature_proportion 0.054493993520736694 n_clusters 2
pwd: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main
File: /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate
UID: 2063769
GID: 200270
Status-Change-Time: 1724762786.0
Size: 2165 Bytes
Permissions: -rw-r--r--
Owner: s4122485
Last access: 1727815132.0
Last modification: 1724759185.0
Hostname: i7186
pwd: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main
File: main_omniopt.py
UID: 2063769
GID: 200270
Status-Change-Time: 1727277242.0
Size: 1729 Bytes
Permissions: -rw-r--r--
Owner: s4122485
Last access: 1727815132.0
Last modification: 1727277242.0
Hostname: i7186
========
DEBUG INFOS END
module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 697 confidence 0.01 feature_proportion 0.054493993520736694 n_clusters 2
stdout:
RESULT: 0.8416814248003475
OO-Info: runtime: 51
OO-Info: lpd: 0.0005429879373141308
Result: 0.8416814248003475
EXIT_CODE: 0
submitit INFO (2024-10-01 22:52:52,250) - Job completed successfully
submitit INFO (2024-10-01 22:52:52,253) - Exiting after successful completion
Job-Infos
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background-image: url("data:image/svg+xml;charset=utf-8,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 -0.5 15 17' shape-rendering='crispEdges'%3E%3Cpath stroke='%23e6eefc' d='M0 0h1'/%3E%3Cpath stroke='%23d1e0fd' d='M1 0h1M0 1h1m3 0h2M2 3h1M2 4h1'/%3E%3Cpath stroke='%23cad8f9' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23c4d3f7' d='M3 0h1M0 3h1M0 4h1'/%3E%3Cpath stroke='%23bfd0f8' d='M4 0h2M0 5h1'/%3E%3Cpath stroke='%23bdcef7' d='M6 0h1M0 6h1'/%3E%3Cpath stroke='%23baccf4' d='M7 0h1m6 2h1m-1 5h1m-1 1h1'/%3E%3Cpath stroke='%23b8cbf6' d='M8 0h1M0 7h1M0 8h1'/%3E%3Cpath stroke='%23b7caf5' d='M9 0h2M0 9h1'/%3E%3Cpath stroke='%23b5c8f7' d='M11 0h1'/%3E%3Cpath stroke='%23b3c7f5' d='M12 0h1'/%3E%3Cpath stroke='%23afc5f4' d='M13 0h1'/%3E%3Cpath stroke='%23dce6f9' d='M14 0h1'/%3E%3Cpath stroke='%23e1eafe' d='M1 1h1'/%3E%3Cpath stroke='%23dae6fe' d='M2 1h1M1 2h1'/%3E%3Cpath stroke='%23d4e1fc' d='M3 1h1M1 3h1M1 4h1'/%3E%3Cpath stroke='%23d0ddfc' d='M6 1h1M1 5h1'/%3E%3Cpath stroke='%23cedbfd' d='M7 1h1M4 2h2'/%3E%3Cpath stroke='%23cad9fd' d='M8 1h1M6 2h1M3 5h1'/%3E%3Cpath stroke='%23c8d8fb' d='M9 1h2'/%3E%3Cpath stroke='%23c5d6fc' d='M11 1h1M2 11h4'/%3E%3Cpath stroke='%23c2d3fc' d='M12 1h1m-2 1h1M1 11h1m0 1h2m-2 1h2'/%3E%3Cpath stroke='%23bccefa' d='M13 1h1m-1 1h1m-1 1h1m-1 1h1M3 15h4'/%3E%3Cpath stroke='%23b9c9f3' d='M14 1h1M3 16h4'/%3E%3Cpath stroke='%23d8e3fc' d='M2 2h1'/%3E%3Cpath stroke='%23d1defd' d='M3 2h1'/%3E%3Cpath stroke='%23c9d8fc' d='M7 2h1M4 3h3M4 4h3M3 6h1m1 0h2M1 7h1M1 8h1'/%3E%3Cpath stroke='%23c5d5fc' d='M8 2h1m-8 8h5'/%3E%3Cpath stroke='%23c5d3fc' d='M9 2h2'/%3E%3Cpath stroke='%23bed0fc' d='M12 2h1M8 3h1M8 4h1m-8 8h1m-1 1h1m0 1h1m1 0h3'/%3E%3Cpath stroke='%23cddbfc' d='M3 3h1M3 4h1M1 6h2'/%3E%3Cpath stroke='%23c8d5fb' d='M7 3h1M7 4h1'/%3E%3Cpath stroke='%23bbcefd' d='M9 3h4M9 4h4M8 5h1M7 6h1'/%3E%3Cpath stroke='%23bcccf3' d='M14 3h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23ceddfd' d='M2 5h1'/%3E%3Cpath stroke='%23c8d6fb' d='M4 5h4M1 9h3'/%3E%3Cpath stroke='%23bacdfc' d='M9 5h2m1 0h2M1 14h1'/%3E%3Cpath stroke='%23b9cdfb' d='M11 5h1M8 6h2m2 0h2m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%234d6185' d='M4 6h1m5 0h1M3 7h3m3 0h3M4 8h3m1 0h3M5 9h5m-4 1h3m-2 1h1'/%3E%3Cpath stroke='%23b7cdfc' d='M11 6h1m0 1h1m-1 1h1'/%3E%3Cpath stroke='%23cad8fd' d='M2 7h1M2 8h2'/%3E%3Cpath stroke='%23c1d3fb' d='M6 7h2M7 8h1M4 9h1'/%3E%3Cpath stroke='%23b6cefb' d='M8 7h1m2 1h1m-2 1h3m-2 1h2'/%3E%3Cpath stroke='%23b6cdfb' d='M13 9h1m-6 6h1'/%3E%3Cpath stroke='%23b9cbf3' d='M14 9h1'/%3E%3Cpath stroke='%23b4c8f6' d='M0 10h1'/%3E%3Cpath stroke='%23bdd3fb' d='M9 10h2m-4 4h1'/%3E%3Cpath stroke='%23b5cdfa' d='M13 10h1'/%3E%3Cpath stroke='%23b5c9f3' d='M14 10h1'/%3E%3Cpath stroke='%23b1c7f6' d='M0 11h1'/%3E%3Cpath stroke='%23c3d5fd' d='M6 11h1'/%3E%3Cpath stroke='%23bad4fc' d='M8 11h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b2cffb' d='M9 11h4m-2 3h1'/%3E%3Cpath stroke='%23b1cbfa' d='M13 11h1m-3 4h1'/%3E%3Cpath stroke='%23b3c8f5' d='M14 11h1m-7 5h3'/%3E%3Cpath stroke='%23adc3f6' d='M0 12h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c2d5fc' d='M4 12h4m-4 1h4'/%3E%3Cpath stroke='%23b7d3fc' d='M9 12h2m-2 1h2m-3 1h1'/%3E%3Cpath stroke='%23b3d1fc' d='M11 12h1m-1 1h1'/%3E%3Cpath stroke='%23afcdfb' d='M12 12h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23afcbfa' d='M13 12h1m-1 1h1'/%3E%3Cpath stroke='%23b2c8f4' d='M14 12h1m-1 1h1m-4 3h1'/%3E%3Cpath stroke='%23c1d2fb' d='M3 14h1'/%3E%3Cpath stroke='%23b6d1fb' d='M9 14h2'/%3E%3Cpath stroke='%23adc9f9' d='M13 14h1m-2 1h1'/%3E%3Cpath stroke='%23b1c6f3' d='M14 14h1m-3 2h1'/%3E%3Cpath stroke='%23abc1f4' d='M0 15h1'/%3E%3Cpath stroke='%23b7cbf9' d='M1 15h1'/%3E%3Cpath stroke='%23b9cefb' d='M2 15h1'/%3E%3Cpath stroke='%23b9cffb' d='M7 15h1'/%3E%3Cpath stroke='%23b2cdfb' d='M9 15h2'/%3E%3Cpath stroke='%23aec8f7' d='M13 15h1'/%3E%3Cpath stroke='%23b0c5f2' d='M14 15h1m-2 1h1'/%3E%3Cpath stroke='%23dbe3f8' d='M0 16h1'/%3E%3Cpath stroke='%23b7c6f1' d='M1 16h1'/%3E%3Cpath stroke='%23b8c9f2' d='M2 16h1m4 0h1'/%3E%3Cpath stroke='%23d9e3f6' d='M14 16h1'/%3E%3C/svg%3E");
background-size: 15px;
font-size: 11px;
border: none;
background-color: #fff;
box-sizing: border-box;
height: 21px;
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
position: relative;
padding: 5px 32px 32px 5px;
background-position: top 50% right 2px;
background-repeat: no-repeat;
border-radius: 0;
border: 1px solid black;
}
body {
font-family: 'IBM Plex Sans', 'Source Sans Pro', sans-serif;
background-color: #fafafa;
font-variant: oldstyle-nums;
text-shadow: 0 0.05em 0.1em rgba(0,0,0,0.2);
scroll-behavior: smooth;
text-wrap: balance;
text-rendering: optimizeLegibility;
-webkit-font-smoothing: antialiased;
-moz-osx-font-smoothing: grayscale;
font-feature-settings: "ss02", "liga", "onum";
}
.marked_text {
background-color: yellow;
}
.time_picker_container {
font-variant: small-caps;
width: 100%;
}
.time_picker_container > input {
width: 50px;
}
#loader {
display: grid;
justify-content: center;
align-items: center;
height: 100%;
}
.no_linebreak {
line-break: auto;
}
.dark_code_bg {
background-color: #363636;
color: white;
}
.code_bg {
background-color: #C0C0C0;
}
#commands {
line-break: anywhere;
}
.color_red {
color: red;
}
.color_orange {
color: orange;
}
table > tbody > tr:nth-child(odd) {
background-color: #fafafa;
}
table > tbody > tr:nth-child(even) {
background-color: #ddd;
}
table {
border-collapse: collapse;
margin: 25px 0;
min-width: 200px;
}
th {
background-color: #4eae46;
color: #ffffff;
text-align: left;
border: 0px;
}
.error_element {
background-color: #e57373;
border-radius: 10px;
padding: 4px;
display: none;
}
button {
background-color: #4eae46;
border: 1px solid #2A8387;
border-radius: 4px;
box-shadow: rgba(0, 0, 0, 0.12) 0 1px 1px;
cursor: pointer;
display: block;
line-height: 100%;
outline: 0;
padding: 11px 15px 12px;
text-align: center;
transition: box-shadow .05s ease-in-out, opacity .05s ease-in-out;
user-select: none;
-webkit-user-select: none;
touch-action: manipulation;
}
button:hover {
box-shadow: rgba(255, 255, 255, 0.3) 0 0 2px inset, rgba(0, 0, 0, 0.4) 0 1px 2px;
text-decoration: none;
transition-duration: .15s, .15s;
}
button:active {
box-shadow: rgba(0, 0, 0, 0.15) 0 2px 4px inset, rgba(0, 0, 0, 0.4) 0 1px 1px;
}
button:disabled {
cursor: not-allowed;
opacity: .6;
}
button:disabled:active {
pointer-events: none;
}
button:disabled:hover {
box-shadow: none;
}
.half_width_td {
vertical-align: baseline;
width: 50%;
}
#scads_bar {
width: 100%;
min-height: 80px;
margin: 0;
padding: 0;
user-select: none;
user-drag: none;
-webkit-user-drag: none;
user-select: none;
-moz-user-select: none;
-webkit-user-select: none;
-ms-user-select: none;
display: -webkit-box;
}
.tab {
display: inline-block;
padding: 0px;
margin: 0px;
font-size: 16px;
font-weight: bold;
text-align: center;
border-radius: 25px;
text-decoration: none !important;
transition: background-color 0.3s, color 0.3s;
color: unset !important;
}
.tooltipster-base {
border: 1px solid black;
position: absolute;
border-radius: 8px;
padding: 2px;
color: white;
background-color: #61686f;
width: 70%;
min-width: 200px;
pointer-events: none;
}
td {
padding-top: 3px;
padding-bottom: 3px;
}
.left_side {
text-align: right;
}
.right_side {
text-align: left;
}
.spinner {
border: 8px solid rgba(0, 0, 0, 0.1);
border-left: 8px solid #3498db;
border-radius: 50%;
width: 50px;
height: 50px;
animation: spin 1s linear infinite;
}
@keyframes spin {
0% {
transform: rotate(0deg);
}
100% {
transform: rotate(360deg);
}
}
#spinner-overlay {
-webkit-text-stroke: 1px black;
white !important;
position: fixed;
top: 0;
left: 0;
width: 100%;
height: 100%;
display: flex;
justify-content: center;
align-items: center;
z-index: 9999;
}
#spinner-container {
text-align: center;
color: #fff;
display: contents;
}
#spinner-text {
font-size: 3vw;
margin-left: 10px;
}
a, a:visited, a:active, a:hover, a:link {
color: #007bff;
text-decoration: none;
}
.copy-container {
display: inline-block;
position: relative;
cursor: pointer;
margin-left: 10px;
color: blue;
}
.copy-container:hover {
text-decoration: underline;
}
.clipboard-icon {
position: absolute;
top: 5px;
right: 5px;
font-size: 1.5em;
}
#main_tab {
overflow: scroll;
width: max-content;
}
.ui-tabs .ui-tabs-nav li {
user-select: none;
}
.stacktrace_table {
background-color: black !important;
color: white !important;
}
#breadcrumb {
user-select: none;
}
#statusBar {
user-select: none;
}
.error_line {
background-color: red !important;
color: white !important;
}
.header_table {
border: 0px !important;
padding: 0px !important;
width: revert !important;
min-width: revert !important;
}
.img_auto_width {
max-width: revert !important;
}
#main_dir_or_plot_view {
display: inline-grid;
}
#refresh_button {
width: 300px;
}
._share_link {
color: black !important;
}
#footer_element {
height: 30px;
background-color: #f8f9fa;
padding: 0px;
text-align: center;
border-top: 1px solid #dee2e6;
width: 100%;
box-sizing: border-box;
position: fixed;
bottom: 0;
z-index: 2;
margin-left: -9px;
z-index: 99;
}
.switch {
position: relative;
display: inline-block;
width: 50px;
height: 26px;
}
.switch input {
opacity: 0;
width: 0;
height: 0;
}
.slider {
position: absolute;
cursor: pointer;
top: 0;
left: 0;
right: 0;
bottom: 0;
background-color: #ccc;
transition: .4s;
border-radius: 26px;
}
.slider:before {
position: absolute;
content: "";
height: 20px;
width: 20px;
left: 3px;
bottom: 3px;
background-color: white;
transition: .4s;
border-radius: 50%;
}
input:checked + .slider {
background-color: #444;
}
input:checked + .slider:before {
transform: translateX(24px);
}
.mode-text {
position: absolute;
top: 5px;
left: 65px;
font-size: 14px;
color: black;
transition: .4s;
width: 60px;
display: block;
font-size: 0.7rem;
text-align: center;
}
input:checked + .slider .mode-text {
content: "Dark Mode";
color: white;
}
#mainContent {
height: fit-content;
min-height: 100%;
}
li {
text-align: left;
}
#share_path {
margin-bottom: 20px;
margin-top: 20px;
}
#sortForm {
margin-bottom: 20px;
}
.share_folder_buttons {
margin-top: 10px;
margin-bottom: 10px;
}
.nav_tab_button {
margin: 10px;
}
.header_table {
margin: 10px;
}
.no_border {
border: unset !important;
}
.gui_table {
padding: 5px !important;
}
.gui_parameter_row {
}
.gui_parameter_row_cell {
border: unset !important;
}
.gui_param_table {
width: 95%;
margin: unset !important;
}
table td, table tr,
.parameterRow table {
padding: 2px !important;
}
.parameterRow table {
margin: 0px;
border: unset;
}
.parameterRow > td {
border: 0px !important;
}
.parameter_config_table td, .parameter_config_table tr, #config_table th, #config_table td, #hidden_config_table th, #hidden_config_table td {
border: 0px !important;
}
.green_text {
color: green;
}
.remove_parameter {
white-space: pre;
}
select {
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
background-color: #fff;
color: #222;
padding: 5px 30px 5px 5px;
border: 1px solid #555;
border-radius: 5px;
cursor: pointer;
outline: none;
transition: all 0.3s ease;
background:
url("data:image/svg+xml;charset=UTF-8,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 10 6'%3E%3Cpath fill='%23888' d='M0 0l5 6 5-6z'/%3E%3C/svg%3E")
no-repeat right 10px center,
linear-gradient(180deg, #fff, #ecebe5 86%, #d8d0c4);
background-size: 12px, auto;
}
select:hover {
border-color: #888;
}
select:focus {
border-color: #4caf50;
box-shadow: 0 0 5px rgba(76, 175, 80, 0.5);
}
select::-ms-expand {
display: none;
}
input, textarea {
border-radius: 5px;
}
#search {
width: 200px;
max-width: 70%;
background-image: url(images/search.svg);
background-repeat: no-repeat;
background-size: auto 40px;
height: 40px;
line-height: 40px;
padding-left: 40px;
box-sizing: border-box;
}
input[type="checkbox"] {
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
width: 25px;
height: 25px;
border: 2px solid #3498db;
border-radius: 5px;
background-color: #fff;
position: relative;
cursor: pointer;
transition: all 0.3s ease;
width: 25px !important;
}
input[type="checkbox"]:checked {
background-color: #3498db;
border-color: #2980b9;
}
input[type="checkbox"]:checked::before {
content: '✔';
position: absolute;
left: 4px;
top: 2px;
color: #fff;
}
input[type="checkbox"]:hover {
border-color: #2980b9;
background-color: #3caffc;
}
.toc {
margin-bottom: 20px;
}
.toc li {
margin-bottom: 5px;
}
.toc a {
text-decoration: none;
color: #007bff;
}
.toc a:hover {
text-decoration: underline;
}
.table-container {
width: 100%;
overflow-x: auto;
}
.section-header {
background-color: #1d6f9a !important;
color: white;
}
.warning {
color: red;
}
.li_list a {
text-decoration: none;
color: #007bff;
}
.gridjs-td {
white-space: nowrap;
}
th, td {
border: 1px solid gray !important;
}
.no_border {
border: 0px !important;
}
.no_break {
}
img {
user-select: none;
pointer-events: none;
}
#config_table, #hidden_config_table {
user-select: none;
}
.copy_clipboard_button {
margin-bottom: 10px;
}
.badge_table {
background-color: unset !important;
}
.make_markable {
user-select: text;
}
.header-container {
display: flex;
flex-wrap: wrap;
align-items: center;
justify-content: space-between;
gap: 1rem;
padding: 10px;
background: var(--header-bg, #fff);
border-bottom: 1px solid #ccc;
}
.header-logo-group {
display: flex;
gap: 1rem;
align-items: center;
flex: 1 1 auto;
min-width: 200px;
}
.logo-img {
max-height: 45px;
height: auto;
width: auto;
object-fit: contain;
pointer-events: unset;
}
.header-badges {
flex-direction: column;
gap: 5px;
align-items: flex-start;
flex: 0 1 auto;
margin-top: auto;
margin-bottom: auto;
}
.badge-img {
height: auto;
max-width: 130px;
}
.header-tabs {
margin-top: 10px;
display: flex;
flex-wrap: wrap;
gap: 10px;
flex: 2 1 100%;
justify-content: center;
}
.nav-tab {
display: inline-block;
text-decoration: none;
padding: 8px 16px;
border-radius: 20px;
background: linear-gradient(to right, #4a90e2, #357ABD);
color: white;
font-weight: bold;
white-space: nowrap;
transition: background 0.2s ease-in-out, transform 0.2s;
box-shadow: 0 2px 4px rgba(0,0,0,0.2);
}
.nav-tab:hover {
background: linear-gradient(to right, #5aa0f2, #4a90e2);
transform: translateY(-2px);
}
.current-tag {
padding-left: 10px;
font-size: 0.9rem;
color: #666;
}
.header-theme-toggle {
flex: 1 1 auto;
align-items: center;
margin-top: 20px;
min-width: 120px;
}
.switch {
position: relative;
display: inline-block;
width: 60px;
height: 30px;
}
.switch input {
display: none;
}
.slider {
position: absolute;
top: 0; left: 0; right: 0; bottom: 0;
background-color: #ccc;
border-radius: 34px;
cursor: pointer;
}
.slider::before {
content: "";
position: absolute;
height: 24px;
width: 24px;
left: 3px;
bottom: 3px;
background-color: white;
transition: .4s;
border-radius: 50%;
}
input:checked + .slider {
background-color: #2196F3;
}
input:checked + .slider::before {
transform: translateX(30px);
}
@media (max-width: 768px) {
.header-logo-group,
.header-badges,
.header-theme-toggle {
justify-content: center;
flex: 1 1 100%;
text-align: center;
}
.logo-img {
max-height: 50px;
pointer-events: unset;
}
.badge-img {
max-width: 100px;
}
.nav-tab {
font-size: 0.9rem;
padding: 6px 12px;
}
.header_button {
font-size: 2em;
}
}
.header_button {
margin-top: 20px;
margin: 5px;
}
.line_break_anywhere {
line-break: anywhere;
}
.responsive-container {
display: flex;
flex-wrap: wrap;
justify-content: space-between;
gap: 20px;
}
.responsive-container .half {
flex: 1 1 48%;
box-sizing: border-box;
min-width: 500px;
}
.config-section table {
width: 100%;
border-collapse: collapse;
}
@media (max-width: 768px) {
.responsive-container .half {
flex: 1 1 100%;
}
}
@keyframes spin {
0% {
transform: rotate(0deg);
}
100% {
transform: rotate(360deg);
}
}
.rotate {
animation: spin 2s linear infinite;
display: inline-block;
}
/*! XP.css v0.2.6 - https: //botoxparty.github.io/XP.css/ */
body{
color: #222
}
.surface{
background: #ece9d8
}
u{
text-decoration: none;
border-bottom: .5px solid #222
}
a{
color: #00f
}
a: focus{
outline: 1px dotted #00f
}
code,code *{
font-family: monospace
}
pre{
display: block;
padding: 12px 8px;
background-color: #000;
color: silver;
font-size: 1rem;
margin: 0;
overflow: scroll;
}
summary: focus{
outline: 1px dotted #000
}
: :-webkit-scrollbar{
width: 16px
}
: :-webkit-scrollbar: horizontal{
height: 17px
}
: :-webkit-scrollbar-track{
background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='2' height='2' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M1 0H0v1h1v1h1V1H1V0z' fill='silver'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 0H1v1H0v1h1V1h1V0z' fill='%23fff'/%3E%3C/svg%3E")
}
: :-webkit-scrollbar-thumb{
background-color: #dfdfdf;
box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #fff,inset -2px -2px grey,inset 2px 2px #dfdfdf
}
: :-webkit-scrollbar-button: horizontal: end: increment,: :-webkit-scrollbar-button: horizontal: start: decrement,: :-webkit-scrollbar-button: vertical: end: increment,: :-webkit-scrollbar-button: vertical: start: decrement{
display: block
}
: :-webkit-scrollbar-button: vertical: start{
background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 6H7v1H6v1H5v1H4v1h7V9h-1V8H9V7H8V6z' fill='%23000'/%3E%3C/svg%3E")
}
: :-webkit-scrollbar-button: vertical: end{
background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 6H4v1h1v1h1v1h1v1h1V9h1V8h1V7h1V6z' fill='%23000'/%3E%3C/svg%3E")
}
: :-webkit-scrollbar-button: horizontal: start{
width: 16px;
background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 4H8v1H7v1H6v1H5v1h1v1h1v1h1v1h1V4z' fill='%23000'/%3E%3C/svg%3E")
}
: :-webkit-scrollbar-button: horizontal: end{
width: 16px;
background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M7 4H6v7h1v-1h1V9h1V8h1V7H9V6H8V5H7V4z' fill='%23000'/%3E%3C/svg%3E")
}
button{
border: none;
background: #ece9d8;
box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #fff,inset -2px -2px grey,inset 2px 2px #dfdfdf;
border-radius: 0;
min-width: 75px;
min-height: 23px;
padding: 0 12px
}
button: not(: disabled).active,button: not(: disabled): active{
box-shadow: inset -1px -1px #fff,inset 1px 1px #0a0a0a,inset -2px -2px #dfdfdf,inset 2px 2px grey
}
button.focused,button: focus{
outline: 1px dotted #000;
outline-offset: -4px
}
label{
display: inline-flex;
align-items: center
}
textarea{
padding: 3px 4px;
border: none;
background-color: #fff;
box-sizing: border-box;
-webkit-appearance: none;
-moz-appearance: none;
appearance: none;
border-radius: 0
}
textarea: focus{
outline: none
}
select: focus option{
color: #000;
background-color: #fff
}
.vertical-bar{
width: 4px;
height: 20px;
background: silver;
box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #fff,inset -2px -2px grey,inset 2px 2px #dfdfdf
}
&: disabled,&: disabled+label{
color: grey;
text-shadow: 1px 1px 0 #fff
}
input[type=radio]+label{
line-height: 13px;
position: relative;
margin-left: 19px
}
input[type=radio]+label: before{
content: "";
position: absolute;
top: 0;
left: -19px;
display: inline-block;
width: 13px;
height: 13px;
margin-right: 6px;
background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='12' height='12' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 0H4v1H2v1H1v2H0v4h1v2h1V8H1V4h1V2h2V1h4v1h2V1H8V0z' fill='gray'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 1H4v1H2v2H1v4h1v1h1V8H2V4h1V3h1V2h4v1h2V2H8V1z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 3h1v1H9V3zm1 5V4h1v4h-1zm-2 2V9h1V8h1v2H8zm-4 0v1h4v-1H4zm0 0V9H2v1h2z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 2h-1v2h1v4h-1v2H8v1H4v-1H2v1h2v1h4v-1h2v-1h1V8h1V4h-1V2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M4 2h4v1h1v1h1v4H9v1H8v1H4V9H3V8H2V4h1V3h1V2z' fill='%23fff'/%3E%3C/svg%3E")
}
input[type=radio]: active+label: before{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='12' height='12' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 0H4v1H2v1H1v2H0v4h1v2h1V8H1V4h1V2h2V1h4v1h2V1H8V0z' fill='gray'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 1H4v1H2v2H1v4h1v1h1V8H2V4h1V3h1V2h4v1h2V2H8V1z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 3h1v1H9V3zm1 5V4h1v4h-1zm-2 2V9h1V8h1v2H8zm-4 0v1h4v-1H4zm0 0V9H2v1h2z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 2h-1v2h1v4h-1v2H8v1H4v-1H2v1h2v1h4v-1h2v-1h1V8h1V4h-1V2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M4 2h4v1h1v1h1v4H9v1H8v1H4V9H3V8H2V4h1V3h1V2z' fill='silver'/%3E%3C/svg%3E")
}
input[type=radio]: checked+label: after{
content: "";
display: block;
width: 5px;
height: 5px;
top: 5px;
left: -14px;
position: absolute;
background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='4' height='4' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M3 0H1v1H0v2h1v1h2V3h1V1H3V0z' fill='%23000'/%3E%3C/svg%3E")
}
input[type=radio][disabled]+label: before{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='12' height='12' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 0H4v1H2v1H1v2H0v4h1v2h1V8H1V4h1V2h2V1h4v1h2V1H8V0z' fill='gray'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 1H4v1H2v2H1v4h1v1h1V8H2V4h1V3h1V2h4v1h2V2H8V1z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 3h1v1H9V3zm1 5V4h1v4h-1zm-2 2V9h1V8h1v2H8zm-4 0v1h4v-1H4zm0 0V9H2v1h2z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 2h-1v2h1v4h-1v2H8v1H4v-1H2v1h2v1h4v-1h2v-1h1V8h1V4h-1V2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M4 2h4v1h1v1h1v4H9v1H8v1H4V9H3V8H2V4h1V3h1V2z' fill='silver'/%3E%3C/svg%3E")
}
input[type=radio][disabled]: checked+label: after{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='4' height='4' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M3 0H1v1H0v2h1v1h2V3h1V1H3V0z' fill='gray'/%3E%3C/svg%3E")
}
input[type=email],input[type=password]{
padding: 3px 4px;
border: 1px solid #7f9db9;
background-color: #fff;
box-sizing: border-box;
-webkit-appearance: none;
-moz-appearance: none;
appearance: none;
border-radius: 0;
height: 21px;
line-height: 2
}
input[type=email]: focus,input[type=password]: focus{
outline: none
}
input[type=range]{
-webkit-appearance: none;
width: 100%;
background: transparent
}
input[type=range]: focus{
outline: none
}
input[type=range]: :-webkit-slider-thumb{
-webkit-appearance: none;
background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v16h2v2h2v2h1v-1H3v-2H1V1h9V0z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M1 1v15h1v1h1v1h1v1h2v-1h1v-1h1v-1h1V1z' fill='%23C0C7C8'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v15H8v2H6v2H5v-1h2v-2h2z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v16H9v2H7v2H5v1h1v-2h2v-2h2z' fill='%23000'/%3E%3C/svg%3E")
}
input[type=range]: :-moz-range-thumb{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v16h2v2h2v2h1v-1H3v-2H1V1h9V0z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M1 1v15h1v1h1v1h1v1h2v-1h1v-1h1v-1h1V1z' fill='%23C0C7C8'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v15H8v2H6v2H5v-1h2v-2h2z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v16H9v2H7v2H5v1h1v-2h2v-2h2z' fill='%23000'/%3E%3C/svg%3E")
}
input[type=range]: :-webkit-slider-runnable-track{
background: #000;
border-right: 1px solid grey;
border-bottom: 1px solid grey;
box-shadow: 1px 0 0 #fff,1px 1px 0 #fff,0 1px 0 #fff,-1px 0 0 #a9a9a9,-1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,-1px 1px 0 #fff,1px -1px #a9a9a9
}
input[type=range]: :-moz-range-track{
background: #000;
border-right: 1px solid grey;
border-bottom: 1px solid grey;
box-shadow: 1px 0 0 #fff,1px 1px 0 #fff,0 1px 0 #fff,-1px 0 0 #a9a9a9,-1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,-1px 1px 0 #fff,1px -1px #a9a9a9
}
input[type=range].has-box-indicator: :-webkit-slider-thumb{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v20h1V1h9V0z' fill='%23fff'/%3E%3Cpath fill='%23C0C7C8' d='M1 1h8v18H1z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v19H1v-1h8z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v21H0v-1h10z' fill='%23000'/%3E%3C/svg%3E")
}
input[type=range].has-box-indicator: :-moz-range-thumb{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v20h1V1h9V0z' fill='%23fff'/%3E%3Cpath fill='%23C0C7C8' d='M1 1h8v18H1z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v19H1v-1h8z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v21H0v-1h10z' fill='%23000'/%3E%3C/svg%3E")
}
.is-vertical{
display: inline-block;
width: 4px;
height: 150px;
transform: translateY(50%)
}
.is-vertical>input[type=range]{
width: 150px;
height: 4px;
margin: 0 16px 0 10px;
transform-origin: left;
transform: rotate(270deg) translateX(calc(-50% + 8px))
}
.is-vertical>input[type=range]: :-webkit-slider-runnable-track{
border-left: 1px solid grey;
border-bottom: 1px solid grey;
box-shadow: -1px 0 0 #fff,-1px 1px 0 #fff,0 1px 0 #fff,1px 0 0 #a9a9a9,1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,1px 1px 0 #fff,-1px -1px #a9a9a9
}
.is-vertical>input[type=range]: :-moz-range-track{
border-left: 1px solid grey;
border-bottom: 1px solid grey;
box-shadow: -1px 0 0 #fff,-1px 1px 0 #fff,0 1px 0 #fff,1px 0 0 #a9a9a9,1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,1px 1px 0 #fff,-1px -1px #a9a9a9
}
.is-vertical>input[type=range]: :-webkit-slider-thumb{
transform: translateY(-8px) scaleX(-1)
}
.is-vertical>input[type=range]: :-moz-range-thumb{
transform: translateY(2px) scaleX(-1)
}
.is-vertical>input[type=range].has-box-indicator: :-webkit-slider-thumb{
transform: translateY(-10px) scaleX(-1)
}
.is-vertical>input[type=range].has-box-indicator: :-moz-range-thumb{
transform: translateY(0) scaleX(-1)
}
.window{
font-size: 11px;
box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #dfdfdf,inset -2px -2px grey,inset 2px 2px #fff;
background: #ece9d8;
padding: 3px
}
.window fieldset{
margin-bottom: 9px
}
.title-bar{
background: #000;
padding: 3px 2px 3px 3px;
display: flex;
justify-content: space-between;
align-items: center
}
.title-bar-text{
font-weight: 700;
color: #fff;
letter-spacing: 0;
margin-right: 24px
}
.title-bar-controls button{
padding: 0;
display: block;
min-width: 16px;
min-height: 14px
}
.title-bar-controls button: focus{
outline: none
}
.window-body{
margin: 8px
}
.window-body pre{
margin: -8px
}
.status-bar{
margin: 0 1px;
display: flex;
gap: 1px
}
.status-bar-field{
box-shadow: inset -1px -1px #dfdfdf,inset 1px 1px grey;
flex-grow: 1;
padding: 2px 3px;
margin: 0
}
ul.tree-view{
display: block;
background: #fff;
padding: 6px;
margin: 0
}
ul.tree-view li{
list-style-type: none;
margin-top: 3px
}
ul.tree-view a{
text-decoration: none;
color: #000
}
ul.tree-view a: focus{
background-color: #2267cb;
color: #fff
}
ul.tree-view ul{
margin-top: 3px;
margin-left: 16px;
padding-left: 16px;
border-left: 1px dotted grey
}
ul.tree-view ul>li{
position: relative
}
ul.tree-view ul>li: before{
content: "";
display: block;
position: absolute;
left: -16px;
top: 6px;
width: 12px;
border-bottom: 1px dotted grey
}
ul.tree-view ul>li: last-child: after{
content: "";
display: block;
position: absolute;
left: -20px;
top: 7px;
bottom: 0;
width: 8px;
background: #fff
}
ul.tree-view ul details>summary: before{
margin-left: -22px;
position: relative;
z-index: 1
}
ul.tree-view details{
margin-top: 0
}
ul.tree-view details>summary: before{
text-align: center;
display: block;
float: left;
content: "+";
border: 1px solid grey;
width: 8px;
height: 9px;
line-height: 9px;
margin-right: 5px;
padding-left: 1px;
background-color: #fff
}
ul.tree-view details[open] summary{
margin-bottom: 0
}
ul.tree-view details[open]>summary: before{
content: "-"
}
fieldset{
border-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='5' height='5' fill='gray' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0h5v5H0V2h2v1h1V2H0' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0h4v4H0V1h1v2h2V1H0'/%3E%3C/svg%3E") 2;
padding: 10px;
padding-block-start: 8px;
margin: 0
}
legend{
background: #ece9d8
}
menu[role=tablist]{
position: relative;
margin: 0 0 -2px;
text-indent: 0;
list-style-type: none;
display: flex;
padding-left: 3px
}
menu[role=tablist] button{
z-index: 1;
display: block;
color: #222;
text-decoration: none;
min-width: unset
}
menu[role=tablist] button[aria-selected=true]{
padding-bottom: 2px;margin-top: -2px;background-color: #ece9d8;position: relative;z-index: 8;margin-left: -3px;margin-bottom: 1px
}
menu[role=tablist] button: focus{
outline: 1px dotted #222;outline-offset: -4px
}
menu[role=tablist].justified button{
flex-grow: 1;text-align: center
}
[role=tabpanel]{
padding: 14px;clear: both;background: linear-gradient(180deg,#fcfcfe,#f4f3ee);border: 1px solid #919b9c;position: relative;z-index: 2;margin-bottom: 9px
}
: :-webkit-scrollbar{
width: 17px
}
: :-webkit-scrollbar-corner{
background: #dfdfdf
}
: :-webkit-scrollbar-track: vertical{
background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 17 1' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eeede5' d='M0 0h1m15 0h1'/%3E%3Cpath stroke='%23f3f1ec' d='M1 0h1'/%3E%3Cpath stroke='%23f4f1ec' d='M2 0h1'/%3E%3Cpath stroke='%23f4f3ee' d='M3 0h1'/%3E%3Cpath stroke='%23f5f4ef' d='M4 0h1'/%3E%3Cpath stroke='%23f6f5f0' d='M5 0h1'/%3E%3Cpath stroke='%23f7f7f3' d='M6 0h1'/%3E%3Cpath stroke='%23f9f8f4' d='M7 0h1'/%3E%3Cpath stroke='%23f9f9f7' d='M8 0h1'/%3E%3Cpath stroke='%23fbfbf8' d='M9 0h1'/%3E%3Cpath stroke='%23fbfbf9' d='M10 0h2'/%3E%3Cpath stroke='%23fdfdfa' d='M12 0h1'/%3E%3Cpath stroke='%23fefefb' d='M13 0h3'/%3E%3C/svg%3E")
}
: :-webkit-scrollbar-track: horizontal{
background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 1 17' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eeede5' d='M0 0h1M0 16h1'/%3E%3Cpath stroke='%23f3f1ec' d='M0 1h1'/%3E%3Cpath stroke='%23f4f1ec' d='M0 2h1'/%3E%3Cpath stroke='%23f4f3ee' d='M0 3h1'/%3E%3Cpath stroke='%23f5f4ef' d='M0 4h1'/%3E%3Cpath stroke='%23f6f5f0' d='M0 5h1'/%3E%3Cpath stroke='%23f7f7f3' d='M0 6h1'/%3E%3Cpath stroke='%23f9f8f4' d='M0 7h1'/%3E%3Cpath stroke='%23f9f9f7' d='M0 8h1'/%3E%3Cpath stroke='%23fbfbf8' d='M0 9h1'/%3E%3Cpath stroke='%23fbfbf9' d='M0 10h1m-1 1h1'/%3E%3Cpath stroke='%23fdfdfa' d='M0 12h1'/%3E%3Cpath stroke='%23fefefb' d='M0 13h1m-1 1h1m-1 1h1'/%3E%3C/svg%3E")
}
: :-webkit-scrollbar-thumb{
background-position: 50%;
background-repeat: no-repeat;
background-color: #c8d6fb;
background-size: 7px;
border: 1px solid #fff;
border-radius: 2px;
box-shadow: inset -3px 0 #bad1fc,inset 1px 1px #b7caf5
}
: :-webkit-scrollbar-thumb: vertical{
background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 7 8' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eef4fe' d='M0 0h6M0 2h6M0 4h6M0 6h6'/%3E%3Cpath stroke='%23bad1fc' d='M6 0h1M6 2h1M6 4h1'/%3E%3Cpath stroke='%23c8d6fb' d='M0 1h1M0 3h1M0 5h1M0 7h1'/%3E%3Cpath stroke='%238cb0f8' d='M1 1h6M1 3h6M1 5h6M1 7h6'/%3E%3Cpath stroke='%23bad3fc' d='M6 6h1'/%3E%3C/svg%3E")
}
: :-webkit-scrollbar-thumb: horizontal{
background-size: 8px;background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 8 7' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eef4fe' d='M0 0h1m1 0h1m1 0h1m1 0h1M0 1h1m1 0h1m1 0h1m1 0h1M0 2h1m1 0h1m1 0h1m1 0h1M0 3h1m1 0h1m1 0h1m1 0h1M0 4h1m1 0h1m1 0h1m1 0h1M0 5h1m1 0h1m1 0h1m1 0h1'/%3E%3Cpath stroke='%23c8d6fb' d='M1 0h1m1 0h1m1 0h1m1 0h1'/%3E%3Cpath stroke='%238cb0f8' d='M1 1h1m1 0h1m1 0h1m1 0h1M1 2h1m1 0h1m1 0h1m1 0h1M1 3h1m1 0h1m1 0h1m1 0h1M1 4h1m1 0h1m1 0h1m1 0h1M1 5h1m1 0h1m1 0h1m1 0h1M1 6h1m1 0h1m1 0h1m1 0h1'/%3E%3Cpath stroke='%23bad1fc' d='M0 6h1m1 0h1'/%3E%3Cpath stroke='%23bad3fc' d='M4 6h1m1 0h1'/%3E%3C/svg%3E")
}
: :-webkit-scrollbar-button: vertical: start{
height: 17px;
background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 17 17' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eeede5' d='M0 0h1m15 0h1M0 1h1M0 2h1M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m15 0h1M0 16h1m15 0h1'/%3E%3Cpath stroke='%23fdfdfa' d='M1 0h1'/%3E%3Cpath stroke='%23fff' d='M2 0h14M1 1h1m13 0h1M1 2h1m13 0h1M1 3h1m13 0h1M1 4h1m13 0h1M1 5h1m13 0h1M1 6h1m13 0h1M1 7h1m13 0h1M1 8h1m13 0h1M1 9h1m13 0h1M1 10h1m13 0h1M1 11h1m13 0h1M1 12h1m13 0h1M1 13h1m13 0h1M1 14h1m13 0h1M2 15h13'/%3E%3Cpath stroke='%23e6eefc' d='M2 1h1'/%3E%3Cpath stroke='%23d0dffc' d='M3 1h1M2 2h1'/%3E%3Cpath stroke='%23cad8f9' d='M4 1h1M2 3h1'/%3E%3Cpath stroke='%23c4d2f7' d='M5 1h1'/%3E%3Cpath stroke='%23c0d0f7' d='M6 1h1'/%3E%3Cpath stroke='%23bdcef7' d='M7 1h1M2 6h1'/%3E%3Cpath stroke='%23bbcdf5' d='M8 1h1'/%3E%3Cpath stroke='%23b8cbf6' d='M9 1h1M2 7h1'/%3E%3Cpath stroke='%23b7caf5' d='M10 1h1M2 8h1'/%3E%3Cpath stroke='%23b5c8f7' d='M11 1h1'/%3E%3Cpath stroke='%23b3c7f5' d='M12 1h1'/%3E%3Cpath stroke='%23afc5f4' d='M13 1h1'/%3E%3Cpath stroke='%23dce6f9' d='M14 1h1'/%3E%3Cpath stroke='%23dfe2e1' d='M16 1h1'/%3E%3Cpath stroke='%23e1eafe' d='M3 2h1'/%3E%3Cpath stroke='%23dae6fe' d='M4 2h1M3 3h1'/%3E%3Cpath stroke='%23d4e1fc' d='M5 2h1M3 4h1'/%3E%3Cpath stroke='%23d1e0fd' d='M6 2h1M4 4h1'/%3E%3Cpath stroke='%23d0ddfc' d='M7 2h1M3 5h1'/%3E%3Cpath stroke='%23cedbfd' d='M8 2h1M6 3h1'/%3E%3Cpath stroke='%23cad9fd' d='M9 2h1M7 3h1M5 5h1'/%3E%3Cpath stroke='%23c8d8fb' d='M10 2h1'/%3E%3Cpath stroke='%23c5d6fc' d='M11 2h1m-8 8h1m1 0h1'/%3E%3Cpath stroke='%23c2d3fc' d='M12 2h1m-2 1h1m-9 7h1m0 1h1'/%3E%3Cpath stroke='%23bccefa' d='M13 2h1m-1 2h1m-9 9h2'/%3E%3Cpath stroke='%23b9c9f3' d='M14 2h1M5 14h3'/%3E%3Cpath stroke='%23cfd7dd' d='M16 2h1'/%3E%3Cpath stroke='%23d8e3fc' d='M4 3h1'/%3E%3Cpath stroke='%23d1defd' d='M5 3h1'/%3E%3Cpath stroke='%23c9d8fc' d='M8 3h1M6 4h2M5 6h2M3 7h1'/%3E%3Cpath stroke='%23c5d5fc' d='M9 3h1M3 9h1m3 0h1'/%3E%3Cpath stroke='%23c5d3fc' d='M10 3h1'/%3E%3Cpath stroke='%23bed0fc' d='M12 3h1M9 4h1m-7 7h1m0 1h1'/%3E%3Cpath stroke='%23bccdfa' d='M13 3h1'/%3E%3Cpath stroke='%23baccf4' d='M14 3h1'/%3E%3Cpath stroke='%23bdcbda' d='M16 3h1'/%3E%3Cpath stroke='%23c4d4f7' d='M2 4h1'/%3E%3Cpath stroke='%23cddbfc' d='M5 4h1M3 6h1'/%3E%3Cpath stroke='%23c8d5fb' d='M8 4h1'/%3E%3Cpath stroke='%23bbcefd' d='M10 4h3M9 5h1'/%3E%3Cpath stroke='%23bcccf3' d='M14 4h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b1c2d5' d='M16 4h1'/%3E%3Cpath stroke='%23bed0f8' d='M2 5h1'/%3E%3Cpath stroke='%23ceddfd' d='M4 5h1'/%3E%3Cpath stroke='%23c8d6fb' d='M6 5h2M3 8h2'/%3E%3Cpath stroke='%234d6185' d='M8 5h1M7 6h3M6 7h5M5 8h3m1 0h3M4 9h3m3 0h3m-8 1h1m5 0h1'/%3E%3Cpath stroke='%23bacdfc' d='M10 5h1m1 0h2M3 12h1'/%3E%3Cpath stroke='%23b9cdfb' d='M11 5h1m-2 1h1m1 0h2m-1 1h1'/%3E%3Cpath stroke='%23a8bbd4' d='M16 5h1'/%3E%3Cpath stroke='%23cddafc' d='M4 6h1'/%3E%3Cpath stroke='%23b7cdfc' d='M11 6h1m0 1h1'/%3E%3Cpath stroke='%23a4b8d3' d='M16 6h1'/%3E%3Cpath stroke='%23cad8fd' d='M4 7h2'/%3E%3Cpath stroke='%23b6cefb' d='M11 7h1m0 1h1'/%3E%3Cpath stroke='%23bacbf4' d='M14 7h1'/%3E%3Cpath stroke='%23a0b5d3' d='M16 7h1m-1 1h1m-1 5h1'/%3E%3Cpath stroke='%23c1d3fb' d='M8 8h1'/%3E%3Cpath stroke='%23b6cdfb' d='M13 8h1m-5 5h1'/%3E%3Cpath stroke='%23b9cbf3' d='M14 8h1'/%3E%3Cpath stroke='%23b4c8f6' d='M2 9h1'/%3E%3Cpath stroke='%23c2d5fc' d='M8 9h1m-1 1h1m-3 1h2'/%3E%3Cpath stroke='%23bdd3fb' d='M9 9h1m-2 3h1'/%3E%3Cpath stroke='%23b5cdfa' d='M13 9h1'/%3E%3Cpath stroke='%23b5c9f3' d='M14 9h1'/%3E%3Cpath stroke='%239fb5d2' d='M16 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b1c7f6' d='M2 10h1'/%3E%3Cpath stroke='%23c3d5fd' d='M7 10h1'/%3E%3Cpath stroke='%23bad4fc' d='M9 10h1m-1 1h1'/%3E%3Cpath stroke='%23b2cffb' d='M10 10h1m1 0h1m-2 2h1'/%3E%3Cpath stroke='%23b1cbfa' d='M13 10h1'/%3E%3Cpath stroke='%23b3c8f5' d='M14 10h1m-6 4h2'/%3E%3Cpath stroke='%23adc3f6' d='M2 11h1'/%3E%3Cpath stroke='%23c3d3fd' d='M5 11h1'/%3E%3Cpath stroke='%23c1d5fb' d='M8 11h1'/%3E%3Cpath stroke='%23b7d3fc' d='M10 11h1m-2 1h1'/%3E%3Cpath stroke='%23b3d1fc' d='M11 11h1'/%3E%3Cpath stroke='%23afcefb' d='M12 11h1'/%3E%3Cpath stroke='%23aecafa' d='M13 11h1'/%3E%3Cpath stroke='%23b1c8f3' d='M14 11h1'/%3E%3Cpath stroke='%23acc2f5' d='M2 12h1'/%3E%3Cpath stroke='%23c1d2fb' d='M5 12h1'/%3E%3Cpath stroke='%23bed1fc' d='M6 12h2'/%3E%3Cpath stroke='%23b6d1fb' d='M10 12h1'/%3E%3Cpath stroke='%23afccfb' d='M12 12h1'/%3E%3Cpath stroke='%23adc9f9' d='M13 12h1m-2 1h1'/%3E%3Cpath stroke='%23b1c5f3' d='M14 12h1'/%3E%3Cpath stroke='%23aac0f3' d='M2 13h1'/%3E%3Cpath stroke='%23b7cbf9' d='M3 13h1'/%3E%3Cpath stroke='%23b9cefb' d='M4 13h1'/%3E%3Cpath stroke='%23bbcef9' d='M7 13h1'/%3E%3Cpath stroke='%23b9cffb' d='M8 13h1'/%3E%3Cpath stroke='%23b2cdfb' d='M10 13h1'/%3E%3Cpath stroke='%23b0cbf9' d='M11 13h1'/%3E%3Cpath stroke='%23aec8f7' d='M13 13h1'/%3E%3Cpath stroke='%23b0c5f2' d='M14 13h1'/%3E%3Cpath stroke='%23dbe3f8' d='M2 14h1'/%3E%3Cpath stroke='%23b7c6f1' d='M3 14h1'/%3E%3Cpath stroke='%23b8c9f2' d='M4 14h1m3 0h1'/%3E%3Cpath stroke='%23b2c8f4' d='M11 14h1'/%3E%3Cpath stroke='%23b1c6f3' d='M12 14h1'/%3E%3Cpath stroke='%23b0c4f2' d='M13 14h1'/%3E%3Cpath stroke='%23d9e3f6' d='M14 14h1'/%3E%3Cpath stroke='%23aec0d6' d='M16 14h1'/%3E%3Cpath stroke='%23c3d4e7' d='M1 15h1'/%3E%3Cpath stroke='%23aec4e5' d='M15 15h1'/%3E%3Cpath stroke='%23edf1f3' d='M1 16h1'/%3E%3Cpath stroke='%23aac0e1' d='M2 16h1'/%3E%3Cpath stroke='%2394b1d9' d='M3 16h1'/%3E%3Cpath stroke='%2388a7d8' d='M4 16h1'/%3E%3Cpath stroke='%2383a4d3' d='M5 16h1'/%3E%3Cpath stroke='%237da0d4' d='M6 16h1m3 0h3'/%3E%3Cpath stroke='%237e9fd2' d='M7 16h1'/%3E%3Cpath stroke='%237c9fd3' d='M8 16h2'/%3E%3Cpath stroke='%2382a4d6' d='M13 16h1'/%3E%3Cpath stroke='%2394b0dd' d='M14 16h1'/%3E%3Cpath stroke='%23ecf2f7' d='M15 16h1'/%3E%3C/svg%3E")
}
: :-webkit-scrollbar-button: vertical: end{
height: 17px;
background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 17 17' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eeede5' d='M0 0h1m15 0h1M0 1h1M0 2h1M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m15 0h1M0 16h1m15 0h1'/%3E%3Cpath stroke='%23fdfdfa' d='M1 0h1'/%3E%3Cpath stroke='%23fff' d='M2 0h14M1 1h1m13 0h1M1 2h1m13 0h1M1 3h1m13 0h1M1 4h1m13 0h1M1 5h1m13 0h1M1 6h1m13 0h1M1 7h1m13 0h1M1 8h1m13 0h1M1 9h1m13 0h1M1 10h1m13 0h1M1 11h1m13 0h1M1 12h1m13 0h1M1 13h1m13 0h1M1 14h1m13 0h1M2 15h13'/%3E%3Cpath stroke='%23e6eefc' d='M2 1h1'/%3E%3Cpath stroke='%23d0dffc' d='M3 1h1M2 2h1'/%3E%3Cpath stroke='%23cad8f9' d='M4 1h1M2 3h1'/%3E%3Cpath stroke='%23c4d2f7' d='M5 1h1'/%3E%3Cpath stroke='%23c0d0f7' d='M6 1h1'/%3E%3Cpath stroke='%23bdcef7' d='M7 1h1M2 6h1'/%3E%3Cpath stroke='%23bbcdf5' d='M8 1h1'/%3E%3Cpath stroke='%23b8cbf6' d='M9 1h1M2 7h1'/%3E%3Cpath stroke='%23b7caf5' d='M10 1h1M2 8h1'/%3E%3Cpath stroke='%23b5c8f7' d='M11 1h1'/%3E%3Cpath stroke='%23b3c7f5' d='M12 1h1'/%3E%3Cpath stroke='%23afc5f4' d='M13 1h1'/%3E%3Cpath stroke='%23dce6f9' d='M14 1h1'/%3E%3Cpath stroke='%23dfe2e1' d='M16 1h1'/%3E%3Cpath stroke='%23e1eafe' d='M3 2h1'/%3E%3Cpath stroke='%23dae6fe' d='M4 2h1M3 3h1'/%3E%3Cpath stroke='%23d4e1fc' d='M5 2h1M3 4h1'/%3E%3Cpath stroke='%23d1e0fd' d='M6 2h1M4 4h1'/%3E%3Cpath stroke='%23d0ddfc' d='M7 2h1M3 5h1'/%3E%3Cpath stroke='%23cedbfd' d='M8 2h1M6 3h1'/%3E%3Cpath stroke='%23cad9fd' d='M9 2h1M7 3h1M5 5h1'/%3E%3Cpath stroke='%23c8d8fb' d='M10 2h1'/%3E%3Cpath stroke='%23c5d6fc' d='M11 2h1m-8 8h3'/%3E%3Cpath stroke='%23c2d3fc' d='M12 2h1m-2 1h1m-9 7h1m0 1h1'/%3E%3Cpath stroke='%23bccefa' d='M13 2h1m-1 2h1m-9 9h2'/%3E%3Cpath stroke='%23b9c9f3' d='M14 2h1M5 14h3'/%3E%3Cpath stroke='%23cfd7dd' d='M16 2h1'/%3E%3Cpath stroke='%23d8e3fc' d='M4 3h1'/%3E%3Cpath stroke='%23d1defd' d='M5 3h1'/%3E%3Cpath stroke='%23c9d8fc' d='M8 3h1M6 4h2M6 6h2M3 7h1'/%3E%3Cpath 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}
.window{
box-shadow: inset -1px -1px #00138c,inset 1px 1px #0831d9,inset -2px -2px #001ea0,inset 2px 2px #166aee,inset -3px -3px #003bda,inset 3px 3px #0855dd;
border-top-left-radius: 8px;
border-top-right-radius: 8px;
padding: 0 0 3px;
-webkit-font-smoothing: antialiased
}
.title-bar{
background: linear-gradient(180deg,#0997ff,#0053ee 8%,#0050ee 40%,#06f 88%,#06f 93%,#005bff 95%,#003dd7 96%,#003dd7);
padding: 3px 5px 3px 3px;
border-top: 1px solid #0831d9;
border-left: 1px solid #0831d9;
border-right: 1px solid #001ea0;
border-top-left-radius: 8px;
border-top-right-radius: 7px;
font-size: 13px;
text-shadow: 1px 1px #0f1089;
height: 21px
}
.title-bar-text{
padding-left: 3px
}
.title-bar-controls{
display: flex
}
.title-bar-controls button{
min-width: 21px;
min-height: 21px;
margin-left: 2px;
background-repeat: no-repeat;
background-position: 50%;
box-shadow: none;
background-color: #0050ee;
transition: background .1s;
border: none
}
.title-bar-controls button: active,.title-bar-controls button: focus,.title-bar-controls button: hover{
box-shadow: none!important
}
.title-bar-controls button[aria-label=Minimize]{
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}
.title-bar-controls button[aria-label=Maximize]: not(: disabled): active{
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}
.title-bar-controls button[aria-label=Restore]{
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}
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}
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stroke='%23b5381a' d='M9 4h1M4 9h1'/%3E%3Cpath stroke='%23b8391a' d='M10 4h1m-7 6h1'/%3E%3Cpath stroke='%23ba3a1b' d='M11 4h1m-8 7h2'/%3E%3Cpath stroke='%23bc3b1c' d='M12 4h1m-9 8h1'/%3E%3Cpath stroke='%23bd3c1c' d='M13 4h1m-1 1h1m-2 1h1m-7 6h1m-3 1h2'/%3E%3Cpath stroke='%23be3d1c' d='M14 4h3m-1 1h1m-1 1h1M4 14h1m-1 1h1m-1 1h2'/%3E%3Cpath stroke='%23bf3d1c' d='M17 4h3m-3 1h3m-2 1h2m-1 1h1M4 17h2m-2 1h4m-4 1h4'/%3E%3Cpath stroke='%235b1d0d' d='M1 5h1'/%3E%3Cpath stroke='%239c3016' d='M3 5h1'/%3E%3Cpath stroke='%23a43217' d='M4 5h1'/%3E%3Cpath stroke='%23b8553e' d='M5 5h1'/%3E%3Cpath stroke='%23d59485' d='M6 5h1M5 6h1'/%3E%3Cpath stroke='%23b33619' d='M7 5h1'/%3E%3Cpath stroke='%23b53719' d='M8 5h1'/%3E%3Cpath stroke='%23b8381a' d='M9 5h1M6 8h1'/%3E%3Cpath stroke='%23b9391b' d='M10 5h1'/%3E%3Cpath stroke='%23ba391b' d='M11 5h1M6 9h1m-2 1h1'/%3E%3Cpath stroke='%23bc3b1b' d='M12 5h1m-2 1h1m-6 5h1m-2 1h1'/%3E%3Cpath stroke='%23dc9887' d='M14 5h1'/%3E%3Cpath stroke='%23c85d42' d='M15 5h1M5 15h1'/%3E%3Cpath stroke='%23611f0e' d='M1 6h1'/%3E%3Cpath stroke='%23a23217' d='M3 6h1'/%3E%3Cpath stroke='%23d79585' d='M6 6h1'/%3E%3Cpath stroke='%23d89585' d='M7 6h1'/%3E%3Cpath stroke='%23b8371a' d='M8 6h1'/%3E%3Cpath stroke='%23ba391a' d='M9 6h1'/%3E%3Cpath stroke='%23bb3a1b' d='M10 6h1m-5 4h1'/%3E%3Cpath stroke='%23dd9887' d='M13 6h3m-4 1h1m-2 1h1M9 9h1m-2 2h1m-2 1h1m-2 1h1m-2 1h2'/%3E%3Cpath stroke='%23c03e1d' d='M17 6h1m-2 1h3m0 1h1m-1 1h1M7 16h1m-2 1h2m0 1h1'/%3E%3Cpath stroke='%2365200e' d='M1 7h1'/%3E%3Cpath stroke='%23902d15' d='M2 7h1'/%3E%3Cpath stroke='%23a73418' d='M3 7h1'/%3E%3Cpath stroke='%23af3518' d='M4 7h1'/%3E%3Cpath stroke='%23b43619' d='M5 7h1'/%3E%3Cpath stroke='%23d99585' d='M6 7h1'/%3E%3Cpath stroke='%23da9686' d='M7 7h1'/%3E%3Cpath stroke='%23db9686' d='M8 7h1M7 8h1'/%3E%3Cpath stroke='%23bc3a1b' d='M9 7h1M7 9h1'/%3E%3Cpath stroke='%23bd3b1b' d='M10 7h1m-4 3h1'/%3E%3Cpath stroke='%23be3c1c' d='M11 7h1m-2 1h1m-3 2h1m-2 1h1'/%3E%3Cpath stroke='%23de9987' d='M13 7h2m-3 1h2m-4 1h2m-3 1h1m-2 2h1m-2 2h1'/%3E%3Cpath stroke='%23c03f1d' d='M15 7h1m-9 8h1'/%3E%3Cpath stroke='%236a220f' d='M1 8h1'/%3E%3Cpath stroke='%23952f15' d='M2 8h1'/%3E%3Cpath stroke='%23ac3518' d='M3 8h1'/%3E%3Cpath stroke='%23b63719' d='M5 8h1'/%3E%3Cpath stroke='%23dc9786' d='M8 8h2M8 9h1'/%3E%3Cpath stroke='%23c2401d' d='M14 8h1m2 0h1m1 3h1M8 14h1m-1 2h1m-1 1h1m0 1h1m1 1h1'/%3E%3Cpath stroke='%23c2401e' d='M15 8h2m1 1h1M8 15h1'/%3E%3Cpath stroke='%23c13f1d' d='M18 8h1m0 2h1M9 19h2'/%3E%3Cpath stroke='%23702410' d='M1 9h1'/%3E%3Cpath stroke='%239b3016' d='M2 9h1'/%3E%3Cpath stroke='%23b03619' d='M3 9h1'/%3E%3Cpath stroke='%23b9381a' d='M5 9h1'/%3E%3Cpath stroke='%23df9a88' d='M12 9h1m-2 1h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%23c4421e' d='M13 9h1m2 0h2m0 1h1M9 13h1m9 1h1m-1 1h1M9 16h1m9 0h1M9 17h1m0 1h1m3 1h3'/%3E%3Cpath stroke='%23c5431e' d='M14 9h1'/%3E%3Cpath stroke='%23c5431f' d='M15 9h1m-4 1h1m5 1h1m-9 1h1m-2 2h1m-1 1h1m0 2h1m0 1h1m6 0h1'/%3E%3Cpath stroke='%239e3217' d='M2 10h1'/%3E%3Cpath stroke='%23b4381a' d='M3 10h1'/%3E%3Cpath stroke='%23df9a87' d='M10 10h1m-2 1h1m-2 2h1'/%3E%3Cpath stroke='%23c6441f' d='M13 10h1m3 0h1m-8 3h1m-1 3h1'/%3E%3Cpath stroke='%23c74520' d='M14 10h2m-6 4h1m-1 1h1m7 2h1m-7 1h1m4 0h1'/%3E%3Cpath stroke='%23c7451f' d='M16 10h1m1 2h1'/%3E%3Cpath stroke='%237b2711' d='M1 11h1'/%3E%3Cpath stroke='%23a13217' d='M2 11h1'/%3E%3Cpath stroke='%23b7391a' d='M3 11h1'/%3E%3Cpath stroke='%23e09b88' d='M11 11h1'/%3E%3Cpath stroke='%23e29d89' d='M12 11h1'/%3E%3Cpath stroke='%23c94621' d='M13 11h1m-3 2h1'/%3E%3Cpath stroke='%23ca4721' d='M14 11h1m2 1h1m-7 2h1m-1 1h1m0 2h1m2 1h1'/%3E%3Cpath stroke='%23ca4821' d='M15 11h1m1 6h1'/%3E%3Cpath stroke='%23c94620' d='M16 11h1m1 3h1m-8 2h1m6 0h1'/%3E%3Cpath stroke='%23c84620' d='M17 11h1m0 2h1'/%3E%3Cpath stroke='%23a53418' d='M2 12h1'/%3E%3Cpath stroke='%23b83a1b' d='M3 12h1'/%3E%3Cpath stroke='%23e19d89' d='M11 12h1'/%3E%3Cpath stroke='%23e39e89' d='M12 12h1'/%3E%3Cpath stroke='%23e0947c' d='M13 12h1'/%3E%3Cpath stroke='%23cc4a22' d='M14 12h1m-3 2h1m4 0h1m-6 1h1'/%3E%3Cpath stroke='%23cd4a22' d='M15 12h1m0 1h1m0 2h1m-5 1h1m1 1h1'/%3E%3Cpath stroke='%23cb4922' d='M16 12h1m0 1h1m-5 4h1'/%3E%3Cpath stroke='%23c3411e' d='M19 12h1m-1 1h1m-1 4h1m-8 2h2m3 0h1'/%3E%3Cpath stroke='%23a93618' d='M2 13h1'/%3E%3Cpath stroke='%23dd9987' d='M7 13h1m-2 2h1'/%3E%3Cpath stroke='%23e39f8a' d='M12 13h1'/%3E%3Cpath stroke='%23e59f8b' d='M13 13h1'/%3E%3Cpath stroke='%23e5a08b' d='M14 13h1m-2 1h1'/%3E%3Cpath stroke='%23ce4c23' d='M15 13h1m0 3h1'/%3E%3Cpath stroke='%23882b13' d='M1 14h1'/%3E%3Cpath stroke='%23e6a08b' d='M14 14h1'/%3E%3Cpath stroke='%23e6a18b' d='M15 14h1m-2 1h1'/%3E%3Cpath stroke='%23ce4b23' d='M16 14h1m-4 1h1'/%3E%3Cpath stroke='%238b2c14' d='M1 15h1m-1 1h1'/%3E%3Cpath stroke='%23ac3619' d='M2 15h1'/%3E%3Cpath stroke='%23d76b48' d='M15 15h1'/%3E%3Cpath stroke='%23cf4c23' d='M16 15h1m-2 1h1'/%3E%3Cpath stroke='%23c94721' d='M18 15h1m-3 3h1'/%3E%3Cpath stroke='%23bb3c1b' d='M3 16h1'/%3E%3Cpath stroke='%23bf3e1d' d='M6 16h1'/%3E%3Cpath stroke='%23cb4821' d='M12 16h1'/%3E%3Cpath stroke='%23cd4b23' d='M14 16h1'/%3E%3Cpath stroke='%23cc4922' d='M17 16h1m-4 1h1m1 0h1'/%3E%3Cpath stroke='%238d2d14' d='M1 17h1'/%3E%3Cpath stroke='%23bc3c1b' d='M3 17h1m-1 1h1'/%3E%3Cpath stroke='%23c84520' d='M11 17h1m1 1h1'/%3E%3Cpath stroke='%23ae3719' d='M2 18h1'/%3E%3Cpath stroke='%23c94720' d='M14 18h1'/%3E%3Cpath stroke='%23c95839' d='M19 18h1'/%3E%3Cpath stroke='%23a7bdf0' d='M0 19h1m0 1h1'/%3E%3Cpath stroke='%23ead7d3' d='M1 19h1'/%3E%3Cpath stroke='%23b34e35' d='M2 19h1'/%3E%3Cpath stroke='%23c03e1c' d='M8 19h1'/%3E%3Cpath stroke='%23c9583a' d='M18 19h1'/%3E%3Cpath stroke='%23f3dbd4' d='M19 19h1'/%3E%3Cpath stroke='%23a7bcef' d='M20 19h1m-2 1h1'/%3E%3C/svg%3E")
}
.status-bar{
margin: 0 3px;
box-shadow: inset 0 1px 2px grey;
padding: 2px 1px;
gap: 0
}
.status-bar-field{
-webkit-font-smoothing: antialiased;
box-shadow: none;
padding: 1px 2px;
border-right: 1px solid rgba(208,206,191,.75);
border-left: 1px solid hsla(0,0%,100%,.75)
}
.status-bar-field: first-of-type{
border-left: none
}
.status-bar-field: last-of-type{
border-right: none
}
button{
-webkit-font-smoothing: antialiased;
box-sizing: border-box;
border: 1px solid #003c74;
background: linear-gradient(180deg,#fff,#ecebe5 86%,#d8d0c4);
box-shadow: none;
border-radius: 3px
}
button: not(: disabled).active,button: not(: disabled): active{
box-shadow: none;
background: linear-gradient(180deg,#cdcac3,#e3e3db 8%,#e5e5de 94%,#f2f2f1)
}
button: not(: disabled): hover{
box-shadow: inset -1px 1px #fff0cf,inset 1px 2px #fdd889,inset -2px 2px #fbc761,inset 2px -2px #e5a01a
}
button.focused,button: focus{
box-shadow: inset -1px 1px #cee7ff,inset 1px 2px #98b8ea,inset -2px 2px #bcd4f6,inset 1px -1px #89ade4,inset 2px -2px #89ade4
}
button: :-moz-focus-inner{
border: 0
}
input,label,option,select,textarea{
-webkit-font-smoothing: antialiased
}
input[type=radio]{
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
margin: 0;
background: 0;
position: fixed;
opacity: 0;
border: none
}
input[type=radio]+label{
line-height: 16px
}
input[type=radio]+label: before{
background: linear-gradient(135deg,#dcdcd7,#fff);
border-radius: 50%;
border: 1px solid #1d5281
}
input[type=radio]: not([disabled]): not(: active)+label: hover: before{
box-shadow: inset -2px -2px #f8b636,inset 2px 2px #fedf9c
}
input[type=radio]: active+label: before{
background: linear-gradient(135deg,#b0b0a7,#e3e1d2)
}
input[type=radio]: checked+label: after{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 5 5' shape-rendering='crispEdges'%3E%3Cpath stroke='%23a9dca6' d='M1 0h1M0 1h1'/%3E%3Cpath stroke='%234dbf4a' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23a0d29e' d='M3 0h1M0 3h1'/%3E%3Cpath stroke='%2355d551' d='M1 1h1'/%3E%3Cpath stroke='%2343c33f' d='M2 1h1'/%3E%3Cpath stroke='%2329a826' d='M3 1h1'/%3E%3Cpath stroke='%239acc98' d='M4 1h1M1 4h1'/%3E%3Cpath stroke='%2342c33f' d='M1 2h1'/%3E%3Cpath stroke='%2338b935' d='M2 2h1'/%3E%3Cpath stroke='%2321a121' d='M3 2h1'/%3E%3Cpath stroke='%23269623' d='M4 2h1'/%3E%3Cpath stroke='%232aa827' d='M1 3h1'/%3E%3Cpath stroke='%2322a220' d='M2 3h1'/%3E%3Cpath stroke='%23139210' d='M3 3h1'/%3E%3Cpath stroke='%2398c897' d='M4 3h1'/%3E%3Cpath stroke='%23249624' d='M2 4h1'/%3E%3Cpath stroke='%2398c997' d='M3 4h1'/%3E%3C/svg%3E")
}
input[type=radio]: focus+label{
outline: 1px dotted #000
}
input[type=radio][disabled]+label: before{
border: 1px solid #cac8bb;
background: #fff
}
input[type=radio][disabled]: checked+label: after{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 5 5' shape-rendering='crispEdges'%3E%3Cpath stroke='%23e8e6da' d='M1 0h1M0 1h1'/%3E%3Cpath stroke='%23d2ceb5' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23e5e3d4' d='M3 0h1M0 3h1'/%3E%3Cpath stroke='%23d7d3bd' d='M1 1h1'/%3E%3Cpath stroke='%23d0ccb2' d='M2 1h1M1 2h1'/%3E%3Cpath stroke='%23c7c2a2' d='M3 1h1M1 3h1'/%3E%3Cpath stroke='%23e2dfd0' d='M4 1h1M1 4h1'/%3E%3Cpath stroke='%23cdc8ac' d='M2 2h1'/%3E%3Cpath stroke='%23c5bf9f' d='M3 2h1M2 3h1'/%3E%3Cpath stroke='%23c3bd9c' d='M4 2h1'/%3E%3Cpath stroke='%23bfb995' d='M3 3h1'/%3E%3Cpath stroke='%23e2dfcf' d='M4 3h1M3 4h1'/%3E%3Cpath stroke='%23c4be9d' d='M2 4h1'/%3E%3C/svg%3E")
}
input[type=email],input[type=password],textarea: :selection{
background: #2267cb;
color: #fff
}
input[type=range]: :-webkit-slider-thumb{
height: 21px;
width: 11px;
background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 11 21' shape-rendering='crispEdges'%3E%3Cpath stroke='%23becbd3' d='M1 0h1M0 1h1'/%3E%3Cpath stroke='%23b6c5cd' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23b5c4cd' d='M3 0h5M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23afbfc8' d='M8 0h1M0 14h1'/%3E%3Cpath stroke='%239fb2be' d='M9 0h1M0 15h1'/%3E%3Cpath stroke='%23a6d1b1' d='M1 1h1'/%3E%3Cpath stroke='%236fd16e' d='M2 1h1M1 2h1'/%3E%3Cpath stroke='%2367ce65' d='M3 1h1M1 3h1'/%3E%3Cpath stroke='%2366ce64' d='M4 1h3'/%3E%3Cpath stroke='%2362cd61' d='M7 1h1'/%3E%3Cpath stroke='%2345c343' d='M8 1h1M7 2h1'/%3E%3Cpath stroke='%2363ac76' d='M9 1h1M2 16h1m0 1h1m0 1h1'/%3E%3Cpath stroke='%23879aa6' d='M10 1h1'/%3E%3Cpath stroke='%2363cd62' d='M2 2h1'/%3E%3Cpath stroke='%2349c547' d='M3 2h1M2 3h1'/%3E%3Cpath stroke='%2347c446' d='M4 2h3'/%3E%3Cpath stroke='%2321b71f' d='M8 2h1'/%3E%3Cpath stroke='%231da41c' d='M9 2h1'/%3E%3Cpath stroke='%237d8e99' d='M10 2h1'/%3E%3Cpath stroke='%2325b923' d='M3 3h1'/%3E%3Cpath stroke='%2321b81f' d='M4 3h4M2 15h1'/%3E%3Cpath stroke='%231ea71c' d='M8 3h1'/%3E%3Cpath stroke='%231b9619' d='M9 3h1'/%3E%3Cpath stroke='%23778892' d='M10 3h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f7f7f4' d='M1 4h1M1 5h1M1 6h1M1 7h1M1 8h1M1 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f5f5f2' d='M2 4h1M2 5h1M2 6h1M2 7h1M2 8h1M2 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f3f3ef' d='M3 4h5M3 5h5M3 6h5M3 7h5M3 8h5M3 9h5m-5 1h5m-5 1h5m-5 1h5m-5 1h4m-4 1h3m-2 1h1'/%3E%3Cpath stroke='%23dcdcd9' d='M8 4h1M8 5h1M8 6h1M8 7h1M8 8h1M8 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c3c3c0' d='M9 4h1M9 5h1M9 6h1M9 7h1M9 8h1M9 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f1f1ed' d='M7 13h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%23dbdbd8' d='M8 13h1'/%3E%3Cpath stroke='%23c4c4c1' d='M9 13h1'/%3E%3Cpath stroke='%234bc549' d='M1 14h1'/%3E%3Cpath stroke='%23f4f4f1' d='M2 14h1'/%3E%3Cpath stroke='%23e6e6e2' d='M7 14h1m-2 1h1'/%3E%3Cpath stroke='%23cececa' d='M8 14h1'/%3E%3Cpath stroke='%231a9319' d='M9 14h1'/%3E%3Cpath stroke='%23788993' d='M10 14h1'/%3E%3Cpath stroke='%2369b17b' d='M1 15h1'/%3E%3Cpath stroke='%23f2f2ee' d='M3 15h1m0 1h1'/%3E%3Cpath stroke='%23d0d0cc' d='M7 15h1m-2 1h1'/%3E%3Cpath stroke='%231a9118' d='M8 15h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%234c845a' d='M9 15h1'/%3E%3Cpath stroke='%2372838d' d='M10 15h1'/%3E%3Cpath stroke='%2391a6b2' d='M1 16h1m0 1h1m0 1h1m0 1h1'/%3E%3Cpath stroke='%2321b61f' d='M3 16h1m0 1h1'/%3E%3Cpath stroke='%23e7e7e3' d='M5 16h1'/%3E%3Cpath stroke='%234b8259' d='M8 16h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%236e7e88' d='M9 16h1m-2 1h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%23d7d7d4' d='M5 17h1'/%3E%3Cpath stroke='%231da21b' d='M5 18h1'/%3E%3Cpath stroke='%23589868' d='M5 19h1'/%3E%3Cpath stroke='%2380929e' d='M5 20h1'/%3E%3C/svg%3E");
transform: translateY(-8px)
}
input[type=range]: :-moz-range-thumb{
height: 21px;
width: 11px;
border: 0;
border-radius: 0;
background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 11 21' shape-rendering='crispEdges'%3E%3Cpath stroke='%23becbd3' d='M1 0h1M0 1h1'/%3E%3Cpath stroke='%23b6c5cd' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23b5c4cd' d='M3 0h5M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23afbfc8' d='M8 0h1M0 14h1'/%3E%3Cpath stroke='%239fb2be' d='M9 0h1M0 15h1'/%3E%3Cpath stroke='%23a6d1b1' d='M1 1h1'/%3E%3Cpath stroke='%236fd16e' d='M2 1h1M1 2h1'/%3E%3Cpath stroke='%2367ce65' d='M3 1h1M1 3h1'/%3E%3Cpath stroke='%2366ce64' d='M4 1h3'/%3E%3Cpath stroke='%2362cd61' d='M7 1h1'/%3E%3Cpath stroke='%2345c343' d='M8 1h1M7 2h1'/%3E%3Cpath stroke='%2363ac76' d='M9 1h1M2 16h1m0 1h1m0 1h1'/%3E%3Cpath stroke='%23879aa6' d='M10 1h1'/%3E%3Cpath stroke='%2363cd62' d='M2 2h1'/%3E%3Cpath stroke='%2349c547' d='M3 2h1M2 3h1'/%3E%3Cpath stroke='%2347c446' d='M4 2h3'/%3E%3Cpath stroke='%2321b71f' d='M8 2h1'/%3E%3Cpath stroke='%231da41c' d='M9 2h1'/%3E%3Cpath stroke='%237d8e99' d='M10 2h1'/%3E%3Cpath stroke='%2325b923' d='M3 3h1'/%3E%3Cpath stroke='%2321b81f' d='M4 3h4M2 15h1'/%3E%3Cpath stroke='%231ea71c' d='M8 3h1'/%3E%3Cpath stroke='%231b9619' d='M9 3h1'/%3E%3Cpath stroke='%23778892' d='M10 3h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f7f7f4' d='M1 4h1M1 5h1M1 6h1M1 7h1M1 8h1M1 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f5f5f2' d='M2 4h1M2 5h1M2 6h1M2 7h1M2 8h1M2 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f3f3ef' d='M3 4h5M3 5h5M3 6h5M3 7h5M3 8h5M3 9h5m-5 1h5m-5 1h5m-5 1h5m-5 1h4m-4 1h3m-2 1h1'/%3E%3Cpath stroke='%23dcdcd9' d='M8 4h1M8 5h1M8 6h1M8 7h1M8 8h1M8 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c3c3c0' d='M9 4h1M9 5h1M9 6h1M9 7h1M9 8h1M9 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f1f1ed' d='M7 13h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%23dbdbd8' d='M8 13h1'/%3E%3Cpath stroke='%23c4c4c1' d='M9 13h1'/%3E%3Cpath stroke='%234bc549' d='M1 14h1'/%3E%3Cpath stroke='%23f4f4f1' d='M2 14h1'/%3E%3Cpath stroke='%23e6e6e2' d='M7 14h1m-2 1h1'/%3E%3Cpath stroke='%23cececa' d='M8 14h1'/%3E%3Cpath stroke='%231a9319' d='M9 14h1'/%3E%3Cpath stroke='%23788993' d='M10 14h1'/%3E%3Cpath stroke='%2369b17b' d='M1 15h1'/%3E%3Cpath stroke='%23f2f2ee' d='M3 15h1m0 1h1'/%3E%3Cpath stroke='%23d0d0cc' d='M7 15h1m-2 1h1'/%3E%3Cpath stroke='%231a9118' d='M8 15h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%234c845a' d='M9 15h1'/%3E%3Cpath stroke='%2372838d' d='M10 15h1'/%3E%3Cpath stroke='%2391a6b2' d='M1 16h1m0 1h1m0 1h1m0 1h1'/%3E%3Cpath stroke='%2321b61f' d='M3 16h1m0 1h1'/%3E%3Cpath stroke='%23e7e7e3' d='M5 16h1'/%3E%3Cpath stroke='%234b8259' d='M8 16h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%236e7e88' d='M9 16h1m-2 1h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%23d7d7d4' d='M5 17h1'/%3E%3Cpath stroke='%231da21b' d='M5 18h1'/%3E%3Cpath stroke='%23589868' d='M5 19h1'/%3E%3Cpath stroke='%2380929e' d='M5 20h1'/%3E%3C/svg%3E");
transform: translateY(2px)
}
input[type=range]: :-webkit-slider-runnable-track{
width: 100%;
height: 2px;
box-sizing: border-box;
background: #ecebe4;
border-right: 1px solid #f3f2ea;
border-bottom: 1px solid #f3f2ea;
border-radius: 2px;
box-shadow: 1px 0 0 #fff,1px 1px 0 #fff,0 1px 0 #fff,-1px 0 0 #9d9c99,-1px -1px 0 #9d9c99,0 -1px 0 #9d9c99,-1px 1px 0 #fff,1px -1px #9d9c99
}
input[type=range]: :-moz-range-track{
width: 100%;
height: 2px;
box-sizing: border-box;
background: #ecebe4;
border-right: 1px solid #f3f2ea;
border-bottom: 1px solid #f3f2ea;
border-radius: 2px;
box-shadow: 1px 0 0 #fff,1px 1px 0 #fff,0 1px 0 #fff,-1px 0 0 #9d9c99,-1px -1px 0 #9d9c99,0 -1px 0 #9d9c99,-1px 1px 0 #fff,1px -1px #9d9c99
}
input[type=range].has-box-indicator: :-webkit-slider-thumb{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 11 22' shape-rendering='crispEdges'%3E%3Cpath stroke='%23f2f1e7' d='M0 0h1m9 0h1M0 21h1m9 0h1'/%3E%3Cpath stroke='%23879aa6' d='M1 0h1m8 20h1'/%3E%3Cpath stroke='%237d8e99' d='M2 0h1m7 19h1'/%3E%3Cpath stroke='%23778892' d='M3 0h5m2 3h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23788993' d='M8 0h1m1 2h1'/%3E%3Cpath stroke='%2372838d' d='M9 0h1m0 1h1'/%3E%3Cpath stroke='%239fb2be' d='M0 1h1m8 20h1'/%3E%3Cpath stroke='%2363af76' d='M1 1h1m7 19h1'/%3E%3Cpath stroke='%231eab1c' d='M2 1h1m6 18h1'/%3E%3Cpath stroke='%231c9d1a' d='M3 1h1'/%3E%3Cpath stroke='%231b9a1a' d='M4 1h3m1 0h1m0 1h1'/%3E%3Cpath stroke='%231b9b1a' d='M7 1h1'/%3E%3Cpath stroke='%234d875b' d='M9 1h1'/%3E%3Cpath stroke='%23afbfc8' d='M0 2h1m7 19h1'/%3E%3Cpath stroke='%2346ca44' d='M1 2h1m5 17h1m0 1h1'/%3E%3Cpath stroke='%2322be20' d='M2 2h1m5 17h1'/%3E%3Cpath stroke='%231faf1d' d='M3 2h1'/%3E%3Cpath stroke='%231fae1d' d='M4 2h3'/%3E%3Cpath stroke='%231fad1d' d='M7 2h1'/%3E%3Cpath stroke='%231da11b' d='M8 2h1'/%3E%3Cpath stroke='%23b5c4cd' d='M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m2 3h5'/%3E%3Cpath stroke='%23f7f7f4' d='M1 3h1M1 4h1M1 5h1M1 6h1M1 7h1M1 8h1M1 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f5f5f2' d='M2 3h1M2 4h1M2 5h1M2 6h1M2 7h1M2 8h1M2 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f3f3ef' d='M3 3h4M3 4h5M3 5h5M3 6h5M3 7h5M3 8h5M3 9h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5'/%3E%3Cpath stroke='%23f1f1ed' d='M7 3h1'/%3E%3Cpath stroke='%23dbdbd8' d='M8 3h1'/%3E%3Cpath stroke='%23c4c4c1' d='M9 3h1'/%3E%3Cpath stroke='%23ddddd9' d='M8 4h1M8 18h1'/%3E%3Cpath stroke='%23c6c6c3' d='M9 4h1M9 18h1'/%3E%3Cpath stroke='%23dcdcd9' d='M8 5h1M8 6h1M8 7h1M8 8h1M8 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c3c3c0' d='M9 5h1M9 6h1M9 7h1M9 8h1M9 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b6c5cd' d='M0 19h1m1 2h1'/%3E%3Cpath stroke='%2370d66f' d='M1 19h1m0 1h1'/%3E%3Cpath stroke='%2364d362' d='M2 19h1'/%3E%3Cpath stroke='%234acb48' d='M3 19h1'/%3E%3Cpath stroke='%2348cb46' d='M4 19h3'/%3E%3Cpath stroke='%23becbd3' d='M0 20h1m0 1h1'/%3E%3Cpath stroke='%23a6d2b1' d='M1 20h1'/%3E%3Cpath stroke='%2367d466' d='M3 20h1'/%3E%3Cpath stroke='%2366d465' d='M4 20h3'/%3E%3Cpath stroke='%2363d362' d='M7 20h1'/%3E%3C/svg%3E");transform: translateY(-10px)
}
input[type=range].has-box-indicator: :-moz-range-thumb{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 11 22' shape-rendering='crispEdges'%3E%3Cpath stroke='%23f2f1e7' d='M0 0h1m9 0h1M0 21h1m9 0h1'/%3E%3Cpath stroke='%23879aa6' d='M1 0h1m8 20h1'/%3E%3Cpath stroke='%237d8e99' d='M2 0h1m7 19h1'/%3E%3Cpath stroke='%23778892' d='M3 0h5m2 3h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23788993' d='M8 0h1m1 2h1'/%3E%3Cpath stroke='%2372838d' d='M9 0h1m0 1h1'/%3E%3Cpath stroke='%239fb2be' d='M0 1h1m8 20h1'/%3E%3Cpath stroke='%2363af76' d='M1 1h1m7 19h1'/%3E%3Cpath stroke='%231eab1c' d='M2 1h1m6 18h1'/%3E%3Cpath stroke='%231c9d1a' d='M3 1h1'/%3E%3Cpath stroke='%231b9a1a' d='M4 1h3m1 0h1m0 1h1'/%3E%3Cpath stroke='%231b9b1a' d='M7 1h1'/%3E%3Cpath stroke='%234d875b' d='M9 1h1'/%3E%3Cpath stroke='%23afbfc8' d='M0 2h1m7 19h1'/%3E%3Cpath stroke='%2346ca44' d='M1 2h1m5 17h1m0 1h1'/%3E%3Cpath stroke='%2322be20' d='M2 2h1m5 17h1'/%3E%3Cpath stroke='%231faf1d' d='M3 2h1'/%3E%3Cpath stroke='%231fae1d' d='M4 2h3'/%3E%3Cpath stroke='%231fad1d' d='M7 2h1'/%3E%3Cpath stroke='%231da11b' d='M8 2h1'/%3E%3Cpath stroke='%23b5c4cd' d='M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m2 3h5'/%3E%3Cpath stroke='%23f7f7f4' d='M1 3h1M1 4h1M1 5h1M1 6h1M1 7h1M1 8h1M1 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f5f5f2' d='M2 3h1M2 4h1M2 5h1M2 6h1M2 7h1M2 8h1M2 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f3f3ef' d='M3 3h4M3 4h5M3 5h5M3 6h5M3 7h5M3 8h5M3 9h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5'/%3E%3Cpath stroke='%23f1f1ed' d='M7 3h1'/%3E%3Cpath stroke='%23dbdbd8' d='M8 3h1'/%3E%3Cpath stroke='%23c4c4c1' d='M9 3h1'/%3E%3Cpath stroke='%23ddddd9' d='M8 4h1M8 18h1'/%3E%3Cpath stroke='%23c6c6c3' d='M9 4h1M9 18h1'/%3E%3Cpath stroke='%23dcdcd9' d='M8 5h1M8 6h1M8 7h1M8 8h1M8 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c3c3c0' d='M9 5h1M9 6h1M9 7h1M9 8h1M9 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b6c5cd' d='M0 19h1m1 2h1'/%3E%3Cpath stroke='%2370d66f' d='M1 19h1m0 1h1'/%3E%3Cpath stroke='%2364d362' d='M2 19h1'/%3E%3Cpath stroke='%234acb48' d='M3 19h1'/%3E%3Cpath stroke='%2348cb46' d='M4 19h3'/%3E%3Cpath stroke='%23becbd3' d='M0 20h1m0 1h1'/%3E%3Cpath stroke='%23a6d2b1' d='M1 20h1'/%3E%3Cpath stroke='%2367d466' d='M3 20h1'/%3E%3Cpath stroke='%2366d465' d='M4 20h3'/%3E%3Cpath stroke='%2363d362' d='M7 20h1'/%3E%3C/svg%3E");transform: translateY(0)
}
.is-vertical>input[type=range]: :-webkit-slider-runnable-track{
border-left: 1px solid #f3f2ea;
border-right: 0;
border-bottom: 1px solid #f3f2ea;
box-shadow: -1px 0 0 #fff,-1px 1px 0 #fff,0 1px 0 #fff,1px 0 0 #9d9c99,1px -1px 0 #9d9c99,0 -1px 0 #9d9c99,1px 1px 0 #fff,-1px -1px #9d9c99
}
.is-vertical>input[type=range]: :-moz-range-track{
border-left: 1px solid #f3f2ea;
border-right: 0;
border-bottom: 1px solid #f3f2ea;
box-shadow: -1px 0 0 #fff,-1px 1px 0 #fff,0 1px 0 #fff,1px 0 0 #9d9c99,1px -1px 0 #9d9c99,0 -1px 0 #9d9c99,1px 1px 0 #fff,-1px -1px #9d9c99
}
fieldset{
box-shadow: none;
background: #fff;
border: 1px solid #d0d0bf;
border-radius: 4px;
padding-top: 10px
}
legend{
background: transparent;
color: #0046d5
}
.field-row{
display: flex;
align-items: center
}
.field-row>*+*{
margin-left: 6px
}
[class^=field-row]+[class^=field-row]{
margin-top: 6px
}
.field-row-stacked{
display: flex;
flex-direction: column
}
.field-row-stacked *+*{
margin-top: 6px
}
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[
1727819285,
555.58203125,
51.6
],
[
1727819285,
555.58203125,
42.4
],
[
1727819695,
556.27734375,
50.2
],
[
1727819695,
556.27734375,
54.3
],
[
1727819695,
556.27734375,
50.4
],
[
1727819695,
556.27734375,
40
],
[
1727820034,
432.87890625,
50.2
],
[
1727820034,
432.87890625,
45
],
[
1727820034,
432.87890625,
51.4
],
[
1727820034,
432.87890625,
44.4
],
[
1727820358,
440.87109375,
50.2
],
[
1727820358,
440.87109375,
36.4
],
[
1727820358,
440.87109375,
51
],
[
1727820358,
440.87109375,
50
],
[
1727820761,
448.55859375,
50.2
],
[
1727820761,
448.55859375,
57.4
],
[
1727820761,
448.55859375,
51.2
],
[
1727820761,
448.55859375,
41.9
],
[
1727821172,
441.4140625,
50.2
],
[
1727821172,
441.4140625,
54.3
],
[
1727821172,
441.4140625,
50.4
],
[
1727821172,
441.4140625,
39.4
],
[
1727821623,
452.89453125,
50.2
],
[
1727821623,
452.89453125,
38.2
],
[
1727821623,
452.89453125,
50.4
],
[
1727821623,
452.89453125,
51
],
[
1727822216,
452.63671875,
50.2
],
[
1727822216,
452.63671875,
55.3
],
[
1727822216,
452.63671875,
48.7
],
[
1727822216,
452.63671875,
58.7
],
[
1727822764,
437.609375,
50.2
],
[
1727822764,
437.609375,
50
],
[
1727822764,
437.609375,
50.4
],
[
1727822764,
437.609375,
42.4
],
[
1727823200,
435.96484375,
50.2
],
[
1727823200,
435.96484375,
38.2
],
[
1727823200,
435.96484375,
51.5
],
[
1727823200,
435.96484375,
40.6
],
[
1727823636,
435.4375,
50.2
],
[
1727823636,
435.4375,
38.2
],
[
1727823636,
435.4375,
51.5
],
[
1727823636,
435.4375,
40.6
],
[
1727824080,
432.55859375,
50.2
],
[
1727824080,
432.55859375,
46.5
],
[
1727824080,
432.55859375,
51.7
],
[
1727824080,
432.55859375,
39.4
],
[
1727824545,
441.23046875,
50.2
],
[
1727824545,
441.23046875,
39.4
],
[
1727824545,
441.23046875,
50.2
],
[
1727824545,
441.23046875,
57.8
],
[
1727824958,
440.6796875,
50.2
],
[
1727824958,
440.6796875,
53.3
],
[
1727824958,
440.6796875,
50.3
],
[
1727824958,
440.6796875,
40.6
],
[
1727825490,
443.74609375,
50.2
],
[
1727825490,
443.74609375,
52.8
],
[
1727825490,
443.74609375,
49.9
],
[
1727825490,
443.74609375,
55.6
],
[
1727825932,
443.5078125,
50.2
],
[
1727825932,
443.5078125,
47.5
],
[
1727825932,
443.5078125,
50.3
],
[
1727825932,
443.5078125,
42.4
],
[
1727826372,
443.40625,
50.1
],
[
1727826372,
443.40625,
51.2
],
[
1727826372,
443.40625,
50.1
],
[
1727826372,
443.40625,
40.6
],
[
1727826843,
446.078125,
50.2
],
[
1727826843,
446.078125,
54.3
],
[
1727826843,
446.078125,
49.3
],
[
1727826843,
446.078125,
58.1
],
[
1727827271,
447.640625,
50.2
],
[
1727827271,
447.640625,
36.4
],
[
1727827271,
447.640625,
51.4
],
[
1727827271,
447.640625,
37.5
],
[
1727827679,
439.05859375,
50.1
],
[
1727827679,
439.05859375,
55.6
],
[
1727827679,
439.05859375,
49.7
],
[
1727827679,
439.05859375,
51.3
],
[
1727828105,
448.30078125,
50.2
],
[
1727828105,
448.30078125,
48.9
],
[
1727828105,
448.30078125,
50.7
],
[
1727828105,
448.30078125,
55.6
],
[
1727828457,
444.8515625,
50.1
],
[
1727828457,
444.8515625,
53.2
],
[
1727828457,
444.8515625,
50.1
],
[
1727828457,
444.8515625,
38.7
],
[
1727828859,
440.9609375,
50.1
],
[
1727828859,
440.9609375,
52.2
],
[
1727828859,
440.9609375,
49.2
],
[
1727828859,
440.9609375,
57.8
],
[
1727829259,
441.6875,
50.1
],
[
1727829259,
441.6875,
52
],
[
1727829308,
441.6796875,
49.8
],
[
1727829308,
441.6796875,
38.9
]
];
var tab_main_worker_cpu_ram_headers_json = [
"timestamp",
"ram_usage_mb",
"cpu_usage_percent"
];
"use strict";
function add_default_layout_data (layout) {
layout["width"] = get_graph_width();
layout["height"] = get_graph_height();
layout["paper_bgcolor"] = 'rgba(0,0,0,0)';
layout["plot_bgcolor"] = 'rgba(0,0,0,0)';
return layout;
}
function get_marker_size() {
return 12;
}
function get_text_color() {
return theme == "dark" ? "white" : "black";
}
function get_font_size() {
return 14;
}
function get_graph_height() {
return 800;
}
function get_font_data() {
return {
size: get_font_size(),
color: get_text_color()
}
}
function get_axis_title_data(name, axis_type = "") {
if(axis_type) {
return {
text: name,
type: axis_type,
font: get_font_data()
};
}
return {
text: name,
font: get_font_data()
};
}
function get_graph_width() {
var width = document.body.clientWidth || window.innerWidth || document.documentElement.clientWidth;
return Math.max(800, Math.floor(width * 0.9));
}
function createTable(data, headers, table_name) {
if (!$("#" + table_name).length) {
console.error("#" + table_name + " not found");
return;
}
new gridjs.Grid({
columns: headers,
data: data,
search: true,
sort: true
}).render(document.getElementById(table_name));
if (typeof apply_theme_based_on_system_preferences === 'function') {
apply_theme_based_on_system_preferences();
}
colorize_table_entries();
add_colorize_to_gridjs_table();
}
function download_as_file(id, filename) {
var text = $("#" + id).text();
var blob = new Blob([text], {
type: "text/plain"
});
var link = document.createElement("a");
link.href = URL.createObjectURL(blob);
link.download = filename;
document.body.appendChild(link);
link.click();
document.body.removeChild(link);
}
function copy_to_clipboard_from_id (id) {
var text = $("#" + id).text();
copy_to_clipboard(text);
}
function copy_to_clipboard(text) {
if (!navigator.clipboard) {
let textarea = document.createElement("textarea");
textarea.value = text;
document.body.appendChild(textarea);
textarea.select();
try {
document.execCommand("copy");
} catch (err) {
console.error("Copy failed:", err);
}
document.body.removeChild(textarea);
return;
}
navigator.clipboard.writeText(text).then(() => {
console.log("Text copied to clipboard");
}).catch(err => {
console.error("Failed to copy text:", err);
});
}
function filterNonEmptyRows(data) {
var new_data = [];
for (var row_idx = 0; row_idx < data.length; row_idx++) {
var line = data[row_idx];
var line_has_empty_data = false;
for (var col_idx = 0; col_idx < line.length; col_idx++) {
var col_header_name = tab_results_headers_json[col_idx];
var single_data_point = line[col_idx];
if(single_data_point === "" && !special_col_names.includes(col_header_name)) {
line_has_empty_data = true;
continue;
}
}
if(!line_has_empty_data) {
new_data.push(line);
}
}
return new_data;
}
function make_text_in_parallel_plot_nicer() {
$(".parcoords g > g > text").each(function() {
if (theme == "dark") {
$(this)
.css("text-shadow", "unset")
.css("font-size", "0.9em")
.css("fill", "white")
.css("stroke", "black")
.css("stroke-width", "2px")
.css("paint-order", "stroke fill");
} else {
$(this)
.css("text-shadow", "unset")
.css("font-size", "0.9em")
.css("fill", "black")
.css("stroke", "unset")
.css("stroke-width", "unset")
.css("paint-order", "stroke fill");
}
});
}
function createParallelPlot(dataArray, headers, resultNames, ignoreColumns = []) {
if ($("#parallel-plot").data("loaded") == "true") {
return;
}
dataArray = filterNonEmptyRows(dataArray);
const ignoreSet = new Set(ignoreColumns);
const numericalCols = [];
const categoricalCols = [];
const categoryMappings = {};
headers.forEach((header, colIndex) => {
if (ignoreSet.has(header)) return;
const values = dataArray.map(row => row[colIndex]);
if (values.every(val => !isNaN(parseFloat(val)))) {
numericalCols.push({ name: header, index: colIndex });
} else {
categoricalCols.push({ name: header, index: colIndex });
const uniqueValues = [...new Set(values)];
categoryMappings[header] = Object.fromEntries(uniqueValues.map((val, i) => [val, i]));
}
});
const dimensions = [];
numericalCols.forEach(col => {
dimensions.push({
label: col.name,
values: dataArray.map(row => parseFloat(row[col.index])),
range: [
Math.min(...dataArray.map(row => parseFloat(row[col.index]))),
Math.max(...dataArray.map(row => parseFloat(row[col.index])))
]
});
});
categoricalCols.forEach(col => {
dimensions.push({
label: col.name,
values: dataArray.map(row => categoryMappings[col.name][row[col.index]]),
tickvals: Object.values(categoryMappings[col.name]),
ticktext: Object.keys(categoryMappings[col.name])
});
});
let colorScale = null;
let colorValues = null;
if (resultNames.length > 1) {
let selectBox = '<select id="result-select" style="margin-bottom: 10px;">';
selectBox += '<option value="none">No color</option>';
var k = 0;
resultNames.forEach(resultName => {
var minMax = result_min_max[k];
if(minMax === undefined) {
minMax = "min [automatically chosen]"
}
selectBox += `<option value="${resultName}">${resultName} (${minMax})</option>`;
k = k + 1;
});
selectBox += '</select>';
$("#parallel-plot").before(selectBox);
$("#result-select").change(function() {
const selectedResult = $(this).val();
if (selectedResult === "none") {
colorValues = null;
colorScale = null;
} else {
const resultCol = numericalCols.find(col => col.name.toLowerCase() === selectedResult.toLowerCase());
colorValues = dataArray.map(row => parseFloat(row[resultCol.index]));
let minResult = Math.min(...colorValues);
let maxResult = Math.max(...colorValues);
var _result_min_max_idx = result_names.indexOf(selectedResult);
let invertColor = false;
if (result_min_max.length > _result_min_max_idx) {
invertColor = result_min_max[_result_min_max_idx] === "max";
}
colorScale = invertColor
? [[0, 'red'], [1, 'green']]
: [[0, 'green'], [1, 'red']];
}
updatePlot();
});
} else {
let invertColor = false;
if (Object.keys(result_min_max).length == 1) {
invertColor = result_min_max[0] === "max";
}
colorScale = invertColor
? [[0, 'red'], [1, 'green']]
: [[0, 'green'], [1, 'red']];
const resultCol = numericalCols.find(col => col.name.toLowerCase() === resultNames[0].toLowerCase());
colorValues = dataArray.map(row => parseFloat(row[resultCol.index]));
}
function updatePlot() {
const trace = {
type: 'parcoords',
dimensions: dimensions,
line: colorValues ? { color: colorValues, colorscale: colorScale } : {},
unselected: {
line: {
color: get_text_color(),
opacity: 0
}
},
};
dimensions.forEach(dim => {
if (!dim.line) {
dim.line = {};
}
if (!dim.line.color) {
dim.line.color = 'rgba(169,169,169, 0.01)';
}
});
Plotly.newPlot('parallel-plot', [trace], add_default_layout_data({}));
make_text_in_parallel_plot_nicer();
}
updatePlot();
$("#parallel-plot").data("loaded", "true");
make_text_in_parallel_plot_nicer();
}
function plotWorkerUsage() {
if($("#workerUsagePlot").data("loaded") == "true") {
return;
}
var data = tab_worker_usage_csv_json;
if (!Array.isArray(data) || data.length === 0) {
console.error("Invalid or empty data provided.");
return;
}
let timestamps = [];
let desiredWorkers = [];
let realWorkers = [];
for (let i = 0; i < data.length; i++) {
let entry = data[i];
if (!Array.isArray(entry) || entry.length < 3) {
console.warn("Skipping invalid entry:", entry);
continue;
}
let unixTime = parseFloat(entry[0]);
let desired = parseInt(entry[1], 10);
let real = parseInt(entry[2], 10);
if (isNaN(unixTime) || isNaN(desired) || isNaN(real)) {
console.warn("Skipping invalid numerical values:", entry);
continue;
}
timestamps.push(new Date(unixTime * 1000).toISOString());
desiredWorkers.push(desired);
realWorkers.push(real);
}
let trace1 = {
x: timestamps,
y: desiredWorkers,
mode: 'lines+markers',
name: 'Desired Workers',
line: {
color: 'blue'
}
};
let trace2 = {
x: timestamps,
y: realWorkers,
mode: 'lines+markers',
name: 'Real Workers',
line: {
color: 'red'
}
};
let layout = {
title: "Worker Usage Over Time",
xaxis: {
title: get_axis_title_data("Time", "date")
},
yaxis: {
title: get_axis_title_data("Number of Workers")
},
legend: {
x: 0,
y: 1
}
};
Plotly.newPlot('workerUsagePlot', [trace1, trace2], add_default_layout_data(layout));
$("#workerUsagePlot").data("loaded", "true");
}
function plotCPUAndRAMUsage() {
if($("#mainWorkerCPURAM").data("loaded") == "true") {
return;
}
var timestamps = tab_main_worker_cpu_ram_csv_json.map(row => new Date(row[0] * 1000));
var ramUsage = tab_main_worker_cpu_ram_csv_json.map(row => row[1]);
var cpuUsage = tab_main_worker_cpu_ram_csv_json.map(row => row[2]);
var trace1 = {
x: timestamps,
y: cpuUsage,
mode: 'lines+markers',
marker: {
size: get_marker_size(),
},
name: 'CPU Usage (%)',
type: 'scatter',
yaxis: 'y1'
};
var trace2 = {
x: timestamps,
y: ramUsage,
mode: 'lines+markers',
marker: {
size: get_marker_size(),
},
name: 'RAM Usage (MB)',
type: 'scatter',
yaxis: 'y2'
};
var layout = {
title: 'CPU and RAM Usage Over Time',
xaxis: {
title: get_axis_title_data("Timestamp", "date"),
tickmode: 'array',
tickvals: timestamps.filter((_, index) => index % Math.max(Math.floor(timestamps.length / 10), 1) === 0),
ticktext: timestamps.filter((_, index) => index % Math.max(Math.floor(timestamps.length / 10), 1) === 0).map(t => t.toLocaleString()),
tickangle: -45
},
yaxis: {
title: get_axis_title_data("CPU Usage (%)"),
rangemode: 'tozero'
},
yaxis2: {
title: get_axis_title_data("RAM Usage (MB)"),
overlaying: 'y',
side: 'right',
rangemode: 'tozero'
},
legend: {
x: 0.1,
y: 0.9
}
};
var data = [trace1, trace2];
Plotly.newPlot('mainWorkerCPURAM', data, add_default_layout_data(layout));
$("#mainWorkerCPURAM").data("loaded", "true");
}
function plotScatter2d() {
if ($("#plotScatter2d").data("loaded") == "true") {
return;
}
var plotDiv = document.getElementById("plotScatter2d");
var minInput = document.getElementById("minValue");
var maxInput = document.getElementById("maxValue");
if (!minInput || !maxInput) {
minInput = document.createElement("input");
minInput.id = "minValue";
minInput.type = "number";
minInput.placeholder = "Min Value";
minInput.step = "any";
maxInput = document.createElement("input");
maxInput.id = "maxValue";
maxInput.type = "number";
maxInput.placeholder = "Max Value";
maxInput.step = "any";
var inputContainer = document.createElement("div");
inputContainer.style.marginBottom = "10px";
inputContainer.appendChild(minInput);
inputContainer.appendChild(maxInput);
plotDiv.appendChild(inputContainer);
}
var resultSelect = document.getElementById("resultSelect");
if (result_names.length > 1 && !resultSelect) {
resultSelect = document.createElement("select");
resultSelect.id = "resultSelect";
resultSelect.style.marginBottom = "10px";
var sortedResults = [...result_names].sort();
sortedResults.forEach(result => {
var option = document.createElement("option");
option.value = result;
option.textContent = result;
resultSelect.appendChild(option);
});
var selectContainer = document.createElement("div");
selectContainer.style.marginBottom = "10px";
selectContainer.appendChild(resultSelect);
plotDiv.appendChild(selectContainer);
}
minInput.addEventListener("input", updatePlots);
maxInput.addEventListener("input", updatePlots);
if (resultSelect) {
resultSelect.addEventListener("change", updatePlots);
}
updatePlots();
async function updatePlots() {
var minValue = parseFloat(minInput.value);
var maxValue = parseFloat(maxInput.value);
if (isNaN(minValue)) minValue = -Infinity;
if (isNaN(maxValue)) maxValue = Infinity;
while (plotDiv.children.length > 2) {
plotDiv.removeChild(plotDiv.lastChild);
}
var selectedResult = resultSelect ? resultSelect.value : result_names[0];
var resultIndex = tab_results_headers_json.findIndex(header =>
header.toLowerCase() === selectedResult.toLowerCase()
);
var resultValues = tab_results_csv_json.map(row => row[resultIndex]);
var minResult = Math.min(...resultValues.filter(value => value !== null && value !== ""));
var maxResult = Math.max(...resultValues.filter(value => value !== null && value !== ""));
if (minValue !== -Infinity) minResult = Math.max(minResult, minValue);
if (maxValue !== Infinity) maxResult = Math.min(maxResult, maxValue);
var invertColor = result_min_max[result_names.indexOf(selectedResult)] === "max";
var numericColumns = tab_results_headers_json.filter(col =>
!special_col_names.includes(col) && !result_names.includes(col) &&
tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
);
if (numericColumns.length < 2) {
console.error("Not enough columns for Scatter-Plots");
return;
}
for (let i = 0; i < numericColumns.length; i++) {
for (let j = i + 1; j < numericColumns.length; j++) {
let xCol = numericColumns[i];
let yCol = numericColumns[j];
let xIndex = tab_results_headers_json.indexOf(xCol);
let yIndex = tab_results_headers_json.indexOf(yCol);
let data = tab_results_csv_json.map(row => ({
x: parseFloat(row[xIndex]),
y: parseFloat(row[yIndex]),
result: row[resultIndex] !== "" ? parseFloat(row[resultIndex]) : null
}));
data = data.filter(d => d.result >= minResult && d.result <= maxResult);
let layoutTitle = `${xCol} (x) vs ${yCol} (y), result: ${selectedResult}`;
let layout = {
title: layoutTitle,
xaxis: {
title: get_axis_title_data(xCol)
},
yaxis: {
title: get_axis_title_data(yCol)
},
showlegend: false
};
let subDiv = document.createElement("div");
let spinnerContainer = document.createElement("div");
spinnerContainer.style.display = "flex";
spinnerContainer.style.alignItems = "center";
spinnerContainer.style.justifyContent = "center";
spinnerContainer.style.width = layout.width + "px";
spinnerContainer.style.height = layout.height + "px";
spinnerContainer.style.position = "relative";
let spinner = document.createElement("div");
spinner.className = "spinner";
spinner.style.width = "40px";
spinner.style.height = "40px";
let loadingText = document.createElement("span");
loadingText.innerText = `Loading ${layoutTitle}`;
loadingText.style.marginLeft = "10px";
spinnerContainer.appendChild(spinner);
spinnerContainer.appendChild(loadingText);
plotDiv.appendChild(spinnerContainer);
await new Promise(resolve => setTimeout(resolve, 50));
let colors = data.map(d => {
if (d.result === null) {
return 'rgb(0, 0, 0)';
} else {
let norm = (d.result - minResult) / (maxResult - minResult);
if (invertColor) {
norm = 1 - norm;
}
return `rgb(${Math.round(255 * norm)}, ${Math.round(255 * (1 - norm))}, 0)`;
}
});
let trace = {
x: data.map(d => d.x),
y: data.map(d => d.y),
mode: 'markers',
marker: {
size: get_marker_size(),
color: data.map(d => d.result !== null ? d.result : null),
colorscale: invertColor ? [
[0, 'red'],
[1, 'green']
] : [
[0, 'green'],
[1, 'red']
],
colorbar: {
title: 'Result',
tickvals: [minResult, maxResult],
ticktext: [`${minResult}`, `${maxResult}`]
},
symbol: data.map(d => d.result === null ? 'x' : 'circle'),
},
text: data.map(d => d.result !== null ? `Result: ${d.result}` : 'No result'),
type: 'scatter',
showlegend: false
};
try {
plotDiv.replaceChild(subDiv, spinnerContainer);
} catch (err) {
//
}
Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
}
}
}
$("#plotScatter2d").data("loaded", "true");
}
function plotScatter3d() {
if ($("#plotScatter3d").data("loaded") == "true") {
return;
}
var plotDiv = document.getElementById("plotScatter3d");
if (!plotDiv) {
console.error("Div element with id 'plotScatter3d' not found");
return;
}
plotDiv.innerHTML = "";
var minInput3d = document.getElementById("minValue3d");
var maxInput3d = document.getElementById("maxValue3d");
if (!minInput3d || !maxInput3d) {
minInput3d = document.createElement("input");
minInput3d.id = "minValue3d";
minInput3d.type = "number";
minInput3d.placeholder = "Min Value";
minInput3d.step = "any";
maxInput3d = document.createElement("input");
maxInput3d.id = "maxValue3d";
maxInput3d.type = "number";
maxInput3d.placeholder = "Max Value";
maxInput3d.step = "any";
var inputContainer3d = document.createElement("div");
inputContainer3d.style.marginBottom = "10px";
inputContainer3d.appendChild(minInput3d);
inputContainer3d.appendChild(maxInput3d);
plotDiv.appendChild(inputContainer3d);
}
var select3d = document.getElementById("select3dScatter");
if (result_names.length > 1 && !select3d) {
if (!select3d) {
select3d = document.createElement("select");
select3d.id = "select3dScatter";
select3d.style.marginBottom = "10px";
select3d.innerHTML = result_names.map(name => `<option value="${name}">${name}</option>`).join("");
select3d.addEventListener("change", updatePlots3d);
plotDiv.appendChild(select3d);
}
}
minInput3d.addEventListener("input", updatePlots3d);
maxInput3d.addEventListener("input", updatePlots3d);
updatePlots3d();
async function updatePlots3d() {
var selectedResult = select3d ? select3d.value : result_names[0];
var minValue3d = parseFloat(minInput3d.value);
var maxValue3d = parseFloat(maxInput3d.value);
if (isNaN(minValue3d)) minValue3d = -Infinity;
if (isNaN(maxValue3d)) maxValue3d = Infinity;
while (plotDiv.children.length > 2) {
plotDiv.removeChild(plotDiv.lastChild);
}
var resultIndex = tab_results_headers_json.findIndex(header =>
header.toLowerCase() === selectedResult.toLowerCase()
);
var resultValues = tab_results_csv_json.map(row => row[resultIndex]);
var minResult = Math.min(...resultValues.filter(value => value !== null && value !== ""));
var maxResult = Math.max(...resultValues.filter(value => value !== null && value !== ""));
if (minValue3d !== -Infinity) minResult = Math.max(minResult, minValue3d);
if (maxValue3d !== Infinity) maxResult = Math.min(maxResult, maxValue3d);
var invertColor = result_min_max[result_names.indexOf(selectedResult)] === "max";
var numericColumns = tab_results_headers_json.filter(col =>
!special_col_names.includes(col) && !result_names.includes(col) &&
tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
);
if (numericColumns.length < 3) {
console.error("Not enough columns for 3D scatter plots");
return;
}
for (let i = 0; i < numericColumns.length; i++) {
for (let j = i + 1; j < numericColumns.length; j++) {
for (let k = j + 1; k < numericColumns.length; k++) {
let xCol = numericColumns[i];
let yCol = numericColumns[j];
let zCol = numericColumns[k];
let xIndex = tab_results_headers_json.indexOf(xCol);
let yIndex = tab_results_headers_json.indexOf(yCol);
let zIndex = tab_results_headers_json.indexOf(zCol);
let data = tab_results_csv_json.map(row => ({
x: parseFloat(row[xIndex]),
y: parseFloat(row[yIndex]),
z: parseFloat(row[zIndex]),
result: row[resultIndex] !== "" ? parseFloat(row[resultIndex]) : null
}));
data = data.filter(d => d.result >= minResult && d.result <= maxResult);
let layoutTitle = `${xCol} (x) vs ${yCol} (y) vs ${zCol} (z), result: ${selectedResult}`;
let layout = {
title: layoutTitle,
scene: {
xaxis: {
title: get_axis_title_data(xCol)
},
yaxis: {
title: get_axis_title_data(yCol)
},
zaxis: {
title: get_axis_title_data(zCol)
}
},
showlegend: false
};
let spinnerContainer = document.createElement("div");
spinnerContainer.style.display = "flex";
spinnerContainer.style.alignItems = "center";
spinnerContainer.style.justifyContent = "center";
spinnerContainer.style.width = layout.width + "px";
spinnerContainer.style.height = layout.height + "px";
spinnerContainer.style.position = "relative";
let spinner = document.createElement("div");
spinner.className = "spinner";
spinner.style.width = "40px";
spinner.style.height = "40px";
let loadingText = document.createElement("span");
loadingText.innerText = `Loading ${layoutTitle}`;
loadingText.style.marginLeft = "10px";
spinnerContainer.appendChild(spinner);
spinnerContainer.appendChild(loadingText);
plotDiv.appendChild(spinnerContainer);
await new Promise(resolve => setTimeout(resolve, 50));
let colors = data.map(d => {
if (d.result === null) {
return 'rgb(0, 0, 0)';
} else {
let norm = (d.result - minResult) / (maxResult - minResult);
if (invertColor) {
norm = 1 - norm;
}
return `rgb(${Math.round(255 * norm)}, ${Math.round(255 * (1 - norm))}, 0)`;
}
});
let trace = {
x: data.map(d => d.x),
y: data.map(d => d.y),
z: data.map(d => d.z),
mode: 'markers',
marker: {
size: get_marker_size(),
color: data.map(d => d.result !== null ? d.result : null),
colorscale: invertColor ? [
[0, 'red'],
[1, 'green']
] : [
[0, 'green'],
[1, 'red']
],
colorbar: {
title: 'Result',
tickvals: [minResult, maxResult],
ticktext: [`${minResult}`, `${maxResult}`]
},
},
text: data.map(d => d.result !== null ? `Result: ${d.result}` : 'No result'),
type: 'scatter3d',
showlegend: false
};
let subDiv = document.createElement("div");
try {
plotDiv.replaceChild(subDiv, spinnerContainer);
} catch (err) {
//
}
Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
}
}
}
}
$("#plotScatter3d").data("loaded", "true");
}
async function load_pareto_graph() {
if($("#tab_pareto_fronts").data("loaded") == "true") {
return;
}
var data = pareto_front_data;
if (!data || typeof data !== "object") {
console.error("Invalid data format for pareto_front_data");
return;
}
if (!Object.keys(data).length) {
console.warn("No data found in pareto_front_data");
return;
}
let categories = Object.keys(data);
let allMetrics = new Set();
function extractMetrics(obj, prefix = "") {
let keys = Object.keys(obj);
for (let key of keys) {
let newPrefix = prefix ? `${prefix} -> ${key}` : key;
if (typeof obj[key] === "object" && !Array.isArray(obj[key])) {
extractMetrics(obj[key], newPrefix);
} else {
if (!newPrefix.includes("param_dicts") && !newPrefix.includes(" -> sems -> ") && !newPrefix.includes("absolute_metrics")) {
allMetrics.add(newPrefix);
}
}
}
}
for (let cat of categories) {
extractMetrics(data[cat]);
}
allMetrics = Array.from(allMetrics);
function extractValues(obj, metricPath, values) {
let parts = metricPath.split(" -> ");
let data = obj;
for (let part of parts) {
if (data && typeof data === "object") {
data = data[part];
} else {
return;
}
}
if (Array.isArray(data)) {
values.push(...data);
}
}
let graphContainer = document.getElementById("pareto_front_graphs_container");
graphContainer.classList.add("invert_in_dark_mode");
graphContainer.innerHTML = "";
var already_plotted = [];
for (let i = 0; i < allMetrics.length; i++) {
for (let j = i + 1; j < allMetrics.length; j++) {
let xMetric = allMetrics[i];
let yMetric = allMetrics[j];
let xValues = [];
let yValues = [];
for (let cat of categories) {
let metricData = data[cat];
extractValues(metricData, xMetric, xValues);
extractValues(metricData, yMetric, yValues);
}
xValues = xValues.filter(v => v !== undefined && v !== null);
yValues = yValues.filter(v => v !== undefined && v !== null);
let cleanXMetric = xMetric.replace(/.* -> /g, "");
let cleanYMetric = yMetric.replace(/.* -> /g, "");
let plot_key = `${cleanXMetric}-${cleanYMetric}`;
if (xValues.length > 0 && yValues.length > 0 && xValues.length === yValues.length && !already_plotted.includes(plot_key)) {
let div = document.createElement("div");
div.id = `pareto_front_graph_${i}_${j}`;
div.style.marginBottom = "20px";
graphContainer.appendChild(div);
let layout = {
title: `${cleanXMetric} vs ${cleanYMetric}`,
xaxis: {
title: get_axis_title_data(cleanXMetric)
},
yaxis: {
title: get_axis_title_data(cleanYMetric)
},
hovermode: "closest"
};
let trace = {
x: xValues,
y: yValues,
mode: "markers",
marker: {
size: get_marker_size(),
},
type: "scatter",
name: `${cleanXMetric} vs ${cleanYMetric}`
};
Plotly.newPlot(div.id, [trace], add_default_layout_data(layout));
already_plotted.push(plot_key);
}
}
}
if (typeof apply_theme_based_on_system_preferences === 'function') {
apply_theme_based_on_system_preferences();
}
$("#tab_pareto_fronts").data("loaded", "true");
}
async function plot_worker_cpu_ram() {
if($("#worker_cpu_ram_pre").data("loaded") == "true") {
return;
}
const logData = $("#worker_cpu_ram_pre").text();
const regex = /^Unix-Timestamp: (\d+), Hostname: ([\w-]+), CPU: ([\d.]+)%, RAM: ([\d.]+) MB \/ ([\d.]+) MB$/;
const hostData = {};
logData.split("\n").forEach(line => {
line = line.trim();
const match = line.match(regex);
if (match) {
const timestamp = new Date(parseInt(match[1]) * 1000);
const hostname = match[2];
const cpu = parseFloat(match[3]);
const ram = parseFloat(match[4]);
if (!hostData[hostname]) {
hostData[hostname] = { timestamps: [], cpuUsage: [], ramUsage: [] };
}
hostData[hostname].timestamps.push(timestamp);
hostData[hostname].cpuUsage.push(cpu);
hostData[hostname].ramUsage.push(ram);
}
});
if (!Object.keys(hostData).length) {
console.log("No valid data found");
return;
}
const container = document.getElementById("cpuRamWorkerChartContainer");
container.innerHTML = "";
var i = 1;
Object.entries(hostData).forEach(([hostname, { timestamps, cpuUsage, ramUsage }], index) => {
const chartId = `workerChart_${index}`;
const chartDiv = document.createElement("div");
chartDiv.id = chartId;
chartDiv.style.marginBottom = "40px";
container.appendChild(chartDiv);
const cpuTrace = {
x: timestamps,
y: cpuUsage,
mode: "lines+markers",
name: "CPU Usage (%)",
yaxis: "y1",
line: {
color: "red"
}
};
const ramTrace = {
x: timestamps,
y: ramUsage,
mode: "lines+markers",
name: "RAM Usage (MB)",
yaxis: "y2",
line: {
color: "blue"
}
};
const layout = {
title: `Worker CPU and RAM Usage - ${hostname}`,
xaxis: {
title: get_axis_title_data("Timestamp", "date")
},
yaxis: {
title: get_axis_title_data("CPU Usage (%)"),
side: "left",
color: "red"
},
yaxis2: {
title: get_axis_title_data("RAM Usage (MB)"),
side: "right",
overlaying: "y",
color: "blue"
},
showlegend: true
};
Plotly.newPlot(chartId, [cpuTrace, ramTrace], add_default_layout_data(layout));
i++;
});
$("#plot_worker_cpu_ram_button").remove();
$("#worker_cpu_ram_pre").data("loaded", "true");
}
function load_log_file(log_nr, filename) {
var pre_id = `single_run_${log_nr}_pre`;
if (!$("#" + pre_id).data("loaded")) {
const params = new URLSearchParams(window.location.search);
const user_id = params.get('user_id');
const experiment_name = params.get('experiment_name');
const run_nr = params.get('run_nr');
var url = `get_log?user_id=${user_id}&experiment_name=${experiment_name}&run_nr=${run_nr}&filename=${filename}`;
fetch(url)
.then(response => response.json())
.then(data => {
if (data.data) {
$("#" + pre_id).html(data.data);
$("#" + pre_id).data("loaded", true);
} else {
log(`No 'data' key found in response.`);
}
$("#spinner_log_" + log_nr).remove();
})
.catch(error => {
log(`Error loading log: ${error}`);
$("#spinner_log_" + log_nr).remove();
});
}
}
function load_debug_log () {
var pre_id = `here_debuglogs_go`;
if (!$("#" + pre_id).data("loaded")) {
const params = new URLSearchParams(window.location.search);
const user_id = params.get('user_id');
const experiment_name = params.get('experiment_name');
const run_nr = params.get('run_nr');
var url = `get_debug_log?user_id=${user_id}&experiment_name=${experiment_name}&run_nr=${run_nr}`;
fetch(url)
.then(response => response.json())
.then(data => {
$("#debug_log_spinner").remove();
if (data.data) {
try {
$("#" + pre_id).html(data.data);
} catch (err) {
$("#" + pre_id).text(`Error loading data: ${err}`);
}
$("#" + pre_id).data("loaded", true);
if (typeof apply_theme_based_on_system_preferences === 'function') {
apply_theme_based_on_system_preferences();
}
} else {
log(`No 'data' key found in response.`);
}
})
.catch(error => {
log(`Error loading log: ${error}`);
$("#debug_log_spinner").remove();
});
}
}
function plotBoxplot() {
if ($("#plotBoxplot").data("loaded") == "true") {
return;
}
var numericColumns = tab_results_headers_json.filter(col =>
!special_col_names.includes(col) && !result_names.includes(col) &&
tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
);
if (numericColumns.length < 1) {
console.error("Not enough numeric columns for Boxplot");
return;
}
var resultIndex = tab_results_headers_json.findIndex(function(header) {
return result_names.includes(header.toLowerCase());
});
var resultValues = tab_results_csv_json.map(row => row[resultIndex]);
var minResult = Math.min(...resultValues.filter(value => value !== null && value !== ""));
var maxResult = Math.max(...resultValues.filter(value => value !== null && value !== ""));
var plotDiv = document.getElementById("plotBoxplot");
plotDiv.innerHTML = "";
let traces = numericColumns.map(col => {
let index = tab_results_headers_json.indexOf(col);
let data = tab_results_csv_json.map(row => parseFloat(row[index]));
return {
y: data,
type: 'box',
name: col,
boxmean: 'sd',
marker: {
color: 'rgb(0, 255, 0)'
},
};
});
let layout = {
title: 'Boxplot of Numerical Columns',
xaxis: {
title: get_axis_title_data("Columns")
},
yaxis: {
title: get_axis_title_data("Value")
},
showlegend: false
};
Plotly.newPlot(plotDiv, traces, add_default_layout_data(layout));
$("#plotBoxplot").data("loaded", "true");
}
function plotHeatmap() {
if ($("#plotHeatmap").data("loaded") === "true") {
return;
}
var numericColumns = tab_results_headers_json.filter(col => {
if (special_col_names.includes(col) || result_names.includes(col)) {
return false;
}
let index = tab_results_headers_json.indexOf(col);
return tab_results_csv_json.every(row => {
let value = parseFloat(row[index]);
return !isNaN(value) && isFinite(value);
});
});
if (numericColumns.length < 2) {
console.error("Not enough valid numeric columns for Heatmap");
return;
}
var columnData = numericColumns.map(col => {
let index = tab_results_headers_json.indexOf(col);
return tab_results_csv_json.map(row => parseFloat(row[index]));
});
var dataMatrix = numericColumns.map((_, i) =>
numericColumns.map((_, j) => {
let values = columnData[i].map((val, index) => (val + columnData[j][index]) / 2);
return values.reduce((a, b) => a + b, 0) / values.length;
})
);
var trace = {
z: dataMatrix,
x: numericColumns,
y: numericColumns,
colorscale: 'Viridis',
type: 'heatmap'
};
var layout = {
xaxis: {
title: get_axis_title_data("Columns")
},
yaxis: {
title: get_axis_title_data("Columns")
},
showlegend: false
};
var plotDiv = document.getElementById("plotHeatmap");
plotDiv.innerHTML = "";
Plotly.newPlot(plotDiv, [trace], add_default_layout_data(layout));
$("#plotHeatmap").data("loaded", "true");
}
function plotHistogram() {
if ($("#plotHistogram").data("loaded") == "true") {
return;
}
var numericColumns = tab_results_headers_json.filter(col =>
!special_col_names.includes(col) && !result_names.includes(col) &&
tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
);
if (numericColumns.length < 1) {
console.error("Not enough columns for Histogram");
return;
}
var plotDiv = document.getElementById("plotHistogram");
plotDiv.innerHTML = "";
const colorPalette = ['#ff9999', '#66b3ff', '#99ff99', '#ffcc99', '#c2c2f0', '#ffb3e6'];
let traces = numericColumns.map((col, index) => {
let data = tab_results_csv_json.map(row => parseFloat(row[tab_results_headers_json.indexOf(col)]));
return {
x: data,
type: 'histogram',
name: col,
opacity: 0.7,
marker: {
color: colorPalette[index % colorPalette.length]
},
autobinx: true
};
});
let layout = {
title: 'Histogram of Numerical Columns',
xaxis: {
title: get_axis_title_data("Value")
},
yaxis: {
title: get_axis_title_data("Frequency")
},
showlegend: true,
barmode: 'overlay'
};
Plotly.newPlot(plotDiv, traces, add_default_layout_data(layout));
$("#plotHistogram").data("loaded", "true");
}
function plotViolin() {
if ($("#plotViolin").data("loaded") == "true") {
return;
}
var numericColumns = tab_results_headers_json.filter(col =>
!special_col_names.includes(col) && !result_names.includes(col) &&
tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
);
if (numericColumns.length < 1) {
console.error("Not enough columns for Violin Plot");
return;
}
var plotDiv = document.getElementById("plotViolin");
plotDiv.innerHTML = "";
let traces = numericColumns.map(col => {
let index = tab_results_headers_json.indexOf(col);
let data = tab_results_csv_json.map(row => parseFloat(row[index]));
return {
y: data,
type: 'violin',
name: col,
box: {
visible: true
},
line: {
color: 'rgb(0, 255, 0)'
},
marker: {
color: 'rgb(0, 255, 0)'
},
meanline: {
visible: true
},
};
});
let layout = {
title: 'Violin Plot of Numerical Columns',
yaxis: {
title: get_axis_title_data("Value")
},
xaxis: {
title: get_axis_title_data("Columns")
},
showlegend: false
};
Plotly.newPlot(plotDiv, traces, add_default_layout_data(layout));
$("#plotViolin").data("loaded", "true");
}
function plotExitCodesPieChart() {
if ($("#plotExitCodesPieChart").data("loaded") == "true") {
return;
}
var exitCodes = tab_job_infos_csv_json.map(row => row[tab_job_infos_headers_json.indexOf("exit_code")]);
var exitCodeCounts = exitCodes.reduce(function(counts, exitCode) {
counts[exitCode] = (counts[exitCode] || 0) + 1;
return counts;
}, {});
var labels = Object.keys(exitCodeCounts);
var values = Object.values(exitCodeCounts);
var plotDiv = document.getElementById("plotExitCodesPieChart");
plotDiv.innerHTML = "";
var trace = {
labels: labels,
values: values,
type: 'pie',
hoverinfo: 'label+percent',
textinfo: 'label+value',
marker: {
colors: ['#ff9999','#66b3ff','#99ff99','#ffcc99','#c2c2f0']
}
};
var layout = {
title: 'Exit Code Distribution',
showlegend: true
};
Plotly.newPlot(plotDiv, [trace], add_default_layout_data(layout));
$("#plotExitCodesPieChart").data("loaded", "true");
}
function plotResultEvolution() {
if ($("#plotResultEvolution").data("loaded") == "true") {
return;
}
result_names.forEach(resultName => {
var relevantColumns = tab_results_headers_json.filter(col =>
!special_col_names.includes(col) && !col.startsWith("OO_Info") && col.toLowerCase() !== resultName.toLowerCase()
);
var xColumnIndex = tab_results_headers_json.indexOf("trial_index");
var resultIndex = tab_results_headers_json.indexOf(resultName);
let data = tab_results_csv_json.map(row => ({
x: row[xColumnIndex],
y: parseFloat(row[resultIndex])
}));
data.sort((a, b) => a.x - b.x);
let xData = data.map(item => item.x);
let yData = data.map(item => item.y);
let trace = {
x: xData,
y: yData,
mode: 'lines+markers',
name: resultName,
line: {
shape: 'linear'
},
marker: {
size: get_marker_size()
}
};
let layout = {
title: `Evolution of ${resultName} over time`,
xaxis: {
title: get_axis_title_data("Trial-Index")
},
yaxis: {
title: get_axis_title_data(resultName)
},
showlegend: true
};
let subDiv = document.createElement("div");
document.getElementById("plotResultEvolution").appendChild(subDiv);
Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
});
$("#plotResultEvolution").data("loaded", "true");
}
function plotResultPairs() {
if ($("#plotResultPairs").data("loaded") == "true") {
return;
}
var plotDiv = document.getElementById("plotResultPairs");
plotDiv.innerHTML = "";
for (let i = 0; i < result_names.length; i++) {
for (let j = i + 1; j < result_names.length; j++) {
let xName = result_names[i];
let yName = result_names[j];
let xIndex = tab_results_headers_json.indexOf(xName);
let yIndex = tab_results_headers_json.indexOf(yName);
let data = tab_results_csv_json
.filter(row => row[xIndex] !== "" && row[yIndex] !== "")
.map(row => ({
x: parseFloat(row[xIndex]),
y: parseFloat(row[yIndex]),
status: row[tab_results_headers_json.indexOf("trial_status")]
}));
let colors = data.map(d => d.status === "COMPLETED" ? 'green' : (d.status === "FAILED" ? 'red' : 'gray'));
let trace = {
x: data.map(d => d.x),
y: data.map(d => d.y),
mode: 'markers',
marker: {
size: get_marker_size(),
color: colors
},
text: data.map(d => `Status: ${d.status}`),
type: 'scatter',
showlegend: false
};
let layout = {
xaxis: {
title: get_axis_title_data(xName)
},
yaxis: {
title: get_axis_title_data(yName)
},
showlegend: false
};
let subDiv = document.createElement("div");
plotDiv.appendChild(subDiv);
Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
}
}
$("#plotResultPairs").data("loaded", "true");
}
function add_up_down_arrows_for_scrolling () {
const upArrow = document.createElement('div');
const downArrow = document.createElement('div');
const style = document.createElement('style');
style.innerHTML = `
.scroll-arrow {
position: fixed;
right: 10px;
z-index: 100;
cursor: pointer;
font-size: 25px;
display: none;
background-color: green;
color: white;
padding: 5px;
outline: 2px solid white;
box-shadow: 0 0 10px rgba(0, 0, 0, 0.5);
transition: background-color 0.3s, transform 0.3s;
}
.scroll-arrow:hover {
background-color: darkgreen;
transform: scale(1.1);
}
#up-arrow {
top: 10px;
}
#down-arrow {
bottom: 10px;
}
`;
document.head.appendChild(style);
upArrow.id = "up-arrow";
upArrow.classList.add("scroll-arrow");
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boxpoints: 'outliers', // Zeigt nur Ausreißer außerhalb der Whiskers
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}
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var statuses = Object.keys(status_counts);
var counts = Object.values(status_counts);
var colors = statuses.map((status, i) =>
status === "FAILED" ? "#FF0000" : `hsl(${30 + ((i * 137) % 330)}, 70%, 50%)`
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x: statuses,
y: counts,
type: 'bar',
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title: 'Distribution of Job Status',
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createParallelPlot(tab_results_csv_json, tab_results_headers_json, result_names, special_col_names);;
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</script>
<h1> Overview</h1>
<h2>Best parameter (total: 0, failed: 263): </h2><table cellspacing="0" cellpadding="5"><thead><tr><th> n_samples</th><th>confidence</th><th>feature_proportion</th><th>n_clusters</th><th>result </th></tr></thead><tbody><tr><td> 169</td><td>0.001</td><td>0.100332</td><td>1</td><td>0.828650 </td></tr></tbody></table><h2>Experiment parameters: </h2><table cellspacing="0" cellpadding="5"><thead><tr><th> Name</th><th>Type</th><th>Lower bound</th><th>Upper bound</th><th>Values</th><th>Type </th></tr></thead><tbody><tr><td> n_samples</td><td>range</td><td>100</td><td>1000</td><td></td><td>int </td></tr><tr><td> confidence</td><td>choice</td><td></td><td></td><td>0.001, 0.005,</td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>0.01, 0.025,</td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>0.05, 0.1,</td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>0.25</td><td></td></tr><tr><td> feature_propo…</td><td>range</td><td>0</td><td>0.2</td><td></td><td>float </td></tr><tr><td> n_clusters</td><td>range</td><td>1</td><td>4</td><td></td><td>int </td></tr></tbody></table><br><h2>Number of evaluations:</h2>
<table>
<tbody>
<tr>
<th>Failed</th>
<th>Succeeded</th>
<th>Running</th>
<th>Total</th>
</tr>
<tr>
<td>263</td>
<td>228</td>
<td>11</td>
<td>502</td>
</tr>
</tbody>
</table>
<h1> Results</h1>
<div id='tab_results_csv_table'></div>
<button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("tab_results_csv_table_pre")'> Copy raw data to clipboard</button>
<button onclick='download_as_file("tab_results_csv_table_pre", "results.csv")'> Download »results.csv« as file</button>
<pre id='tab_results_csv_table_pre'>trial_index,arm_name,trial_status,generation_method,result,n_samples,confidence,feature_proportion,n_clusters
0,0_0,COMPLETED,Sobol,0.841681424800347466330663337430,697,0.010000000000000000208166817117,0.054493993520736694335937500000,2
1,1_0,COMPLETED,Sobol,0.851505329635446228664363843563,531,0.050000000000000002775557561563,0.089709608070552351866133733438,3
2,2_0,COMPLETED,Sobol,0.848598255755672159494906736654,165,0.050000000000000002775557561563,0.133431331813335413150056751874,1
3,3_0,COMPLETED,Sobol,0.841714839442643802946975029045,970,0.005000000000000000104083408559,0.180374011769890790768400279376,1
4,4_0,COMPLETED,Sobol,0.841848498011828816345314407954,164,0.001000000000000000020816681712,0.050916207581758500533286593281,2
5,5_0,COMPLETED,Sobol,0.844855815818491673319101664674,880,0.250000000000000000000000000000,0.032522250898182392120361328125,4
6,6_0,COMPLETED,Sobol,0.841013131954422399338966442883,156,0.010000000000000000208166817117,0.064752514474093914031982421875,1
7,7_0,COMPLETED,Sobol,0.849333377886189788696924551914,743,0.005000000000000000104083408559,0.050803099945187571440108342813,4
8,8_0,COMPLETED,Sobol,0.847562401844488277902200934477,401,0.010000000000000000208166817117,0.017815119586884975433349609375,3
9,9_0,COMPLETED,Sobol,0.849433621813078465478952239209,612,0.050000000000000002775557561563,0.028564392961561681921756061797,4
10,10_0,COMPLETED,Sobol,0.861228990543656203193734199886,267,0.050000000000000002775557561563,0.136976843513548385278255636877,3
11,11_0,COMPLETED,Sobol,0.842483376215457546720699610887,903,0.001000000000000000020816681712,0.168821467645466349871696820628,4
12,12_0,COMPLETED,Sobol,0.841982156581013829743653786863,545,0.010000000000000000208166817117,0.014081121794879436839864617070,1
13,13_0,COMPLETED,Sobol,0.850736792862632373868336799205,129,0.005000000000000000104083408559,0.124128070846199992094405217813,4
14,14_0,COMPLETED,Sobol,0.848330938617302132698227978835,269,0.005000000000000000104083408559,0.022765718959271909194175265156,3
15,15_0,COMPLETED,Sobol,0.838941424132054636153554838529,218,0.001000000000000000020816681712,0.153062728978693496362240011877,1
16,16_0,COMPLETED,Sobol,0.843151669061382724734698967950,916,0.050000000000000002775557561563,0.003580087795853614807128906250,3
17,17_0,COMPLETED,Sobol,0.843218498345975175922717426147,701,0.010000000000000000208166817117,0.053518407605588437514487765156,2
18,18_0,COMPLETED,Sobol,0.848097036121228331495558450115,187,0.010000000000000000208166817117,0.168143008649349223748714621252,4
19,19_0,COMPLETED,Sobol,0.844388010826344070913762607233,856,0.005000000000000000104083408559,0.150274576433002959863216574377,2
20,20_0,COMPLETED,BoTorch,0.842048985865606280931672245060,281,0.001000000000000000020816681712,0.095511931688158177577996355012,1
21,21_0,COMPLETED,BoTorch,0.843920205834196579530726012308,462,0.001000000000000000020816681712,0.168500437375803557848996661050,1
22,22_0,COMPLETED,BoTorch,0.850436061081966121477648812288,100,0.001000000000000000020816681712,0.116121120229294508274797692593,1
23,23_0,COMPLETED,BoTorch,0.850436061081966121477648812288,100,0.001000000000000000020816681712,0.049297150296263164692689429103,1
24,24_0,COMPLETED,BoTorch,0.850436061081966121477648812288,100,0.001000000000000000020816681712,0.196277381682319645994638790398,1
25,25_0,COMPLETED,BoTorch,0.846125572225749356114476995572,514,0.001000000000000000020816681712,0.111283680291679329399379128063,1
26,26_0,FAILED,BoTorch,,1000,0.100000000000000005551115123126,0.000000000000000000000000000000,1
27,27_0,COMPLETED,BoTorch,0.838172887359240781357527794171,1000,0.001000000000000000020816681712,0.078333816082492915833235258560,1
28,28_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,1
29,29_0,FAILED,BoTorch,,100,0.001000000000000000020816681712,0.000000000000000000000000000000,1
30,30_0,COMPLETED,BoTorch,0.844454840110936633124083527946,411,0.001000000000000000020816681712,0.200000000000000011102230246252,1
31,31_0,COMPLETED,BoTorch,0.842483376215457546720699610887,1000,0.025000000000000001387778780781,0.082678555004395748451173631111,1
32,32_0,FAILED,BoTorch,,543,0.250000000000000000000000000000,0.000000000000000000000000000000,1
33,33_0,COMPLETED,BoTorch,0.836101179536873018172116189817,1000,0.050000000000000002775557561563,0.200000000000000011102230246252,1
34,34_0,COMPLETED,BoTorch,0.845290206168342939108129030501,100,0.001000000000000000020816681712,0.200000000000000011102230246252,2
35,35_0,COMPLETED,BoTorch,0.842884351923012697938020210131,1000,0.250000000000000000000000000000,0.116724986725779869556340884174,1
36,36_0,COMPLETED,BoTorch,0.844621913322417872116432135954,917,0.100000000000000005551115123126,0.039491857602488959766429132969,1
37,37_0,COMPLETED,BoTorch,0.840411668393089783535288006533,1000,0.001000000000000000020816681712,0.022693055889432149629936219526,2
38,38_0,FAILED,BoTorch,,100,0.100000000000000005551115123126,0.000000000000000000000000000000,1
39,39_0,COMPLETED,BoTorch,0.846559962575600621903504361399,491,0.001000000000000000020816681712,0.134851359300241835370570697705,1
40,40_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,2
41,41_0,COMPLETED,BoTorch,0.842249473719383856540332544682,391,0.001000000000000000020816681712,0.088530554386544446643370065431,1
42,42_0,FAILED,BoTorch,,626,0.250000000000000000000000000000,0.000000000000000000000000000000,1
43,29_0,FAILED,BoTorch,,100,0.001000000000000000020816681712,0.000000000000000000000000000000,1
44,44_0,COMPLETED,BoTorch,0.836836301667390647374134005076,988,0.050000000000000002775557561563,0.200000000000000011102230246252,2
45,45_0,COMPLETED,BoTorch,0.850135329301299869086960825371,236,0.005000000000000000104083408559,0.163511983093401397360011628734,1
46,46_0,COMPLETED,BoTorch,0.843118254419086499140689738852,947,0.001000000000000000020816681712,0.044674076127555001347602114947,1
47,47_0,COMPLETED,BoTorch,0.840612156246867359143948306155,1000,0.001000000000000000020816681712,0.150188058050470196747028239770,2
48,48_0,COMPLETED,BoTorch,0.842483376215457546720699610887,1000,0.025000000000000001387778780781,0.200000000000000011102230246252,1
49,28_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,1
50,50_0,COMPLETED,BoTorch,0.837972399505463316771169957065,1000,0.100000000000000005551115123126,0.200000000000000011102230246252,1
51,51_0,COMPLETED,BoTorch,0.843886791191900353936716783210,938,0.050000000000000002775557561563,0.200000000000000011102230246252,1
52,52_0,COMPLETED,BoTorch,0.842349717646272644344662694493,239,0.001000000000000000020816681712,0.196681510834082223793117805144,2
53,53_0,COMPLETED,BoTorch,0.847094596852340675496861877036,948,0.100000000000000005551115123126,0.200000000000000011102230246252,1
54,54_0,COMPLETED,BoTorch,0.837972399505463316771169957065,1000,0.100000000000000005551115123126,0.161267362247732248814457989283,1
55,28_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,1
56,56_0,FAILED,BoTorch,,1000,0.005000000000000000104083408559,0.000000000000000000000000000000,1
57,57_0,COMPLETED,BoTorch,0.841948741938717493127342095249,1000,0.010000000000000000208166817117,0.122306006176385206885015577427,3
58,58_0,COMPLETED,BoTorch,0.838172887359240781357527794171,1000,0.001000000000000000020816681712,0.164751269798091320994970487845,1
59,59_0,COMPLETED,BoTorch,0.838039228790055767959188415261,1000,0.001000000000000000020816681712,0.200000000000000011102230246252,3
60,60_0,COMPLETED,BoTorch,0.849299963243893452080612860300,219,0.005000000000000000104083408559,0.093164711561329383027185713217,1
61,61_0,COMPLETED,BoTorch,0.841414107661977439533984579612,929,0.001000000000000000020816681712,0.001804314210812638617775771621,1
62,62_0,FAILED,BoTorch,,922,0.001000000000000000020816681712,0.000000000000000000000000000000,1
63,63_0,FAILED,BoTorch,,680,0.010000000000000000208166817117,0.000000000000000000000000000000,1
64,64_0,COMPLETED,BoTorch,0.840511912319978682361920618860,1000,0.005000000000000000104083408559,0.199963376911347967546106474401,3
65,65_0,COMPLETED,BoTorch,0.844822401176195447725092435576,1000,0.050000000000000002775557561563,0.136985669248943897624570809057,2
66,66_0,COMPLETED,BoTorch,0.842717278711531347923369139608,1000,0.100000000000000005551115123126,0.200000000000000011102230246252,3
67,67_0,COMPLETED,BoTorch,0.839877034116349729941930490895,1000,0.010000000000000000208166817117,0.120525135066867267186196954754,2
68,68_0,COMPLETED,BoTorch,0.840812644100644934752608605777,1000,0.250000000000000000000000000000,0.200000000000000011102230246252,2
69,69_0,COMPLETED,BoTorch,0.841514351588866227338314729423,1000,0.025000000000000001387778780781,0.196387355196368795784422900397,2
70,70_0,COMPLETED,BoTorch,0.839877034116349729941930490895,1000,0.010000000000000000208166817117,0.036178118103656724258154753215,2
71,71_0,COMPLETED,BoTorch,0.837671667724797064380481970147,1000,0.001000000000000000020816681712,0.041099193598007593974941187298,3
72,72_0,COMPLETED,BoTorch,0.841480936946570001744305500324,1000,0.025000000000000001387778780781,0.200000000000000011102230246252,3
73,73_0,COMPLETED,BoTorch,0.842550205500050108931020531600,1000,0.050000000000000002775557561563,0.137913496287657311167862417278,3
74,74_0,COMPLETED,BoTorch,0.840812644100644934752608605777,1000,0.250000000000000000000000000000,0.156104640761024149320235210325,3
75,75_0,FAILED,BoTorch,,759,0.001000000000000000020816681712,0.000000000000000000000000000000,1
76,76_0,COMPLETED,BoTorch,0.842683864069235122329359910509,1000,0.100000000000000005551115123126,0.132336088654343403403501611137,2
77,77_0,FAILED,BoTorch,,798,0.001000000000000000020816681712,0.000000000000000000000000000000,2
78,78_0,COMPLETED,BoTorch,0.840411668393089783535288006533,1000,0.001000000000000000020816681712,0.200000000000000011102230246252,2
79,79_0,COMPLETED,BoTorch,0.838172887359240781357527794171,1000,0.001000000000000000020816681712,0.200000000000000011102230246252,1
80,80_0,FAILED,BoTorch,,613,0.001000000000000000020816681712,0.000000000000000000000000000000,1
81,81_0,COMPLETED,BoTorch,0.840612156246867359143948306155,1000,0.001000000000000000020816681712,0.095136665646274654051239849650,2
82,82_0,FAILED,BoTorch,,643,0.050000000000000002775557561563,0.000000000000000000000000000000,1
83,83_0,COMPLETED,BoTorch,0.842216059077087519924020853068,1000,0.025000000000000001387778780781,0.200000000000000011102230246252,4
84,84_0,COMPLETED,BoTorch,0.842149229792495068736002394871,853,0.001000000000000000020816681712,0.200000000000000011102230246252,2
85,85_0,FAILED,BoTorch,,1000,0.010000000000000000208166817117,0.000000000000000000000000000000,1
86,86_0,COMPLETED,BoTorch,0.839542887693387251957233274879,1000,0.005000000000000000104083408559,0.125480464875883351849594760097,1
87,87_0,COMPLETED,BoTorch,0.838172887359240781357527794171,1000,0.001000000000000000020816681712,0.120728018491730412775631009481,1
88,88_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,4
89,89_0,COMPLETED,BoTorch,0.839108497343535875145903446537,1000,0.001000000000000000020816681712,0.111585437177154703225490095519,3
90,90_0,FAILED,BoTorch,,736,0.001000000000000000020816681712,0.000000000000000000000000000000,1
91,91_0,FAILED,BoTorch,,742,0.025000000000000001387778780781,0.000000000000000000000000000000,1
92,92_0,COMPLETED,BoTorch,0.840946302669829948150947984686,1000,0.001000000000000000020816681712,0.102829485131717024426478701571,4
93,93_0,FAILED,BoTorch,,1000,0.005000000000000000104083408559,0.000000000000000000000000000000,3
94,94_0,FAILED,BoTorch,,1000,0.005000000000000000104083408559,0.000000000000000000000000000000,2
95,95_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,3
96,96_0,COMPLETED,BoTorch,0.840612156246867359143948306155,1000,0.001000000000000000020816681712,0.200000000000000011102230246252,4
97,97_0,FAILED,BoTorch,,639,0.001000000000000000020816681712,0.000000000000000000000000000000,1
98,98_0,FAILED,BoTorch,,1000,0.005000000000000000104083408559,0.000000000000000000000000000000,4
99,99_0,COMPLETED,BoTorch,0.836869716309686872968143234175,1000,0.001000000000000000020816681712,0.157408464426212507669688989154,4
100,100_0,COMPLETED,BoTorch,0.841915327296421267533332866151,1000,0.025000000000000001387778780781,0.121584838410418255572054135882,4
101,101_0,RUNNING,BoTorch,,990,0.050000000000000002775557561563,0.200000000000000011102230246252,1
102,102_0,COMPLETED,BoTorch,0.842416546930865095532681152690,977,0.050000000000000002775557561563,0.200000000000000011102230246252,2
103,103_0,COMPLETED,BoTorch,0.842282888361680082134341773781,978,0.025000000000000001387778780781,0.200000000000000011102230246252,2
104,104_0,COMPLETED,BoTorch,0.841881912654125041939323637052,977,0.050000000000000002775557561563,0.200000000000000011102230246252,3
105,105_0,FAILED,BoTorch,,987,0.001000000000000000020816681712,0.000000000000000000000000000000,3
106,106_0,COMPLETED,BoTorch,0.846727035787081860895852969406,985,0.001000000000000000020816681712,0.200000000000000011102230246252,4
107,107_0,COMPLETED,BoTorch,0.837671667724797064380481970147,987,0.050000000000000002775557561563,0.200000000000000011102230246252,1
108,108_0,COMPLETED,BoTorch,0.845256791526046713514119801403,974,0.010000000000000000208166817117,0.035122731151610186994815876460,2
109,88_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,4
110,110_0,COMPLETED,BoTorch,0.839977278043238517746260640706,978,0.100000000000000005551115123126,0.200000000000000011102230246252,2
111,111_0,COMPLETED,BoTorch,0.844488254753232858718092757044,974,0.025000000000000001387778780781,0.112830492604275980927930334019,3
112,112_0,COMPLETED,BoTorch,0.844755571891602885514771514863,981,0.001000000000000000020816681712,0.200000000000000011102230246252,3
113,113_0,COMPLETED,BoTorch,0.852507768904333884663060416642,670,0.010000000000000000208166817117,0.065467168958601135164698803237,2
114,114_0,COMPLETED,BoTorch,0.849868012162929842290282067552,973,0.005000000000000000104083408559,0.200000000000000011102230246252,3
115,115_0,COMPLETED,BoTorch,0.847061182210044449902852647938,677,0.010000000000000000208166817117,0.064885476415393231186534706012,1
116,116_0,COMPLETED,BoTorch,0.842015571223310055337663015962,202,0.001000000000000000020816681712,0.200000000000000011102230246252,1
117,117_0,COMPLETED,BoTorch,0.837170448090353236381133683608,899,0.001000000000000000020816681712,0.145199366594284118292534913053,1
118,118_0,COMPLETED,BoTorch,0.840779229458348709158599376678,332,0.001000000000000000020816681712,0.101228831414884881678695194296,1
119,98_0,FAILED,BoTorch,,1000,0.005000000000000000104083408559,0.000000000000000000000000000000,4
120,120_0,COMPLETED,BoTorch,0.842850937280716472344010981033,909,0.010000000000000000208166817117,0.104310504741430179476147088735,1
121,121_0,COMPLETED,BoTorch,0.838774350920573397161206230521,889,0.001000000000000000020816681712,0.009651100271967950894325127820,1
122,122_0,COMPLETED,BoTorch,0.842282888361680082134341773781,662,0.001000000000000000020816681712,0.083601222593334148514010450981,1
123,123_0,FAILED,BoTorch,,573,0.001000000000000000020816681712,0.000000000000000000000000000000,1
124,124_0,FAILED,BoTorch,,902,0.005000000000000000104083408559,0.000000000000000000000000000000,4
125,125_0,FAILED,BoTorch,,900,0.010000000000000000208166817117,0.000000000000000000000000000000,1
126,126_0,COMPLETED,BoTorch,0.851572158920038790874684764276,680,0.005000000000000000104083408559,0.200000000000000011102230246252,1
127,127_0,COMPLETED,BoTorch,0.838540448424499595958536701801,920,0.005000000000000000104083408559,0.200000000000000011102230246252,1
128,128_0,COMPLETED,BoTorch,0.845925084371971780505816695950,319,0.001000000000000000020816681712,0.200000000000000011102230246252,1
129,88_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,4
130,130_0,COMPLETED,BoTorch,0.838607277709092158168857622513,1000,0.001000000000000000020816681712,0.050536297826837009439238102004,4
131,131_0,COMPLETED,BoTorch,0.840812644100644934752608605777,1000,0.250000000000000000000000000000,0.200000000000000011102230246252,4
132,132_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,4
133,133_0,COMPLETED,BoTorch,0.840812644100644934752608605777,1000,0.250000000000000000000000000000,0.082610991424067137245401681866,4
134,134_0,FAILED,BoTorch,,682,0.001000000000000000020816681712,0.000000000000000000000000000000,1
135,135_0,FAILED,BoTorch,,1000,0.010000000000000000208166817117,0.000000000000000000000000000000,4
136,136_0,COMPLETED,BoTorch,0.842884351923012697938020210131,1000,0.250000000000000000000000000000,0.200000000000000011102230246252,1
137,137_0,FAILED,BoTorch,,653,0.250000000000000000000000000000,0.000000000000000000000000000000,1
138,131_0,COMPLETED,BoTorch,0.840812644100644934752608605777,1000,0.250000000000000000000000000000,0.200000000000000011102230246252,4
139,139_0,FAILED,BoTorch,,412,0.001000000000000000020816681712,0.000000000000000000000000000000,1
140,140_0,COMPLETED,BoTorch,0.845524108664416740310798559221,800,0.001000000000000000020816681712,0.031895402522216786955766565370,1
141,88_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,4
142,142_0,FAILED,BoTorch,,648,0.001000000000000000020816681712,0.000000000000000000000000000000,1
143,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1
144,144_0,FAILED,BoTorch,,744,0.001000000000000000020816681712,0.000000000000000000000000000000,1
145,145_0,FAILED,BoTorch,,944,0.001000000000000000020816681712,0.000000000000000000000000000000,3
146,28_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,1
147,147_0,COMPLETED,BoTorch,0.843385571557456525937368496670,827,0.250000000000000000000000000000,0.200000000000000011102230246252,4
148,135_0,FAILED,BoTorch,,1000,0.010000000000000000208166817117,0.000000000000000000000000000000,4
149,149_0,FAILED,BoTorch,,483,0.001000000000000000020816681712,0.000000000000000000000000000000,1
150,88_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,4
151,95_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,3
152,152_0,FAILED,BoTorch,,421,0.001000000000000000020816681712,0.000000000000000000000000000000,1
153,153_0,FAILED,BoTorch,,852,0.001000000000000000020816681712,0.000000000000000000000000000000,2
154,154_0,FAILED,BoTorch,,679,0.250000000000000000000000000000,0.000000000000000000000000000000,1
155,155_0,FAILED,BoTorch,,490,0.250000000000000000000000000000,0.000000000000000000000000000000,1
156,88_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,4
157,157_0,FAILED,BoTorch,,419,0.001000000000000000020816681712,0.000000000000000000000000000000,1
158,28_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,1
159,135_0,FAILED,BoTorch,,1000,0.010000000000000000208166817117,0.000000000000000000000000000000,4
160,160_0,COMPLETED,BoTorch,0.838674106993684609356876080710,1000,0.001000000000000000020816681712,0.079668850794297974005075957393,3
161,161_0,COMPLETED,BoTorch,0.843218498345975175922717426147,1000,0.005000000000000000104083408559,0.031497912163918916073068743344,4
162,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1
163,163_0,FAILED,BoTorch,,454,0.001000000000000000020816681712,0.000000000000000000000000000000,2
164,132_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,4
165,165_0,RUNNING,BoTorch,,1000,0.250000000000000000000000000000,0.140743753073893668181781890780,4
166,166_0,FAILED,BoTorch,,965,0.025000000000000001387778780781,0.000000000000000000000000000000,3
167,93_0,FAILED,BoTorch,,1000,0.005000000000000000104083408559,0.000000000000000000000000000000,3
168,168_0,FAILED,BoTorch,,1000,0.025000000000000001387778780781,0.000000000000000000000000000000,4
169,135_0,FAILED,BoTorch,,1000,0.010000000000000000208166817117,0.000000000000000000000000000000,4
170,95_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,3
171,98_0,FAILED,BoTorch,,1000,0.005000000000000000104083408559,0.000000000000000000000000000000,4
172,172_0,COMPLETED,BoTorch,0.843719717980419003922065712686,1000,0.010000000000000000208166817117,0.072570910156620455078169129592,4
173,173_0,COMPLETED,BoTorch,0.842683864069235122329359910509,1000,0.010000000000000000208166817117,0.200000000000000011102230246252,1
174,28_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,1
175,152_0,FAILED,BoTorch,,421,0.001000000000000000020816681712,0.000000000000000000000000000000,1
176,88_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,4
177,177_0,FAILED,BoTorch,,100,0.250000000000000000000000000000,0.000000000000000000000000000000,1
178,95_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,3
179,179_0,FAILED,BoTorch,,640,0.250000000000000000000000000000,0.000000000000000000000000000000,1
180,180_0,FAILED,BoTorch,,510,0.001000000000000000020816681712,0.000000000000000000000000000000,1
181,181_0,COMPLETED,BoTorch,0.838172887359240781357527794171,1000,0.001000000000000000020816681712,0.145277293813302343927773563337,1
182,132_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,4
183,88_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,4
184,184_0,COMPLETED,BoTorch,0.840612156246867359143948306155,1000,0.001000000000000000020816681712,0.079814653597244183957926111361,2
185,185_0,FAILED,BoTorch,,465,0.250000000000000000000000000000,0.000000000000000000000000000000,1
186,186_0,FAILED,BoTorch,,224,0.250000000000000000000000000000,0.000000000000000000000000000000,1
187,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1
188,188_0,COMPLETED,BoTorch,0.841748254084940028540984258143,1000,0.001000000000000000020816681712,0.058638395449828718819507145099,4
189,189_0,FAILED,BoTorch,,246,0.250000000000000000000000000000,0.000000000000000000000000000000,1
190,190_0,FAILED,BoTorch,,408,0.001000000000000000020816681712,0.000000000000000000000000000000,1
191,88_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,4
192,132_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,4
193,193_0,FAILED,BoTorch,,670,0.250000000000000000000000000000,0.000000000000000000000000000000,1
194,194_0,FAILED,BoTorch,,455,0.001000000000000000020816681712,0.000000000000000000000000000000,1
195,28_0,RUNNING,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,1
196,196_0,FAILED,BoTorch,,559,0.001000000000000000020816681712,0.000000000000000000000000000000,1
197,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1
198,198_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,3
199,95_0,RUNNING,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,3
200,200_0,FAILED,BoTorch,,424,0.001000000000000000020816681712,0.000000000000000000000000000000,1
201,177_0,FAILED,BoTorch,,100,0.250000000000000000000000000000,0.000000000000000000000000000000,1
202,40_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,2
203,85_0,FAILED,BoTorch,,1000,0.010000000000000000208166817117,0.000000000000000000000000000000,1
204,204_0,FAILED,BoTorch,,353,0.001000000000000000020816681712,0.000000000000000000000000000000,1
205,205_0,COMPLETED,BoTorch,0.858522404517659598610634930083,356,0.250000000000000000000000000000,0.010170518095815836087658645681,1
206,206_0,FAILED,BoTorch,,407,0.250000000000000000000000000000,0.000000000000000000000000000000,1
207,207_0,FAILED,BoTorch,,403,0.001000000000000000020816681712,0.000000000000000000000000000000,1
208,88_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,4
209,209_0,FAILED,BoTorch,,416,0.001000000000000000020816681712,0.000000000000000000000000000000,1
210,95_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,3
211,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1
212,198_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,3
213,132_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,4
214,214_0,FAILED,BoTorch,,1000,0.050000000000000002775557561563,0.000000000000000000000000000000,1
215,215_0,FAILED,BoTorch,,719,0.250000000000000000000000000000,0.000000000000000000000000000000,1
216,216_0,COMPLETED,BoTorch,0.846626791860193073091522819595,812,0.250000000000000000000000000000,0.200000000000000011102230246252,1
217,217_0,FAILED,BoTorch,,806,0.250000000000000000000000000000,0.000000000000000000000000000000,1
218,218_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,2
219,219_0,COMPLETED,BoTorch,0.846125572225749356114476995572,551,0.010000000000000000208166817117,0.021834769656869645881869246296,1
220,220_0,COMPLETED,BoTorch,0.845423864737527952506468409410,742,0.250000000000000000000000000000,0.148382318208447216978385085895,1
221,221_0,COMPLETED,BoTorch,0.839977278043238517746260640706,911,0.001000000000000000020816681712,0.190363033361253264352797032188,1
222,222_0,COMPLETED,BoTorch,0.840278009823904881159251090139,904,0.001000000000000000020816681712,0.072089437293909916504297541451,2
223,223_0,COMPLETED,BoTorch,0.842683864069235122329359910509,888,0.001000000000000000020816681712,0.200000000000000011102230246252,1
224,224_0,COMPLETED,BoTorch,0.839442643766498464152903125068,904,0.001000000000000000020816681712,0.049333454538326923510815902318,1
225,225_0,COMPLETED,BoTorch,0.842784107996123910133690060320,893,0.001000000000000000020816681712,0.200000000000000011102230246252,2
226,226_0,COMPLETED,BoTorch,0.838440204497610919176509014505,915,0.001000000000000000020816681712,0.200000000000000011102230246252,2
227,227_0,COMPLETED,BoTorch,0.840445083035386120151599698147,354,0.001000000000000000020816681712,0.022174112886802592459201122210,1
228,228_0,COMPLETED,BoTorch,0.842583620142346445547332223214,355,0.001000000000000000020816681712,0.200000000000000011102230246252,1
229,229_0,COMPLETED,BoTorch,0.840511912319978682361920618860,988,0.001000000000000000020816681712,0.142672710143254860559736130199,1
230,230_0,COMPLETED,BoTorch,0.850135329301299869086960825371,349,0.001000000000000000020816681712,0.015762747529365114806942926862,2
231,231_0,COMPLETED,BoTorch,0.842583620142346445547332223214,981,0.250000000000000000000000000000,0.200000000000000011102230246252,3
232,232_0,COMPLETED,BoTorch,0.839609716977979703145251733076,901,0.005000000000000000104083408559,0.091054695575964281206715611461,2
233,233_0,COMPLETED,BoTorch,0.847929962909747092503209842107,353,0.005000000000000000104083408559,0.140399676928489897109741946224,1
234,234_0,COMPLETED,BoTorch,0.840278009823904881159251090139,930,0.001000000000000000020816681712,0.200000000000000011102230246252,1
235,235_0,FAILED,BoTorch,,333,0.001000000000000000020816681712,0.000000000000000000000000000000,3
236,236_0,COMPLETED,BoTorch,0.844321181541751619725744149036,921,0.005000000000000000104083408559,0.200000000000000011102230246252,3
237,237_0,FAILED,BoTorch,,358,0.001000000000000000020816681712,0.000000000000000000000000000000,3
238,56_0,FAILED,BoTorch,,1000,0.005000000000000000104083408559,0.000000000000000000000000000000,1
239,239_0,FAILED,BoTorch,,869,0.001000000000000000020816681712,0.000000000000000000000000000000,1
240,240_0,COMPLETED,BoTorch,0.842182644434791294330011623970,974,0.250000000000000000000000000000,0.127576543277154758060376593676,4
241,241_0,COMPLETED,BoTorch,0.841146790523607412737305821793,920,0.001000000000000000020816681712,0.144808163674682910393443080466,1
242,242_0,FAILED,BoTorch,,713,0.025000000000000001387778780781,0.000000000000000000000000000000,1
243,243_0,COMPLETED,BoTorch,0.842784107996123910133690060320,348,0.001000000000000000020816681712,0.055481838679636158451202732067,4
244,244_0,COMPLETED,BoTorch,0.843185083703678950328708197048,899,0.025000000000000001387778780781,0.200000000000000011102230246252,4
245,245_0,FAILED,BoTorch,,644,0.001000000000000000020816681712,0.000000000000000000000000000000,1
246,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1
247,88_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,4
248,248_0,COMPLETED,BoTorch,0.840411668393089783535288006533,1000,0.001000000000000000020816681712,0.120948394532869235584726652633,2
249,249_0,COMPLETED,BoTorch,0.845323620810639164702138259599,690,0.250000000000000000000000000000,0.200000000000000011102230246252,4
250,132_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,4
251,132_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,4
252,252_0,FAILED,BoTorch,,1000,0.050000000000000002775557561563,0.000000000000000000000000000000,4
253,56_0,FAILED,BoTorch,,1000,0.005000000000000000104083408559,0.000000000000000000000000000000,1
254,254_0,FAILED,BoTorch,,717,0.001000000000000000020816681712,0.000000000000000000000000000000,1
255,255_0,FAILED,BoTorch,,924,0.005000000000000000104083408559,0.000000000000000000000000000000,1
256,256_0,FAILED,BoTorch,,832,0.025000000000000001387778780781,0.000000000000000000000000000000,1
257,132_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,4
258,258_0,FAILED,BoTorch,,1000,0.100000000000000005551115123126,0.000000000000000000000000000000,4
259,88_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,4
260,260_0,FAILED,BoTorch,,953,0.001000000000000000020816681712,0.000000000000000000000000000000,3
261,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1
262,262_0,COMPLETED,BoTorch,0.840812644100644934752608605777,1000,0.250000000000000000000000000000,0.155225728258488848698704032358,2
263,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1
264,264_0,FAILED,BoTorch,,523,0.001000000000000000020816681712,0.000000000000000000000000000000,1
265,56_0,FAILED,BoTorch,,1000,0.005000000000000000104083408559,0.000000000000000000000000000000,1
266,132_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,4
267,252_0,FAILED,BoTorch,,1000,0.050000000000000002775557561563,0.000000000000000000000000000000,4
268,260_0,FAILED,BoTorch,,953,0.001000000000000000020816681712,0.000000000000000000000000000000,3
269,269_0,COMPLETED,BoTorch,0.844020449761085256312753699603,901,0.050000000000000002775557561563,0.007906343953206008620671063625,3
270,56_0,FAILED,BoTorch,,1000,0.005000000000000000104083408559,0.000000000000000000000000000000,1
271,271_0,FAILED,BoTorch,,991,0.100000000000000005551115123126,0.000000000000000000000000000000,3
272,88_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,4
273,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1
274,274_0,FAILED,BoTorch,,632,0.001000000000000000020816681712,0.000000000000000000000000000000,1
275,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1
276,56_0,FAILED,BoTorch,,1000,0.005000000000000000104083408559,0.000000000000000000000000000000,1
277,277_0,FAILED,BoTorch,,893,0.005000000000000000104083408559,0.000000000000000000000000000000,1
278,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1
279,279_0,FAILED,BoTorch,,863,0.010000000000000000208166817117,0.000000000000000000000000000000,1
280,280_0,FAILED,BoTorch,,506,0.001000000000000000020816681712,0.000000000000000000000000000000,1
281,281_0,COMPLETED,BoTorch,0.853343134961740190647105919197,327,0.001000000000000000020816681712,0.200000000000000011102230246252,4
282,258_0,FAILED,BoTorch,,1000,0.100000000000000005551115123126,0.000000000000000000000000000000,4
283,132_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,4
284,284_0,FAILED,BoTorch,,643,0.001000000000000000020816681712,0.000000000000000000000000000000,1
285,285_0,FAILED,BoTorch,,538,0.001000000000000000020816681712,0.000000000000000000000000000000,4
286,286_0,FAILED,BoTorch,,560,0.001000000000000000020816681712,0.000000000000000000000000000000,1
287,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1
288,218_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,2
289,88_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,4
290,132_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,4
291,291_0,COMPLETED,BoTorch,0.844621913322417872116432135954,917,0.100000000000000005551115123126,0.039495576573283820709381330971,1
292,40_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,2
293,88_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,4
294,294_0,FAILED,BoTorch,,452,0.001000000000000000020816681712,0.000000000000000000000000000000,1
295,295_0,COMPLETED,BoTorch,0.840812644100644934752608605777,1000,0.250000000000000000000000000000,0.117482891287608026686939410865,3
296,296_0,COMPLETED,BoTorch,0.840812644100644934752608605777,1000,0.100000000000000005551115123126,0.200000000000000011102230246252,4
297,297_0,COMPLETED,BoTorch,0.843753132622715229516074941785,359,0.001000000000000000020816681712,0.024196096071949932393430060529,1
298,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1
299,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1
300,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1
301,301_0,COMPLETED,BoTorch,0.842182644434791294330011623970,1000,0.100000000000000005551115123126,0.118353408697022405293708402496,4
302,302_0,COMPLETED,BoTorch,0.840110936612423531144600019616,995,0.050000000000000002775557561563,0.200000000000000011102230246252,1
303,303_0,COMPLETED,BoTorch,0.837170448090353236381133683608,896,0.005000000000000000104083408559,0.013358932732360865106024938598,1
304,304_0,COMPLETED,BoTorch,0.845858255087379329317798237753,913,0.005000000000000000104083408559,0.200000000000000011102230246252,2
305,305_0,FAILED,BoTorch,,895,0.001000000000000000020816681712,0.000000000000000000000000000000,1
306,306_0,COMPLETED,BoTorch,0.842483376215457546720699610887,929,0.005000000000000000104083408559,0.200000000000000011102230246252,1
307,307_0,COMPLETED,BoTorch,0.840311424466201106753260319238,932,0.010000000000000000208166817117,0.200000000000000011102230246252,1
308,308_0,COMPLETED,BoTorch,0.838005814147759542365179186163,217,0.001000000000000000020816681712,0.200000000000000011102230246252,2
309,309_0,COMPLETED,BoTorch,0.838807765562869622755215459620,903,0.005000000000000000104083408559,0.200000000000000011102230246252,1
310,310_0,COMPLETED,BoTorch,0.841648010158051240736654108332,996,0.050000000000000002775557561563,0.200000000000000011102230246252,1
311,311_0,COMPLETED,BoTorch,0.842015571223310055337663015962,924,0.005000000000000000104083408559,0.200000000000000011102230246252,2
312,312_0,COMPLETED,BoTorch,0.837471179871019488771821670525,158,0.001000000000000000020816681712,0.008219790664827255136093420163,1
313,313_0,COMPLETED,BoTorch,0.837270692017241913163161370903,165,0.005000000000000000104083408559,0.140777008799616937251286685751,1
314,314_0,FAILED,BoTorch,,991,0.005000000000000000104083408559,0.000000000000000000000000000000,1
315,315_0,FAILED,BoTorch,,987,0.100000000000000005551115123126,0.000000000000000000000000000000,4
316,316_0,COMPLETED,BoTorch,0.843084839776790162524378047237,986,0.100000000000000005551115123126,0.184930903161941134760226645994,4
317,317_0,COMPLETED,BoTorch,0.830287031777324768810899513483,164,0.001000000000000000020816681712,0.084980383925100724806789287413,1
318,318_0,RUNNING,BoTorch,,165,0.005000000000000000104083408559,0.029829687685756223203270565136,1
319,319_0,COMPLETED,BoTorch,0.840445083035386120151599698147,159,0.001000000000000000020816681712,0.123440122463064183566672227244,1
320,320_0,FAILED,BoTorch,,885,0.005000000000000000104083408559,0.000000000000000000000000000000,1
321,321_0,COMPLETED,BoTorch,0.831356300330804987019917007274,168,0.001000000000000000020816681712,0.040692450743706837235080797655,1
322,322_0,FAILED,BoTorch,,874,0.001000000000000000020816681712,0.000000000000000000000000000000,3
323,323_0,COMPLETED,BoTorch,0.840511912319978682361920618860,175,0.001000000000000000020816681712,0.002339118748376654757098469517,1
324,324_0,FAILED,BoTorch,,723,0.025000000000000001387778780781,0.000000000000000000000000000000,1
325,325_0,COMPLETED,BoTorch,0.838005814147759542365179186163,156,0.005000000000000000104083408559,0.083567982087696418558309119362,1
326,326_0,FAILED,BoTorch,,861,0.001000000000000000020816681712,0.000000000000000000000000000000,4
327,327_0,COMPLETED,BoTorch,0.828649714304808382436817737471,169,0.001000000000000000020816681712,0.100332095958836395310775913003,1
328,328_0,FAILED,BoTorch,,886,0.005000000000000000104083408559,0.000000000000000000000000000000,2
329,329_0,FAILED,BoTorch,,716,0.050000000000000002775557561563,0.000000000000000000000000000000,2
330,330_0,FAILED,BoTorch,,730,0.010000000000000000208166817117,0.000000000000000000000000000000,1
331,331_0,COMPLETED,BoTorch,0.842216059077087519924020853068,986,0.100000000000000005551115123126,0.200000000000000011102230246252,1
332,332_0,FAILED,BoTorch,,877,0.010000000000000000208166817117,0.000000000000000000000000000000,1
333,333_0,COMPLETED,BoTorch,0.834363618137467843993704263994,172,0.001000000000000000020816681712,0.084898414484966266968513082247,1
334,334_0,FAILED,BoTorch,,873,0.001000000000000000020816681712,0.000000000000000000000000000000,3
335,335_0,COMPLETED,BoTorch,0.843786547265011566132386633399,889,0.005000000000000000104083408559,0.008676660294084570165806802322,3
336,336_0,COMPLETED,BoTorch,0.834363618137467843993704263994,172,0.001000000000000000020816681712,0.085852013275284078108740004609,1
337,337_0,FAILED,BoTorch,,872,0.005000000000000000104083408559,0.000000000000000000000000000000,2
338,338_0,FAILED,BoTorch,,711,0.001000000000000000020816681712,0.000000000000000000000000000000,1
339,339_0,FAILED,BoTorch,,863,0.025000000000000001387778780781,0.000000000000000000000000000000,1
340,340_0,FAILED,BoTorch,,875,0.001000000000000000020816681712,0.000000000000000000000000000000,4
341,341_0,FAILED,BoTorch,,871,0.010000000000000000208166817117,0.000000000000000000000000000000,2
342,342_0,FAILED,BoTorch,,897,0.001000000000000000020816681712,0.000000000000000000000000000000,4
343,343_0,COMPLETED,BoTorch,0.837571423797908276576151820336,171,0.001000000000000000020816681712,0.085041675570839858622207430017,1
344,344_0,FAILED,BoTorch,,852,0.050000000000000002775557561563,0.000000000000000000000000000000,1
345,345_0,FAILED,BoTorch,,871,0.025000000000000001387778780781,0.000000000000000000000000000000,1
346,346_0,FAILED,BoTorch,,859,0.001000000000000000020816681712,0.000000000000000000000000000000,1
347,347_0,COMPLETED,BoTorch,0.843686303338122778328056483588,933,0.100000000000000005551115123126,0.054333929002806674590786428780,1
348,332_0,FAILED,BoTorch,,877,0.010000000000000000208166817117,0.000000000000000000000000000000,1
349,349_0,COMPLETED,BoTorch,0.843251912988271401516726655245,851,0.025000000000000001387778780781,0.040025767910441205355009941513,1
350,350_0,COMPLETED,BoTorch,0.843385571557456525937368496670,831,0.025000000000000001387778780781,0.101709554600000778856738747891,1
351,338_0,FAILED,BoTorch,,711,0.001000000000000000020816681712,0.000000000000000000000000000000,1
352,352_0,COMPLETED,BoTorch,0.840912888027533611534636293072,853,0.025000000000000001387778780781,0.028619189780432263692233618713,1
353,353_0,FAILED,BoTorch,,873,0.005000000000000000104083408559,0.000000000000000000000000000000,1
354,354_0,FAILED,BoTorch,,732,0.010000000000000000208166817117,0.000000000000000000000000000000,1
355,355_0,RUNNING,BoTorch,,847,0.010000000000000000208166817117,0.110757259339255800800749796053,1
356,356_0,FAILED,BoTorch,,857,0.050000000000000002775557561563,0.000000000000000000000000000000,1
357,357_0,FAILED,BoTorch,,859,0.250000000000000000000000000000,0.000000000000000000000000000000,1
358,358_0,FAILED,BoTorch,,877,0.001000000000000000020816681712,0.000000000000000000000000000000,1
359,359_0,FAILED,BoTorch,,771,0.250000000000000000000000000000,0.000000000000000000000000000000,4
360,360_0,FAILED,BoTorch,,738,0.010000000000000000208166817117,0.000000000000000000000000000000,1
361,361_0,FAILED,BoTorch,,765,0.100000000000000005551115123126,0.000000000000000000000000000000,3
362,362_0,FAILED,BoTorch,,714,0.001000000000000000020816681712,0.000000000000000000000000000000,1
363,363_0,COMPLETED,BoTorch,0.842850937280716472344010981033,742,0.005000000000000000104083408559,0.055052424409314459907704986108,1
364,364_0,FAILED,BoTorch,,606,0.001000000000000000020816681712,0.000000000000000000000000000000,1
365,365_0,FAILED,BoTorch,,751,0.025000000000000001387778780781,0.000000000000000000000000000000,2
366,366_0,COMPLETED,BoTorch,0.861228990543656203193734199886,100,0.250000000000000000000000000000,0.200000000000000011102230246252,4
367,367_0,FAILED,BoTorch,,733,0.050000000000000002775557561563,0.000000000000000000000000000000,1
368,368_0,FAILED,BoTorch,,719,0.010000000000000000208166817117,0.000000000000000000000000000000,1
369,369_0,COMPLETED,BoTorch,0.846292645437230595106825603580,737,0.025000000000000001387778780781,0.038154239066357273357787960322,1
370,370_0,FAILED,BoTorch,,754,0.050000000000000002775557561563,0.000000000000000000000000000000,2
371,371_0,COMPLETED,BoTorch,0.861228990543656203193734199886,100,0.250000000000000000000000000000,0.200000000000000011102230246252,3
372,372_0,FAILED,BoTorch,,761,0.050000000000000002775557561563,0.000000000000000000000000000000,1
373,373_0,FAILED,BoTorch,,703,0.001000000000000000020816681712,0.000000000000000000000000000000,1
374,374_0,COMPLETED,BoTorch,0.834363618137467843993704263994,172,0.001000000000000000020816681712,0.090442087505985466200364442102,1
375,375_0,FAILED,BoTorch,,769,0.250000000000000000000000000000,0.000000000000000000000000000000,4
376,376_0,COMPLETED,BoTorch,0.845323620810639164702138259599,760,0.250000000000000000000000000000,0.071603655009983099843928755490,4
377,377_0,FAILED,BoTorch,,434,0.001000000000000000020816681712,0.000000000000000000000000000000,1
378,378_0,FAILED,BoTorch,,863,0.001000000000000000020816681712,0.000000000000000000000000000000,1
379,379_0,FAILED,BoTorch,,443,0.001000000000000000020816681712,0.000000000000000000000000000000,3
380,380_0,COMPLETED,BoTorch,0.844254352257159057515423228324,436,0.001000000000000000020816681712,0.000000000000000000298907180617,1
381,381_0,COMPLETED,BoTorch,0.849934841447522293478300525749,763,0.100000000000000005551115123126,0.035206496838175102559453932827,3
382,382_0,COMPLETED,BoTorch,0.846593377217896847497513590497,738,0.025000000000000001387778780781,0.036793639676769289426072617744,1
383,383_0,COMPLETED,BoTorch,0.850770207504928599462346028304,422,0.001000000000000000020816681712,0.044328048130094027667880141053,2
384,384_0,FAILED,BoTorch,,445,0.001000000000000000020816681712,0.000000000000000000000000000000,4
385,385_0,FAILED,BoTorch,,602,0.001000000000000000020816681712,0.000000000000000000000000000000,1
386,386_0,FAILED,BoTorch,,576,0.001000000000000000020816681712,0.000000000000000000000000000000,4
387,387_0,FAILED,BoTorch,,616,0.001000000000000000020816681712,0.000000000000000000000000000000,3
388,388_0,FAILED,BoTorch,,858,0.001000000000000000020816681712,0.000000000000000000000000000000,1
389,389_0,FAILED,BoTorch,,572,0.001000000000000000020816681712,0.000000000000000000000000000000,2
390,390_0,FAILED,BoTorch,,842,0.001000000000000000020816681712,0.000000000000000000000000000000,4
391,391_0,COMPLETED,BoTorch,0.851271427139372427461694314843,597,0.001000000000000000020816681712,0.031408823450167593083204309323,4
392,392_0,FAILED,BoTorch,,538,0.001000000000000000020816681712,0.000000000000000000000000000000,3
393,393_0,FAILED,BoTorch,,545,0.001000000000000000020816681712,0.000000000000000000000000000000,4
394,394_0,FAILED,BoTorch,,543,0.001000000000000000020816681712,0.000000000000000000000000000000,3
395,395_0,FAILED,BoTorch,,868,0.001000000000000000020816681712,0.000000000000000000000000000000,1
396,396_0,FAILED,BoTorch,,844,0.001000000000000000020816681712,0.000000000000000000000000000000,4
397,397_0,FAILED,BoTorch,,859,0.001000000000000000020816681712,0.000000000000000000000000000000,3
398,398_0,COMPLETED,BoTorch,0.845824840445082992701486546139,839,0.005000000000000000104083408559,0.068559442791628247282353925129,4
399,373_0,FAILED,BoTorch,,703,0.001000000000000000020816681712,0.000000000000000000000000000000,1
400,400_0,FAILED,BoTorch,,860,0.001000000000000000020816681712,0.000000000000000000000000000000,1
401,401_0,FAILED,BoTorch,,707,0.001000000000000000020816681712,0.000000000000000000000000000000,1
402,402_0,COMPLETED,BoTorch,0.854245330303739058841472342465,478,0.250000000000000000000000000000,0.200000000000000011102230246252,1
403,403_0,COMPLETED,BoTorch,0.843953620476492805124735241407,849,0.005000000000000000104083408559,0.044349552237808925747586386024,3
404,404_0,FAILED,BoTorch,,867,0.001000000000000000020816681712,0.000000000000000000000000000000,1
405,405_0,COMPLETED,BoTorch,0.844688742607010434326753056666,674,0.001000000000000000020816681712,0.009341796367090933472798752746,1
406,406_0,COMPLETED,BoTorch,0.847061182210044449902852647938,841,0.005000000000000000104083408559,0.068689304510479470833317350298,4
407,407_0,COMPLETED,BoTorch,0.846158986868045581708486224670,835,0.010000000000000000208166817117,0.200000000000000011102230246252,4
408,408_0,COMPLETED,BoTorch,0.844688742607010434326753056666,850,0.001000000000000000020816681712,0.067445689928380250788286787156,4
409,409_0,FAILED,BoTorch,,870,0.005000000000000000104083408559,0.000000000000000000000000000000,1
410,410_0,FAILED,BoTorch,,616,0.250000000000000000000000000000,0.000000000000000000000000000000,1
411,411_0,FAILED,BoTorch,,658,0.250000000000000000000000000000,0.000000000000000000000000000000,1
412,28_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,1
413,413_0,RUNNING,BoTorch,,977,0.001000000000000000020816681712,0.035353581424803895427722011391,1
414,414_0,FAILED,BoTorch,,688,0.250000000000000000000000000000,0.000000000000000000000000000000,1
415,415_0,FAILED,BoTorch,,647,0.250000000000000000000000000000,0.000000000000000000000000000000,1
416,416_0,RUNNING,BoTorch,,689,0.005000000000000000104083408559,0.088299343110396666389760866878,2
417,417_0,COMPLETED,BoTorch,0.851505329635446228664363843563,625,0.100000000000000005551115123126,0.046617598594046953663916355026,1
418,418_0,FAILED,BoTorch,,853,0.250000000000000000000000000000,0.000000000000000000000000000000,1
419,239_0,FAILED,BoTorch,,869,0.001000000000000000020816681712,0.000000000000000000000000000000,1
420,56_0,FAILED,BoTorch,,1000,0.005000000000000000104083408559,0.000000000000000000000000000000,1
421,421_0,FAILED,BoTorch,,870,0.001000000000000000020816681712,0.000000000000000000000000000000,1
422,422_0,FAILED,BoTorch,,878,0.005000000000000000104083408559,0.000000000000000000000000000000,1
423,423_0,COMPLETED,BoTorch,0.839576302335683477551242503978,997,0.001000000000000000020816681712,0.151175894104641828086244004226,2
424,424_0,COMPLETED,BoTorch,0.834363618137467843993704263994,172,0.001000000000000000020816681712,0.091518382375551154961357269713,1
425,28_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,1
426,426_0,COMPLETED,BoTorch,0.839576302335683477551242503978,896,0.001000000000000000020816681712,0.064976667097237081338612085801,1
427,427_0,FAILED,BoTorch,,882,0.010000000000000000208166817117,0.000000000000000000000000000000,1
428,428_0,COMPLETED,BoTorch,0.854746549938182886840820629004,166,0.010000000000000000208166817117,0.007916691422013058185291889401,2
429,400_0,FAILED,BoTorch,,860,0.001000000000000000020816681712,0.000000000000000000000000000000,1
430,421_0,FAILED,BoTorch,,870,0.001000000000000000020816681712,0.000000000000000000000000000000,1
431,418_0,FAILED,BoTorch,,853,0.250000000000000000000000000000,0.000000000000000000000000000000,1
432,432_0,FAILED,BoTorch,,871,0.005000000000000000104083408559,0.000000000000000000000000000000,1
433,433_0,FAILED,BoTorch,,849,0.250000000000000000000000000000,0.000000000000000000000000000000,1
434,434_0,FAILED,BoTorch,,862,0.001000000000000000020816681712,0.000000000000000000000000000000,1
435,435_0,COMPLETED,BoTorch,0.837571423797908276576151820336,171,0.001000000000000000020816681712,0.081554789913772227083477162068,1
436,436_0,COMPLETED,BoTorch,0.845256791526046713514119801403,847,0.010000000000000000208166817117,0.110796472013699159875343980275,1
437,437_0,COMPLETED,BoTorch,0.845256791526046713514119801403,846,0.005000000000000000104083408559,0.073481745543256329900039247605,1
438,438_0,COMPLETED,BoTorch,0.844621913322417872116432135954,846,0.010000000000000000208166817117,0.119762452563734994592792304502,1
439,378_0,FAILED,BoTorch,,863,0.001000000000000000020816681712,0.000000000000000000000000000000,1
440,440_0,FAILED,BoTorch,,951,0.250000000000000000000000000000,0.000000000000000000000000000000,4
441,441_0,COMPLETED,BoTorch,0.847027767567748224308843418839,474,0.001000000000000000020816681712,0.200000000000000011102230246252,4
442,442_0,FAILED,BoTorch,,859,0.050000000000000002775557561563,0.000000000000000000000000000000,1
443,443_0,COMPLETED,BoTorch,0.841280449092792426135645200702,823,0.050000000000000002775557561563,0.054795325065888779436651390142,1
444,444_0,FAILED,BoTorch,,485,0.001000000000000000020816681712,0.000000000000000000000000000000,4
445,445_0,FAILED,BoTorch,,850,0.250000000000000000000000000000,0.000000000000000000000000000000,1
446,446_0,FAILED,BoTorch,,817,0.100000000000000005551115123126,0.000000000000000000000000000000,1
447,447_0,COMPLETED,BoTorch,0.844388010826344070913762607233,791,0.025000000000000001387778780781,0.061686006754933277174135497489,1
448,448_0,FAILED,BoTorch,,865,0.250000000000000000000000000000,0.000000000000000000000000000000,1
449,449_0,COMPLETED,BoTorch,0.841213619808199974947626742505,913,0.250000000000000000000000000000,0.200000000000000011102230246252,4
450,450_0,COMPLETED,BoTorch,0.844521669395529084312101986143,826,0.100000000000000005551115123126,0.024479787667490447711227119498,1
451,451_0,COMPLETED,BoTorch,0.844889230460787898913110893773,872,0.100000000000000005551115123126,0.087459538912774192898069713920,1
452,452_0,COMPLETED,BoTorch,0.845490694022120514716789330123,874,0.250000000000000000000000000000,0.142505053436539269595684231717,1
453,453_0,COMPLETED,BoTorch,0.839843619474053504347921261797,906,0.100000000000000005551115123126,0.122111802412221512326162553563,4
454,454_0,COMPLETED,BoTorch,0.829318007150733449428514632018,170,0.001000000000000000020816681712,0.082511324772335595256755880200,1
455,455_0,FAILED,BoTorch,,948,0.250000000000000000000000000000,0.000000000000000000000000000000,4
456,456_0,FAILED,BoTorch,,872,0.001000000000000000020816681712,0.000000000000000000000000000000,2
457,457_0,COMPLETED,BoTorch,0.843853376549604017320405091596,937,0.250000000000000000000000000000,0.032865611685334965297311526911,4
458,458_0,FAILED,BoTorch,,440,0.250000000000000000000000000000,0.000000000000000000000000000000,4
459,459_0,COMPLETED,BoTorch,0.852507768904333884663060416642,483,0.250000000000000000000000000000,0.138543368017125051450122441565,2
460,132_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,4
461,461_0,RUNNING,BoTorch,,917,0.250000000000000000000000000000,0.101099448492499285889856253107,4
462,462_0,FAILED,BoTorch,,958,0.250000000000000000000000000000,0.000000000000000000000000000000,4
463,463_0,COMPLETED,BoTorch,0.855782403849366768433526431181,419,0.250000000000000000000000000000,0.200000000000000011102230246252,4
464,464_0,COMPLETED,BoTorch,0.848364353259598358292237207934,744,0.001000000000000000020816681712,0.154140333250431804668068025421,2
465,28_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,1
466,466_0,COMPLETED,BoTorch,0.838239716643833343567848714883,995,0.001000000000000000020816681712,0.039936804951470949998082460297,1
467,467_0,COMPLETED,BoTorch,0.836635813813613182787776167970,992,0.001000000000000000020816681712,0.145731579467055089027738290497,2
468,468_0,COMPLETED,BoTorch,0.843285327630567738133038346859,587,0.001000000000000000020816681712,0.200000000000000011102230246252,1
469,469_0,FAILED,BoTorch,,592,0.001000000000000000020816681712,0.000000000000000000000000000000,1
470,470_0,FAILED,BoTorch,,578,0.001000000000000000020816681712,0.000000000000000000000000000000,1
471,471_0,COMPLETED,BoTorch,0.844655327964714097710441365052,764,0.001000000000000000020816681712,0.200000000000000011102230246252,1
472,472_0,COMPLETED,BoTorch,0.842048985865606280931672245060,620,0.001000000000000000020816681712,0.059614754602420799711737231519,1
473,473_0,COMPLETED,BoTorch,0.847295084706118251105522176658,569,0.001000000000000000020816681712,0.076344581826440008343048759798,1
474,474_0,FAILED,BoTorch,,591,0.001000000000000000020816681712,0.000000000000000000000000000000,1
475,475_0,COMPLETED,BoTorch,0.844020449761085256312753699603,553,0.005000000000000000104083408559,0.016882991409375016494953669621,1
476,28_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,1
477,477_0,COMPLETED,BoTorch,0.844922645103084235529422585387,597,0.001000000000000000020816681712,0.138171192439053180933683506737,1
478,478_0,FAILED,BoTorch,,627,0.005000000000000000104083408559,0.000000000000000000000000000000,1
479,479_0,FAILED,BoTorch,,482,0.025000000000000001387778780781,0.000000000000000000000000000000,1
480,480_0,COMPLETED,BoTorch,0.848364353259598358292237207934,536,0.025000000000000001387778780781,0.093540873183005385227417605165,1
481,28_0,FAILED,BoTorch,,1000,0.001000000000000000020816681712,0.000000000000000000000000000000,1
482,482_0,COMPLETED,BoTorch,0.840411668393089783535288006533,1000,0.001000000000000000020816681712,0.190977909933611328385794081441,2
483,79_0,COMPLETED,BoTorch,0.838172887359240781357527794171,1000,0.001000000000000000020816681712,0.200000000000000011102230246252,1
484,484_0,FAILED,BoTorch,,901,0.010000000000000000208166817117,0.000000000000000000000000000000,1
485,485_0,COMPLETED,BoTorch,0.843452400842048977125386954867,970,0.001000000000000000020816681712,0.054632609609757000479479671640,1
486,143_0,FAILED,BoTorch,,1000,0.250000000000000000000000000000,0.000000000000000000000000000000,1
487,487_0,FAILED,BoTorch,,933,0.001000000000000000020816681712,0.000000000000000000000000000000,4
488,56_0,FAILED,BoTorch,,1000,0.005000000000000000104083408559,0.000000000000000000000000000000,1
489,214_0,FAILED,BoTorch,,1000,0.050000000000000002775557561563,0.000000000000000000000000000000,1
490,490_0,COMPLETED,BoTorch,0.837504594513315714365830899624,901,0.010000000000000000208166817117,0.014863759215553230472184331745,1
491,491_0,FAILED,BoTorch,,934,0.001000000000000000020816681712,0.000000000000000000000000000000,4
492,492_0,FAILED,BoTorch,,1000,0.025000000000000001387778780781,0.000000000000000000000000000000,1
493,493_0,COMPLETED,BoTorch,0.842683864069235122329359910509,969,0.001000000000000000020816681712,0.041497825915564869048157703446,1
494,494_0,COMPLETED,BoTorch,0.845357035452935501318449951214,886,0.010000000000000000208166817117,0.050868498622799768194013836364,1
495,495_0,FAILED,BoTorch,,909,0.010000000000000000208166817117,0.000000000000000000000000000000,1
496,496_0,RUNNING,BoTorch,,1000,0.010000000000000000208166817117,0.089052782861047646845165104423,2
497,497_0,FAILED,BoTorch,,932,0.001000000000000000020816681712,0.000000000000000000000000000000,4
498,498_0,COMPLETED,BoTorch,0.838507033782203370364527472702,1000,0.001000000000000000020816681712,0.050592622158597444492755812462,4
499,499_0,COMPLETED,BoTorch,0.845524108664416740310798559221,842,0.010000000000000000208166817117,0.118382806633066620105587674061,1
500,500_0,COMPLETED,BoTorch,0.841079961239014961549287363596,980,0.001000000000000000020816681712,0.130073246876293596718809908452,2
501,501_0,RUNNING,BoTorch,,980,0.001000000000000000020816681712,0.130061492637200015742848790978,2
</pre>
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<button onclick='download_as_file("tab_results_csv_table_pre", "results.csv")'> Download »results.csv« as file</button>
<script>
createTable(tab_results_csv_json, tab_results_headers_json, 'tab_results_csv_table');</script>
<h1> Errors</h1>
<button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("simple_pre_tab_tab_errors")'> Copy raw data to clipboard</button>
<button onclick='download_as_file("simple_pre_tab_tab_errors", "oo_errors.txt")'> Download »oo_errors.txt« as file</button>
<pre id='simple_pre_tab_tab_errors'><span style="background-color: black; color: white">
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2328959/2328959_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.1 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2328961/2328961_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2328962/2328962_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 100 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(100, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2328965/2328965_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 543 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(543, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2328971/2328971_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 100 confidence 0.1 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(100, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2328973/2328973_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2328975/2328975_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 626 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(626, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2328976/2328976_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 100 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(100, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2328982/2328982_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2328988/2328988_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2328989/2328989_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2328995/2328995_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 922 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(922, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2328996/2328996_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 680 confidence 0.01 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(680, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329009/2329009_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 759 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(759, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329011/2329011_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 798 confidence 0.001 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(798, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329014/2329014_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 613 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(613, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329016/2329016_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 643 confidence 0.05 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(643, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329019/2329019_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.01 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329026/2329026_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329034/2329034_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 736 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(736, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329037/2329037_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 742 confidence 0.025 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(742, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329039/2329039_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329040/2329040_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329048/2329048_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329056/2329056_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 639 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(639, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329062/2329062_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329099/2329099_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 987 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(987, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329103/2329103_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329113/2329113_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329117/2329117_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 573 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(573, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329118/2329118_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 902 confidence 0.005 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(902, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329119/2329119_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 900 confidence 0.01 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(900, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329123/2329123_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329126/2329126_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329128/2329128_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 682 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(682, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329129/2329129_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.01 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329131/2329131_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 653 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(653, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329133/2329133_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 412 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(412, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329135/2329135_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329136/2329136_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 648 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(648, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329137/2329137_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329138/2329138_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 744 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(744, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329139/2329139_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 944 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(944, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329140/2329140_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329142/2329142_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.01 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329143/2329143_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 483 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(483, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329144/2329144_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329145/2329145_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329146/2329146_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 421 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(421, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329148/2329148_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 679 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(679, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329147/2329147_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 852 confidence 0.001 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(852, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329149/2329149_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 490 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(490, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329150/2329150_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329151/2329151_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 419 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(419, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329152/2329152_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329153/2329153_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.01 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329156/2329156_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329157/2329157_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 454 confidence 0.001 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(454, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329158/2329158_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329160/2329160_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 965 confidence 0.025 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(965, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329161/2329161_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329163/2329163_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.025 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329164/2329164_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.01 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329165/2329165_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329166/2329166_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329169/2329169_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329170/2329170_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 421 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(421, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329171/2329171_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329172/2329172_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 100 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(100, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329173/2329173_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329174/2329174_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 640 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(640, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329175/2329175_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 510 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(510, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329177/2329177_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329178/2329178_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329180/2329180_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 465 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(465, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329181/2329181_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 224 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(224, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329182/2329182_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329184/2329184_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 246 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(246, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329185/2329185_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 408 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(408, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329186/2329186_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329187/2329187_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329188/2329188_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 670 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(670, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329189/2329189_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 455 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(455, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329191/2329191_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 559 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(559, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329192/2329192_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329193/2329193_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329195/2329195_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 424 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(424, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329196/2329196_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 100 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(100, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329197/2329197_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329198/2329198_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.01 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329199/2329199_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 353 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(353, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329201/2329201_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 407 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(407, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329202/2329202_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 403 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(403, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329203/2329203_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329204/2329204_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 416 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(416, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329205/2329205_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329206/2329206_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329207/2329207_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329208/2329208_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329209/2329209_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.05 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329210/2329210_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 719 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(719, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329212/2329212_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 806 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(806, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329213/2329213_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329230/2329230_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 333 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(333, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329232/2329232_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 358 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(358, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329233/2329233_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329234/2329234_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 869 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(869, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329237/2329237_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 713 confidence 0.025 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(713, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329241/2329241_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 644 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(644, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329242/2329242_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329243/2329243_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329246/2329246_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329247/2329247_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329248/2329248_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.05 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329249/2329249_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329250/2329250_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 717 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(717, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329251/2329251_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 924 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(924, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329252/2329252_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 832 confidence 0.025 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(832, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329253/2329253_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329254/2329254_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.1 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329255/2329255_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329256/2329256_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 953 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(953, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329257/2329257_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329259/2329259_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329260/2329260_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 523 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(523, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329261/2329261_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329262/2329262_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329263/2329263_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.05 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329264/2329264_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 953 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(953, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329266/2329266_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329267/2329267_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 991 confidence 0.1 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(991, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329268/2329268_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329269/2329269_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329270/2329270_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 632 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(632, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329271/2329271_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329272/2329272_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329273/2329273_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 893 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(893, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329274/2329274_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329275/2329275_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 863 confidence 0.01 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(863, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329276/2329276_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 506 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(506, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329278/2329278_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.1 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329279/2329279_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329280/2329280_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 643 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(643, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329281/2329281_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 538 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(538, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329282/2329282_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 560 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(560, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329283/2329283_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329284/2329284_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329285/2329285_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329286/2329286_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329288/2329288_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329289/2329289_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329290/2329290_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 452 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(452, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329294/2329294_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329295/2329295_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329296/2329296_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329301/2329301_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 895 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(895, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329310/2329310_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 991 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(991, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329311/2329311_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 987 confidence 0.1 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(987, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329316/2329316_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 885 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(885, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329318/2329318_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 874 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(874, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329320/2329320_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 723 confidence 0.025 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(723, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329322/2329322_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 861 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(861, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329324/2329324_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 886 confidence 0.005 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(886, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329325/2329325_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 716 confidence 0.05 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(716, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329326/2329326_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 730 confidence 0.01 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(730, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329328/2329328_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 877 confidence 0.01 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(877, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329330/2329330_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 873 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(873, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329333/2329333_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 872 confidence 0.005 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(872, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329334/2329334_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 711 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(711, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329335/2329335_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 863 confidence 0.025 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(863, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329336/2329336_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 875 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(875, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329337/2329337_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 871 confidence 0.01 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(871, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329338/2329338_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 897 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(897, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329340/2329340_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 852 confidence 0.05 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(852, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329341/2329341_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 871 confidence 0.025 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(871, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329342/2329342_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 859 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(859, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329344/2329344_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 877 confidence 0.01 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(877, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329347/2329347_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 711 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(711, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329349/2329349_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 873 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(873, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329350/2329350_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 732 confidence 0.01 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(732, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329352/2329352_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 857 confidence 0.05 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(857, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329353/2329353_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 859 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(859, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329354/2329354_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 877 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(877, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329355/2329355_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 771 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(771, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329356/2329356_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 738 confidence 0.01 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(738, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329357/2329357_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 765 confidence 0.1 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(765, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329358/2329358_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 714 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(714, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329360/2329360_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 606 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(606, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329361/2329361_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 751 confidence 0.025 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(751, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329363/2329363_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 733 confidence 0.05 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(733, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329364/2329364_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 719 confidence 0.01 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(719, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329366/2329366_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 754 confidence 0.05 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(754, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329368/2329368_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 761 confidence 0.05 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(761, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329369/2329369_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 703 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(703, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329371/2329371_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 769 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(769, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329373/2329373_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 434 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(434, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329374/2329374_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 863 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(863, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329375/2329375_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 443 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(443, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329380/2329380_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 445 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(445, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329381/2329381_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 602 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(602, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329382/2329382_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 576 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(576, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329383/2329383_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 616 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(616, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329384/2329384_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 858 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(858, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329385/2329385_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 572 confidence 0.001 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(572, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329386/2329386_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 842 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(842, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329388/2329388_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 538 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(538, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329389/2329389_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 545 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(545, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329390/2329390_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 543 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(543, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329391/2329391_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 868 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(868, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329392/2329392_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 844 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(844, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329393/2329393_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 859 confidence 0.001 feature_proportion 0 n_clusters 3
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(859, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329395/2329395_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 703 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(703, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329396/2329396_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 860 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(860, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329397/2329397_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 707 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(707, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329400/2329400_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 867 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(867, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329405/2329405_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 870 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(870, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329406/2329406_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 616 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(616, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329407/2329407_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 658 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(658, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329408/2329408_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329410/2329410_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 688 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(688, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329411/2329411_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 647 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(647, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329414/2329414_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 853 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(853, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329415/2329415_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 869 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(869, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329416/2329416_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329417/2329417_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 870 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(870, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329418/2329418_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 878 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(878, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329421/2329421_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329423/2329423_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 882 confidence 0.01 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(882, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329425/2329425_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 860 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(860, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329426/2329426_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 870 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(870, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329427/2329427_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 853 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(853, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329548/2329548_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 862 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(862, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329525/2329525_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 871 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(871, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329536/2329536_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 849 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(849, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329595/2329595_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 863 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(863, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329596/2329596_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 951 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(951, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329598/2329598_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 859 confidence 0.05 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(859, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329600/2329600_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 485 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(485, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329601/2329601_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 850 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(850, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329602/2329602_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 817 confidence 0.1 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(817, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329604/2329604_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 865 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(865, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329611/2329611_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 948 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(948, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329612/2329612_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 872 confidence 0.001 feature_proportion 0 n_clusters 2
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(872, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329614/2329614_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 440 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(440, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329616/2329616_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329618/2329618_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 958 confidence 0.25 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(958, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329621/2329621_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329625/2329625_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 592 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(592, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329626/2329626_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 578 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(578, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329630/2329630_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 591 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(591, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329632/2329632_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329634/2329634_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 627 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(627, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329635/2329635_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 482 confidence 0.025 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(482, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329637/2329637_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.001 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329640/2329640_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 901 confidence 0.01 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(901, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329642/2329642_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.25 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329643/2329643_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 933 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(933, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329644/2329644_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.005 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329645/2329645_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.05 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329647/2329647_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 934 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(934, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329648/2329648_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 1000 confidence 0.025 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(1000, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329651/2329651_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 909 confidence 0.01 feature_proportion 0 n_clusters 1
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(909, 0)) while a minimum of 1
Out file /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/unsupervised-concept-drift-detection-main/runs/ClusteredStatisticalTestDriftDetectionMethod_Powersupply/0/single_runs/2329653/2329653_0_log.out contains potential errors:
Program-Code: module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main_omniopt.py Powersupply 1000 ClusteredStatisticalTestDriftDetectionMethod n_samples 932 confidence 0.001 feature_proportion 0 n_clusters 4
- Got no result.
- Non-zero exit-code detected: 1
- raise ValueError(ValueError: Found array with 0 feature(s) (shape=(932, 0)) while a minimum of 1
</span></pre><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("simple_pre_tab_tab_errors")'> Copy raw data to clipboard</button>
<button onclick='download_as_file("simple_pre_tab_tab_errors", "oo_errors.txt")'> Download »oo_errors.txt« as file</button>
<h1> CPU/RAM-Usage (main)</h1>
<div class='invert_in_dark_mode' id='mainWorkerCPURAM'></div><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("pre_tab_main_worker_cpu_ram")'> Copy raw data to clipboard</button>
<button onclick='download_as_file("pre_tab_main_worker_cpu_ram", "cpu_ram_usage.csv")'> Download »cpu_ram_usage.csv« as file</button>
<pre id="pre_tab_main_worker_cpu_ram">timestamp,ram_usage_mb,cpu_usage_percent
1727815908,478.8203125,49.7
1727815908,479.04296875,48.1
1727815908,479.04296875,49.9
1727815908,479.04296875,37.5
1727815908,479.04296875,56.5
1727815908,479.04296875,49.1
1727815908,479.04296875,57.8
1727815954,486.43359375,49.8
1727815954,486.43359375,55.3
1727815954,486.43359375,49.5
1727815954,486.43359375,48.7
1727815955,486.43359375,49.7
1727815955,486.43359375,50.0
1727815955,486.43359375,50.0
1727815955,486.43359375,51.0
1727815957,486.43359375,49.7
1727815957,486.43359375,40.0
1727815957,486.43359375,52.9
1727815957,486.43359375,40.6
1727815958,486.43359375,49.8
1727815958,486.43359375,55.3
1727815958,486.43359375,49.5
1727815958,486.43359375,41.2
1727815959,486.43359375,49.7
1727815959,486.43359375,54.3
1727815959,486.43359375,49.1
1727815959,486.43359375,52.5
1727815961,488.31640625,49.7
1727815961,488.31640625,54.3
1727815961,488.31640625,48.5
1727815961,488.31640625,51.2
1727815962,488.31640625,49.7
1727815962,488.31640625,54.3
1727815962,488.31640625,49.0
1727815962,488.31640625,40.6
1727815964,488.31640625,49.8
1727815964,488.31640625,55.3
1727815964,488.31640625,49.1
1727815964,488.31640625,55.6
1727815965,488.31640625,49.7
1727815965,488.31640625,47.5
1727815965,488.31640625,49.0
1727815965,488.31640625,57.8
1727815966,488.31640625,49.7
1727815966,488.31640625,43.9
1727815966,488.31640625,53.2
1727815966,488.31640625,39.4
1727815969,489.234375,49.9
1727815969,489.234375,54.3
1727815969,489.234375,49.5
1727815969,489.234375,57.8
1727815972,489.24609375,49.9
1727815972,489.24609375,48.8
1727815972,489.24609375,48.1
1727815972,489.24609375,58.7
1727815975,489.3203125,49.9
1727815975,489.3203125,40.0
1727815975,489.3203125,49.5
1727815975,489.3203125,55.6
1727815977,489.3203125,49.9
1727815977,489.3203125,35.3
1727815977,489.3203125,55.1
1727815977,489.3203125,38.7
1727815979,489.3203125,49.9
1727815979,489.3203125,55.6
1727815979,489.3203125,50.0
1727815979,489.3203125,38.7
1727815982,489.3203125,49.9
1727815982,489.3203125,56.5
1727815982,489.3203125,50.5
1727815982,489.3203125,40.0
1727815984,489.3203125,49.9
1727815984,489.3203125,37.1
1727815984,489.3203125,52.5
1727815984,489.3203125,39.4
1727815987,489.3984375,49.8
1727815987,489.3984375,54.3
1727815987,489.3984375,48.1
1727815987,489.3984375,56.2
1727815989,489.40234375,49.9
1727815989,489.40234375,47.6
1727815989,489.40234375,52.4
1727815989,489.40234375,40.6
1727815992,489.5625,49.9
1727815992,489.5625,39.4
1727815992,489.5625,48.6
1727815992,489.5625,58.1
1727815995,489.5625,49.9
1727815995,489.5625,57.4
1727815995,489.5625,47.2
1727815995,489.5625,58.1
1727815997,489.609375,49.9
1727815997,489.609375,56.5
1727815997,489.609375,48.6
1727815997,489.609375,57.8
1727815999,489.609375,49.8
1727815999,489.609375,54.3
1727815999,489.609375,48.6
1727815999,489.609375,52.5
1727816001,489.703125,49.9
1727816001,489.703125,53.3
1727816001,489.703125,47.3
1727816001,489.703125,57.8
1727816004,489.70703125,49.9
1727816004,489.70703125,56.5
1727816004,489.70703125,48.6
1727816004,489.70703125,37.5
1727816006,489.73046875,49.9
1727816006,489.73046875,56.5
1727816006,489.73046875,48.2
1727816006,489.73046875,55.0
1727816008,489.73046875,49.8
1727816008,489.73046875,58.3
1727816008,489.73046875,45.9
1727816008,489.73046875,58.1
1727816011,489.73046875,49.9
1727816011,489.73046875,53.2
1727816011,489.73046875,46.8
1727816011,489.73046875,55.6
1727816013,489.73828125,49.9
1727816013,489.73828125,56.3
1727816013,489.73828125,46.4
1727816013,489.73828125,56.8
1727816015,489.73828125,49.9
1727816015,489.73828125,44.4
1727816015,489.73828125,52.5
1727816015,489.73828125,43.7
1727816018,489.73828125,49.9
1727816018,489.73828125,56.8
1727816018,489.73828125,49.5
1727816018,489.73828125,56.8
1727816020,489.73828125,49.8
1727816020,489.73828125,55.6
1727816020,489.73828125,45.0
1727816020,489.73828125,56.9
1727816022,489.75,49.8
1727816022,489.75,55.6
1727816022,489.75,47.2
1727816022,489.75,53.7
1727816025,489.75,49.9
1727816025,489.75,55.6
1727816025,489.75,47.3
1727816025,489.75,56.8
1727816027,489.75,49.8
1727816027,489.75,54.3
1727816027,489.75,46.8
1727816027,489.75,57.8
1727816029,489.75,49.8
1727816029,489.75,54.3
1727816029,489.75,46.4
1727816029,489.75,56.8
1727816031,489.75,49.8
1727816031,489.75,54.2
1727816031,489.75,51.2
1727816031,489.75,38.7
1727816033,489.75,49.9
1727816033,489.75,38.9
1727816033,489.75,52.0
1727816033,489.75,44.1
1727816035,489.75,49.9
1727816035,489.75,40.0
1727816035,489.75,52.0
1727816035,489.75,40.6
1727816038,489.75,49.9
1727816038,489.75,57.8
1727816038,489.75,45.5
1727816038,489.75,58.1
1727816040,489.75,49.9
1727816040,489.75,53.2
1727816040,489.75,51.2
1727816040,489.75,41.9
1727816042,489.75,49.9
1727816042,489.75,37.5
1727816042,489.75,52.4
1727816042,489.75,40.0
1727816044,489.75,49.9
1727816044,489.75,53.2
1727816044,489.75,49.6
1727816044,489.75,56.8
1727816046,489.75,49.8
1727816046,489.75,53.2
1727816046,489.75,46.4
1727816046,489.75,57.8
1727816048,489.75,49.9
1727816048,489.75,38.2
1727816048,489.75,52.0
1727816048,489.75,55.8
1727816050,489.75,49.8
1727816050,489.75,55.6
1727816050,489.75,46.4
1727816050,489.75,56.8
1727816053,489.84375,49.9
1727816053,489.84375,39.4
1727816053,489.84375,50.0
1727816053,489.84375,56.5
1727816055,489.84375,49.9
1727816055,489.84375,39.4
1727816055,489.84375,50.4
1727816055,489.84375,56.8
1727816057,489.84375,49.8
1727816057,489.84375,41.7
1727816057,489.84375,53.6
1727816057,489.84375,38.7
1727816059,489.84375,49.8
1727816059,489.84375,54.9
1727816059,489.84375,47.7
1727816059,489.84375,56.8
1727816061,489.84375,49.8
1727816061,489.84375,55.3
1727816061,489.84375,49.6
1727816061,489.84375,39.4
1727816063,489.84375,49.9
1727816063,489.84375,39.4
1727816063,489.84375,51.2
1727816063,489.84375,40.0
1727816066,489.84375,49.9
1727816066,489.84375,40.0
1727816066,489.84375,52.0
1727816066,489.84375,37.5
1727816068,489.84375,49.9
1727816068,489.84375,37.5
1727816068,489.84375,50.8
1727816068,489.84375,56.5
1727816070,489.88671875,49.9
1727816070,489.88671875,54.3
1727816070,489.88671875,50.8
1727816070,489.88671875,48.7
1727816073,489.88671875,49.9
1727816073,489.88671875,56.5
1727816073,489.88671875,49.4
1727816073,489.88671875,42.4
1727816075,489.88671875,49.9
1727816075,489.88671875,38.9
1727816075,489.88671875,54.0
1727816075,489.88671875,38.7
1727816077,489.88671875,49.9
1727816077,489.88671875,48.7
1727816077,489.88671875,47.9
1727816077,489.88671875,56.5
1727816079,489.88671875,49.8
1727816079,489.88671875,38.9
1727816079,489.88671875,50.4
1727816079,489.88671875,56.5
1727816081,489.88671875,49.9
1727816081,489.88671875,38.2
1727816081,489.88671875,50.8
1727816081,489.88671875,56.8
1727816083,489.88671875,49.9
1727816083,489.88671875,37.5
1727816083,489.88671875,52.7
1727816083,489.88671875,37.1
1727816086,489.88671875,49.9
1727816086,489.88671875,44.4
1727816086,489.88671875,49.0
1727816086,489.88671875,58.1
1727816214,529.5234375,50.1
1727816214,529.5234375,53.1
1727816214,529.5234375,52.1
1727816214,529.5234375,38.7
1727816254,530.078125,50.2
1727816254,530.078125,53.2
1727816254,530.078125,51.0
1727816254,530.078125,36.4
1727816366,531.9609375,50.2
1727816366,531.9609375,53.2
1727816366,531.9609375,49.4
1727816366,531.9609375,50.0
1727816472,534.65234375,50.2
1727816472,534.65234375,48.9
1727816472,534.65234375,50.3
1727816472,534.65234375,44.1
1727816605,535.72265625,50.2
1727816605,535.72265625,52.7
1727816605,535.72265625,49.7
1727816605,535.72265625,40.6
1727816713,538.6640625,50.2
1727816713,538.6640625,54.3
1727816713,538.6640625,49.0
1727816713,538.6640625,38.7
1727816872,540.56640625,50.2
1727816872,540.56640625,39.4
1727816872,540.56640625,52.4
1727816872,540.56640625,42.4
1727817232,540.9765625,50.3
1727817232,540.9765625,53.2
1727817232,540.9765625,50.3
1727817232,540.9765625,40.6
1727817494,541.3359375,50.2
1727817494,541.3359375,43.2
1727817494,541.3359375,50.0
1727817494,541.3359375,52.4
1727817693,546.296875,50.2
1727817693,546.296875,39.4
1727817693,546.296875,50.3
1727817693,546.296875,51.3
1727817956,551.16015625,50.2
1727817956,551.16015625,55.3
1727817956,551.16015625,50.0
1727817957,551.16015625,48.6
1727818291,550.5625,50.2
1727818291,550.5625,54.2
1727818291,550.5625,49.8
1727818291,550.5625,51.2
1727818600,553.140625,50.2
1727818600,553.140625,36.4
1727818600,553.140625,52.5
1727818600,553.140625,40.6
1727818954,551.89453125,50.2
1727818954,551.89453125,46.2
1727818954,551.89453125,49.1
1727818954,551.89453125,57.8
1727819285,555.58203125,50.2
1727819285,555.58203125,38.2
1727819285,555.58203125,51.6
1727819285,555.58203125,42.4
1727819695,556.27734375,50.2
1727819695,556.27734375,54.3
1727819695,556.27734375,50.4
1727819695,556.27734375,40.0
1727820034,432.87890625,50.2
1727820034,432.87890625,45.0
1727820034,432.87890625,51.4
1727820034,432.87890625,44.4
1727820358,440.87109375,50.2
1727820358,440.87109375,36.4
1727820358,440.87109375,51.0
1727820358,440.87109375,50.0
1727820761,448.55859375,50.2
1727820761,448.55859375,57.4
1727820761,448.55859375,51.2
1727820761,448.55859375,41.9
1727821172,441.4140625,50.2
1727821172,441.4140625,54.3
1727821172,441.4140625,50.4
1727821172,441.4140625,39.4
1727821623,452.89453125,50.2
1727821623,452.89453125,38.2
1727821623,452.89453125,50.4
1727821623,452.89453125,51.0
1727822216,452.63671875,50.2
1727822216,452.63671875,55.3
1727822216,452.63671875,48.7
1727822216,452.63671875,58.7
1727822764,437.609375,50.2
1727822764,437.609375,50.0
1727822764,437.609375,50.4
1727822764,437.609375,42.4
1727823200,435.96484375,50.2
1727823200,435.96484375,38.2
1727823200,435.96484375,51.5
1727823200,435.96484375,40.6
1727823636,435.4375,50.2
1727823636,435.4375,38.2
1727823636,435.4375,51.5
1727823636,435.4375,40.6
1727824080,432.55859375,50.2
1727824080,432.55859375,46.5
1727824080,432.55859375,51.7
1727824080,432.55859375,39.4
1727824545,441.23046875,50.2
1727824545,441.23046875,39.4
1727824545,441.23046875,50.2
1727824545,441.23046875,57.8
1727824958,440.6796875,50.2
1727824958,440.6796875,53.3
1727824958,440.6796875,50.3
1727824958,440.6796875,40.6
1727825490,443.74609375,50.2
1727825490,443.74609375,52.8
1727825490,443.74609375,49.9
1727825490,443.74609375,55.6
1727825932,443.5078125,50.2
1727825932,443.5078125,47.5
1727825932,443.5078125,50.3
1727825932,443.5078125,42.4
1727826372,443.40625,50.1
1727826372,443.40625,51.2
1727826372,443.40625,50.1
1727826372,443.40625,40.6
1727826843,446.078125,50.2
1727826843,446.078125,54.3
1727826843,446.078125,49.3
1727826843,446.078125,58.1
1727827271,447.640625,50.2
1727827271,447.640625,36.4
1727827271,447.640625,51.4
1727827271,447.640625,37.5
1727827679,439.05859375,50.1
1727827679,439.05859375,55.6
1727827679,439.05859375,49.7
1727827679,439.05859375,51.3
1727828105,448.30078125,50.2
1727828105,448.30078125,48.9
1727828105,448.30078125,50.7
1727828105,448.30078125,55.6
1727828457,444.8515625,50.1
1727828457,444.8515625,53.2
1727828457,444.8515625,50.1
1727828457,444.8515625,38.7
1727828859,440.9609375,50.1
1727828859,440.9609375,52.2
1727828859,440.9609375,49.2
1727828859,440.9609375,57.8
1727829259,441.6875,50.1
1727829259,441.6875,52.0
1727829308,441.6796875,49.8
1727829308,441.6796875,38.9
</pre><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("pre_tab_main_worker_cpu_ram")'> Copy raw data to clipboard</button>
<button onclick='download_as_file("pre_tab_main_worker_cpu_ram", "cpu_ram_usage.csv")'> Download »cpu_ram_usage.csv« as file</button>
<h1> Parallel Plot</h1>
<div class="invert_in_dark_mode" id="parallel-plot"></div>
<h1> Job Status Distribution</h1>
<div class="invert_in_dark_mode" id="plotJobStatusDistribution"></div>
<h1> Boxplots</h1>
<div class="invert_in_dark_mode" id="plotBoxplot"></div>
<h1> Violin</h1>
<div class="invert_in_dark_mode" id="plotViolin"></div>
<h1> Histogram</h1>
<div class="invert_in_dark_mode" id="plotHistogram"></div>
<h1> Heatmap</h1>
<div class="invert_in_dark_mode" id="plotHeatmap"></div><br>
<h1>Correlation Heatmap Explanation</h1>
<p>
This is a heatmap that visualizes the correlation between numerical columns in a dataset. The values represented in the heatmap show the strength and direction of relationships between different variables.
</p>
<h2>How It Works</h2>
<p>
The heatmap uses a matrix to represent correlations between each pair of numerical columns. The calculation behind this is based on the concept of "correlation," which measures how strongly two variables are related. A correlation can be positive, negative, or zero:
</p>
<ul>
<li><strong>Positive correlation</strong>: Both variables increase or decrease together (e.g., if the temperature rises, ice cream sales increase).</li>
<li><strong>Negative correlation</strong>: As one variable increases, the other decreases (e.g., as the price of a product rises, the demand for it decreases).</li>
<li><strong>Zero correlation</strong>: There is no relationship between the two variables (e.g., height and shoe size might show zero correlation in some contexts).</li>
</ul>
<h2>Color Scale: Yellow to Purple (Viridis)</h2>
<p>
The heatmap uses a color scale called "Viridis," which ranges from yellow to purple. Here's what the colors represent:
</p>
<ul>
<li><strong>Yellow (brightest)</strong>: A strong positive correlation (close to +1). This indicates that as one variable increases, the other increases in a very predictable manner.</li>
<li><strong>Green</strong>: A moderate positive correlation. Variables are still positively related, but the relationship is not as strong.</li>
<li><strong>Blue</strong>: A weak or near-zero correlation. There is a small or no discernible relationship between the variables.</li>
<li><strong>Purple (darkest)</strong>: A strong negative correlation (close to -1). This indicates that as one variable increases, the other decreases in a very predictable manner.</li>
</ul>
<h2>What the Heatmap Shows</h2>
<p>
In the heatmap, each cell represents the correlation between two numerical columns. The color of the cell is determined by the correlation coefficient: from yellow for strong positive correlations, through green and blue for weaker correlations, to purple for strong negative correlations.
</p>
<h1> Exit-Codes</h1>
<div class="invert_in_dark_mode" id="plotExitCodesPieChart"></div>
</body>
</html>