OmniOpt2

Setting	Value
Model for non-random steps	BOTORCH_MODULAR
Max. nr. evaluations	500
Number random steps	20
Nr. of workers (parameter)	30
Main process memory (GB)	8
Worker memory (GB)	32

Name	Type	Lower bound	Upper bound	Values	Type	Log Scale?
recent_samples_size	range	1	5000		int	No
feature_id	fixed			0
batch_size	range	1	5000		int	No
divergence	choice			str\(\'H\'\), str\(\'KL\'\)
detect_batch	choice			1, 2, 3
statistic	choice			str\(\'stdev\'\), str\(\'tstat\'\)
significance	range	0.001	0.999		float	No
subsets	range	1	100		int	No

Failed	Succeeded	Running	Total
124	380	6	510

name	min/max
ACCURACY	max
RUNTIME	min

start_time,end_time,run_time,program_string,recent_samples_size,batch_size,divergence,detect_batch,statistic,significance,subsets,feature_id,ACCURACY,RUNTIME,exit_code,signal,hostname,OO_Info_runtime,OO_Info_peak_memory,OO_Info_mean_memory,OO_Info_lpd,OO_Info_portion_req_label,OO_Info_SLURM_JOB_ID
1743371549,1743371568,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2898 feature_id 0 batch_size 2267 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.9264353577475994 subsets 53,2898,2267,str\(\'H\'\),1,str\(\'tstat\'\),0.9264353577475994,53,0,0.2,6,0,None,i7102,6,758.50390625,756.78125,-1,0.08868299139642621,3828581
1743371547,1743371572,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3789 feature_id 0 batch_size 923 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.7525551124811173 subsets 87,3789,923,str\(\'KL\'\),3,str\(\'tstat\'\),0.7525551124811173,87,0,0.22,6,0,None,i7154,6,749.8515625,749.6458333333334,-1,0,3828326
1743371547,1743371573,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3688 feature_id 0 batch_size 4728 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.7195025321617723 subsets 28,3688,4728,str\(\'H\'\),1,str\(\'tstat\'\),0.7195025321617723,28,0,0.2,5,0,None,i7141,5,750.6953125,750.5234375,-1,0,3828457
1743371549,1743371575,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 130 feature_id 0 batch_size 2806 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.02548688580840826 subsets 20,130,2806,str\(\'H\'\),2,str\(\'stdev\'\),0.02548688580840826,20,0,0.2,4,0,None,i7146,4,751.375,751.1171875,-1,0,3828406
1743371551,1743371576,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2413 feature_id 0 batch_size 1620 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.4951464280989021 subsets 67,2413,1620,str\(\'KL\'\),3,str\(\'stdev\'\),0.4951464280989021,67,0,0.2,4,0,None,i7144,4,749.73046875,749.5520833333334,-1,0,3828433
1743371569,1743371614,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1623 feature_id 0 batch_size 4159 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.17225318533182143 subsets 43,1623,4159,str\(\'KL\'\),2,str\(\'stdev\'\),0.17225318533182143,43,0,0.2,4,0,None,i7009,4,750.0078125,749.8307291666666,-1,0,3828713
1743371584,1743371622,38,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 902 feature_id 0 batch_size 189 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.32620021064393223 subsets 95,902,189,str\(\'H\'\),2,str\(\'stdev\'\),0.32620021064393223,95,0,0.29,25,0,None,i7185,25,750.58203125,750.425,-1,0.06254136333553938,3828841
1743371636,1743371655,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4561 feature_id 0 batch_size 3307 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.5853452934771777 subsets 11,4561,3307,str\(\'KL\'\),3,str\(\'tstat\'\),0.5853452934771777,11,0,0.2,4,0,None,i7183,4,749.78515625,749.5911458333334,-1,0,3828886
1743371817,1743371836,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4850 feature_id 0 batch_size 1493 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.6755754890907556 subsets 62,4850,1493,str\(\'H\'\),2,str\(\'stdev\'\),0.6755754890907556,62,0,0.2,6,0,None,i7184,6,751.43359375,751.1783854166666,-1,0.32660489741892784,3829038
1743371844,1743371870,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1233 feature_id 0 batch_size 4620 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.4201877424456179 subsets 44,1233,4620,str\(\'KL\'\),1,str\(\'tstat\'\),0.4201877424456179,44,0,0.2,5,0,None,i7161,5,750.8515625,750.6888020833334,-1,0,3829252
1743371845,1743371870,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3398 feature_id 0 batch_size 453 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.5024947959277779 subsets 78,3398,453,str\(\'KL\'\),2,str\(\'stdev\'\),0.5024947959277779,78,0,0.25,9,0,None,i7107,9,750.17578125,749.859375,-1,0,3829555
1743371848,1743371873,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2606 feature_id 0 batch_size 2835 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.8335472971089184 subsets 3,2606,2835,str\(\'KL\'\),1,str\(\'stdev\'\),0.8335472971089184,3,0,0.2,5,0,None,i7144,5,749.87109375,749.7265625,-1,0.27663798808735934,3829420
1743371849,1743371875,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1293 feature_id 0 batch_size 972 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.07507479900307953 subsets 92,1293,972,str\(\'H\'\),3,str\(\'tstat\'\),0.07507479900307953,92,0,0.21,6,0,None,i7149,6,750.1484375,749.91796875,-1,0,3829375
1743371858,1743371896,38,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2085 feature_id 0 batch_size 3590 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.2745712294690311 subsets 17,2085,3590,str\(\'H\'\),3,str\(\'tstat\'\),0.2745712294690311,17,0,0.2,4,0,None,i7002,4,750.68359375,750.5338541666666,-1,0,3829766
1743372005,1743372024,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 461 feature_id 0 batch_size 2081 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.24529264404810966 subsets 70,461,2081,str\(\'KL\'\),1,str\(\'tstat\'\),0.24529264404810966,70,0,0.2,7,0,None,i7180,7,751.90625,751.69921875,-1,0.027134348113831898,3829918
1743372142,1743372168,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4078 feature_id 0 batch_size 3953 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.9683822459243238 subsets 37,4078,3953,str\(\'H\'\),3,str\(\'stdev\'\),0.9683822459243238,37,0,0.2,4,0,None,i7176,4,751.6484375,751.4817708333334,-1,0,3830068
1743372144,1743372170,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4227 feature_id 0 batch_size 1993 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.2921925953757018 subsets 23,4227,1993,str\(\'KL\'\),2,str\(\'tstat\'\),0.2921925953757018,23,0,0.2,4,0,None,i7164,4,750.93359375,750.62109375,-1,0,3830163
1743372145,1743372171,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 611 feature_id 0 batch_size 3885 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.5477361920028925 subsets 84,611,3885,str\(\'H\'\),3,str\(\'stdev\'\),0.5477361920028925,84,0,0.2,4,0,None,i7151,4,749.90234375,749.7356770833334,-1,0,3830289
1743372146,1743372171,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3229 feature_id 0 batch_size 3659 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.19676591384410858 subsets 64,3229,3659,str\(\'H\'\),2,str\(\'tstat\'\),0.19676591384410858,64,0,0.2,4,0,None,i7014,4,750.8359375,750.6888020833334,-1,0,3830563
1743372147,1743372172,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1916 feature_id 0 batch_size 541 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.955021648881957 subsets 31,1916,541,str\(\'KL\'\),1,str\(\'stdev\'\),0.955021648881957,31,0,0.29,7,0,None,i7139,7,750.01953125,749.8736979166666,-1,0.17902051621442752,3830400
1743372196,1743372215,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2770 feature_id 0 batch_size 1197 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.4029592611100525 subsets 39,2770,1197,str\(\'H\'\),3,str\(\'tstat\'\),0.4029592611100525,39,0,0.2,5,0,None,i7182,5,751.01171875,750.79296875,-1,0.13070814030443414,3830735
1743372274,1743372294,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1457 feature_id 0 batch_size 3080 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.6309168513789774 subsets 57,1457,3080,str\(\'KL\'\),1,str\(\'stdev\'\),0.6309168513789774,57,0,0.2,5,0,None,i7180,5,749.72265625,749.5716145833334,-1,0,3830802
1743372442,1743372461,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1089 feature_id 0 batch_size 1269 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.8472397764082998 subsets 9,1089,1269,str\(\'H\'\),3,str\(\'stdev\'\),0.8472397764082998,9,0,0.2,5,0,None,i7178,5,750.61328125,750.4010416666666,-1,0.1783587028457975,3830949
1743372446,1743372465,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1791 feature_id 0 batch_size 2354 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.5993037433121353 subsets 6,1791,2354,str\(\'H\'\),2,str\(\'tstat\'\),0.5993037433121353,6,0,0.2,4,0,None,i7059,4,749.83984375,749.5065104166666,-1,0,3831375
1743372442,1743372468,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4705 feature_id 0 batch_size 4377 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.1242451114282012 subsets 98,4705,4377,str\(\'KL\'\),2,str\(\'tstat\'\),0.1242451114282012,98,0,0.2,4,0,None,i7164,4,750.953125,750.7786458333334,-1,0,3831051
1743372443,1743372468,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3066 feature_id 0 batch_size 4227 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.37510348923131825 subsets 90,3066,4227,str\(\'KL\'\),3,str\(\'stdev\'\),0.37510348923131825,90,0,0.2,4,0,None,i7012,4,750.9765625,750.8216145833334,-1,0,3831436
1743372445,1743372470,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 753 feature_id 0 batch_size 3239 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.8820426757000387 subsets 58,753,3239,str\(\'KL\'\),2,str\(\'tstat\'\),0.8820426757000387,58,0,0.2,4,0,None,i7141,4,750.3125,750.1380208333334,-1,0,3831259
1743372445,1743372471,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4412 feature_id 0 batch_size 101 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.15475768502987922 subsets 48,4412,101,str\(\'H\'\),1,str\(\'stdev\'\),0.15475768502987922,48,0,0.29,7,0,None,i7153,7,750.78125,750.6471354166666,-1,0.06684315023163467,3831153
1743372497,1743372516,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3525 feature_id 0 batch_size 1845 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.0433134132642299 subsets 14,3525,1845,str\(\'KL\'\),3,str\(\'stdev\'\),0.0433134132642299,14,0,0.2,4,0,None,i7179,4,749.78125,749.6041666666666,-1,0,3831599
1743372617,1743372636,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2250 feature_id 0 batch_size 4972 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.7975905225761235 subsets 81,2250,4972,str\(\'H\'\),1,str\(\'tstat\'\),0.7975905225761235,81,0,0.2,7,0,None,i7179,7,750.28125,750.0703125,-1,0,3831707
1743384442,1743384455,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2426 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 1,2426,1,str\(\'H\'\),1,str\(\'stdev\'\),0.001,1,0,None,None,1,None,i7007,3839643
1743384440,1743384459,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1874 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 1,1874,1,str\(\'H\'\),1,str\(\'tstat\'\),0.001,1,0,None,None,1,None,i7006,3839652
1743384440,1743384459,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 37,1,1,str\(\'H\'\),1,str\(\'tstat\'\),0.001,37,0,None,None,1,None,i7005,3839658
1743384440,1743384459,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 24,1,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,24,0,None,None,1,None,i7006,3839651
1743384440,1743384459,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 1,5000,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,1,0,None,None,1,None,i7005,3839664
1743384440,1743384459,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3528 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 1,3528,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,1,0,None,None,1,None,i7006,3839654
1743384440,1743384459,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 1,1,1,str\(\'H\'\),1,str\(\'tstat\'\),0.001,1,0,None,None,1,None,i7005,3839662
1743384442,1743384461,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 1,1,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,1,0,None,None,1,None,i7007,3839640
1743384442,1743384461,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 1,5000,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,1,0,None,None,1,None,i7007,3839647
1743384442,1743384461,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3256 feature_id 0 batch_size 2541 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 52,3256,2541,str\(\'KL\'\),3,str\(\'stdev\'\),0.999,52,0,0.2,4,0,None,i7007,4,750.27734375,750.1171875,-1,0,3839645
1743384442,1743384461,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 1,1,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,1,0,None,None,1,None,i7007,3839641
1743384442,1743384461,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 1,5000,1,str\(\'H\'\),1,str\(\'stdev\'\),0.999,1,0,None,None,1,None,i7004,3839674
1743384442,1743384461,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2379 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 43,2379,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,43,0,None,None,1,None,i7004,3839676
1743384442,1743384461,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 151 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 34,5000,151,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,34,0,0.2,4,0,None,i7009,4,750.51953125,750.3684895833334,-1,0.0499669093315685,3839637
1743384442,1743384461,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2045 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 1,2045,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,1,0,None,None,1,None,i7009,3839638
1743384442,1743384461,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 1,1,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,1,0,None,None,1,None,i7009,3839636
1743384442,1743384461,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4209 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.8179704985356723 subsets 1,4209,1,str\(\'H\'\),1,str\(\'stdev\'\),0.8179704985356723,1,0,None,None,1,None,i7009,3839634
1743384442,1743384461,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4992 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 1,4992,1,str\(\'H\'\),1,str\(\'tstat\'\),0.001,1,0,None,None,1,None,i7009,3839639
1743384440,1743384466,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 406 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 1,5000,406,str\(\'H\'\),1,str\(\'stdev\'\),0.001,1,0,0.32,8,0,None,i7006,8,750.296875,750.1744791666666,-1,0.27895433487756455,3839650
1743384440,1743384466,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 31,1,1,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,31,0,0.31,8,0,None,i7006,8,750.08984375,749.8736979166666,-1,0.0843812045003309,3839656
1743384440,1743384466,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2803 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 1,2803,1,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,1,0,0.31,8,0,None,i7005,8,750.05078125,749.8255208333334,-1,0.08471211118464593,3839666
1743384440,1743384466,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 1,1,1,str\(\'H\'\),3,str\(\'tstat\'\),0.001,1,0,0.31,8,0,None,i7005,8,750.109375,749.8893229166666,-1,0.08471211118464593,3839668
1743384440,1743384466,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 1,1,1,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,1,0,0.31,9,0,None,i7006,9,750.65234375,750.38671875,-1,0.0843812045003309,3839648
1743384440,1743384466,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 100,5000,1,str\(\'H\'\),1,str\(\'tstat\'\),0.001,100,0,None,None,1,None,i7006,3839649
1743384440,1743384466,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 100,1,1,str\(\'H\'\),1,str\(\'tstat\'\),0.001,100,0,None,None,1,None,i7005,3839660
1743384442,1743384467,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 1,1,1,str\(\'H\'\),3,str\(\'tstat\'\),0.999,1,0,0.31,8,0,None,i7007,8,750.4765625,750.2643229166666,-1,0.0843812045003309,3839644
1743384442,1743384467,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 1,1,1,str\(\'KL\'\),3,str\(\'stdev\'\),0.001,1,0,0.31,8,0,None,i7007,8,749.69140625,749.5364583333334,-1,0.0843812045003309,3839646
1743384442,1743384467,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 10,5000,1,str\(\'H\'\),3,str\(\'stdev\'\),0.999,10,0,0.31,8,0,None,i7004,8,750.69140625,750.5234375,-1,0.0843812045003309,3839670
1743384442,1743384467,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 5000 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 47,1,5000,str\(\'H\'\),3,str\(\'stdev\'\),0.999,47,0,0.2,4,0,None,i7004,4,751.7109375,751.54296875,-1,0,3839672
1743384442,1743384467,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 38,5000,1,str\(\'KL\'\),3,str\(\'stdev\'\),0.999,38,0,0.31,8,0,None,i7007,8,750.65625,750.5013020833334,-1,0.0843812045003309,3839642
1743389901,1743389914,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 1,1,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,1,0,None,None,1,None,i7176,3846382
1743389904,1743389923,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 287 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 1,1,287,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,1,0,0.32,8,0,None,i7168,8,750.91015625,750.7408854166666,-1,0.2882197220383852,3846387
1743389904,1743389923,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 414 feature_id 0 batch_size 3834 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 1,414,3834,str\(\'H\'\),1,str\(\'stdev\'\),0.999,1,0,0.2,8,0,None,i7167,8,750.1015625,750,-1,0,3846390
1743389921,1743389940,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 3832 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 1,5000,3832,str\(\'H\'\),1,str\(\'stdev\'\),0.001,1,0,0.2,8,0,None,i7180,8,751.20703125,751.0807291666666,-1,0,3846395
1743389921,1743389946,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 3641 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 100,5000,3641,str\(\'H\'\),1,str\(\'tstat\'\),0.999,100,0,0.2,11,0,None,i7171,11,751.11328125,750.955078125,-1,0,3846401
1743389934,1743389953,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 430 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 1,1,430,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,1,0,0.32,8,0,None,i7168,8,750.90625,750.7747395833334,-1,0.33454665784248844,3846414
1743389934,1743389953,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 100,1,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,100,0,None,None,1,None,i7169,3846408
1743389941,1743389954,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 2398 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 100,1,2398,str\(\'H\'\),3,str\(\'tstat\'\),0.001,100,0,0.2,4,0,None,i7163,4,750.453125,750.2552083333334,-1,0,3846426
1743389941,1743389960,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 152 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 1,1,152,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,1,0,0.33,8,0,None,i7166,8,749.94921875,749.8177083333334,-1,0.2941760423560556,3846420
1743389964,1743389977,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4054 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 1,4054,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,1,0,None,None,1,None,i7162,3846444
1743389964,1743389983,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4673 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 100,4673,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,100,0,None,None,1,None,i7163,3846438
1743389961,1743389986,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 3966 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 100,1,3966,str\(\'H\'\),1,str\(\'tstat\'\),0.999,100,0,0.2,11,0,None,i7171,11,751.1015625,750.9384765625,-1,0,3846432
1743389981,1743390000,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 3673 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 1,1,3673,str\(\'H\'\),1,str\(\'tstat\'\),0.001,1,0,0.2,9,0,None,i7166,9,751.8671875,751.6901041666666,-1,0,3846454
1743389981,1743390000,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 5000 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 1,5000,5000,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,1,0,0.2,4,0,None,i7176,4,749.9375,749.7486979166666,-1,0,3846449
1743389994,1743390013,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 5000 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 1,1,5000,str\(\'H\'\),2,str\(\'stdev\'\),0.001,1,0,0.2,4,0,None,i7162,4,750.5390625,750.3723958333334,-1,0,3846466
1743389994,1743390013,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1599 feature_id 0 batch_size 394 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 1,1599,394,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,1,0,0.32,9,0,None,i7171,9,750.66015625,750.4830729166666,-1,0.2511581733951026,3846460
1743390000,1743390013,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 5000 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 100,5000,5000,str\(\'H\'\),2,str\(\'stdev\'\),0.999,100,0,0.2,4,0,None,i7159,4,750.3203125,750.1744791666666,-1,0,3846477
1743390001,1743390020,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 3373 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 100,5000,3373,str\(\'H\'\),1,str\(\'tstat\'\),0.001,100,0,0.2,11,0,None,i7177,11,751.01953125,750.841796875,-1,0,3846471
1743390021,1743390040,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 385 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 100,1,385,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,100,0,0.2,10,0,None,i7176,10,750.21484375,750.0576171875,-1,0,3846482
1743390024,1743390043,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 5000 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 1,1,5000,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,1,0,0.2,4,0,None,i7157,4,750.90234375,750.74609375,-1,0,3846497
1743390025,1743390044,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 94 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 1,1,94,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,1,0,0.33,8,0,None,i7161,8,750.5546875,750.3815104166666,-1,0.33388484447385836,3846492
1743390021,1743390046,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 4033 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 100,5000,4033,str\(\'H\'\),1,str\(\'stdev\'\),0.001,100,0,0.2,11,0,None,i7166,11,751.1171875,751.0048828125,-1,0,3846487
1743390041,1743390054,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 1,1,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,1,0,None,None,1,None,i7178,3846506
1743390041,1743390060,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 3967 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 1,5000,3967,str\(\'H\'\),1,str\(\'stdev\'\),0.999,1,0,0.2,8,0,None,i7185,8,750.70703125,750.5494791666666,-1,0,3846501
1743390042,1743390061,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 2212 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 100,5000,2212,str\(\'H\'\),3,str\(\'stdev\'\),0.999,100,0,0.2,5,0,None,i7167,5,751.171875,750.98828125,-1,0,3846510
1743390054,1743390067,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 5000 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 100,5000,5000,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,100,0,0.2,4,0,None,i7159,4,750.625,750.4713541666666,-1,0,3846519
1743390054,1743390067,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 5000 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 1,1,5000,str\(\'KL\'\),2,str\(\'stdev\'\),0.001,1,0,0.2,4,0,None,i7174,4,750.45703125,750.24609375,-1,0,3846514
1743390061,1743390080,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 236 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 1,1,236,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,1,0,0.32,8,0,None,i7178,8,750.63671875,750.48046875,-1,0.2756452680344143,3846526
1743390061,1743390080,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 4005 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 1,1,4005,str\(\'H\'\),1,str\(\'tstat\'\),0.001,1,0,0.2,8,0,None,i7184,8,750.51953125,750.3307291666666,-1,0,3846523
1743390061,1743390080,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 3655 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 1,5000,3655,str\(\'H\'\),1,str\(\'stdev\'\),0.999,1,0,0.2,8,0,None,i7158,8,750.29296875,750.15625,-1,0,3846530
1743393646,1743393666,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 132 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 33,5000,132,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,33,0,0.3,6,0,None,i7019,6,751.06640625,750.8997395833334,-1,0.08735936465916612,3852234
1743393651,1743393671,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 569 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 50,5000,569,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,50,0,0.29,7,0,None,i7016,7,750.515625,750.33984375,-1,0.18828590337524817,3852247
1743393652,1743393671,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4594 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 1,4594,1,str\(\'KL\'\),2,str\(\'stdev\'\),0.001,1,0,0.31,8,0,None,i7167,8,750.37109375,750.1028645833334,-1,0.0843812045003309,3852240
1743393681,1743393701,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 504 feature_id 0 batch_size 2919 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.1871411244524289 subsets 1,504,2919,str\(\'KL\'\),2,str\(\'stdev\'\),0.1871411244524289,1,0,0.2,4,0,None,i7017,4,750.18359375,749.9322916666666,-1,0.3044341495698213,3852265
1743393682,1743393701,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2646 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.07694319898740085 subsets 1,2646,1,str\(\'KL\'\),2,str\(\'stdev\'\),0.07694319898740085,1,0,0.31,9,0,None,i7161,9,751.328125,751.0794270833334,-1,0.0843812045003309,3852259
1743393686,1743393705,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4495 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 1,4495,1,str\(\'H\'\),2,str\(\'stdev\'\),0.001,1,0,0.31,8,0,None,i7010,8,749.71484375,749.4778645833334,-1,0.0843812045003309,3852275
1743393686,1743393705,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 3006 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 62,1,3006,str\(\'KL\'\),3,str\(\'stdev\'\),0.001,62,0,0.2,4,0,None,i7016,4,748.31640625,748.1341145833334,-1,0,3852270
1743393706,1743393719,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4986 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 8,4986,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,8,0,None,None,1,None,i7138,3852280
1743393706,1743393719,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 58,5000,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,58,0,None,None,1,None,i7009,3852289
1743393707,1743393726,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3707 feature_id 0 batch_size 1398 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.43452075897605874 subsets 46,3707,1398,str\(\'KL\'\),1,str\(\'stdev\'\),0.43452075897605874,46,0,0.2,5,0,None,i7017,5,750.02734375,749.8684895833334,-1,0.26373262739907344,3852285
1743393711,1743393730,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2337 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.6317923694717827 subsets 48,2337,1,str\(\'H\'\),3,str\(\'stdev\'\),0.6317923694717827,48,0,0.31,8,0,None,i7016,8,750.171875,749.9856770833334,-1,0.0843812045003309,3852292
1743393726,1743393739,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 2792 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 100,1,2792,str\(\'KL\'\),3,str\(\'stdev\'\),0.999,100,0,0.2,4,0,None,i7015,4,751.625,751.4348958333334,-1,0,3852305
1743393726,1743393739,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 22,5000,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,22,0,None,None,1,None,i7009,3852307
1743393726,1743393745,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 2153 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 1,1,2153,str\(\'KL\'\),2,str\(\'stdev\'\),0.999,1,0,0.2,5,0,None,i7135,5,750.54296875,750.25,-1,0.050959629384513566,3852302
1743393726,1743393752,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3389 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 1,3389,1,str\(\'H\'\),2,str\(\'stdev\'\),0.001,1,0,0.31,8,0,None,i7177,8,750.32421875,750.046875,-1,0.0843812045003309,3852298
1743393666,1743393754,88,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 34,5000,1,str\(\'KL\'\),2,str\(\'stdev\'\),0.001,34,0,0.31,80,0,None,i7107,80,750.10546875,750.030859375,-1,0.0843812045003309,3852253
1743393741,1743393754,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 2998 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 1,1,2998,str\(\'KL\'\),3,str\(\'stdev\'\),0.001,1,0,0.2,4,0,None,i7155,4,750.4921875,750.27734375,-1,0,3852312
1743393746,1743393759,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4293 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 52,4293,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,52,0,None,None,1,None,i7011,3852353
1743393747,1743393759,12,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 3367 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 1,1,3367,str\(\'KL\'\),2,str\(\'stdev\'\),0.999,1,0,0.2,4,0,None,i7159,4,749.97265625,749.76953125,-1,0,3852320
1743393747,1743393759,12,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.3772300045804381 subsets 1,1,1,str\(\'H\'\),1,str\(\'stdev\'\),0.3772300045804381,1,0,None,None,1,None,i7158,3852322
1743393747,1743393760,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 75,5000,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,75,0,None,None,1,None,i7149,3852335
1743393741,1743393761,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3335 feature_id 0 batch_size 444 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.041132239094725694 subsets 1,3335,444,str\(\'KL\'\),2,str\(\'stdev\'\),0.041132239094725694,1,0,0.29,6,0,None,i7016,6,750.078125,749.84765625,-1,0.07313037723362012,3852316
1743393746,1743393766,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 5000 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 100,1,5000,str\(\'H\'\),2,str\(\'stdev\'\),0.001,100,0,0.2,4,0,None,i7154,4,750.5546875,750.3723958333334,-1,0,3852327
1743393746,1743393766,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2705 feature_id 0 batch_size 3032 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 100,2705,3032,str\(\'H\'\),3,str\(\'stdev\'\),0.001,100,0,0.2,4,0,None,i7016,4,749.96875,749.75390625,-1,0,3852343
1743393746,1743393766,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3665 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 1,3665,1,str\(\'KL\'\),2,str\(\'stdev\'\),0.001,1,0,0.31,9,0,None,i7009,9,750.82421875,750.53515625,-1,0.0843812045003309,3852357
1743393747,1743393766,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 505 feature_id 0 batch_size 3071 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 100,505,3071,str\(\'KL\'\),3,str\(\'stdev\'\),0.001,100,0,0.2,4,0,None,i7014,4,750.3515625,750.1744791666666,-1,0,3852347
1743393747,1743393766,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 463 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 1,5000,463,str\(\'KL\'\),2,str\(\'stdev\'\),0.001,1,0,0.29,6,0,None,i7152,6,751.03125,750.7890625,-1,0.10456651224354732,3852331
1743393747,1743393766,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4268 feature_id 0 batch_size 821 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 29,4268,821,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,29,0,0.26,6,0,None,i7156,6,749.87109375,749.7252604166666,-1,0.15354070152217075,3852325
1743393742,1743393768,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 6,5000,1,str\(\'KL\'\),2,str\(\'stdev\'\),0.001,6,0,0.31,10,0,None,i7161,10,750.390625,750.11328125,-1,0.0843812045003309,3852310
1743393747,1743393773,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 2713 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 100,5000,2713,str\(\'KL\'\),2,str\(\'stdev\'\),0.001,100,0,0.2,10,0,None,i7059,10,750.49609375,750.2356770833334,-1,0,3852339
1743397849,1743397868,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 460 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.6019763021087475 subsets 100,460,1,str\(\'H\'\),3,str\(\'stdev\'\),0.6019763021087475,100,0,0.31,8,0,None,i7177,8,749.94921875,749.7734375,-1,0.0843812045003309,3857832
1743397849,1743397868,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 19 feature_id 0 batch_size 1557 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 15,19,1557,str\(\'H\'\),1,str\(\'stdev\'\),0.001,15,0,0.2,6,0,None,i7179,6,751.171875,751.0286458333334,-1,0,3857829
1743397849,1743397868,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1835 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.3927356521279098 subsets 71,1835,1,str\(\'H\'\),3,str\(\'stdev\'\),0.3927356521279098,71,0,0.31,8,0,None,i7183,8,750.06640625,749.8984375,-1,0.0843812045003309,3857825
1743397853,1743397873,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 2529 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 22,5000,2529,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,22,0,0.2,5,0,None,i7168,5,750.69921875,750.4921875,-1,0.17538054268696227,3857842
1743397869,1743397882,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 406 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 78,406,1,str\(\'H\'\),1,str\(\'stdev\'\),0.001,78,0,None,None,1,None,i7180,3857847
1743397869,1743397888,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2179 feature_id 0 batch_size 100 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 39,2179,100,str\(\'H\'\),1,str\(\'stdev\'\),0.001,39,0,0.29,7,0,None,i7163,7,751.28515625,751.1393229166666,-1,0.13269358041032428,3857852
1743397883,1743397903,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1733 feature_id 0 batch_size 1952 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 17,1733,1952,str\(\'H\'\),1,str\(\'stdev\'\),0.001,17,0,0.2,6,0,None,i7177,6,750.671875,750.50390625,-1,0,3857862
1743397884,1743397903,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2674 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 87,2674,1,str\(\'H\'\),3,str\(\'stdev\'\),0.001,87,0,0.31,8,0,None,i7181,8,750.73046875,750.5625,-1,0.0843812045003309,3857857
1743397889,1743397908,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 553 feature_id 0 batch_size 2410 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 73,553,2410,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,73,0,0.2,6,0,None,i7171,6,749.96875,749.6223958333334,-1,0,3857870
1743397889,1743397908,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3497 feature_id 0 batch_size 1170 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 14,3497,1170,str\(\'H\'\),1,str\(\'stdev\'\),0.001,14,0,0.23,6,0,None,i7180,6,751.01171875,750.8502604166666,-1,0,3857866
1743397889,1743397908,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 457 feature_id 0 batch_size 2685 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 26,457,2685,str\(\'H\'\),1,str\(\'stdev\'\),0.999,26,0,0.2,5,0,None,i7168,5,751.4375,751.2643229166666,-1,0.22700198544010589,3857873
1743397909,1743397922,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1057 feature_id 0 batch_size 5000 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 69,1057,5000,str\(\'H\'\),3,str\(\'stdev\'\),0.001,69,0,0.2,4,0,None,i7176,4,749.66796875,749.4934895833334,-1,0,3857882
1743397913,1743397926,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 350 feature_id 0 batch_size 5000 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 24,350,5000,str\(\'H\'\),3,str\(\'stdev\'\),0.001,24,0,0.2,4,0,None,i7180,4,750.57421875,750.359375,-1,0,3857887
1743397914,1743397927,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 743 feature_id 0 batch_size 5000 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 12,743,5000,str\(\'H\'\),1,str\(\'stdev\'\),0.999,12,0,0.2,4,0,None,i7171,4,751.16015625,751.0026041666666,-1,0,3857890
1743397909,1743397929,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2136 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.3046890934406183 subsets 63,2136,1,str\(\'H\'\),3,str\(\'tstat\'\),0.3046890934406183,63,0,0.31,9,0,None,i7181,9,748.484375,748.2630208333334,-1,0.0843812045003309,3857877
1743397914,1743397933,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1227 feature_id 0 batch_size 269 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 11,1227,269,str\(\'H\'\),1,str\(\'stdev\'\),0.001,11,0,0.23,5,0,None,i7161,5,751.40625,751.2356770833334,-1,0.08901389808074123,3857896
1743397929,1743397942,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3954 feature_id 0 batch_size 559 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 39,3954,559,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,39,0,0.2,5,0,None,i7175,5,749.91796875,749.7200520833334,-1,0.18497683653209795,3857900
1743397929,1743397948,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 4888 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 82,1,4888,str\(\'H\'\),2,str\(\'stdev\'\),0.999,82,0,0.2,4,0,None,i7161,4,750.90625,750.7434895833334,-1,0,3857906
1743397943,1743397956,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4814 feature_id 0 batch_size 2422 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 84,4814,2422,str\(\'KL\'\),3,str\(\'stdev\'\),0.999,84,0,0.2,4,0,None,i7180,4,749.7890625,749.5598958333334,-1,0,3857909
1743397944,1743397963,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1736 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 77,1736,1,str\(\'KL\'\),3,str\(\'stdev\'\),0.001,77,0,0.31,9,0,None,i7161,9,750.30859375,750.0924479166666,-1,0.0843812045003309,3857917
1743397944,1743397963,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 5000 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 55,5000,5000,str\(\'H\'\),2,str\(\'stdev\'\),0.001,55,0,0.2,4,0,None,i7178,4,749.859375,749.6731770833334,-1,0,3857912
1743397950,1743397963,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3337 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 85,3337,1,str\(\'H\'\),1,str\(\'stdev\'\),0.001,85,0,None,None,1,None,i7159,3857924
1743397950,1743397969,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1613 feature_id 0 batch_size 2213 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 17,1613,2213,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,17,0,0.2,5,0,None,i7157,5,751.15234375,751.0260416666666,-1,0.07081403044341496,3857930
1743397950,1743397969,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 292 feature_id 0 batch_size 1066 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 7,292,1066,str\(\'H\'\),2,str\(\'stdev\'\),0.001,7,0,0.2,6,0,None,i7161,6,750.44140625,750.1796875,-1,0.04401058901389808,3857921
1743397950,1743397969,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 526 feature_id 0 batch_size 351 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.8227334616257287 subsets 65,526,351,str\(\'H\'\),3,str\(\'stdev\'\),0.8227334616257287,65,0,0.26,5,0,None,i7156,5,750.19921875,750.0455729166666,-1,0.03540701522170748,3857935
1743397951,1743397970,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 5000 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 58,1,5000,str\(\'KL\'\),2,str\(\'tstat\'\),0.001,58,0,0.2,4,0,None,i7155,4,750.98046875,750.8046875,-1,0,3857945
1743397951,1743397970,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 198 feature_id 0 batch_size 854 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.9928678484782556 subsets 52,198,854,str\(\'KL\'\),3,str\(\'stdev\'\),0.9928678484782556,52,0,0.2,5,0,None,i7155,5,751.0390625,750.8736979166666,-1,0.18630046326935804,3857941
1743397950,1743397976,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 94,1,1,str\(\'H\'\),3,str\(\'tstat\'\),0.999,94,0,0.31,9,0,None,i7156,9,750.875,750.68359375,-1,0.0843812045003309,3857933
1743397950,1743397994,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1424 feature_id 0 batch_size 65 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 70,1424,65,str\(\'H\'\),1,str\(\'stdev\'\),0.001,70,0,0.3,31,0,None,i7158,31,748.57421875,748.4895833333334,-1,0.12905360688285902,3857927
1743397853,1743398848,995,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4916 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 69,4916,1,str\(\'H\'\),2,str\(\'stdev\'\),0.001,69,0,0.31,984,0,None,i7175,984,751.421875,751.413250309406,-1,0.0843812045003309,3857837
1743402027,1743402046,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 136 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.6395270651609382 subsets 1,136,1,str\(\'KL\'\),2,str\(\'tstat\'\),0.6395270651609382,1,0,0.31,9,0,None,i7166,9,750.2109375,749.8723958333334,-1,0.0843812045003309,3863589
1743402027,1743402046,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4991 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.27995105610741294 subsets 1,4991,1,str\(\'H\'\),2,str\(\'stdev\'\),0.27995105610741294,1,0,0.31,8,0,None,i7167,8,751.07421875,750.81640625,-1,0.0843812045003309,3863587
1743402031,1743402051,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4945 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.358861660434549 subsets 1,4945,1,str\(\'KL\'\),3,str\(\'stdev\'\),0.358861660434549,1,0,0.31,8,0,None,i7179,8,751.2578125,751.0716145833334,-1,0.0843812045003309,3863594
1743402031,1743402051,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1467 feature_id 0 batch_size 10 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.46110577771497874 subsets 1,1467,10,str\(\'H\'\),1,str\(\'stdev\'\),0.46110577771497874,1,0,0.33,9,0,None,i7162,9,749.78515625,749.6614583333334,-1,0.3378557246856386,3863600
1743402051,1743402070,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4053 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.9586695959016093 subsets 1,4053,1,str\(\'H\'\),2,str\(\'stdev\'\),0.9586695959016093,1,0,0.31,8,0,None,i7178,8,750.91015625,750.6315104166666,-1,0.0843812045003309,3863608
1743402057,1743402076,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1837 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 100,1837,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,100,0,None,None,1,None,i7167,3863620
1743402051,1743402077,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4843 feature_id 0 batch_size 608 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.4670844736592145 subsets 100,4843,608,str\(\'H\'\),2,str\(\'stdev\'\),0.4670844736592145,100,0,0.23,11,0,None,i7181,11,750.453125,750.26171875,-1,0,3863603
1743402071,1743402084,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4072 feature_id 0 batch_size 3216 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.3993384289690653 subsets 100,4072,3216,str\(\'H\'\),2,str\(\'tstat\'\),0.3993384289690653,100,0,0.2,4,0,None,i7169,4,751.31640625,751.109375,-1,0,3863630
1743402086,1743402105,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 162 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.6739090017349895 subsets 1,162,1,str\(\'KL\'\),3,str\(\'stdev\'\),0.6739090017349895,1,0,0.31,8,0,None,i7179,8,750.6953125,750.5052083333334,-1,0.0843812045003309,3863635
1743402091,1743402111,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1531 feature_id 0 batch_size 1058 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.23964796248642342 subsets 1,1531,1058,str\(\'H\'\),2,str\(\'stdev\'\),0.23964796248642342,1,0,0.24,6,0,None,i7170,6,751.24609375,750.9830729166666,-1,0,3863650
1743402091,1743402123,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2332 feature_id 0 batch_size 38 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.4746445065729965 subsets 55,2332,38,str\(\'H\'\),2,str\(\'stdev\'\),0.4746445065729965,55,0,0.31,18,0,None,i7177,18,751.046875,750.837890625,-1,0.09298477829252151,3863645
1743402111,1743402124,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2995 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.758750346824325 subsets 1,2995,1,str\(\'H\'\),1,str\(\'tstat\'\),0.758750346824325,1,0,None,None,1,None,i7183,3863655
1743402111,1743402130,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2535 feature_id 0 batch_size 13 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.299031971553422 subsets 1,2535,13,str\(\'KL\'\),1,str\(\'stdev\'\),0.299031971553422,1,0,0.33,9,0,None,i7178,9,750.4921875,750.3528645833334,-1,0.3365320979483786,3863664
1743402116,1743402135,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1318 feature_id 0 batch_size 83 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.7132918573424345 subsets 27,1318,83,str\(\'KL\'\),3,str\(\'tstat\'\),0.7132918573424345,27,0,0.31,5,0,None,i7172,5,749.6953125,749.4401041666666,-1,0.08239576439444077,3863672
1743402117,1743402136,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1955 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.4403109839914902 subsets 1,1955,1,str\(\'H\'\),2,str\(\'tstat\'\),0.4403109839914902,1,0,0.31,10,0,None,i7175,10,750.921875,750.6223958333334,-1,0.0843812045003309,3863668
1743402131,1743402144,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4180 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.7811482740048856 subsets 92,4180,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.7811482740048856,92,0,None,None,1,None,i7176,3863685
1743402131,1743402144,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3612 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.557873599293076 subsets 26,3612,1,str\(\'H\'\),1,str\(\'stdev\'\),0.557873599293076,26,0,None,None,1,None,i7181,3863677
1743402111,1743402149,38,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3237 feature_id 0 batch_size 298 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.5031558383819461 subsets 100,3237,298,str\(\'H\'\),2,str\(\'stdev\'\),0.5031558383819461,100,0,0.28,24,0,None,i7179,24,751,750.84140625,-1,0.12739907346128393,3863660
1743402131,1743402151,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 238 feature_id 0 batch_size 15 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.3070686704070192 subsets 4,238,15,str\(\'H\'\),1,str\(\'tstat\'\),0.3070686704070192,4,0,0.31,6,0,None,i7179,6,750.9609375,750.7734375,-1,0.1128391793514229,3863680
1743402131,1743402151,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2035 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.31364320396786566 subsets 32,2035,1,str\(\'KL\'\),3,str\(\'stdev\'\),0.31364320396786566,32,0,0.31,8,0,None,i7177,8,751.625,751.4700520833334,-1,0.0843812045003309,3863683
1743402146,1743402166,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1232 feature_id 0 batch_size 4 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.258427762862883 subsets 78,1232,4,str\(\'KL\'\),3,str\(\'stdev\'\),0.258427762862883,78,0,0.31,7,0,None,i7175,7,750.22265625,749.98828125,-1,0.07941760423560557,3863693
1743402146,1743402166,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2574 feature_id 0 batch_size 69 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.6784788121419356 subsets 29,2574,69,str\(\'KL\'\),2,str\(\'stdev\'\),0.6784788121419356,29,0,0.31,6,0,None,i7176,6,750.52734375,750.2591145833334,-1,0.09133024487094639,3863691
1743402147,1743402166,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 182 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.8174554968035623 subsets 1,182,1,str\(\'H\'\),2,str\(\'stdev\'\),0.8174554968035623,1,0,0.31,10,0,None,i7183,10,751.33203125,751.0768229166666,-1,0.0843812045003309,3863687
1743402147,1743402167,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 264 feature_id 0 batch_size 290 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.4625058292976017 subsets 1,264,290,str\(\'KL\'\),1,str\(\'stdev\'\),0.4625058292976017,1,0,0.32,8,0,None,i7174,8,750.078125,749.95703125,-1,0.29814692256783587,3863695
1743402146,1743402172,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4483 feature_id 0 batch_size 286 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.2990855316140312 subsets 100,4483,286,str\(\'H\'\),1,str\(\'tstat\'\),0.2990855316140312,100,0,0.2,11,0,None,i7178,11,750.2734375,750.1064453125,-1,0,3863689
1743402155,1743402174,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2925 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.5939513947755402 subsets 100,2925,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.5939513947755402,100,0,None,None,1,None,i7182,3863697
1743402027,1743402185,158,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3818 feature_id 0 batch_size 14 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.47177117183420186 subsets 90,3818,14,str\(\'H\'\),2,str\(\'stdev\'\),0.47177117183420186,90,0,0.3,145,0,None,i7172,145,751.4375,751.3876378676471,-1,0.05559232296492389,3863582
1743402071,1743402310,239,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 764 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 47,764,1,str\(\'H\'\),2,str\(\'stdev\'\),0.999,47,0,0.31,224,0,None,i7177,224,750.734375,750.7040625,-1,0.0843812045003309,3863625
1743402057,1743402428,371,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 54 feature_id 0 batch_size 11 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.5053999632243663 subsets 94,54,11,str\(\'H\'\),1,str\(\'tstat\'\),0.5053999632243663,94,0,0.31,358,0,None,i7171,358,751.34765625,751.3304893092105,-1,0.1029119788219722,3863616
1743402086,1743405316,3230,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 316 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 93,316,1,str\(\'H\'\),2,str\(\'stdev\'\),0.999,93,0,0.31,3218,0,None,i7177,3218,750.421875,742.3129701967592,-1,0.0843812045003309,3863640
1743407857,1743407877,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1420 feature_id 0 batch_size 56 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.058620199606248855 subsets 48,1420,56,str\(\'KL\'\),3,str\(\'tstat\'\),0.058620199606248855,48,0,0.31,5,0,None,i7133,5,749.94140625,749.703125,-1,0.037061548643282594,3872150
1743407859,1743407878,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1235 feature_id 0 batch_size 196 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.0792869177100236 subsets 10,1235,196,str\(\'KL\'\),3,str\(\'tstat\'\),0.0792869177100236,10,0,0.25,5,0,None,i7138,5,750.796875,750.5755208333334,-1,0.06485771012574454,3872113
1743407859,1743407878,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2271 feature_id 0 batch_size 146 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.08568406785301444 subsets 31,2271,146,str\(\'KL\'\),3,str\(\'tstat\'\),0.08568406785301444,31,0,0.27,5,0,None,i7138,5,751.4921875,751.2799479166666,-1,0.09662475181998677,3872112
1743407859,1743407878,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4595 feature_id 0 batch_size 126 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.08523058569028485 subsets 93,4595,126,str\(\'KL\'\),3,str\(\'stdev\'\),0.08523058569028485,93,0,0.3,5,0,None,i7138,5,750.421875,750.2356770833334,-1,0.08338848444738584,3872110
1743407859,1743407878,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1106 feature_id 0 batch_size 227 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.2273747414952457 subsets 51,1106,227,str\(\'KL\'\),3,str\(\'tstat\'\),0.2273747414952457,51,0,0.29,5,0,None,i7137,5,750.33984375,750.1041666666666,-1,0.07511581733951025,3872118
1743407859,1743407878,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 506 feature_id 0 batch_size 177 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.385365269962491 subsets 47,506,177,str\(\'KL\'\),3,str\(\'stdev\'\),0.385365269962491,47,0,0.29,5,0,None,i7137,5,750.87890625,750.7135416666666,-1,0.1171409662475182,3872115
1743407859,1743407878,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 102 feature_id 0 batch_size 62 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.8883010833426637 subsets 13,102,62,str\(\'KL\'\),1,str\(\'tstat\'\),0.8883010833426637,13,0,0.29,6,0,None,i7128,6,751.8671875,751.6432291666666,-1,0.08206485771012574,3872172
1743407859,1743407878,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4227 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 83,4227,1,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,83,0,0.31,8,0,None,i7125,8,750.7265625,750.4830729166666,-1,0.08471211118464593,3872179
1743407859,1743407879,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 227 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 20,227,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,20,0,None,None,1,None,i7135,3872136
1743407860,1743407879,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2274 feature_id 0 batch_size 218 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.4312362805715608 subsets 23,2274,218,str\(\'KL\'\),3,str\(\'stdev\'\),0.4312362805715608,23,0,0.29,5,0,None,i7127,5,749.85546875,749.69140625,-1,0.07213765718067505,3872175
1743407860,1743407879,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 746 feature_id 0 batch_size 101 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.900279244893964 subsets 16,746,101,str\(\'H\'\),3,str\(\'tstat\'\),0.900279244893964,16,0,0.31,5,0,None,i7130,5,750.4609375,750.2408854166666,-1,0.10721376571806751,3872164
1743407861,1743407880,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 211 feature_id 0 batch_size 250 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.38291646524916556 subsets 69,211,250,str\(\'KL\'\),3,str\(\'stdev\'\),0.38291646524916556,69,0,0.29,5,0,None,i7129,5,751.32421875,751.140625,-1,0.1654533421575116,3872169
1743407857,1743407883,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1290 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 74,1290,1,str\(\'H\'\),3,str\(\'stdev\'\),0.999,74,0,0.31,8,0,None,i7133,8,751.140625,750.9947916666666,-1,0.0843812045003309,3872153
1743407864,1743407883,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 116 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 93,116,1,str\(\'H\'\),1,str\(\'stdev\'\),0.001,93,0,None,None,1,None,i7132,3872162
1743407858,1743407883,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 916 feature_id 0 batch_size 189 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.05367223163790892 subsets 94,916,189,str\(\'KL\'\),3,str\(\'stdev\'\),0.05367223163790892,94,0,0.29,5,0,None,i7140,5,751.625,751.4427083333334,-1,0.06254136333553938,3872103
1743407859,1743407884,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 820 feature_id 0 batch_size 20 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.32459851224657693 subsets 76,820,20,str\(\'H\'\),3,str\(\'tstat\'\),0.32459851224657693,76,0,0.31,5,0,None,i7134,5,751.3828125,751.1744791666666,-1,0.07279947054930509,3872147
1743407859,1743407884,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2100 feature_id 0 batch_size 684 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 95,2100,684,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,95,0,0.2,9,0,None,i7134,9,750.0625,749.9114583333334,-1,0.22634017207147583,3872144
1743407859,1743407885,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 504 feature_id 0 batch_size 408 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.45247597682466323 subsets 48,504,408,str\(\'KL\'\),1,str\(\'stdev\'\),0.45247597682466323,48,0,0.28,7,0,None,i7139,7,749.80078125,749.6549479166666,-1,0.13500992720052946,3872105
1743407859,1743407885,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1896 feature_id 0 batch_size 116 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 52,1896,116,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,52,0,0.28,5,0,None,i7136,5,750.0390625,749.7981770833334,-1,0.03838517538054269,3872126
1743407859,1743407885,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 400 feature_id 0 batch_size 172 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.17021367664236517 subsets 72,400,172,str\(\'KL\'\),3,str\(\'stdev\'\),0.17021367664236517,72,0,0.3,5,0,None,i7139,5,749.95703125,749.76953125,-1,0.11383189940436797,3872108
1743407859,1743407885,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1177 feature_id 0 batch_size 115 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.04798866900347338 subsets 77,1177,115,str\(\'KL\'\),3,str\(\'tstat\'\),0.04798866900347338,77,0,0.29,5,0,None,i7136,5,750.87109375,750.6302083333334,-1,0.07610853739245532,3872123
1743407859,1743407885,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4696 feature_id 0 batch_size 405 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.47562790177634195 subsets 21,4696,405,str\(\'KL\'\),1,str\(\'stdev\'\),0.47562790177634195,21,0,0.28,7,0,None,i7136,7,751.77734375,751.6302083333334,-1,0.1340172071475844,3872120
1743407859,1743407885,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4803 feature_id 0 batch_size 406 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.8616113959631666 subsets 17,4803,406,str\(\'KL\'\),1,str\(\'tstat\'\),0.8616113959631666,17,0,0.28,6,0,None,i7136,6,749.96484375,749.796875,-1,0.1343481138318994,3872130
1743407859,1743407885,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 103 feature_id 0 batch_size 50 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.03592914404238952 subsets 83,103,50,str\(\'KL\'\),3,str\(\'tstat\'\),0.03592914404238952,83,0,0.3,5,0,None,i7135,5,749.8828125,749.6458333333334,-1,0.0827266710787558,3872139
1743407859,1743407885,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2677 feature_id 0 batch_size 149 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.369720258367999 subsets 34,2677,149,str\(\'KL\'\),3,str\(\'tstat\'\),0.369720258367999,34,0,0.29,5,0,None,i7135,5,750.2578125,750.0234375,-1,0.0986101919258769,3872132
1743407860,1743407885,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4476 feature_id 0 batch_size 179 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 8,4476,179,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,8,0,0.25,5,0,None,i7132,5,750.078125,749.8658854166666,-1,0.04930509596293845,3872158
1743407860,1743407885,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4631 feature_id 0 batch_size 1057 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 23,4631,1057,str\(\'H\'\),1,str\(\'tstat\'\),0.999,23,0,0.2,4,0,None,i7132,4,750.49609375,750.3151041666666,-1,0,3872156
1743407860,1743407885,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3259 feature_id 0 batch_size 1063 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 70,3259,1063,str\(\'H\'\),1,str\(\'stdev\'\),0.999,70,0,0.2,6,0,None,i7132,6,751.0703125,750.9388020833334,-1,0,3872160
1743407860,1743407892,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2841 feature_id 0 batch_size 680 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 93,2841,680,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,93,0,0.28,19,0,None,i7130,19,750.109375,749.9990234375,-1,0.013567174056915949,3872166
1743407859,1743407941,82,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2949 feature_id 0 batch_size 16 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 86,2949,16,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,86,0,0.28,63,0,None,i7134,63,751.3828125,751.3185763888889,-1,0.037061548643282594,3872142
1743410857,1743410876,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 638 feature_id 0 batch_size 88 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 26,638,88,str\(\'KL\'\),2,str\(\'stdev\'\),0.999,26,0,0.3,5,0,None,i7002,5,751.31640625,751.0442708333334,-1,0.05823957643944408,3876417
1743410857,1743410877,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1458 feature_id 0 batch_size 572 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 30,1458,572,str\(\'KL\'\),2,str\(\'stdev\'\),0.999,30,0,0.2,5,0,None,i7001,5,751.0859375,750.8177083333334,-1,0.18927862342819324,3876420
1743410876,1743410889,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.695656408354447 subsets 1,1,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.695656408354447,1,0,None,None,1,None,i7174,3876430
1743410880,1743410893,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 13 feature_id 0 batch_size 3247 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 65,13,3247,str\(\'H\'\),2,str\(\'stdev\'\),0.999,65,0,0.2,4,0,None,i7161,4,749.7265625,749.5416666666666,-1,0,3876438
1743410880,1743410893,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 1,1,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,1,0,None,None,1,None,i7156,3876441
1743410876,1743410895,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4295 feature_id 0 batch_size 961 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 32,4295,961,str\(\'KL\'\),2,str\(\'stdev\'\),0.999,32,0,0.21,6,0,None,i7178,6,750.109375,749.8424479166666,-1,0,3876425
1743410876,1743410896,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1007 feature_id 0 batch_size 2849 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 55,1007,2849,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,55,0,0.2,5,0,None,i7185,5,750.01171875,749.69140625,-1,0,3876422
1743410876,1743410896,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 100,1,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,100,0,None,None,1,None,i7183,3876423
1743410877,1743410896,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1319 feature_id 0 batch_size 377 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 27,1319,377,str\(\'KL\'\),2,str\(\'stdev\'\),0.999,27,0,0.26,6,0,None,i7176,6,751.6328125,751.3684895833334,-1,0.08702845797485109,3876428
1743410881,1743410900,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 260 feature_id 0 batch_size 35 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.23296173182317148 subsets 30,260,35,str\(\'KL\'\),2,str\(\'stdev\'\),0.23296173182317148,30,0,0.31,7,0,None,i7167,7,748.4609375,748.1796875,-1,0.1042356055592323,3876434
1743410896,1743410915,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4849 feature_id 0 batch_size 2357 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 46,4849,2357,str\(\'KL\'\),2,str\(\'stdev\'\),0.999,46,0,0.2,5,0,None,i7179,5,751.10546875,750.7955729166666,-1,0,3876445
1743410896,1743410915,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 794 feature_id 0 batch_size 104 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.7271070632911173 subsets 52,794,104,str\(\'KL\'\),1,str\(\'stdev\'\),0.7271070632911173,52,0,0.28,9,0,None,i7177,9,751.140625,750.9856770833334,-1,0.13765718067504965,3876449
1743410910,1743410930,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 362 feature_id 0 batch_size 1152 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 34,362,1152,str\(\'KL\'\),2,str\(\'stdev\'\),0.999,34,0,0.2,5,0,None,i7176,5,750.44140625,750.15625,-1,0.10092653871608206,3876457
1743410911,1743410930,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 558 feature_id 0 batch_size 81 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.9018851268884566 subsets 34,558,81,str\(\'H\'\),2,str\(\'stdev\'\),0.9018851268884566,34,0,0.31,6,0,None,i7163,6,749.91796875,749.63671875,-1,0.10721376571806751,3876462
1743410896,1743410934,38,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1511 feature_id 0 batch_size 139 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.1593941225601231 subsets 95,1511,139,str\(\'KL\'\),1,str\(\'stdev\'\),0.1593941225601231,95,0,0.27,24,0,None,i7164,24,750.83203125,750.73046875,-1,0,3876453
1743410916,1743410935,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1275 feature_id 0 batch_size 774 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 30,1275,774,str\(\'KL\'\),2,str\(\'stdev\'\),0.999,30,0,0.23,5,0,None,i7161,5,750.7109375,750.4375,-1,0,3876472
1743410916,1743410936,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3259 feature_id 0 batch_size 2483 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.4636872804255573 subsets 62,3259,2483,str\(\'H\'\),2,str\(\'stdev\'\),0.4636872804255573,62,0,0.2,6,0,None,i7167,6,750.078125,749.8424479166666,-1,0,3876468
1743410936,1743410955,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3723 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.880921229656788 subsets 100,3723,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.880921229656788,100,0,None,None,1,None,i7173,3876483
1743410936,1743410956,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4321 feature_id 0 batch_size 3478 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 72,4321,3478,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,72,0,0.2,5,0,None,i7185,5,750.64453125,750.46875,-1,0,3876475
1743410940,1743410960,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2577 feature_id 0 batch_size 942 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.4898256222843603 subsets 51,2577,942,str\(\'KL\'\),2,str\(\'stdev\'\),0.4898256222843603,51,0,0.21,6,0,None,i7164,6,751.96484375,751.703125,-1,0,3876487
1743410941,1743410960,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1702 feature_id 0 batch_size 14 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.95437827709471 subsets 24,1702,14,str\(\'KL\'\),2,str\(\'stdev\'\),0.95437827709471,24,0,0.3,6,0,None,i7159,6,749.81640625,749.5455729166666,-1,0.0658504301786896,3876493
1743410941,1743410966,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4714 feature_id 0 batch_size 2956 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.650324417728417 subsets 100,4714,2956,str\(\'KL\'\),2,str\(\'tstat\'\),0.650324417728417,100,0,0.2,11,0,None,i7162,11,751.84375,751.5986328125,-1,0,3876490
1743410956,1743410975,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1089 feature_id 0 batch_size 240 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 28,1089,240,str\(\'KL\'\),2,str\(\'stdev\'\),0.999,28,0,0.29,6,0,None,i7161,6,749.96875,749.7252604166666,-1,0.05327597617471873,3876501
1743410957,1743410976,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4339 feature_id 0 batch_size 4218 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.46740717188428654 subsets 100,4339,4218,str\(\'KL\'\),1,str\(\'stdev\'\),0.46740717188428654,100,0,0.2,10,0,None,i7157,10,751.74609375,751.654296875,-1,0,3876506
1743410936,1743410981,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4194 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 25,4194,1,str\(\'H\'\),2,str\(\'stdev\'\),0.999,25,0,0.31,31,0,None,i7178,31,751.66796875,751.5286458333334,-1,0.0843812045003309,3876479
1743410957,1743410982,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4842 feature_id 0 batch_size 4907 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.3530725742954505 subsets 100,4842,4907,str\(\'KL\'\),1,str\(\'tstat\'\),0.3530725742954505,100,0,0.2,11,0,None,i7174,11,750.94140625,750.7705078125,-1,0,3876498
1743410970,1743410989,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2805 feature_id 0 batch_size 183 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.6662996870285316 subsets 39,2805,183,str\(\'KL\'\),1,str\(\'stdev\'\),0.6662996870285316,39,0,0.2,5,0,None,i7179,5,749.74609375,749.5716145833334,-1,0.06055592322964924,3876510
1743410976,1743410995,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2518 feature_id 0 batch_size 503 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.277470330084398 subsets 49,2518,503,str\(\'KL\'\),2,str\(\'stdev\'\),0.277470330084398,49,0,0.21,5,0,None,i7160,5,751.6953125,751.4153645833334,-1,0.16644606221045666,3876521
1743410971,1743411009,38,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3729 feature_id 0 batch_size 87 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.25229383304246894 subsets 73,3729,87,str\(\'KL\'\),1,str\(\'stdev\'\),0.25229383304246894,73,0,0.28,25,0,None,i7175,25,749.96875,749.85703125,-1,0.14394440767703506,3876513
1743410976,1743411014,38,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1101 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 22,1101,1,str\(\'KL\'\),2,str\(\'stdev\'\),0.999,22,0,0.31,26,0,None,i7179,26,750.69140625,750.53671875,-1,0.0843812045003309,3876517
1743414815,1743414877,62,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4626 feature_id 0 batch_size 109 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.32562821550449306 subsets 100,4626,109,str\(\'H\'\),3,str\(\'stdev\'\),0.32562821550449306,100,0,0.3,5,0,None,i7059,5,750.9609375,750.7591145833334,-1,0.036068828590337526,3880064
1743414917,1743414968,51,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4310 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.2099375229866567 subsets 23,4310,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.2099375229866567,23,0,None,None,1,None,i7060,3880060
1743414917,1743414968,51,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 112 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.8166114289580793 subsets 1,112,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.8166114289580793,1,0,None,None,1,None,i7060,3880046
1743414917,1743414974,57,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1531 feature_id 0 batch_size 37 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.47737639821120154 subsets 15,1531,37,str\(\'KL\'\),2,str\(\'stdev\'\),0.47737639821120154,15,0,0.31,5,0,None,i7060,5,750.359375,750.1067708333334,-1,0.085704831237591,3880049
1743414917,1743414974,57,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1266 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.45990217845317377 subsets 91,1266,1,str\(\'H\'\),3,str\(\'tstat\'\),0.45990217845317377,91,0,0.31,8,0,None,i7060,8,750.484375,750.2604166666666,-1,0.0843812045003309,3880056
1743414916,1743414987,71,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2825 feature_id 0 batch_size 82 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 65,2825,82,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,65,0,0.31,17,0,None,i7066,17,760.98046875,756.3330078125,-1,0.10853739245532759,3879984
1743414917,1743414993,76,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 560 feature_id 0 batch_size 49 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.7681605045300435 subsets 69,560,49,str\(\'KL\'\),2,str\(\'tstat\'\),0.7681605045300435,69,0,0.31,30,0,None,i7060,30,750.76953125,750.58046875,-1,0.10059563203176704,3880053
1743414963,1743415020,57,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 437 feature_id 0 batch_size 226 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.32827788415579806 subsets 61,437,226,str\(\'H\'\),1,str\(\'tstat\'\),0.32827788415579806,61,0,0.21,7,0,None,i7064,7,749.984375,749.7786458333334,-1,0.14956982131039048,3880012
1743414963,1743415020,57,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3813 feature_id 0 batch_size 260 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.47316379252743374 subsets 63,3813,260,str\(\'H\'\),1,str\(\'tstat\'\),0.47316379252743374,63,0,0.25,8,0,None,i7064,8,750.95703125,750.75390625,-1,0.08603573792190602,3880010
1743414963,1743415020,57,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1599 feature_id 0 batch_size 31 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.28992691108994717 subsets 32,1599,31,str\(\'H\'\),1,str\(\'tstat\'\),0.28992691108994717,32,0,0.3,8,0,None,i7064,8,749.859375,749.6510416666666,-1,0.0771012574454004,3880001
1743414963,1743415020,57,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4382 feature_id 0 batch_size 58 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 83,4382,58,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,83,0,0.2,7,0,None,i7064,7,749.66796875,749.5377604166666,-1,0.019192587690271344,3880008
1743414963,1743415026,63,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1232 feature_id 0 batch_size 73 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.7262110078329269 subsets 70,1232,73,str\(\'KL\'\),1,str\(\'stdev\'\),0.7262110078329269,70,0,0.22,11,0,None,i7064,11,750.60546875,750.4921875,-1,0.09662475181998677,3880003
1743414987,1743415032,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3784 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.7784138620836765 subsets 66,3784,1,str\(\'H\'\),1,str\(\'stdev\'\),0.7784138620836765,66,0,None,None,1,None,i7063,3880022
1743414987,1743415031,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 75 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 1,75,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,1,0,None,None,1,None,i7063,3880017
1743414963,1743415033,70,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4965 feature_id 0 batch_size 77 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.872843444045444 subsets 67,4965,77,str\(\'KL\'\),2,str\(\'tstat\'\),0.872843444045444,67,0,0.31,19,0,None,i7064,19,750.04296875,749.8125,-1,0.07743216412971542,3880006
1743414963,1743415033,70,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4454 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 21,4454,1,str\(\'H\'\),2,str\(\'stdev\'\),0.001,21,0,0.31,20,0,None,i7064,20,750.69921875,750.55859375,-1,0.0843812045003309,3880013
1743414987,1743415038,51,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1279 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.5472962483485219 subsets 11,1279,1,str\(\'H\'\),3,str\(\'stdev\'\),0.5472962483485219,11,0,0.31,8,0,None,i7063,8,750.91796875,750.4453125,-1,0.0843812045003309,3880028
1743414987,1743415038,51,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3442 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 100,3442,1,str\(\'H\'\),1,str\(\'stdev\'\),0.999,100,0,None,None,1,None,i7063,3880025
1743415000,1743415038,38,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 316 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 50,316,1,str\(\'H\'\),1,str\(\'stdev\'\),0.999,50,0,None,None,1,None,i7062,3880034
1743415000,1743415044,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4947 feature_id 0 batch_size 141 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.21612514757011628 subsets 20,4947,141,str\(\'H\'\),1,str\(\'stdev\'\),0.21612514757011628,20,0,0.27,6,0,None,i7062,6,749.875,749.73828125,-1,0.1399735274652548,3880031
1743415000,1743415044,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2116 feature_id 0 batch_size 420 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 65,2116,420,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,65,0,0.27,7,0,None,i7062,7,751.625,751.33203125,-1,0.13898080741230973,3880042
1743415004,1743415048,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 688 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 57,688,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,57,0,None,None,1,None,i7065,3879999
1743415004,1743415048,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 54 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.31218260608135223 subsets 62,54,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.31218260608135223,62,0,None,None,1,None,i7065,3879996
1743415004,1743415054,50,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1030 feature_id 0 batch_size 33 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.3479217722379494 subsets 15,1030,33,str\(\'KL\'\),2,str\(\'stdev\'\),0.3479217722379494,15,0,0.31,6,0,None,i7065,6,763.953125,760.421875,-1,0.08735936465916612,3879994
1743415000,1743415063,63,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 316 feature_id 0 batch_size 114 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 89,316,114,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,89,0,0.25,26,0,None,i7062,26,750.4296875,750.35234375,-1,0.11317008603573792,3880037
1743415004,1743415079,75,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 634 feature_id 0 batch_size 33 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.6313245960888477 subsets 69,634,33,str\(\'KL\'\),2,str\(\'tstat\'\),0.6313245960888477,69,0,0.31,35,0,None,i7065,35,767.43359375,762.6796875,-1,0.07643944407677035,3879986
1743415004,1743415085,81,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3762 feature_id 0 batch_size 24 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.5660110866615501 subsets 67,3762,24,str\(\'H\'\),1,str\(\'stdev\'\),0.5660110866615501,67,0,0.29,37,0,None,i7065,37,755.6171875,752.9752604166666,-1,0.08735936465916612,3879988
1743415004,1743415198,194,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 436 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.4005149683994038 subsets 42,436,1,str\(\'H\'\),2,str\(\'stdev\'\),0.4005149683994038,42,0,0.31,152,0,None,i7065,152,757.80078125,755.2348090277778,-1,0.0843812045003309,3879990
1743414987,1743415877,890,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3424 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 66,3424,1,str\(\'KL\'\),2,str\(\'stdev\'\),0.999,66,0,0.31,845,0,None,i7063,845,763.16796875,753.3565463362069,-1,0.0843812045003309,3880020
1743420763,1743420782,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2041 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 70,2041,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,70,0,None,None,1,None,i7104,3890320
1743420763,1743420783,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 1,1,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,1,0,None,None,1,None,i7112,3890246
1743420764,1743420790,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1496 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 64,1496,1,str\(\'H\'\),3,str\(\'tstat\'\),0.999,64,0,0.31,9,0,None,i7120,9,751.30859375,751.1171875,-1,0.0843812045003309,3890212
1743420764,1743420790,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2356 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 45,2356,1,str\(\'H\'\),3,str\(\'stdev\'\),0.001,45,0,0.31,8,0,None,i7109,8,750.3515625,750.2044270833334,-1,0.0843812045003309,3890261
1743420764,1743420790,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 617 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.7139984244375279 subsets 58,617,1,str\(\'H\'\),3,str\(\'tstat\'\),0.7139984244375279,58,0,0.31,8,0,None,i7109,8,750.92578125,750.703125,-1,0.0843812045003309,3890268
1743420765,1743420790,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3552 feature_id 0 batch_size 104 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.7314643182197376 subsets 36,3552,104,str\(\'KL\'\),2,str\(\'tstat\'\),0.7314643182197376,36,0,0.31,7,0,None,i7100,7,750.02734375,749.72265625,-1,0.10324288550628723,3890363
1743420765,1743420791,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1240 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 1,1240,1,str\(\'KL\'\),2,str\(\'tstat\'\),0.001,1,0,0.31,9,0,None,i7122,9,751.5703125,751.2903645833334,-1,0.0843812045003309,3890198
1743420765,1743420791,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2273 feature_id 0 batch_size 37 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.8838209709979359 subsets 53,2273,37,str\(\'H\'\),3,str\(\'tstat\'\),0.8838209709979359,53,0,0.31,6,0,None,i7102,6,750.19140625,749.9895833333334,-1,0.08537392455327597,3890347
1743420765,1743420791,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 127 feature_id 0 batch_size 39 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.5453607773844488 subsets 1,127,39,str\(\'H\'\),3,str\(\'tstat\'\),0.5453607773844488,1,0,0.31,7,0,None,i7107,7,750.375,750.1458333333334,-1,0.06452680344142951,3890290
1743420765,1743420791,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4753 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 74,4753,1,str\(\'H\'\),3,str\(\'tstat\'\),0.999,74,0,0.31,9,0,None,i7101,9,751.5078125,751.31640625,-1,0.0843812045003309,3890351
1743420766,1743420791,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4777 feature_id 0 batch_size 9 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.6296299260177005 subsets 1,4777,9,str\(\'KL\'\),1,str\(\'tstat\'\),0.6296299260177005,1,0,0.33,10,0,None,i7108,10,751.32421875,751.1982421875,-1,0.33620119126406356,3890275
1743420763,1743420795,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 13,1,1,str\(\'H\'\),2,str\(\'tstat\'\),0.001,13,0,0.31,13,0,None,i7104,13,749.8515625,749.638671875,-1,0.08471211118464593,3890324
1743420764,1743420796,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 599 feature_id 0 batch_size 145 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 57,599,145,str\(\'KL\'\),2,str\(\'tstat\'\),0.001,57,0,0.27,9,0,None,i7103,9,751.7734375,751.45703125,-1,0.09596293845135671,3890330
1743420765,1743420804,39,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1261 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 17,1261,1,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,17,0,0.31,18,0,None,i7102,18,749.91796875,749.6923828125,-1,0.0843812045003309,3890343
1743420765,1743420810,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2176 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.5157499309611075 subsets 20,2176,1,str\(\'KL\'\),2,str\(\'tstat\'\),0.5157499309611075,20,0,0.31,22,0,None,i7101,22,751.46484375,751.278125,-1,0.0843812045003309,3890360
1743420764,1743420822,58,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 26,1,1,str\(\'KL\'\),2,str\(\'tstat\'\),0.001,26,0,0.31,39,0,None,i7114,39,750.40234375,750.2486979166666,-1,0.08471211118464593,3890239
1743420765,1743420834,69,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1476 feature_id 0 batch_size 2 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.5793552056040459 subsets 31,1476,2,str\(\'H\'\),1,str\(\'tstat\'\),0.5793552056040459,31,0,0.32,53,0,None,i7100,53,750.2109375,750.13720703125,-1,0.16115155526141628,3890367
1743420764,1743420834,70,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1786 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.8111140379147402 subsets 28,1786,1,str\(\'KL\'\),2,str\(\'tstat\'\),0.8111140379147402,28,0,0.31,56,0,None,i7117,56,750.96875,750.85205078125,-1,0.0843812045003309,3890225
1743420765,1743420849,84,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3876 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 29,3876,1,str\(\'H\'\),2,str\(\'tstat\'\),0.999,29,0,0.31,65,0,None,i7107,65,751.03125,750.9301215277778,-1,0.0843812045003309,3890281
1743420765,1743420854,89,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 573 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.5450200456601461 subsets 32,573,1,str\(\'KL\'\),2,str\(\'tstat\'\),0.5450200456601461,32,0,0.31,67,0,None,i7105,67,749.90234375,749.7986111111111,-1,0.0843812045003309,3890308
1743420763,1743420884,121,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3736 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.0652120258765017 subsets 38,3736,1,str\(\'H\'\),2,str\(\'tstat\'\),0.0652120258765017,38,0,0.31,109,0,None,i7115,109,750.21875,750.15234375,-1,0.0843812045003309,3890232
1743420764,1743420909,145,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2129 feature_id 0 batch_size 3 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.6596988648587893 subsets 44,2129,3,str\(\'KL\'\),1,str\(\'tstat\'\),0.6596988648587893,44,0,0.32,123,0,None,i7106,123,751.4453125,751.4098958333333,-1,0.15784248841826604,3890300
1743420764,1743420909,145,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4224 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 39,4224,1,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,39,0,0.31,125,0,None,i7103,125,750.4296875,750.37265625,-1,0.0843812045003309,3890336
1743420765,1743420986,221,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 612 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.27310570193547523 subsets 45,612,1,str\(\'KL\'\),2,str\(\'tstat\'\),0.27310570193547523,45,0,0.31,200,0,None,i7105,200,750.15234375,750.1120923913044,-1,0.0843812045003309,3890314
1743420765,1743420992,227,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4734 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.6004521158849069 subsets 45,4734,1,str\(\'KL\'\),2,str\(\'tstat\'\),0.6004521158849069,45,0,0.31,206,0,None,i7100,206,750.515625,750.4777513586956,-1,0.0843812045003309,3890371
1743420765,1743423529,2764,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4590 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 90,4590,1,str\(\'H\'\),2,str\(\'tstat\'\),0.001,90,0,0.31,2745,0,None,i7101,2745,751.50390625,751.5006204873646,-1,0.08471211118464593,3890355
1743427049,1743427062,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 1,1,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,1,0,None,None,1,None,i7114,3897934
1743427055,1743427068,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2108 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 69,2108,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,69,0,None,None,1,None,i7113,3897937
1743427049,1743427068,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2134 feature_id 0 batch_size 4839 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.3631907184031876 subsets 100,2134,4839,str\(\'KL\'\),2,str\(\'tstat\'\),0.3631907184031876,100,0,0.2,4,0,None,i7125,4,750.4921875,750.26953125,-1,0,3897930
1743427050,1743427070,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4586 feature_id 0 batch_size 5000 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 1,4586,5000,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,1,0,0.2,4,0,None,i7103,4,750.12890625,749.9739583333334,-1,0,3897988
1743427032,1743427070,38,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1231 feature_id 0 batch_size 41 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.47718892521247136 subsets 67,1231,41,str\(\'KL\'\),2,str\(\'stdev\'\),0.47718892521247136,67,0,0.3,26,0,None,i7116,26,750.12109375,749.9671875,-1,0.08471211118464593,3897922
1743427051,1743427070,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 1,1,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,1,0,None,None,1,None,i7110,3897950
1743427051,1743427070,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1300 feature_id 0 batch_size 4192 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.7635157571145409 subsets 31,1300,4192,str\(\'KL\'\),2,str\(\'tstat\'\),0.7635157571145409,31,0,0.2,4,0,None,i7112,4,750.1875,750.0325520833334,-1,0,3897941
1743427051,1743427071,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1293 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 18,1293,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,18,0,None,None,1,None,i7137,3897926
1743427053,1743427072,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3519 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 52,3519,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,52,0,None,None,1,None,i7105,3897974
1743427053,1743427072,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 36 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 61,36,1,str\(\'H\'\),1,str\(\'tstat\'\),0.001,61,0,None,None,1,None,i7099,3898021
1743427054,1743427073,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 440 feature_id 0 batch_size 3853 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.46230275409746874 subsets 1,440,3853,str\(\'H\'\),3,str\(\'stdev\'\),0.46230275409746874,1,0,0.2,4,0,None,i7109,4,750.16015625,749,-1,0,3897955
1743427051,1743427077,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4125 feature_id 0 batch_size 311 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.46173241856063807 subsets 67,4125,311,str\(\'KL\'\),2,str\(\'stdev\'\),0.46173241856063807,67,0,0.28,9,0,None,i7100,9,751.2578125,750.9895833333334,-1,0.1029119788219722,3898012
1743427051,1743427077,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2000 feature_id 0 batch_size 5000 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.8407597452620873 subsets 47,2000,5000,str\(\'H\'\),3,str\(\'tstat\'\),0.8407597452620873,47,0,0.2,4,0,None,i7097,4,750.546875,750.37890625,-1,0,3898042
1743427051,1743427077,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4418 feature_id 0 batch_size 39 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.7641330290177224 subsets 27,4418,39,str\(\'KL\'\),3,str\(\'stdev\'\),0.7641330290177224,27,0,0.31,5,0,None,i7104,5,750.61328125,750.4453125,-1,0.05162144275314361,3897979
1743427051,1743427077,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3077 feature_id 0 batch_size 5000 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.4616094274809679 subsets 100,3077,5000,str\(\'KL\'\),3,str\(\'tstat\'\),0.4616094274809679,100,0,0.2,4,0,None,i7106,4,751.5859375,751.4114583333334,-1,0,3897964
1743427051,1743427077,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4492 feature_id 0 batch_size 3286 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.7151822193015706 subsets 33,4492,3286,str\(\'H\'\),2,str\(\'tstat\'\),0.7151822193015706,33,0,0.2,4,0,None,i7104,4,749.78125,749.6145833333334,-1,0,3897983
1743427051,1743427077,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 936 feature_id 0 batch_size 4916 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.4215353441871278 subsets 89,936,4916,str\(\'KL\'\),2,str\(\'tstat\'\),0.4215353441871278,89,0,0.2,4,0,None,i7100,4,750.26171875,750.0833333333334,-1,0,3898017
1743427051,1743427077,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4185 feature_id 0 batch_size 5000 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 27,4185,5000,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,27,0,0.2,4,0,None,i7101,4,749.69921875,749.5442708333334,-1,0,3898007
1743427051,1743427077,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3867 feature_id 0 batch_size 5000 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 1,3867,5000,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,1,0,0.2,8,0,None,i7112,8,750.1953125,749.0833333333334,-1,0,3897945
1743427053,1743427079,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2106 feature_id 0 batch_size 7 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.7331451432720942 subsets 85,2106,7,str\(\'H\'\),3,str\(\'stdev\'\),0.7331451432720942,85,0,0.3,5,0,None,i7105,5,751.08203125,750.890625,-1,0.0671740569159497,3897970
1743427053,1743427079,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4443 feature_id 0 batch_size 5000 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.8352476322897082 subsets 29,4443,5000,str\(\'H\'\),2,str\(\'tstat\'\),0.8352476322897082,29,0,0.2,4,0,None,i7099,4,751.5859375,751.4192708333334,-1,0,3898025
1743427053,1743427079,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4763 feature_id 0 batch_size 97 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.7339688605282539 subsets 100,4763,97,str\(\'H\'\),3,str\(\'tstat\'\),0.7339688605282539,100,0,0.3,5,0,None,i7099,5,751.08984375,750.8606770833334,-1,0.09629384513567174,3898029
1743427054,1743427079,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2019 feature_id 0 batch_size 5000 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 14,2019,5000,str\(\'H\'\),2,str\(\'tstat\'\),0.999,14,0,0.2,5,0,None,i7102,5,751.7265625,751.55859375,-1,0,3898001
1743427056,1743427082,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1345 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 100,1345,1,str\(\'KL\'\),3,str\(\'stdev\'\),0.999,100,0,0.31,10,0,None,i7108,10,750.51953125,750.3046875,-1,0.0843812045003309,3897959
1743427051,1743427083,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2306 feature_id 0 batch_size 5000 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 100,2306,5000,str\(\'H\'\),1,str\(\'stdev\'\),0.999,100,0,0.2,11,0,None,i7097,11,751.26171875,751.154296875,-1,0,3898045
1743427051,1743427083,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4873 feature_id 0 batch_size 4016 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.4774099837227718 subsets 1,4873,4016,str\(\'H\'\),1,str\(\'tstat\'\),0.4774099837227718,1,0,0.2,8,0,None,i7098,8,750.265625,750.0846354166666,-1,0,3898032
1743427051,1743427083,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1032 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 1,1032,1,str\(\'H\'\),3,str\(\'stdev\'\),0.999,1,0,0.31,8,0,None,i7098,8,751.3046875,751.1341145833334,-1,0.0843812045003309,3898039
1743427054,1743427085,31,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4583 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 23,4583,1,str\(\'H\'\),3,str\(\'stdev\'\),0.001,23,0,0.31,9,0,None,i7102,9,749.953125,749.78515625,-1,0.0843812045003309,3897993
1743427054,1743427085,31,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 434 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 100,434,1,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,100,0,0.31,9,0,None,i7102,9,751.40234375,751.1770833333334,-1,0.08471211118464593,3897997
1743427051,1743427115,64,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2125 feature_id 0 batch_size 142 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.365545421451216 subsets 100,2125,142,str\(\'KL\'\),2,str\(\'stdev\'\),0.365545421451216,100,0,0.3,41,0,None,i7098,41,751.0703125,750.9525669642857,-1,0.09397749834546658,3898035
1743429745,1743429758,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4424 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.7724119954719625 subsets 1,4424,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.7724119954719625,1,0,None,None,1,None,i7159,3901136
1743429745,1743429758,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1043 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 19,1043,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,19,0,None,None,1,None,i7148,3901142
1743429746,1743429765,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2590 feature_id 0 batch_size 60 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.42315907500420685 subsets 14,2590,60,str\(\'KL\'\),3,str\(\'tstat\'\),0.42315907500420685,14,0,0.3,5,0,None,i7143,5,750.890625,750.6653645833334,-1,0.07941760423560557,3901185
1743429746,1743429765,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 74 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 72,74,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,72,0,None,None,1,None,i7146,3901155
1743429746,1743429765,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2382 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 1,2382,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,1,0,None,None,1,None,i7144,3901179
1743429746,1743429766,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1843 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 60,1843,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,60,0,None,None,1,None,i7137,3901248
1743429746,1743429766,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 363 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 46,363,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,46,0,None,None,1,None,i7137,3901245
1743429746,1743429766,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3567 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.7102574091337118 subsets 12,3567,1,str\(\'H\'\),1,str\(\'stdev\'\),0.7102574091337118,12,0,None,None,1,None,i7142,3901195
1743429746,1743429766,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4472 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 83,4472,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,83,0,None,None,1,None,i7140,3901218
1743429747,1743429766,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1653 feature_id 0 batch_size 61 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.7651617234431743 subsets 1,1653,61,str\(\'KL\'\),3,str\(\'tstat\'\),0.7651617234431743,1,0,0.31,5,0,None,i7145,5,750.0625,749.8541666666666,-1,0.08537392455327597,3901170
1743429747,1743429766,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 1,1,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,1,0,None,None,1,None,i7141,3901208
1743429746,1743429771,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2636 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.19939616430098983 subsets 1,2636,1,str\(\'KL\'\),2,str\(\'tstat\'\),0.19939616430098983,1,0,0.31,9,0,None,i7143,9,750.14453125,749.8658854166666,-1,0.0843812045003309,3901190
1743429746,1743429772,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1815 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.818486261389271 subsets 100,1815,1,str\(\'H\'\),3,str\(\'stdev\'\),0.818486261389271,100,0,0.31,8,0,None,i7135,8,751.234375,751.0885416666666,-1,0.0843812045003309,3901266
1743429746,1743429772,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1536 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.4681561249140703 subsets 100,1536,1,str\(\'H\'\),1,str\(\'stdev\'\),0.4681561249140703,100,0,None,None,1,None,i7136,3901252
1743429746,1743429772,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3912 feature_id 0 batch_size 22 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.5473913704205263 subsets 1,3912,22,str\(\'KL\'\),2,str\(\'stdev\'\),0.5473913704205263,1,0,0.32,6,0,None,i7146,6,749.88671875,749.65625,-1,0.1684315023163468,3901160
1743429746,1743429772,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3373 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.27964683397068757 subsets 100,3373,1,str\(\'KL\'\),3,str\(\'tstat\'\),0.27964683397068757,100,0,0.31,9,0,None,i7142,9,749.93359375,749.7083333333334,-1,0.0843812045003309,3901202
1743429746,1743429772,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1548 feature_id 0 batch_size 21 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.9090077342825877 subsets 1,1548,21,str\(\'H\'\),1,str\(\'stdev\'\),0.9090077342825877,1,0,0.33,8,0,None,i7135,8,750.5234375,750.4036458333334,-1,0.33223031105228323,3901270
1743429747,1743429772,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3192 feature_id 0 batch_size 131 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.34371569958287945 subsets 1,3192,131,str\(\'H\'\),3,str\(\'tstat\'\),0.34371569958287945,1,0,0.3,5,0,None,i7144,5,749.84765625,749.6171875,-1,0.1300463269358041,3901174
1743429746,1743429772,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3241 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.6224985969365002 subsets 100,3241,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.6224985969365002,100,0,None,None,1,None,i7140,3901213
1743429746,1743429778,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 162 feature_id 0 batch_size 39 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.13389458316797231 subsets 15,162,39,str\(\'KL\'\),1,str\(\'tstat\'\),0.13389458316797231,15,0,0.3,5,0,None,i7138,5,750.15234375,749.9583333333334,-1,0.09033752481800132,3901238
1743429746,1743429778,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1534 feature_id 0 batch_size 26 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.13951276177972263 subsets 1,1534,26,str\(\'KL\'\),1,str\(\'tstat\'\),0.13951276177972263,1,0,0.33,9,0,None,i7136,9,750.94921875,750.7786458333334,-1,0.3365320979483786,3901256
1743429747,1743429778,31,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4179 feature_id 0 batch_size 378 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.6325682300702601 subsets 87,4179,378,str\(\'KL\'\),2,str\(\'tstat\'\),0.6325682300702601,87,0,0.26,12,0,None,i7136,12,750.97265625,750.7431640625,-1,0.08901389808074123,3901260
1743429747,1743429778,31,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 234 feature_id 0 batch_size 33 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.5604923507726822 subsets 79,234,33,str\(\'KL\'\),3,str\(\'tstat\'\),0.5604923507726822,79,0,0.31,5,0,None,i7139,5,750.14453125,749.9270833333334,-1,0.07643944407677035,3901228
1743429747,1743429778,31,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3420 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 60,3420,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,60,0,None,None,1,None,i7139,3901223
1743429747,1743429779,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3876 feature_id 0 batch_size 4 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.5452185949960902 subsets 18,3876,4,str\(\'H\'\),3,str\(\'tstat\'\),0.5452185949960902,18,0,0.31,6,0,None,i7139,6,749.78125,749.5455729166666,-1,0.07677035076108538,3901233
1743429746,1743429784,38,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 112 feature_id 0 batch_size 382 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.5506956151471658 subsets 87,112,382,str\(\'KL\'\),2,str\(\'tstat\'\),0.5506956151471658,87,0,0.25,11,0,None,i7138,11,751.89453125,751.6533203125,-1,0,3901240
1743429746,1743429790,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3384 feature_id 0 batch_size 179 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.17963865487584693 subsets 100,3384,179,str\(\'H\'\),2,str\(\'stdev\'\),0.17963865487584693,100,0,0.3,29,0,None,i7147,29,751.25,751.10546875,-1,0.05923229649238915,3901146
1743429746,1743429835,89,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4812 feature_id 0 batch_size 32 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.5772347998793552 subsets 87,4812,32,str\(\'KL\'\),2,str\(\'tstat\'\),0.5772347998793552,87,0,0.31,75,0,None,i7173,75,750.55078125,750.4546875,-1,0.08471211118464593,3901130
1743429746,1743429891,145,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2843 feature_id 0 batch_size 18 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.523013797308277 subsets 85,2843,18,str\(\'H\'\),2,str\(\'tstat\'\),0.523013797308277,85,0,0.31,132,0,None,i7135,132,751.875,751.548095703125,-1,0.09530112508272667,3901263
1743436352,1743436365,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 59,1,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,59,0,None,None,1,None,i7167,3908748
1743436352,1743436365,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 348 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 70,348,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,70,0,None,None,1,None,i7173,3908743
1743436352,1743436365,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2765 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 40,2765,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,40,0,None,None,1,None,i7140,3908787
1743436353,1743436366,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4606 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 57,4606,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,57,0,None,None,1,None,i7135,3908805
1743436352,1743436371,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2301 feature_id 0 batch_size 245 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 50,2301,245,str\(\'KL\'\),2,str\(\'tstat\'\),0.001,50,0,0.26,7,0,None,i7158,7,750.59375,750.2395833333334,-1,0.08107213765718067,3908751
1743436352,1743436371,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2742 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 55,2742,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,55,0,None,None,1,None,i7133,3908818
1743436352,1743436371,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1553 feature_id 0 batch_size 57 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.728694883871713 subsets 13,1553,57,str\(\'H\'\),1,str\(\'stdev\'\),0.728694883871713,13,0,0.29,5,0,None,i7176,5,750.1640625,750.0104166666666,-1,0.01886168100595632,3908740
1743436352,1743436371,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4122 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 81,4122,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,81,0,None,None,1,None,i7138,3908792
1743436352,1743436372,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 736 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.49650234481915834 subsets 15,736,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.49650234481915834,15,0,None,None,1,None,i7131,3908828
1743436353,1743436372,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4752 feature_id 0 batch_size 348 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.48259183231796576 subsets 16,4752,348,str\(\'KL\'\),1,str\(\'tstat\'\),0.48259183231796576,16,0,0.25,6,0,None,i7135,6,751.16796875,750.9700520833334,-1,0.14460622104566512,3908809
1743436353,1743436372,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1357 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 38,1357,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,38,0,None,None,1,None,i7124,3908868
1743436353,1743436372,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1938 feature_id 0 batch_size 15 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.22243669707604294 subsets 16,1938,15,str\(\'KL\'\),2,str\(\'tstat\'\),0.22243669707604294,16,0,0.31,6,0,None,i7137,6,749.98046875,749.6458333333334,-1,0.09794837855724686,3908798
1743436353,1743436372,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1097 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 16,1097,1,str\(\'H\'\),1,str\(\'stdev\'\),0.999,16,0,None,None,1,None,i7124,3908863
1743436353,1743436372,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1159 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 77,1159,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,77,0,None,None,1,None,i7125,3908857
1743436353,1743436372,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4768 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 1,4768,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,1,0,None,None,1,None,i7132,3908822
1743436352,1743436378,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4746 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.6105375604721266 subsets 100,4746,1,str\(\'H\'\),1,str\(\'stdev\'\),0.6105375604721266,100,0,None,None,1,None,i7154,3908757
1743436352,1743436378,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2674 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.4771342615696618 subsets 100,2674,1,str\(\'H\'\),1,str\(\'stdev\'\),0.4771342615696618,100,0,None,None,1,None,i7127,3908847
1743436353,1743436379,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2771 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.19841436604451027 subsets 13,2771,1,str\(\'H\'\),3,str\(\'stdev\'\),0.19841436604451027,13,0,0.31,8,0,None,i7152,8,750.8671875,750.7174479166666,-1,0.0843812045003309,3908763
1743436353,1743436379,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4960 feature_id 0 batch_size 312 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.8156832359290982 subsets 67,4960,312,str\(\'KL\'\),1,str\(\'tstat\'\),0.8156832359290982,67,0,0.26,8,0,None,i7130,8,750.41796875,750.2369791666666,-1,0.10324288550628723,3908834
1743436353,1743436379,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1432 feature_id 0 batch_size 244 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.5634226170135361 subsets 88,1432,244,str\(\'KL\'\),1,str\(\'stdev\'\),0.5634226170135361,88,0,0.22,12,0,None,i7129,12,751.92578125,751.79296875,-1,0.1614824619457313,3908841
1743436354,1743436379,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 1,1,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,1,0,None,None,1,None,i7141,3908782
1743436354,1743436380,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 100,1,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,100,0,None,None,1,None,i7144,3908775
1743436353,1743436384,31,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 941 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.1388083904012413 subsets 18,941,1,str\(\'H\'\),2,str\(\'stdev\'\),0.1388083904012413,18,0,0.31,16,0,None,i7127,16,751.05859375,750.8720703125,-1,0.0843812045003309,3908851
1743436373,1743436393,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 62,1,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,62,0,None,None,1,None,i7183,3908880
1743436373,1743436398,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3136 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.16181287064109384 subsets 1,3136,1,str\(\'H\'\),3,str\(\'stdev\'\),0.16181287064109384,1,0,0.31,9,0,None,i7170,9,751.14453125,750.99609375,-1,0.0843812045003309,3908884
1743436372,1743436410,38,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3394 feature_id 0 batch_size 241 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.7501275840051188 subsets 100,3394,241,str\(\'H\'\),1,str\(\'stdev\'\),0.7501275840051188,100,0,0.23,23,0,None,i7160,23,750.4296875,750.340625,-1,0.07974851091992058,3908890
1743436391,1743436411,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3962 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.543766858416138 subsets 34,3962,1,str\(\'H\'\),3,str\(\'stdev\'\),0.543766858416138,34,0,0.31,8,0,None,i7170,8,750.41015625,750.2421875,-1,0.0843812045003309,3908901
1743436391,1743436411,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4899 feature_id 0 batch_size 42 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.57076220287193 subsets 45,4899,42,str\(\'H\'\),3,str\(\'tstat\'\),0.57076220287193,45,0,0.31,5,0,None,i7174,5,751.22265625,750.9934895833334,-1,0.06121773659827928,3908896
1743436352,1743436674,322,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4544 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 50,4544,1,str\(\'KL\'\),2,str\(\'tstat\'\),0.001,50,0,0.31,306,0,None,i7148,306,751.19921875,751.169981060606,-1,0.08471211118464593,3908768
1743436361,1743436682,321,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1825 feature_id 0 batch_size 6 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.23925505043228648 subsets 79,1825,6,str\(\'H\'\),1,str\(\'tstat\'\),0.23925505043228648,79,0,0.31,308,0,None,i7160,308,751.13671875,751.1148200757576,-1,0.08934480476505625,3908875
1743439751,1743439764,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 1,5000,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,1,0,None,None,1,None,i7181,3912199
1743439751,1743439770,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 1,5000,1,str\(\'H\'\),2,str\(\'tstat\'\),0.999,1,0,0.31,9,0,None,i7182,9,750.75,750.4205729166666,-1,0.0843812045003309,3912197
1743439751,1743439770,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4425 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 82,4425,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,82,0,None,None,1,None,i7181,3912200
1743439751,1743439770,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 24,1,1,str\(\'H\'\),3,str\(\'stdev\'\),0.999,24,0,0.31,8,0,None,i7181,8,750.578125,750.4296875,-1,0.0843812045003309,3912201
1743439751,1743439771,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 206 feature_id 0 batch_size 164 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 48,206,164,str\(\'H\'\),2,str\(\'tstat\'\),0.001,48,0,0.27,7,0,None,i7183,7,750.9765625,750.6731770833334,-1,0.054268696227663796,3912196
1743439752,1743439771,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4970 feature_id 0 batch_size 48 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.24967531626831704 subsets 31,4970,48,str\(\'KL\'\),2,str\(\'stdev\'\),0.24967531626831704,31,0,0.31,7,0,None,i7180,7,751.46875,751.21484375,-1,0.08504301786896096,3912203
1743439751,1743439783,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4362 feature_id 0 batch_size 3 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.22903653699542637 subsets 31,4362,3,str\(\'H\'\),2,str\(\'stdev\'\),0.22903653699542637,31,0,0.31,18,0,None,i7182,18,750.9296875,750.71875,-1,0.062210456651224356,3912198
1743439772,1743439785,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3787 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 10,3787,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,10,0,None,None,1,None,i7180,3912205
1743439772,1743439785,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 62 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 54,62,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,54,0,None,None,1,None,i7177,3912214
1743439772,1743439791,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3005 feature_id 0 batch_size 48 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.8250457890726165 subsets 1,3005,48,str\(\'H\'\),2,str\(\'tstat\'\),0.8250457890726165,1,0,0.32,7,0,None,i7179,7,750.171875,749.8723958333334,-1,0.15883520847121113,3912206
1743439772,1743439791,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 1,5000,1,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,1,0,0.31,9,0,None,i7179,9,750.69921875,750.4830729166666,-1,0.0843812045003309,3912207
1743439772,1743439791,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 436 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 48,1,436,str\(\'H\'\),2,str\(\'tstat\'\),0.001,48,0,0.24,6,0,None,i7181,6,751.2109375,750.8619791666666,-1,0,3912204
1743439772,1743439791,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 204 feature_id 0 batch_size 824 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.6442935392546353 subsets 8,204,824,str\(\'KL\'\),1,str\(\'tstat\'\),0.6442935392546353,8,0,0.26,6,0,None,i7177,6,750.60546875,750.4348958333334,-1,0.15651886168100596,3912210
1743439772,1743439791,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2746 feature_id 0 batch_size 611 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 1,2746,611,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,1,0,0.31,9,0,None,i7177,9,751.53515625,751.3697916666666,-1,0.1472534745201853,3912212
1743439781,1743439800,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 59,5000,1,str\(\'KL\'\),3,str\(\'stdev\'\),0.999,59,0,0.31,8,0,None,i7181,8,750.76171875,750.5625,-1,0.0843812045003309,3912218
1743439781,1743439800,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 100,5000,1,str\(\'H\'\),3,str\(\'tstat\'\),0.999,100,0,0.31,8,0,None,i7182,8,750.2109375,750.015625,-1,0.0843812045003309,3912216
1743439781,1743439800,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 73 feature_id 0 batch_size 61 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.6880776689675354 subsets 16,73,61,str\(\'KL\'\),1,str\(\'stdev\'\),0.6880776689675354,16,0,0.24,5,0,None,i7178,5,750.52734375,750.3502604166666,-1,0.06055592322964924,3912220
1743439792,1743439805,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 466 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.12767914296978664 subsets 1,466,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.12767914296978664,1,0,None,None,1,None,i7173,3912231
1743439792,1743439805,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 479 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 74,479,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,74,0,None,None,1,None,i7173,3912234
1743439781,1743439806,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2863 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.6894914984463154 subsets 1,2863,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.6894914984463154,1,0,None,None,1,None,i7176,3912223
1743439792,1743439812,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4831 feature_id 0 batch_size 2 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.3260692018482544 subsets 1,4831,2,str\(\'KL\'\),1,str\(\'tstat\'\),0.3260692018482544,1,0,0.32,10,0,None,i7180,10,750.18359375,750.0078125,-1,0.16115155526141628,3912226
1743439811,1743439830,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 906 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 90,906,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,90,0,None,None,1,None,i7179,3912240
1743439812,1743439832,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 5000 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 63,5000,5000,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,63,0,0.2,6,0,None,i7170,6,748.60546875,748.4140625,-1,0,3912250
1743439811,1743439837,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4957 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 9,4957,1,str\(\'H\'\),2,str\(\'tstat\'\),0.001,9,0,0.31,11,0,None,i7182,11,751.0546875,750.8427734375,-1,0.08471211118464593,3912236
1743439811,1743439837,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 787 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 1,5000,787,str\(\'H\'\),1,str\(\'tstat\'\),0.999,1,0,0.3,8,0,None,i7173,8,750.96875,750.7708333333334,-1,0.11978821972203839,3912247
1743439812,1743439838,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1533 feature_id 0 batch_size 1148 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.7317881114597805 subsets 1,1533,1148,str\(\'KL\'\),1,str\(\'tstat\'\),0.7317881114597805,1,0,0.29,8,0,None,i7168,8,750.39453125,750.2278645833334,-1,0.09827928524156188,3912255
1743439811,1743439843,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 469 feature_id 0 batch_size 27 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 57,469,27,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,57,0,0.29,16,0,None,i7178,16,750.15625,749.986328125,-1,0.06254136333553938,3912242
1743439832,1743439858,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4624 feature_id 0 batch_size 56 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.2798320307556 subsets 50,4624,56,str\(\'H\'\),1,str\(\'tstat\'\),0.2798320307556,50,0,0.27,8,0,None,i7180,8,750.6328125,750.4075520833334,-1,0.018530774321641297,3912258
1743439751,1743439858,107,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4526 feature_id 0 batch_size 8 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 56,4526,8,str\(\'H\'\),1,str\(\'tstat\'\),0.999,56,0,0.32,97,0,None,i7180,97,749.9609375,749.9117838541666,-1,0.1270681667769689,3912202
1743439772,1743440011,239,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 246 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 47,246,1,str\(\'H\'\),2,str\(\'tstat\'\),0.001,47,0,0.31,229,0,None,i7179,229,750.18359375,748.38453125,-1,0.08471211118464593,3912208
1743442542,1743442555,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 374 feature_id 0 batch_size 13 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 12,374,13,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,12,0,0.27,5,0,None,i7150,5,751.25,751.0494791666666,-1,0.04301786896095301,3915075
1743442542,1743442562,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 227 feature_id 0 batch_size 2 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.7622474793940456 subsets 16,227,2,str\(\'H\'\),2,str\(\'stdev\'\),0.7622474793940456,16,0,0.31,9,0,None,i7145,9,750.4765625,750.2161458333334,-1,0.05526141628060887,3915077
1743442542,1743442562,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2195 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 60,2195,1,str\(\'H\'\),3,str\(\'stdev\'\),0.001,60,0,0.31,8,0,None,i7169,8,750.828125,750.6666666666666,-1,0.0843812045003309,3915072
1743442553,1743442566,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 580 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 1,580,1,str\(\'H\'\),1,str\(\'stdev\'\),0.999,1,0,None,None,1,None,i7134,3915089
1743442553,1743442566,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2316 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 23,2316,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,23,0,None,None,1,None,i7171,3915084
1743442553,1743442572,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3530 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 47,3530,1,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,47,0,0.31,8,0,None,i7144,8,751.43359375,751.1783854166666,-1,0.0843812045003309,3915086
1743442553,1743442573,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4715 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 88,4715,1,str\(\'KL\'\),3,str\(\'stdev\'\),0.999,88,0,0.31,9,0,None,i7180,9,751.69921875,751.4752604166666,-1,0.0843812045003309,3915080
1743442572,1743442585,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3915 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.7227977160933051 subsets 1,3915,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.7227977160933051,1,0,None,None,1,None,i7182,3915092
1743442573,1743442586,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4451 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 11,4451,1,str\(\'H\'\),1,str\(\'tstat\'\),0.001,11,0,None,None,1,None,i7138,3915110
1743442571,1743442591,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1550 feature_id 0 batch_size 61 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.43475390820747123 subsets 87,1550,61,str\(\'H\'\),3,str\(\'stdev\'\),0.43475390820747123,87,0,0.3,5,0,None,i7169,5,751.65625,751.4752604166666,-1,0.04037061548643282,3915098
1743442572,1743442591,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4185 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.7829956442664032 subsets 80,4185,1,str\(\'H\'\),3,str\(\'tstat\'\),0.7829956442664032,80,0,0.31,8,0,None,i7173,8,750.76171875,750.5182291666666,-1,0.0843812045003309,3915095
1743442572,1743442592,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1172 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 62,1172,1,str\(\'KL\'\),3,str\(\'stdev\'\),0.001,62,0,0.31,8,0,None,i7150,8,750.30859375,750.1158854166666,-1,0.0843812045003309,3915105
1743442573,1743442592,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2694 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 36,2694,1,str\(\'H\'\),3,str\(\'tstat\'\),0.001,36,0,0.31,8,0,None,i7145,8,751.3515625,751.1328125,-1,0.08471211118464593,3915107
1743442593,1743442606,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1509 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.6907413220968381 subsets 1,1509,1,str\(\'H\'\),1,str\(\'stdev\'\),0.6907413220968381,1,0,None,None,1,None,i7177,3915116
1743442593,1743442612,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4638 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.7974325451565547 subsets 90,4638,1,str\(\'H\'\),3,str\(\'tstat\'\),0.7974325451565547,90,0,0.31,9,0,None,i7154,9,750.75390625,750.5390625,-1,0.0843812045003309,3915119
1743442593,1743442613,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4476 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.19531688067704717 subsets 57,4476,1,str\(\'H\'\),3,str\(\'stdev\'\),0.19531688067704717,57,0,0.31,8,0,None,i7149,8,749.6640625,749.4830729166666,-1,0.0843812045003309,3915122
1743442602,1743442614,12,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 1,5000,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,1,0,None,None,1,None,i7150,3915132
1743442593,1743442618,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1264 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 34,1264,1,str\(\'H\'\),3,str\(\'stdev\'\),0.001,34,0,0.31,10,0,None,i7180,10,750.9140625,750.7330729166666,-1,0.0843812045003309,3915113
1743442602,1743442621,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4046 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 100,4046,1,str\(\'H\'\),3,str\(\'stdev\'\),0.001,100,0,0.31,8,0,None,i7169,8,749.90234375,749.7213541666666,-1,0.0843812045003309,3915129
1743442602,1743442622,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2937 feature_id 0 batch_size 8 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.8165567658580923 subsets 14,2937,8,str\(\'H\'\),3,str\(\'stdev\'\),0.8165567658580923,14,0,0.3,6,0,None,i7175,6,750.484375,750.2526041666666,-1,0.05559232296492389,3915125
1743442613,1743442626,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4956 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.8787241833738622 subsets 1,4956,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.8787241833738622,1,0,None,None,1,None,i7145,3915137
1743442613,1743442632,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2797 feature_id 0 batch_size 79 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.21245128372201277 subsets 25,2797,79,str\(\'H\'\),2,str\(\'tstat\'\),0.21245128372201277,25,0,0.3,6,0,None,i7150,6,751.18359375,750.86328125,-1,0.02614162806088683,3915134
1743442613,1743442632,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1688 feature_id 0 batch_size 25 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.49623927996915307 subsets 61,1688,25,str\(\'KL\'\),3,str\(\'tstat\'\),0.49623927996915307,61,0,0.31,6,0,None,i7138,6,749.78125,749.56640625,-1,0.09099933818663138,3915141
1743442632,1743442651,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3822 feature_id 0 batch_size 7 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.38441519276899044 subsets 10,3822,7,str\(\'KL\'\),1,str\(\'stdev\'\),0.38441519276899044,10,0,0.31,7,0,None,i7157,7,750.80078125,750.6328125,-1,0.08901389808074123,3915153
1743442633,1743442652,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1262 feature_id 0 batch_size 403 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 1,1262,403,str\(\'H\'\),1,str\(\'stdev\'\),0.999,1,0,0.32,8,0,None,i7150,8,750.74609375,750.6080729166666,-1,0.27200529450694905,3915157
1743442633,1743442652,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4972 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.5112587294391101 subsets 58,4972,1,str\(\'H\'\),3,str\(\'stdev\'\),0.5112587294391101,58,0,0.31,8,0,None,i7145,8,750.0078125,749.8268229166666,-1,0.0843812045003309,3915162
1743442632,1743442658,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4219 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.48085232713959436 subsets 87,4219,1,str\(\'H\'\),3,str\(\'stdev\'\),0.48085232713959436,87,0,0.31,10,0,None,i7175,10,750.33984375,750.19140625,-1,0.0843812045003309,3915149
1743442632,1743442658,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1861 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 65,1861,1,str\(\'H\'\),3,str\(\'tstat\'\),0.001,65,0,0.31,10,0,None,i7181,10,750.23046875,750.0390625,-1,0.08471211118464593,3915145
1743442652,1743442672,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2942 feature_id 0 batch_size 30 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 15,2942,30,str\(\'H\'\),1,str\(\'stdev\'\),0.999,15,0,0.29,5,0,None,i7180,5,750.63671875,750.4609375,-1,0.07941760423560557,3915165
1743442573,1743442687,114,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 921 feature_id 0 batch_size 50 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.610494704928633 subsets 100,921,50,str\(\'H\'\),2,str\(\'tstat\'\),0.610494704928633,100,0,0.31,97,0,None,i7163,97,751.58203125,751.5,-1,0.0827266710787558,3915101
1743445473,1743445493,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4266 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.696058130448914 subsets 1,4266,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.696058130448914,1,0,None,None,1,None,i7130,3917738
1743445483,1743445496,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 592 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.8276235787492148 subsets 1,592,1,str\(\'H\'\),1,str\(\'tstat\'\),0.8276235787492148,1,0,None,None,1,None,i7168,3917748
1743445473,1743445499,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1394 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.5220544699380553 subsets 100,1394,1,str\(\'KL\'\),3,str\(\'tstat\'\),0.5220544699380553,100,0,0.31,9,0,None,i7130,9,751.41796875,751.2083333333334,-1,0.0843812045003309,3917741
1743445483,1743445502,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1906 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.18813464421003157 subsets 90,1906,1,str\(\'H\'\),3,str\(\'tstat\'\),0.18813464421003157,90,0,0.31,9,0,None,i7181,9,750.05859375,749.8372395833334,-1,0.0843812045003309,3917744
1743445483,1743445502,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1051 feature_id 0 batch_size 72 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.6461004463803258 subsets 71,1051,72,str\(\'H\'\),3,str\(\'stdev\'\),0.6461004463803258,71,0,0.3,5,0,None,i7167,5,750.70703125,750.5130208333334,-1,0,3917750
1743445494,1743445506,12,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2074 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 12,2074,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,12,0,None,None,1,None,i7130,3917760
1743445493,1743445506,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4158 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 21,4158,1,str\(\'H\'\),1,str\(\'tstat\'\),0.001,21,0,None,None,1,None,i7140,3917753
1743445494,1743445506,12,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4939 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 26,4939,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,26,0,None,None,1,None,i7130,3917763
1743445494,1743445513,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2835 feature_id 0 batch_size 554 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.2023523161649863 subsets 1,2835,554,str\(\'KL\'\),1,str\(\'tstat\'\),0.2023523161649863,1,0,0.31,8,0,None,i7131,8,750.44140625,749.2838541666666,-1,0.25512905360688287,3917756
1743445512,1743445525,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2642 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 12,2642,1,str\(\'H\'\),1,str\(\'tstat\'\),0.001,12,0,None,None,1,None,i7181,3917766
1743445512,1743445525,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 1,5000,1,str\(\'H\'\),1,str\(\'tstat\'\),0.001,1,0,None,None,1,None,i7164,3917773
1743445513,1743445526,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1515 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 27,1515,1,str\(\'H\'\),1,str\(\'tstat\'\),0.001,27,0,None,None,1,None,i7152,3917776
1743445513,1743445532,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4906 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.8363167858744418 subsets 49,4906,1,str\(\'KL\'\),3,str\(\'stdev\'\),0.8363167858744418,49,0,0.31,8,0,None,i7176,8,749.75,749.54296875,-1,0.0843812045003309,3917768
1743445513,1743445532,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4735 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 15,4735,1,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,15,0,0.31,9,0,None,i7131,9,749.78515625,749.55078125,-1,0.0843812045003309,3917778
1743445514,1743445539,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 320 feature_id 0 batch_size 103 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.18626794261606497 subsets 1,320,103,str\(\'H\'\),1,str\(\'stdev\'\),0.18626794261606497,1,0,0.33,8,0,None,i7130,8,750.36328125,750.234375,-1,0.3269358041032429,3917784
1743445513,1743445539,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 1,1,1,str\(\'H\'\),2,str\(\'stdev\'\),0.999,1,0,0.31,8,0,None,i7130,8,750.96484375,750.7265625,-1,0.0843812045003309,3917781
1743445533,1743445552,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3669 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 11,3669,1,str\(\'H\'\),3,str\(\'stdev\'\),0.001,11,0,0.31,9,0,None,i7131,9,750.90625,750.7591145833334,-1,0.0843812045003309,3917790
1743445533,1743445552,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 978 feature_id 0 batch_size 14 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.8216954715351797 subsets 39,978,14,str\(\'H\'\),3,str\(\'tstat\'\),0.8216954715351797,39,0,0.31,6,0,None,i7130,6,751.7578125,751.55078125,-1,0.09265387160820648,3917793
1743445533,1743445552,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4480 feature_id 0 batch_size 44 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.8073416155479994 subsets 8,4480,44,str\(\'H\'\),1,str\(\'stdev\'\),0.8073416155479994,8,0,0.26,5,0,None,i7168,5,750.2421875,750.1106770833334,-1,0.051952349437458634,3917786
1743445543,1743445556,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4368 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.11192446987350546 subsets 7,4368,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.11192446987350546,7,0,None,None,1,None,i7163,3917804
1743445542,1743445561,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1203 feature_id 0 batch_size 2 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.19358042334777492 subsets 13,1203,2,str\(\'KL\'\),3,str\(\'stdev\'\),0.19358042334777492,13,0,0.31,7,0,None,i7173,7,749.5859375,749.39453125,-1,0.057246856386499005,3917801
1743445542,1743445562,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3457 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 21,3457,1,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,21,0,0.31,9,0,None,i7182,9,749.71484375,749.4778645833334,-1,0.08471211118464593,3917796
1743445553,1743445566,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4433 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.5795779491881602 subsets 11,4433,1,str\(\'H\'\),1,str\(\'tstat\'\),0.5795779491881602,11,0,None,None,1,None,i7153,3917810
1743445543,1743445569,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4249 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.8082612749905473 subsets 38,4249,1,str\(\'KL\'\),3,str\(\'tstat\'\),0.8082612749905473,38,0,0.31,11,0,None,i7178,11,751.6171875,751.41015625,-1,0.0843812045003309,3917798
1743445553,1743445572,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3597 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.7172881768095194 subsets 9,3597,1,str\(\'H\'\),3,str\(\'tstat\'\),0.7172881768095194,9,0,0.31,9,0,None,i7173,9,750.76953125,750.51953125,-1,0.0843812045003309,3917807
1743445554,1743445580,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 339 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.17820247783605092 subsets 1,339,1,str\(\'KL\'\),3,str\(\'tstat\'\),0.17820247783605092,1,0,0.31,10,0,None,i7149,10,750.17578125,749.9505208333334,-1,0.0843812045003309,3917814
1743445572,1743445585,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4084 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 7,4084,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,7,0,None,None,1,None,i7181,3917818
1743445572,1743445592,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4254 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.8570401123326281 subsets 1,4254,1,str\(\'H\'\),3,str\(\'stdev\'\),0.8570401123326281,1,0,0.31,8,0,None,i7164,8,750.96875,750.78125,-1,0.0843812045003309,3917825
1743445574,1743445593,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 618 feature_id 0 batch_size 519 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.7257902708283595 subsets 1,618,519,str\(\'KL\'\),1,str\(\'stdev\'\),0.7257902708283595,1,0,0.31,9,0,None,i7163,9,750.234375,750.0859375,-1,0.1972203838517538,3917827
1743445573,1743445598,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4300 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.7331848775579899 subsets 11,4300,1,str\(\'H\'\),2,str\(\'tstat\'\),0.7331848775579899,11,0,0.31,12,0,None,i7173,12,750.41796875,750.1640625,-1,0.0843812045003309,3917822
1743449895,1743449908,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4615 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 15,4615,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,15,0,None,None,1,None,i7173,3924712
1743449895,1743449914,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1472 feature_id 0 batch_size 823 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 6,1472,823,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,6,0,0.23,5,0,None,i7171,5,750.953125,750.6393229166666,-1,0,3924717
1743449895,1743449914,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3611 feature_id 0 batch_size 1017 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.27645758774256135 subsets 1,3611,1017,str\(\'KL\'\),1,str\(\'stdev\'\),0.27645758774256135,1,0,0.29,8,0,None,i7173,8,751.02734375,750.9036458333334,-1,0.01158173395102581,3924715
1743449915,1743449928,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4594 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 55,4594,1,str\(\'H\'\),1,str\(\'stdev\'\),0.999,55,0,None,None,1,None,i7173,3924720
1743449915,1743449934,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2272 feature_id 0 batch_size 115 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 24,2272,115,str\(\'H\'\),1,str\(\'tstat\'\),0.001,24,0,0.2,5,0,None,i7171,5,750.52734375,750.3203125,-1,0.03805426869622766,3924725
1743449924,1743449936,12,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 790 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 85,790,1,str\(\'H\'\),1,str\(\'stdev\'\),0.001,85,0,None,None,1,None,i7173,3924730
1743449924,1743449943,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3503 feature_id 0 batch_size 862 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.3906019251466765 subsets 10,3503,862,str\(\'KL\'\),1,str\(\'stdev\'\),0.3906019251466765,10,0,0.22,6,0,None,i7171,6,750.42578125,750.265625,-1,0,3924736
1743449935,1743449948,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 431 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.30281541807907314 subsets 33,431,1,str\(\'H\'\),1,str\(\'stdev\'\),0.30281541807907314,33,0,None,None,1,None,i7170,3924749
1743449935,1743449954,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1785 feature_id 0 batch_size 1855 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 1,1785,1855,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,1,0,0.2,5,0,None,i7170,5,751.6796875,751.4609375,-1,0,3924745
1743449954,1743449967,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2064 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 78,2064,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,78,0,None,None,1,None,i7173,3924757
1743449955,1743449968,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4319 feature_id 0 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 24,4319,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,24,0,None,None,1,None,i7171,3924764
1743449955,1743449968,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 754 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 16,754,1,str\(\'H\'\),1,str\(\'tstat\'\),0.001,16,0,None,None,1,None,i7171,3924771
1743449975,1743449995,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2205 feature_id 0 batch_size 653 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.14208136710210653 subsets 31,2205,653,str\(\'KL\'\),2,str\(\'stdev\'\),0.14208136710210653,31,0,0.25,5,0,None,i7173,5,751.484375,751.1901041666666,-1,0,3924780
1743449984,1743450003,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4077 feature_id 0 batch_size 835 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.6104863248118095 subsets 7,4077,835,str\(\'KL\'\),2,str\(\'stdev\'\),0.6104863248118095,7,0,0.22,6,0,None,i7171,6,751.52734375,751.2552083333334,-1,0,3924786
1743449996,1743450016,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4186 feature_id 0 batch_size 772 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 1,4186,772,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,1,0,0.27,7,0,None,i7178,7,750.0078125,749.6927083333334,-1,0.10489741892786235,3924796
1743449997,1743450016,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4292 feature_id 0 batch_size 1197 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 1,4292,1197,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,1,0,0.23,6,0,None,i7170,6,751.80859375,751.5130208333334,-1,0,3924803
1743450015,1743450028,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4644 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 32,4644,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,32,0,None,None,1,None,i7171,3924818
1743450013,1743450033,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3589 feature_id 0 batch_size 899 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 10,3589,899,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,10,0,0.2,5,0,None,i7173,5,750.22265625,750.0416666666666,-1,0.23097286565188616,3924810
1743450036,1743450049,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4813 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.8720062610635276 subsets 1,4813,1,str\(\'H\'\),1,str\(\'tstat\'\),0.8720062610635276,1,0,None,None,1,None,i7171,3924829
1743450035,1743450055,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4846 feature_id 0 batch_size 716 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.7620271162019403 subsets 20,4846,716,str\(\'H\'\),1,str\(\'stdev\'\),0.7620271162019403,20,0,0.21,6,0,None,i7170,6,749.8359375,749.6653645833334,-1,0.04930509596293845,3924835
1743450044,1743450063,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2844 feature_id 0 batch_size 1650 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.3793017267811763 subsets 100,2844,1650,str\(\'KL\'\),2,str\(\'stdev\'\),0.3793017267811763,100,0,0.2,10,0,None,i7173,10,750.5625,750.3662109375,-1,0,3924843
1743450056,1743450082,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3171 feature_id 0 batch_size 2375 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.7618884031980945 subsets 100,3171,2375,str\(\'KL\'\),1,str\(\'stdev\'\),0.7618884031980945,100,0,0.2,12,0,None,i7171,12,750.24609375,750.1396484375,-1,0.12442091330244871,3924856
1743450074,1743450094,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 733 feature_id 0 batch_size 772 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 1,733,772,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,1,0,0.23,6,0,None,i7178,6,750.78515625,750.5598958333334,-1,0,3924862
1743450075,1743450101,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1426 feature_id 0 batch_size 2145 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.28733416400477496 subsets 100,1426,2145,str\(\'KL\'\),1,str\(\'stdev\'\),0.28733416400477496,100,0,0.2,11,0,None,i7173,11,751.765625,751.6533203125,-1,0.048312375909993384,3924872
1743450095,1743450108,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3869 feature_id 0 batch_size 1043 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.5472222664763893 subsets 10,3869,1043,str\(\'KL\'\),1,str\(\'stdev\'\),0.5472222664763893,10,0,0.2,4,0,None,i7182,4,749.8515625,749.671875,-1,0,3924883
1743450104,1743450124,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 0 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 100,1,1,str\(\'H\'\),1,str\(\'stdev\'\),0.001,100,0,None,None,1,None,i7176,3924892
1743450115,1743450135,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4454 feature_id 0 batch_size 1908 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 39,4454,1908,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,39,0,0.2,4,0,None,i7173,4,750.890625,750.7122395833334,-1,0,3924901
1743450135,1743450155,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4639 feature_id 0 batch_size 17 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.8197150781077498 subsets 27,4639,17,str\(\'KL\'\),2,str\(\'stdev\'\),0.8197150781077498,27,0,0.31,8,0,None,i7185,8,751.19921875,750.9114583333334,-1,0.050628722700198546,3924910
1743450136,1743450162,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 840 feature_id 0 batch_size 1931 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 100,840,1931,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,100,0,0.2,14,0,None,i7180,14,750.16015625,750.0361328125,-1,0,3924925
1743450159,1743450185,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4799 feature_id 0 batch_size 100 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.9178381006808108 subsets 56,4799,100,str\(\'H\'\),2,str\(\'tstat\'\),0.9178381006808108,56,0,0.31,13,0,None,i7183,13,750.921875,750.6953125,-1,0.09927200529450694,3924933

Key	Value
config_yaml	None
config_toml	None
config_json	None
num_random_steps	20
max_eval	500
run_program	[['bW9kdWxlIGxvYWQgR0NDY29yZS8xMC4zLjAgUHl0aG9uICYmIHNvdXJjZSAvZGF0YS9ob3JzZS93cy9zNDEyMjQ4NS1jb21wUGVyZkREL2JlbmNobWFyay92ZW52L2Jpbi9hY3RpdmF0ZSAmJiBw…
experiment_name	CDBD_TMDBalanced5s_ft_0_HoeffdingTreeClassifier_ACCURACY-RUNTIME
mem_gb	32
parameter	[['recent_samples_size', 'range', '1', '5000', 'int'], ['feature_id', 'fixed', '0'], ['batch_size', 'range', '1', '5000', 'int'], ['divergence',
	'choice', "str\\(\\'KL\\'\\),str\\(\\'H\\'\\)"], ['detect_batch', 'choice', '1,2,3'], ['statistic', 'choice',
	"str\\(\\'tstat\\'\\),str\\(\\'stdev\\'\\)"], ['significance', 'range', '0.001', '0.999', 'float'], ['subsets', 'range', '1', '100', 'int']]
continue_previous_job	None
maximize	False
experiment_constraints	None
stderr_to_stdout	False
run_dir	runs
seed	None
decimalrounding	12
enforce_sequential_optimization	False
verbose_tqdm	False
model	BOTORCH_MODULAR
gridsearch	False
occ	False
show_sixel_scatter	False
show_sixel_general	False
show_sixel_trial_index_result	False
follow	False
send_anonymized_usage_stats	True
ui_url	None
root_venv_dir	/home/s4122485
exclude	None
main_process_gb	8
pareto_front_confidence	1
max_nr_of_zero_results	50
disable_search_space_exhaustion_detection	False
abbreviate_job_names	False
orchestrator_file	None
checkout_to_latest_tested_version	False
live_share	False
disable_tqdm	False
workdir	False
max_parallelism	max_eval_times_thousand_plus_thousand
occ_type	euclid
result_names	['ACCURACY=max', 'RUNTIME=min']
minkowski_p	2
signed_weighted_euclidean_weights
generation_strategy	None
generate_all_jobs_at_once	True
revert_to_random_when_seemingly_exhausted	True
num_parallel_jobs	30
worker_timeout	60
slurm_use_srun	False
time	1440
partition	romeo
reservation	None
force_local_execution	False
slurm_signal_delay_s	0
nodes_per_job	1
cpus_per_task	1
account	None
gpus	0
run_mode	local
verbose	False
verbose_break_run_search_table	False
debug	False
no_sleep	False
tests	False
show_worker_percentage_table_at_end	False
auto_exclude_defective_hosts	False
run_tests_that_fail_on_taurus	False
raise_in_eval	False
show_ram_every_n_seconds	False

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<!DOCTYPE html>
<html lang='en'>
	<head>
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		<title>Exported &raquo;s4122485/CDBD_TMDBalanced5s_ft_0_HoeffdingTreeClassifier_ACCURACY-RUNTIME/0&laquo; from OmniOpt2-Share</title>
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				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: 65px;
				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;
			}
			
			.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;
				margin-top: 3px;
			}
			
			.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;
					width: inherit;
				}
			
				.logo-img {
					max-height: 50px;
					pointer-events: unset;
				}
			
				.badge-img {
					max-width: 100px;
				}
			
				.hide_on_mobile {
					display: none;
				}
			
				.nav-tab {
					font-size: 0.9rem;
					padding: 6px 12px;
				}
			
				.header_button {
					white-space: pre;
					font-size: 2em;
				}
			}
			
			.header_button {
				white-space: pre;
				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;
			}
			
			input::placeholder {
				font-family: 'IBM Plex Sans', 'Source Sans Pro', sans-serif;
			}
			
			.gridjs-th-content {
				overflow: visible !important;
			}
			
			.error_text {
				color: red;
			}
			
			h1, h2, h3, h4, h5, h6 {
				margin-top: 1em;
				font-weight: bold;
				color: #333;
				border-left: 5px solid #ccc;
				padding-left: 0.5em;
			}
			
			.no_cursive {
				font-style: normal;	
			}
			
			.caveat {
				background-color: #fff8b3;
				border: 1px solid #f2d600;
				padding: 1em 1em 1em 70px;
				position: relative;
				font-family: sans-serif;
				color: #665500;
				margin: 1em 0;
				border-radius: 4px;
			}
			
			.caveat h1, .caveat h2, .caveat h3, .caveat h4 {
				margin-top: 0;
				margin-bottom: 0.5em;
				font-weight: bold;
			}
			
			.caveat::before {
				content: "⚠️";
				font-size: 50px;
				line-height: 1;
				position: absolute;
				left: 10px;
				top: 50%;
				transform: translateY(-50%);
				pointer-events: none;
				user-select: none;
			}
			
			.caveat.warning::before { content: "⚠️"; }
			.caveat.stop::before { content: "🛑"; }
			.caveat.exclamation::before { content: "❗"; }
			.caveat.alarm::before { content: "🚨"; }
			.caveat.tip::before { content: "💡"; }
			
			.tutorial_icon {
				display: inline-block;
				font-size: 1.3em;
				line-height: 1;
				vertical-align: middle;
				transform: translateY(-10%);
				padding: 0.2em 0;
			}
			
			.highlight {
				background-color: yellow;
				font-weight: bold;
			}
			
			#searchResults li {
				opacity: 0;
				transform: translateY(8px);
				animation: fadeInUp 0.3s ease-out forwards;
				animation-delay: 0.05s;
				list-style: none;
				margin-bottom: 5px;
			}
			
			@keyframes fadeInUp {
				to {
					opacity: 1;
					transform: translateY(0);
				}
			}
			
			.search_headline {
				font-weight: bold;
				margin-top: 1em;
				margin-bottom: 0.3em;
				color: #444;
			}
			
			.search_share_path {
				color: black;
				display: block ruby;
				margin-top: 20px;
			}
			
			@media print {
				#scads_bar {
					display: none !important;
				}
			}
			

			/*! 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 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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' 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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 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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='%23bdd3fb' d='M8 12h1'/%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 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			}
			
			: :-webkit-scrollbar-button: horizontal: start{
				width: 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 0h17m-1 1h1m-1 14h1m-1 1h1'/%3E%3Cpath stroke='%23fdfdfa' d='M0 1h1'/%3E%3Cpath stroke='%23fff' d='M1 1h15M0 2h1m14 0h1M0 3h1m14 0h1M0 4h1m14 0h1M0 5h1m14 0h1M0 6h1m14 0h1M0 7h1m14 0h1M0 8h1m14 0h1M0 9h1m14 0h1M0 10h1m14 0h1M0 11h1m14 0h1M0 12h1m14 0h1M0 13h1m14 0h1M0 14h1m14 0h1M1 15h14'/%3E%3Cpath stroke='%23e6eefc' d='M1 2h1'/%3E%3Cpath stroke='%23d0dffc' d='M2 2h1M1 3h1'/%3E%3Cpath stroke='%23cad8f9' d='M3 2h1M1 4h1'/%3E%3Cpath stroke='%23c4d2f7' d='M4 2h1'/%3E%3Cpath stroke='%23c0d0f7' d='M5 2h1'/%3E%3Cpath stroke='%23bdcef7' d='M6 2h1M1 7h1'/%3E%3Cpath stroke='%23bbcdf5' d='M7 2h2'/%3E%3Cpath stroke='%23b8cbf6' d='M9 2h1M1 8h1'/%3E%3Cpath stroke='%23b7caf5' d='M10 2h1M1 9h1'/%3E%3Cpath stroke='%23b5c8f7' d='M11 2h1'/%3E%3Cpath stroke='%23b3c7f5' d='M12 2h1'/%3E%3Cpath stroke='%23afc5f4' 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			}
			
			: :-webkit-scrollbar-button: horizontal: end{
				width: 17px;
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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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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
			}
			
			menu[role=tablist] button{
				background: linear-gradient(180deg,#fff,#fafaf9 26%,#f0f0ea 95%,#ecebe5);
				margin-left: -1px;
				margin-right: 2px;
				border-radius: 0;
				border-color: #91a7b4;
				border-top-right-radius: 3px;
				border-top-left-radius: 3px;
				padding: 0 12px 3px
			}
			
			menu[role=tablist] button: hover{
				box-shadow: unset;
				border-top: 1px solid #e68b2c;
				box-shadow: inset 0 2px #ffc73c
			}
			
			menu[role=tablist] button[aria-selected=true]{
				border-color: #919b9c;
				margin-right: -1px;
				border-bottom: 1px solid transparent;
				border-top: 1px solid #e68b2c;
				box-shadow: inset 0 2px #ffc73c
			}
			
			menu[role=tablist] button[aria-selected=true]: first-of-type: before{
				content: "";
				display: block;
				position: absolute;
				z-index: -1;
				top: 100%;
				left: -1px;
				height: 2px;
				width: 0;
				border-left: 1px solid #919b9c
			}
			
			[role=tabpanel]{
				box-shadow: inset 1px 1px #fcfcfe,inset -1px -1px #fcfcfe,1px 2px 2px 0 rgba(208,206,191,.75)
			}
			
			ul.tree-view{
				-webkit-font-smoothing: auto;
				border: 1px solid #7f9db9;
				padding: 2px 5px
			}
			
			@keyframes sliding{
				0%{
					transform: translateX(-30px)
				}
			
				to{
					transform: translateX(100%)
				}
			}
			
			progress{
				box-sizing: border-box;
				appearance: none;
				-webkit-appearance: none;
				-moz-appearance: none;
				height: 14px;
				border: 1px solid #686868;
				border-radius: 4px;
				padding: 1px 2px 1px 0;
				overflow: hidden;
				background-color: #fff;
				-webkit-box-shadow: inset 0 0 1px 0 #686868;
				-moz-box-shadow: inset 0 0 1px 0 #686868
			}
			
			progress,progress: not([value]){
				box-shadow: inset 0 0 1px 0 #686868
			}
			
			progress: not([value]){
				-moz-box-shadow: inset 0 0 1px 0 #686868;
				-webkit-box-shadow: inset 0 0 1px 0 #686868;
				height: 14px
			}
			
			progress[value]: :-webkit-progress-bar{
				background-color: transparent
			}
			
			progress[value]: :-webkit-progress-value{
				border-radius: 2px;
				background: repeating-linear-gradient(90deg,#fff 0,#fff 2px,transparent 0,transparent 10px),linear-gradient(180deg,#acedad 0,#7be47d 14%,#4cda50 28%,#2ed330 42%,#42d845 57%,#76e275 71%,#8fe791 85%,#fff)
			}
			
			progress[value]: :-moz-progress-bar{
				border-radius: 2px;
				background: repeating-linear-gradient(90deg,#fff 0,#fff 2px,transparent 0,transparent 10px),linear-gradient(180deg,#acedad 0,#7be47d 14%,#4cda50 28%,#2ed330 42%,#42d845 57%,#76e275 71%,#8fe791 85%,#fff)
			}
			
			progress: not([value]): :-webkit-progress-bar{
				width: 100%;
				background: repeating-linear-gradient(90deg,transparent 0,transparent 8px,#fff 0,#fff 10px,transparent 0,transparent 18px,#fff 0,#fff 20px,transparent 0,transparent 28px,#fff 0,#fff),linear-gradient(180deg,#acedad 0,#7be47d 14%,#4cda50 28%,#2ed330 42%,#42d845 57%,#76e275 71%,#8fe791 85%,#fff);
				animation: sliding 2s linear 0s infinite
			}
			
			progress: not([value]): :-webkit-progress-bar: not([value]){
				animation: sliding 2s linear 0s infinite;
				background: repeating-linear-gradient(90deg,transparent 0,transparent 8px,#fff 0,#fff 10px,transparent 0,transparent 18px,#fff 0,#fff 20px,transparent 0,transparent 28px,#fff 0,#fff),linear-gradient(180deg,#acedad 0,#7be47d 14%,#4cda50 28%,#2ed330 42%,#42d845 57%,#76e275 71%,#8fe791 85%,#fff)
			}
			
			progress: not([value]){
				position: relative
			}
			
			progress: not([value]): before{
				box-sizing: border-box;
				content: "";
				position: absolute;
				top: 0;
				left: 0;
				width: 100%;
				height: 100%;
				background-color: #fff;
				-webkit-box-shadow: inset 0 0 1px 0 #686868;
				-moz-box-shadow: inset 0 0 1px 0 #686868
			}
			
			progress: not([value]): before,progress: not([value]): before: not([value]){
				box-shadow: inset 0 0 1px 0 #686868
			}
			
			progress: not([value]): before: not([value]){
				-moz-box-shadow: inset 0 0 1px 0 #686868;
				-webkit-box-shadow: inset 0 0 1px 0 #686868
			}
			
			progress: not([value]): after{
				box-sizing: border-box;
				content: "";
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			    [
			        1743399947,
			        706.83203125,
			        4.8
			    ],
			    [
			        1743399947,
			        706.83203125,
			        4.6
			    ],
			    [
			        1743399947,
			        706.83203125,
			        4.6
			    ],
			    [
			        1743399947,
			        706.83203125,
			        8.3
			    ],
			    [
			        1743406886,
			        734.4140625,
			        4.8
			    ],
			    [
			        1743406886,
			        734.4140625,
			        4.9
			    ],
			    [
			        1743406886,
			        734.4140625,
			        4.6
			    ],
			    [
			        1743406886,
			        734.4140625,
			        3.6
			    ],
			    [
			        1743409565,
			        725.63671875,
			        5.3
			    ],
			    [
			        1743409565,
			        725.63671875,
			        5.1
			    ],
			    [
			        1743409565,
			        725.63671875,
			        5.1
			    ],
			    [
			        1743409565,
			        725.63671875,
			        3
			    ],
			    [
			        1743412435,
			        799.9375,
			        5.3
			    ],
			    [
			        1743412435,
			        799.9375,
			        5.3
			    ],
			    [
			        1743412435,
			        799.9375,
			        5.1
			    ],
			    [
			        1743412435,
			        799.9375,
			        6.7
			    ],
			    [
			        1743420701,
			        767.07421875,
			        5.3
			    ],
			    [
			        1743420701,
			        767.07421875,
			        5.2
			    ],
			    [
			        1743420701,
			        767.07421875,
			        5.1
			    ],
			    [
			        1743420701,
			        767.07421875,
			        6
			    ],
			    [
			        1743427019,
			        777.1640625,
			        6.1
			    ],
			    [
			        1743427019,
			        777.1640625,
			        5.2
			    ],
			    [
			        1743427019,
			        777.1640625,
			        5.1
			    ],
			    [
			        1743427019,
			        777.1640625,
			        4.9
			    ],
			    [
			        1743429686,
			        780.734375,
			        6.5
			    ],
			    [
			        1743429686,
			        780.734375,
			        5.6
			    ],
			    [
			        1743429686,
			        780.734375,
			        6.2
			    ],
			    [
			        1743429686,
			        780.734375,
			        6.5
			    ],
			    [
			        1743436366,
			        825.33984375,
			        6.6
			    ],
			    [
			        1743436366,
			        825.33984375,
			        5.3
			    ],
			    [
			        1743436366,
			        825.33984375,
			        5.5
			    ],
			    [
			        1743436366,
			        825.33984375,
			        5.7
			    ],
			    [
			        1743439827,
			        781.80859375,
			        6.8
			    ],
			    [
			        1743439827,
			        781.80859375,
			        6.3
			    ],
			    [
			        1743439827,
			        781.80859375,
			        6.5
			    ],
			    [
			        1743439827,
			        781.80859375,
			        8.3
			    ],
			    [
			        1743442553,
			        784.62890625,
			        7
			    ],
			    [
			        1743442553,
			        784.62890625,
			        5
			    ],
			    [
			        1743442553,
			        784.62890625,
			        5.8
			    ],
			    [
			        1743442553,
			        784.62890625,
			        2.9
			    ],
			    [
			        1743445546,
			        788.89453125,
			        6.4
			    ],
			    [
			        1743445546,
			        788.89453125,
			        6.6
			    ],
			    [
			        1743445546,
			        788.89453125,
			        7.2
			    ],
			    [
			        1743445546,
			        788.89453125,
			        6.1
			    ],
			    [
			        1743449961,
			        814.94921875,
			        8.1
			    ],
			    [
			        1743449961,
			        814.94921875,
			        7.4
			    ],
			    [
			        1743449961,
			        814.94921875,
			        7.5
			    ],
			    [
			        1743449961,
			        814.94921875,
			        7.4
			    ],
			    [
			        1743450197,
			        819.171875,
			        7.1
			    ],
			    [
			        1743450197,
			        819.171875,
			        6
			    ]
			];
			var tab_main_worker_cpu_ram_headers_json = [
			    "timestamp",
			    "ram_usage_mb",
			    "cpu_usage_percent"
			];
			
			"use strict";
			
			function add_default_layout_data (layout, no_height = 0) {
				layout["width"] = get_graph_width();
				if (!no_height) {
					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,
					ellipsis: false
				}).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) &&
						!col.startsWith("OO_Info") &&
						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) &&
						!col.startsWith("OO_Info") &&
						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 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) &&
					!col.startsWith("OO_Info") &&
					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;
					}
					if (!col.startsWith("OO_Info")) {
						return;
					}
					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) &&
					!col.startsWith("OO_Info") &&
					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) &&
					!col.startsWith("OO_Info") &&
					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");
				upArrow.classList.add("invert_in_dark_mode");
				upArrow.innerHTML = "&#8593;";
			
				downArrow.id = "down-arrow";
				downArrow.classList.add("scroll-arrow");
				downArrow.classList.add("invert_in_dark_mode");
				downArrow.innerHTML = "&#8595;";
			
				document.body.appendChild(upArrow);
				document.body.appendChild(downArrow);
			
				function checkScrollPosition() {
					const scrollPosition = window.scrollY;
					const pageHeight = document.documentElement.scrollHeight;
					const windowHeight = window.innerHeight;
			
					if (scrollPosition > 0) {
						upArrow.style.display = "block";
					} else {
						upArrow.style.display = "none";
					}
			
					if (scrollPosition + windowHeight < pageHeight) {
						downArrow.style.display = "block";
					} else {
						downArrow.style.display = "none";
					}
				}
			
				window.addEventListener("scroll", checkScrollPosition);
			
				upArrow.addEventListener("click", function () {
					window.scrollTo({ top: 0, behavior: 'smooth' });
				});
			
				downArrow.addEventListener("click", function () {
					window.scrollTo({ top: document.documentElement.scrollHeight, behavior: 'smooth' });
				});
			
				checkScrollPosition();
			
				if (typeof apply_theme_based_on_system_preferences === 'function') {
					apply_theme_based_on_system_preferences();
				}
			}
			
			function plotGPUUsage() {
				if ($("#tab_gpu_usage").data("loaded") === "true") {
					return;
				}
			
				Object.keys(gpu_usage).forEach(node => {
					const nodeData = gpu_usage[node];
			
					var timestamps = [];
					var gpuUtilizations = [];
					var temperatures = [];
			
					nodeData.forEach(entry => {
						try {
							var timestamp = new Date(entry[0]* 1000);
							var utilization = parseFloat(entry[1]);
							var temperature = parseFloat(entry[2]);
			
							if (!isNaN(timestamp) && !isNaN(utilization) && !isNaN(temperature)) {
								timestamps.push(timestamp);
								gpuUtilizations.push(utilization);
								temperatures.push(temperature);
							} else {
								console.warn("Invalid data point:", entry);
							}
						} catch (error) {
							console.error("Error processing GPU data entry:", error, entry);
						}
					});
			
					var trace1 = {
						x: timestamps,
						y: gpuUtilizations,
						mode: 'lines+markers',
						marker: {
							size: get_marker_size(),
						},
						name: 'GPU Utilization (%)',
						type: 'scatter',
						yaxis: 'y1'
					};
			
					var trace2 = {
						x: timestamps,
						y: temperatures,
						mode: 'lines+markers',
						marker: {
							size: get_marker_size(),
						},
						name: 'GPU Temperature (°C)',
						type: 'scatter',
						yaxis: 'y2'
					};
			
					var layout = {
						title: 'GPU Usage Over Time - ' + node,
						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("GPU Utilization (%)"),
							overlaying: 'y',
							rangemode: 'tozero'
						},
						yaxis2: {
							title: get_axis_title_data("GPU Temperature (°C)"),
							overlaying: 'y',
							side: 'right',
							position: 0.85,
							rangemode: 'tozero'
						},
						legend: {
							x: 0.1,
							y: 0.9
						}
					};
			
					var divId = 'gpu_usage_plot_' + node;
			
					if (!document.getElementById(divId)) {
						var div = document.createElement('div');
						div.id = divId;
						div.className = 'gpu-usage-plot';
						document.getElementById('tab_gpu_usage').appendChild(div);
					}
			
					var plotData = [trace1, trace2];
			
					Plotly.newPlot(divId, plotData, add_default_layout_data(layout));
				});
			
				$("#tab_gpu_usage").data("loaded", "true");
			}
			
			function plotResultsDistributionByGenerationMethod() {
				if ("true" === $("#plotResultsDistributionByGenerationMethod").data("loaded")) {
					return;
				}
			
				var res_col = result_names[0];
				var gen_method_col = "generation_node";
			
				var data = {};
			
				tab_results_csv_json.forEach(row => {
					var gen_method = row[tab_results_headers_json.indexOf(gen_method_col)];
					var result = row[tab_results_headers_json.indexOf(res_col)];
			
					if (!data[gen_method]) {
						data[gen_method] = [];
					}
					data[gen_method].push(result);
				});
			
				var traces = Object.keys(data).map(method => {
					return {
						y: data[method],
						type: 'box',
						name: method,
						boxpoints: 'outliers',
						jitter: 0.5,
						pointpos: 0
					};
				});
			
				var layout = {
					title: 'Distribution of Results by Generation Method',
					yaxis: {
						title: get_axis_title_data(res_col)
					},
					xaxis: {
						title: get_axis_title_data("Generation Method")
					},
					boxmode: 'group'
				};
			
				Plotly.newPlot("plotResultsDistributionByGenerationMethod", traces, add_default_layout_data(layout));
				$("#plotResultsDistributionByGenerationMethod").data("loaded", "true");
			}
			
			function plotJobStatusDistribution() {
				if ($("#plotJobStatusDistribution").data("loaded") === "true") {
					return;
				}
			
				var status_col = "trial_status";
				var status_counts = {};
			
				tab_results_csv_json.forEach(row => {
					var status = row[tab_results_headers_json.indexOf(status_col)];
					if (status) {
						status_counts[status] = (status_counts[status] || 0) + 1;
					}
				});
			
				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%)`
				);
			
				var trace = {
					x: statuses,
					y: counts,
					type: 'bar',
					marker: { color: colors }
				};
			
				var layout = {
					title: 'Distribution of Job Status',
					xaxis: { title: 'Trial Status' },
					yaxis: { title: 'Nr. of jobs' }
				};
			
				Plotly.newPlot("plotJobStatusDistribution", [trace], add_default_layout_data(layout));
				$("#plotJobStatusDistribution").data("loaded", "true");
			}
			
			function _colorize_table_entries_by_generation_method () {
				document.querySelectorAll('[data-column-id="generation_node"]').forEach(el => {
					let text = el.textContent.toLowerCase();
					let color = text.includes("manual") ? "green" :
						text.includes("sobol") ? "orange" :
						text.includes("saasbo") ? "pink" :
						text.includes("uniform") ? "lightblue" :
						text.includes("legacy_gpei") ? "sienna" :
						text.includes("bo_mixed") ? "aqua" :
						text.includes("randomforest") ? "darkseagreen" :
						text.includes("external_generator") ? "purple" :
						text.includes("botorch") ? "yellow" : "";
					if (color !== "") {
						el.style.backgroundColor = color;
					}
					el.classList.add("invert_in_dark_mode");
				});
			}
			
			function _colorize_table_entries_by_trial_status () {
				document.querySelectorAll('[data-column-id="trial_status"]').forEach(el => {
					let color = el.textContent.includes("COMPLETED") ? "lightgreen" :
						el.textContent.includes("RUNNING") ? "orange" :
						el.textContent.includes("FAILED") ? "red" :
						el.textContent.includes("ABANDONED") ? "yellow" : "";
					if (color) el.style.backgroundColor = color;
					el.classList.add("invert_in_dark_mode");
				});
			}
			
			function _colorize_table_entries_by_run_time() {
				let cells = [...document.querySelectorAll('[data-column-id="run_time"]')];
				if (cells.length === 0) return;
			
				let values = cells.map(el => parseFloat(el.textContent)).filter(v => !isNaN(v));
				if (values.length === 0) return;
			
				let min = Math.min(...values);
				let max = Math.max(...values);
				let range = max - min || 1;
			
				cells.forEach(el => {
					let value = parseFloat(el.textContent);
					if (isNaN(value)) return;
			
					let ratio = (value - min) / range;
					let red = Math.round(255 * ratio);
					let green = Math.round(255 * (1 - ratio));
			
					el.style.backgroundColor = `rgb(${red}, ${green}, 0)`;
					el.classList.add("invert_in_dark_mode");
				});
			}
			
			function _colorize_table_entries_by_results() {
				result_names.forEach((name, index) => {
					let minMax = result_min_max[index];
					let selector_query = `[data-column-id="${name}"]`;
					let cells = [...document.querySelectorAll(selector_query)];
					if (cells.length === 0) return;
			
					let values = cells.map(el => parseFloat(el.textContent)).filter(v => v > 0 && !isNaN(v));
					if (values.length === 0) return;
			
					let logValues = values.map(v => Math.log(v));
					let logMin = Math.min(...logValues);
					let logMax = Math.max(...logValues);
					let logRange = logMax - logMin || 1;
			
					cells.forEach(el => {
						let value = parseFloat(el.textContent);
						if (isNaN(value) || value <= 0) return;
			
						let logValue = Math.log(value);
						let ratio = (logValue - logMin) / logRange;
						if (minMax === "max") ratio = 1 - ratio;
			
						let red = Math.round(255 * ratio);
						let green = Math.round(255 * (1 - ratio));
			
						el.style.backgroundColor = `rgb(${red}, ${green}, 0)`;
						el.classList.add("invert_in_dark_mode");
					});
				});
			}
			
			function _colorize_table_entries_by_generation_node_or_hostname() {
				["hostname", "generation_node"].forEach(element => {
					let selector_query = '[data-column-id="' + element + '"]:not(.gridjs-th)';
					let cells = [...document.querySelectorAll(selector_query)];
					if (cells.length === 0) return;
			
					let uniqueValues = [...new Set(cells.map(el => el.textContent.trim()))];
					let colorMap = {};
			
					uniqueValues.forEach((value, index) => {
						let hue = Math.round((360 / uniqueValues.length) * index);
						colorMap[value] = `hsl(${hue}, 70%, 60%)`;
					});
			
					cells.forEach(el => {
						let value = el.textContent.trim();
						if (colorMap[value]) {
							el.style.backgroundColor = colorMap[value];
							el.classList.add("invert_in_dark_mode");
						}
					});
				});
			}
			
			function colorize_table_entries () {
				setTimeout(() => {
					if (typeof result_names !== "undefined" && Array.isArray(result_names) && result_names.length > 0) {
						_colorize_table_entries_by_trial_status();
						_colorize_table_entries_by_results();
						_colorize_table_entries_by_run_time();
						_colorize_table_entries_by_generation_method();
						_colorize_table_entries_by_generation_node_or_hostname();
						if (typeof apply_theme_based_on_system_preferences === 'function') {
							apply_theme_based_on_system_preferences();
						}
					}
				}, 300);
			}
			
			function add_colorize_to_gridjs_table () {
				let searchInput = document.querySelector(".gridjs-search-input");
				if (searchInput) {
					searchInput.addEventListener("input", colorize_table_entries);
				}
			}
			
			function updatePreWidths() {
				var width = window.innerWidth * 0.95;
				var pres = document.getElementsByTagName('pre');
				for (var i = 0; i < pres.length; i++) {
					pres[i].style.width = width + 'px';
				}
			}
			
			function demo_mode(nr_sec = 3) {
				let i = 0;
				let tabs = $('menu[role="tablist"] > button');
			
				setInterval(() => {
					tabs.attr('aria-selected', 'false').removeClass('active');
			
					let tab = tabs.eq(i % tabs.length);
					tab.attr('aria-selected', 'true').addClass('active');
			
					tab.trigger('click');
			
					i++;
				}, nr_sec * 1000);
			}
			
			function resizePlotlyCharts() {
				const plotlyElements = document.querySelectorAll('.js-plotly-plot');
			
				if (plotlyElements.length) {
					const windowWidth = window.innerWidth;
					const windowHeight = window.innerHeight;
			
					const newWidth = windowWidth * 0.9;
					const newHeight = windowHeight * 0.9;
			
					plotlyElements.forEach(function(element, index) {
						const layout = {
							width: newWidth,
							height: newHeight,
							plot_bgcolor: 'rgba(0, 0, 0, 0)',
							paper_bgcolor: 'rgba(0, 0, 0, 0)',
						};
			
						Plotly.relayout(element, layout)
					});
				}
			
				make_text_in_parallel_plot_nicer();
				apply_theme_based_on_system_preferences();
			}
			
			function plotTimelineFromGlobals() {
				if (
					typeof tab_results_headers_json === "undefined" ||
					typeof tab_results_csv_json === "undefined" ||
					!Array.isArray(tab_results_headers_json) ||
					!Array.isArray(tab_results_csv_json)
				) {
					console.warn("Global variables 'tab_results_headers_json' or 'tab_results_csv_json' missing or invalid.");
					return null;
				}
			
				const headers = tab_results_headers_json;
				const data = tab_results_csv_json;
			
				const col = name => headers.indexOf(name);
				const ix_trial_index = col("trial_index");
				const ix_start_time = col("start_time");
				const ix_end_time = col("end_time");
				const ix_status = col("trial_status");
			
				if ([ix_trial_index, ix_start_time, ix_end_time, ix_status].some(ix => ix === -1)) {
					console.warn("One or more needed columns missing");
					return null;
				}
			
				const traces = [];
			
				// Add dummy traces for legend
				traces.push({
					type: "scatter",
					mode: "lines",
					x: [null, null],
					y: [null, null],
					line: { color: "green", width: 4 },
					name: "COMPLETED",
					showlegend: true,
					hoverinfo: "none"
				});
				traces.push({
					type: "scatter",
					mode: "lines",
					x: [null, null],
					y: [null, null],
					line: { color: "yellow", width: 4 },
					name: "RUNNING",
					showlegend: true,
					hoverinfo: "none"
				});
				traces.push({
					type: "scatter",
					mode: "lines",
					x: [null, null],
					y: [null, null],
					line: { color: "red", width: 4 },
					name: "FAILED/OTHER",
					showlegend: true,
					hoverinfo: "none"
				});
			
				for (const row of data) {
					const trial_index = row[ix_trial_index];
					const start = row[ix_start_time];
					const end = row[ix_end_time];
					const status = row[ix_status];
			
					if (
						trial_index === "" || start === "" || end === "" ||
						isNaN(start) || isNaN(end)
					) continue;
			
					let color = "red"; // default
					if (status === "COMPLETED") color = "green";
					else if (status === "RUNNING") color = "yellow";
			
					traces.push({
						type: "scatter",
						mode: "lines",
						x: [new Date(start * 1000), new Date(end * 1000)],
						y: [trial_index, trial_index],
						line: { color: color, width: 4 },
						name: `Trial ${trial_index} (${status})`,
						showlegend: false,
						hoverinfo: "x+y+name"
					});
				}
			
				if (traces.length <= 3) { // only dummy traces added
					console.warn("No valid data for plotting found.");
					return null;
				}
			
				const layout = {
					title: "Trial Timeline",
					xaxis: {
						title: "Time",
						type: "date"
					},
					yaxis: {
						title: "Trial Index",
						autorange: "reversed"
					},
					margin: { t: 50 }
				};
			
				Plotly.newPlot('plot_timeline', traces, add_default_layout_data(layout));
				return true;
			}
			
			window.addEventListener('load', updatePreWidths);
			window.addEventListener('resize', updatePreWidths);
			
			$(document).ready(function() {
				colorize_table_entries();
			
				add_up_down_arrows_for_scrolling();
			
				add_colorize_to_gridjs_table();
			});
			
			window.addEventListener('resize', function() {
				resizePlotlyCharts();
			});
			
			"use strict";
			
			function get_row_by_index(idx) {
				if (!Object.keys(window).includes("tab_results_csv_json")) {
					error("tab_results_csv_json is not defined");
					return;
				}
			
				if (!Object.keys(window).includes("tab_results_headers_json")) {
					error("tab_results_headers_json is not defined");
					return;
				}
			
			
				var trial_index_col_idx = tab_results_headers_json.indexOf("trial_index");
			
				if(trial_index_col_idx == -1) {
					error(`"trial_index" could not be found in tab_results_headers_json. Cannot continue`);
			
					return null;
				}
			
				for (var i = 0; i < tab_results_csv_json.length; i++) {
					var row = tab_results_csv_json[i];
					var trial_index = row[trial_index_col_idx];
			
					if (trial_index == idx) {
						return row;
					}
				}
			
				return null;
			}
			
			function load_pareto_graph_from_idxs () {
				if (!Object.keys(window).includes("pareto_idxs")) {
					error("pareto_idxs is not defined");
					return;
				}
			
				if (!Object.keys(window).includes("tab_results_csv_json")) {
					error("tab_results_csv_json is not defined");
					return;
				}
			
				if (!Object.keys(window).includes("tab_results_headers_json")) {
					error("tab_results_headers_json is not defined");
					return;
				}
			
				if(pareto_idxs === null) {
					var err_msg = "pareto_idxs is null. Cannot plot or create tables from empty data. This can be caused by a defective <tt>pareto_idxs.json</tt> file. Please try reloading, or re-calculating the pareto-front and re-submitting if this problem persists.";
					$("#pareto_from_idxs_table").html(`<div class="caveat alarm">${err_msg}</div>`);
					return;	
				}
			
				var table = get_pareto_table_data_from_idx();
			
				var html_tables = createParetoTablesFromData(table);
			
				$("#pareto_from_idxs_table").html(html_tables);
			
				renderParetoFrontPlots(table);
			
				apply_theme_based_on_system_preferences();
			}
			
			function renderParetoFrontPlots(data) {
				try {
					let container = document.getElementById("pareto_front_idxs_plot_container");
					if (!container) {
						console.error("DIV with id 'pareto_front_idxs_plot_container' not found.");
						return;
					}
			
					container.innerHTML = "";
			
					if(data === undefined || data === null) {
						var err_msg = "There was an error getting the data for Pareto-Fronts. See the developer's console to see further details.";
						$("#pareto_from_idxs_table").html(`<div class="caveat alarm">${err_msg}</div>`);
						return;
					}
			
					Object.keys(data).forEach((key, idx) => {
						if (!key.startsWith("Pareto front for ")) return;
			
						let label = key.replace("Pareto front for ", "");
						let [xKey, yKey] = label.split("/");
			
						if (!xKey || !yKey) {
							console.warn("Could not extract two objectives from key:", key);
							return;
						}
			
						let entries = data[key];
						let x = [];
						let y = [];
						let hoverTexts = [];
			
						entries.forEach((entry) => {
							let results = entry.results || {};
							let values = entry.values || {};
			
							let xVal = (results[xKey] || [])[0];
							let yVal = (results[yKey] || [])[0];
			
							if (xVal === undefined || yVal === undefined) {
								console.warn("Missing values for", xKey, yKey, "in", entry);
								return;
							}
			
							x.push(xVal);
							y.push(yVal);
			
							let hoverInfo = [];
			
							if ("trial_index" in values) {
								hoverInfo.push(`<b>Trial Index:</b> ${values.trial_index[0]}`);
							}
			
							Object.keys(values)
								.filter(k => k !== "trial_index")
								.sort()
								.forEach(k => {
									hoverInfo.push(`<b>${k}:</b> ${values[k][0]}`);
								});
			
							Object.keys(results)
								.sort()
								.forEach(k => {
									hoverInfo.push(`<b>${k}:</b> ${results[k][0]}`);
								});
			
							hoverTexts.push(hoverInfo.join("<br>"));
						});
			
						let wrapper = document.createElement("div");
						wrapper.style.marginBottom = "30px";
			
						let titleEl = document.createElement("h3");
						titleEl.textContent = `Pareto Front: ${xKey} (${getMinMaxByResultName(xKey)}) vs ${yKey} (${getMinMaxByResultName(yKey)})`;
						wrapper.appendChild(titleEl);
			
						let divId = `pareto_plot_${idx}`;
						let plotDiv = document.createElement("div");
						plotDiv.id = divId;
						plotDiv.style.width = "100%";
						plotDiv.style.height = "400px";
			
						wrapper.appendChild(plotDiv);
						container.appendChild(wrapper);
			
						let trace = {
							x: x,
							y: y,
							text: hoverTexts,
							hoverinfo: "text",
							mode: "markers",
							type: "scatter",
							marker: {
								size: 8,
								color: 'rgb(31, 119, 180)',
								line: {
									width: 1,
									color: 'black'
								}
							},
							name: label
						};
			
						let layout = {
							xaxis: { title: { text: xKey } },
							yaxis: { title: { text: yKey } },
							margin: { t: 10, l: 60, r: 20, b: 50 },
							hovermode: "closest",
							showlegend: false
						};
			
						Plotly.newPlot(divId, [trace], add_default_layout_data(layout, 1));
					});
				} catch (e) {
					console.error("Error while rendering Pareto front plots:", e);
				}
			}
			
			function createParetoTablesFromData(data) {
				try {
					var container = document.createElement("div");
			
					var parsedData;
					try {
						parsedData = typeof data === "string" ? JSON.parse(data) : data;
					} catch (e) {
						console.error("JSON parsing failed:", e);
						return container;
					}
			
					for (var sectionTitle in parsedData) {
						if (!parsedData.hasOwnProperty(sectionTitle)) {
							continue;
						}
			
						var sectionData = parsedData[sectionTitle];
						var heading = document.createElement("h2");
						heading.textContent = sectionTitle;
						container.appendChild(heading);
			
						var table = document.createElement("table");
						table.style.borderCollapse = "collapse";
						table.style.marginBottom = "2em";
						table.style.width = "100%";
			
						var thead = document.createElement("thead");
						var headerRow = document.createElement("tr");
			
						var allValueKeys = new Set();
						var allResultKeys = new Set();
			
						sectionData.forEach(entry => {
							var values = entry.values || {};
							var results = entry.results || {};
			
							Object.keys(values).forEach(key => {
								allValueKeys.add(key);
							});
			
							Object.keys(results).forEach(key => {
								allResultKeys.add(key);
							});
						});
			
						var sortedValueKeys = Array.from(allValueKeys).sort();
						var sortedResultKeys = Array.from(allResultKeys).sort();
			
						if (sortedValueKeys.includes("trial_index")) {
							sortedValueKeys = sortedValueKeys.filter(k => k !== "trial_index");
							sortedValueKeys.unshift("trial_index");
						}
			
						var allColumns = [...sortedValueKeys, ...sortedResultKeys];
			
						allColumns.forEach(col => {
							var th = document.createElement("th");
							th.textContent = col;
							th.style.border = "1px solid black";
							th.style.padding = "4px";
							headerRow.appendChild(th);
						});
			
						thead.appendChild(headerRow);
						table.appendChild(thead);
			
						var tbody = document.createElement("tbody");
			
						sectionData.forEach(entry => {
							var tr = document.createElement("tr");
			
							allColumns.forEach(col => {
								var td = document.createElement("td");
								td.style.border = "1px solid black";
								td.style.padding = "4px";
			
								var value = null;
			
								if (col in entry.values) {
									value = entry.values[col];
								} else if (col in entry.results) {
									value = entry.results[col];
								}
			
								if (Array.isArray(value)) {
									td.textContent = value.join(", ");
								} else {
									td.textContent = value !== null && value !== undefined ? value : "";
								}
			
								tr.appendChild(td);
							});
			
							tbody.appendChild(tr);
						});
			
						table.appendChild(tbody);
						container.appendChild(table);
					}
			
					return container;
				} catch (err) {
					console.error("Unexpected error:", err);
					var errorDiv = document.createElement("div");
					errorDiv.textContent = "Error generating tables.";
					return errorDiv;
				}
			}
			
			function get_pareto_table_data_from_idx () {
				if (!Object.keys(window).includes("pareto_idxs")) {
					error("pareto_idxs is not defined");
					return;
				}
			
				if (!Object.keys(window).includes("tab_results_csv_json")) {
					error("tab_results_csv_json is not defined");
					return;
				}
			
				if (!Object.keys(window).includes("tab_results_headers_json")) {
					error("tab_results_headers_json is not defined");
					return;
				}
			
				var x_keys = Object.keys(pareto_idxs);
			
				var tables = {};
			
				for (var i = 0; i < x_keys.length; i++) {
					var x_key = x_keys[i];
					var y_keys = Object.keys(pareto_idxs[x_key]);
			
					for (var j = 0; j < y_keys.length; j++) {
						var y_key = y_keys[j];
			
						var indices = pareto_idxs[x_key][y_key];
			
						for (var k = 0; k < indices.length; k++) {
							var idx = indices[k];
							var row = get_row_by_index(idx);
			
							if(row === null) {
								error(`Error getting the row for index ${idx}`);
								return;
							}
			
							var row_dict = {
								"results": {},
								"values": {},
							};
			
							for (var l = 0; l < tab_results_headers_json.length; l++) {
								var header = tab_results_headers_json[l];
			
								if (!special_col_names.includes(header) || header == "trial_index") {
									var val = row[l];
			
									if (result_names.includes(header)) {
										if (!Object.keys(row_dict["results"]).includes(header)) {
											row_dict["results"][header] = [];
										}
			
										row_dict["results"][header].push(val);
									} else {
										if (!Object.keys(row_dict["values"]).includes(header)) {
											row_dict["values"][header] = [];
										}
										row_dict["values"][header].push(val);
									}
								}
								
							}
			
							var table_key = `Pareto front for ${x_key}/${y_key}`;
			
							if(!Object.keys(tables).includes(table_key)) {
								tables[table_key] = [];
							}
			
							tables[table_key].push(row_dict);
						}
			
					}
				}
			
				return tables;
			}
			
			function getMinMaxByResultName(resultName) {
				try {
					if (typeof resultName !== "string") {
						error("Parameter resultName must be a string");
						return;
					}
			
					if (!Array.isArray(result_names)) {
						error("Global variable result_names is not an array or undefined");
						return;
					}
					if (!Array.isArray(result_min_max)) {
						error("Global variable result_min_max is not an array or undefined");
						return;
					}
			
					if (result_names.length !== result_min_max.length) {
						error("Global arrays result_names and result_min_max must have the same length");
						return;
					}
			
					var index = result_names.indexOf(resultName);
					if (index === -1) {
						error("Result name '" + resultName + "' not found in result_names");
						return;
					}
			
					var minMaxValue = result_min_max[index];
			
					if (minMaxValue !== "min" && minMaxValue !== "max") {
						error("Value for result name '" + resultName + "' is invalid: expected 'min' or 'max'");
						return;
					}
			
					return minMaxValue;
			
				} catch (e) {
					error("Unexpected error: " + e.message);
				}
			}
			

			$(document).ready(function() {
				colorize_table_entries();;
				plotWorkerUsage();;
				plotCPUAndRAMUsage();;
				createParallelPlot(tab_results_csv_json, tab_results_headers_json, result_names, special_col_names);;
				plotScatter2d();;
				plotScatter3d();
				plotJobStatusDistribution();;
				plotBoxplot();;
				plotViolin();;
				plotHistogram();;
				plotHeatmap();;
				plotResultPairs();

				colorize_table_entries();
			});
		</script>

					<h1>&nbsp;Overview</h1>
			<h2>Experiment overview:              </h2><table cellspacing="0" cellpadding="5"><thead><tr><th> Setting</th><th>Value           </th></tr></thead><tbody><tr><td> Model for non-random steps</td><td>BOTORCH_MODULAR </td></tr><tr><td> Max. nr. evaluations</td><td>500             </td></tr><tr><td> Number random steps</td><td>20              </td></tr><tr><td> Nr. of workers (parameter)</td><td>30              </td></tr><tr><td> Main process memory (GB)</td><td>8               </td></tr><tr><td> Worker memory (GB)</td><td>32              </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><th>Log Scale? </th></tr></thead><tbody><tr><td> recent_samples_size</td><td>range</td><td>1</td><td>5000</td><td></td><td>int</td><td>No         </td></tr><tr><td> feature_id</td><td>fixed</td><td></td><td></td><td>0</td><td></td><td></td></tr><tr><td> batch_size</td><td>range</td><td>1</td><td>5000</td><td></td><td>int</td><td>No         </td></tr><tr><td> divergence</td><td>choice</td><td></td><td></td><td>str\(\&#039;H\&#039;\), str\(\&#039;KL\&#039;\)</td><td></td><td></td></tr><tr><td> detect_batch</td><td>choice</td><td></td><td></td><td>1, 2, 3</td><td></td><td></td></tr><tr><td> statistic</td><td>choice</td><td></td><td></td><td>str\(\&#039;stdev\&#039;\), str\(\&#039;tstat\&#039;\)</td><td></td><td></td></tr><tr><td> significance</td><td>range</td><td>0.001</td><td>0.999</td><td></td><td>float</td><td>No         </td></tr><tr><td> subsets</td><td>range</td><td>1</td><td>100</td><td></td><td>int</td><td>No         </td></tr></tbody></table><h2>Number of evaluations</h2>
			<table>
			<tbody>
			<tr>
			<th>Failed</th>
			<th>Succeeded</th>
			<th>Running</th>
			<th>Total</th>
			</tr>
			<tr>
			<td>124</td>
			<td>380</td>
			<td>6</td>
			<td>510</td>
			</tr>
			</tbody>
			</table>
			<h2>Result names and types</h2>
			<table>
			<tr><th>name</th><th>min/max</th></tr>
			<tr>
			<td>ACCURACY</td>
			<td>max</td>
			</tr>
			<tr>
			<td>RUNTIME</td>
			<td>min</td>
			</tr>
			</table>
			
			<h1>&nbsp;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 &raquo;results.csv&laquo; as file</button>
<pre id='tab_results_csv_table_pre'>trial_index,arm_name,trial_status,generation_method,generation_node,ACCURACY,RUNTIME,recent_samples_size,batch_size,divergence,detect_batch,statistic,significance,subsets,feature_id
0,0_0,COMPLETED,Sobol,GenerationStep_0,0.220000000000000001110223024625,6.000000000000000000000000000000,3789,923,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.752555112481117283174114618305,87,0
1,1_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,4.000000000000000000000000000000,130,2806,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.025486885808408261261392979691,20,0
2,2_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,4.000000000000000000000000000000,2413,1620,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.495146428098902080527921043540,67,0
3,3_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,5.000000000000000000000000000000,3688,4728,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.719502532161772290209000857431,28,0
4,4_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,6.000000000000000000000000000000,2898,2267,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.926435357747599441680108611763,53,0
5,5_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,4.000000000000000000000000000000,1623,4159,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.172253185331821434544963267399,43,0
6,6_0,COMPLETED,Sobol,GenerationStep_0,0.289999999999999980015985556747,25.000000000000000000000000000000,902,189,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.326200210643932231313613101520,95,0
7,7_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,4.000000000000000000000000000000,4561,3307,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.585345293477177675001144052658,11,0
8,8_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,6.000000000000000000000000000000,4850,1493,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.675575489090755598731163900084,62,0
9,9_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,5.000000000000000000000000000000,1233,4620,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.420187742445617906650312534111,44,0
10,10_0,COMPLETED,Sobol,GenerationStep_0,0.209999999999999992228438827624,6.000000000000000000000000000000,1293,972,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.075074799003079534243099146806,92,0
11,11_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,5.000000000000000000000000000000,2606,2835,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.833547297108918394670240559208,3,0
12,12_0,COMPLETED,Sobol,GenerationStep_0,0.250000000000000000000000000000,9.000000000000000000000000000000,3398,453,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.502494795927777904154254429159,78,0
13,13_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,4.000000000000000000000000000000,2085,3590,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.274571229469031119485578074091,17,0
14,14_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,7.000000000000000000000000000000,461,2081,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.245292644048109659271617033482,70,0
15,15_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,4.000000000000000000000000000000,4078,3953,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.968382245924323759034280101332,37,0
16,16_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,4.000000000000000000000000000000,4227,1993,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.292192595375701802407064633371,23,0
17,17_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,4.000000000000000000000000000000,611,3885,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.547736192002892474661734922847,84,0
18,18_0,COMPLETED,Sobol,GenerationStep_0,0.289999999999999980015985556747,7.000000000000000000000000000000,1916,541,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.955021648881956952692462436971,31,0
19,19_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,4.000000000000000000000000000000,3229,3659,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.196765913844108575325719812099,64,0
20,20_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,5.000000000000000000000000000000,2770,1197,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.402959261110052480159282595196,39,0
21,21_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,5.000000000000000000000000000000,1457,3080,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.630916851378977350250920608232,57,0
22,22_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,5.000000000000000000000000000000,1089,1269,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.847239776408299838372784051899,9,0
23,23_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,4.000000000000000000000000000000,4705,4377,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.124245111428201202019572235713,98,0
24,24_0,COMPLETED,Sobol,GenerationStep_0,0.289999999999999980015985556747,7.000000000000000000000000000000,4412,101,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.154757685029879216154213850132,48,0
25,25_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,4.000000000000000000000000000000,753,3239,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.882042675700038691921633926540,58,0
26,26_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,4.000000000000000000000000000000,1791,2354,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.599303743312135317466982087353,6,0
27,27_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,4.000000000000000000000000000000,3066,4227,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.375103489231318254493174890740,90,0
28,28_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,4.000000000000000000000000000000,3525,1845,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.043313413264229896904033978444,14,0
29,29_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,7.000000000000000000000000000000,2250,4972,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.797590522576123506226508652617,81,0
30,30_0,FAILED,BoTorch,GenerationStep_1,,,4209,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.817970498535672274620367261377,1,0
31,31_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,0
32,32_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,5000,151,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,34,0
33,33_0,FAILED,BoTorch,GenerationStep_1,,,2045,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,0
34,34_0,FAILED,BoTorch,GenerationStep_1,,,4992,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,0
35,35_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,0
36,36_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,0
37,37_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,5000,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,38,0
38,38_0,FAILED,BoTorch,GenerationStep_1,,,2426,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,0
39,39_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,1,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,0
40,40_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,3256,2541,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,52,0
41,41_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,1,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,0
42,42_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,0
43,43_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,9.000000000000000000000000000000,1,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,0
44,44_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,100,0
45,45_0,COMPLETED,BoTorch,GenerationStep_1,0.320000000000000006661338147751,8.000000000000000000000000000000,5000,406,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,0
46,46_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,24,0
47,47_0,FAILED,BoTorch,GenerationStep_1,,,1874,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,0
48,48_0,FAILED,BoTorch,GenerationStep_1,,,3528,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,0
49,49_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,1,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,31,0
50,50_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,37,0
51,51_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,100,0
52,52_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,0
53,53_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,0
54,54_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,2803,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,0
55,55_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,1,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,0
56,56_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,5000,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,10,0
57,57_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,1,5000,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,47,0
58,58_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,0
59,59_0,FAILED,BoTorch,GenerationStep_1,,,2379,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,43,0
60,35_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,0
61,61_0,COMPLETED,BoTorch,GenerationStep_1,0.320000000000000006661338147751,8.000000000000000000000000000000,1,287,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,0
62,62_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,8.000000000000000000000000000000,414,3834,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,0
63,63_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,8.000000000000000000000000000000,5000,3832,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,0
64,64_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,11.000000000000000000000000000000,5000,3641,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,0
65,65_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,100,0
66,66_0,COMPLETED,BoTorch,GenerationStep_1,0.320000000000000006661338147751,8.000000000000000000000000000000,1,430,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,0
67,67_0,COMPLETED,BoTorch,GenerationStep_1,0.330000000000000015543122344752,8.000000000000000000000000000000,1,152,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,0
68,68_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,1,2398,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,100,0
69,69_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,11.000000000000000000000000000000,1,3966,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,0
70,70_0,FAILED,BoTorch,GenerationStep_1,,,4673,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,100,0
71,71_0,FAILED,BoTorch,GenerationStep_1,,,4054,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,0
72,72_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,5000,5000,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,0
73,73_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,9.000000000000000000000000000000,1,3673,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,0
74,74_0,COMPLETED,BoTorch,GenerationStep_1,0.320000000000000006661338147751,9.000000000000000000000000000000,1599,394,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,0
75,75_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,1,5000,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,0
76,76_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,11.000000000000000000000000000000,5000,3373,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,100,0
77,77_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,5000,5000,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,100,0
78,78_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,10.000000000000000000000000000000,1,385,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,100,0
79,79_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,11.000000000000000000000000000000,5000,4033,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,100,0
80,80_0,COMPLETED,BoTorch,GenerationStep_1,0.330000000000000015543122344752,8.000000000000000000000000000000,1,94,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,0
81,81_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,1,5000,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,0
82,82_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,8.000000000000000000000000000000,5000,3967,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,0
83,36_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,0
84,84_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,5.000000000000000000000000000000,5000,2212,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,100,0
85,85_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,1,5000,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,0
86,86_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,5000,5000,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,0
87,87_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,8.000000000000000000000000000000,1,4005,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,0
88,88_0,COMPLETED,BoTorch,GenerationStep_1,0.320000000000000006661338147751,8.000000000000000000000000000000,1,236,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,0
89,89_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,8.000000000000000000000000000000,5000,3655,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,0
90,90_0,COMPLETED,BoTorch,GenerationStep_1,0.299999999999999988897769753748,6.000000000000000000000000000000,5000,132,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,33,0
91,91_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,4594,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,0
92,92_0,COMPLETED,BoTorch,GenerationStep_1,0.289999999999999980015985556747,7.000000000000000000000000000000,5000,569,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,50,0
93,93_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,80.000000000000000000000000000000,5000,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,34,0
94,94_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,9.000000000000000000000000000000,2646,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.076943198987400845956230455158,1,0
95,95_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,504,2919,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.187141124452428891933308818807,1,0
96,96_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,1,3006,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,62,0
97,97_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,4495,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,0
98,98_0,FAILED,BoTorch,GenerationStep_1,,,4986,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,8,0
99,99_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,5.000000000000000000000000000000,3707,1398,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.434520758976058740774561783837,46,0
100,100_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,58,0
101,101_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,2337,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.631792369471782744305698997778,48,0
102,102_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,3389,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,0
103,103_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,5.000000000000000000000000000000,1,2153,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,0
104,104_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,1,2792,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,100,0
105,105_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,22,0
106,106_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,10.000000000000000000000000000000,5000,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,6,0
107,107_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,1,2998,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,0
108,108_0,COMPLETED,BoTorch,GenerationStep_1,0.289999999999999980015985556747,6.000000000000000000000000000000,3335,444,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.041132239094725693562271118253,1,0
109,109_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,1,3367,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,0
110,110_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.377230004580438094130556692107,1,0
111,111_0,COMPLETED,BoTorch,GenerationStep_1,0.260000000000000008881784197001,6.000000000000000000000000000000,4268,821,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,29,0
112,112_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,1,5000,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,100,0
113,113_0,COMPLETED,BoTorch,GenerationStep_1,0.289999999999999980015985556747,6.000000000000000000000000000000,5000,463,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,0
114,114_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,75,0
115,115_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,10.000000000000000000000000000000,5000,2713,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,100,0
116,116_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,2705,3032,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,100,0
117,117_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,505,3071,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,100,0
118,118_0,FAILED,BoTorch,GenerationStep_1,,,4293,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,52,0
119,119_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,9.000000000000000000000000000000,3665,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,0
120,120_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,1835,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.392735652127909784514514512921,71,0
121,121_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,6.000000000000000000000000000000,19,1557,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,15,0
122,122_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,460,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.601976302108747529651111562998,100,0
123,123_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,984.000000000000000000000000000000,4916,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,69,0
124,124_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,5.000000000000000000000000000000,5000,2529,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,22,0
125,125_0,FAILED,BoTorch,GenerationStep_1,,,406,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,78,0
126,126_0,COMPLETED,BoTorch,GenerationStep_1,0.289999999999999980015985556747,7.000000000000000000000000000000,2179,100,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,39,0
127,127_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,2674,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,87,0
128,128_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,6.000000000000000000000000000000,1733,1952,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,17,0
129,129_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,6.000000000000000000000000000000,3497,1170,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,14,0
130,130_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,6.000000000000000000000000000000,553,2410,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,73,0
131,131_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,5.000000000000000000000000000000,457,2685,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,26,0
132,132_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,9.000000000000000000000000000000,2136,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.304689093440618286035004302903,63,0
133,133_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,1057,5000,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,69,0
134,134_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,350,5000,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,24,0
135,135_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,743,5000,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,12,0
136,136_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,5.000000000000000000000000000000,1227,269,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,11,0
137,137_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,5.000000000000000000000000000000,3954,559,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,39,0
138,138_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,1,4888,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,82,0
139,139_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,4814,2422,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,84,0
140,140_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,5000,5000,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,55,0
141,141_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,9.000000000000000000000000000000,1736,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,77,0
142,142_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,6.000000000000000000000000000000,292,1066,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,7,0
143,143_0,FAILED,BoTorch,GenerationStep_1,,,3337,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,85,0
144,144_0,COMPLETED,BoTorch,GenerationStep_1,0.299999999999999988897769753748,31.000000000000000000000000000000,1424,65,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,70,0
145,145_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,5.000000000000000000000000000000,1613,2213,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,17,0
146,146_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,9.000000000000000000000000000000,1,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,94,0
147,147_0,COMPLETED,BoTorch,GenerationStep_1,0.260000000000000008881784197001,5.000000000000000000000000000000,526,351,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.822733461625728690336245563230,65,0
148,148_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,5.000000000000000000000000000000,198,854,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.992867848478255599076192083885,52,0
149,149_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,1,5000,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,58,0
150,150_0,COMPLETED,BoTorch,GenerationStep_1,0.299999999999999988897769753748,145.000000000000000000000000000000,3818,14,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.471771171834201863415358957354,90,0
151,151_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,4991,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.279951056107412943330103871631,1,0
152,152_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,9.000000000000000000000000000000,136,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.639527065160938157362124911742,1,0
153,153_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,4945,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.358861660434548979115021438702,1,0
154,154_0,COMPLETED,BoTorch,GenerationStep_1,0.330000000000000015543122344752,9.000000000000000000000000000000,1467,10,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.461105777714978737336082303955,1,0
155,155_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,11.000000000000000000000000000000,4843,608,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.467084473659214516327864430423,100,0
156,156_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,4053,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.958669595901609272736720868124,1,0
157,157_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,358.000000000000000000000000000000,54,11,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.505399963224366310932111900911,94,0
158,158_0,FAILED,BoTorch,GenerationStep_1,,,1837,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,100,0
159,159_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,224.000000000000000000000000000000,764,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,47,0
160,160_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,4072,3216,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.399338428969065295515150637584,100,0
161,161_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,162,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.673909001734989465681735509861,1,0
162,162_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,3218.000000000000000000000000000000,316,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,93,0
163,163_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,18.000000000000000000000000000000,2332,38,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.474644506572996505155970226042,55,0
164,164_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,6.000000000000000000000000000000,1531,1058,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.239647962486423421468728633954,1,0
165,165_0,FAILED,BoTorch,GenerationStep_1,,,2995,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.758750346824324961580998660793,1,0
166,166_0,COMPLETED,BoTorch,GenerationStep_1,0.280000000000000026645352591004,24.000000000000000000000000000000,3237,298,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.503155838381946107773501353222,100,0
167,167_0,COMPLETED,BoTorch,GenerationStep_1,0.330000000000000015543122344752,9.000000000000000000000000000000,2535,13,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.299031971553421982434883830138,1,0
168,168_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,10.000000000000000000000000000000,1955,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.440310983991490212385855329558,1,0
169,169_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,5.000000000000000000000000000000,1318,83,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.713291857342434498789884855796,27,0
170,170_0,FAILED,BoTorch,GenerationStep_1,,,3612,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.557873599293076005700697805878,26,0
171,171_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,6.000000000000000000000000000000,238,15,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.307068670407019184143138090803,4,0
172,172_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,2035,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.313643203967865658032820874723,32,0
173,173_0,FAILED,BoTorch,GenerationStep_1,,,4180,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.781148274004885623256200233300,92,0
174,174_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,10.000000000000000000000000000000,182,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.817455496803562331464831913763,1,0
175,175_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,11.000000000000000000000000000000,4483,286,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.299085531614031174818535419035,100,0
176,176_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,6.000000000000000000000000000000,2574,69,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.678478812141935616608634518343,29,0
177,177_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,7.000000000000000000000000000000,1232,4,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.258427762862882992589419473006,78,0
178,178_0,COMPLETED,BoTorch,GenerationStep_1,0.320000000000000006661338147751,8.000000000000000000000000000000,264,290,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.462505829297601700478281827600,1,0
179,179_0,FAILED,BoTorch,GenerationStep_1,,,2925,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.593951394775540153503357032605,100,0
180,180_0,COMPLETED,BoTorch,GenerationStep_1,0.289999999999999980015985556747,5.000000000000000000000000000000,916,189,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.053672231637908920931501199902,94,0
181,181_0,COMPLETED,BoTorch,GenerationStep_1,0.280000000000000026645352591004,7.000000000000000000000000000000,504,408,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.452475976824663228548217830394,48,0
182,182_0,COMPLETED,BoTorch,GenerationStep_1,0.299999999999999988897769753748,5.000000000000000000000000000000,400,172,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.170213676642365169255910473112,72,0
183,183_0,COMPLETED,BoTorch,GenerationStep_1,0.299999999999999988897769753748,5.000000000000000000000000000000,4595,126,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.085230585690284854649689805228,93,0
184,184_0,COMPLETED,BoTorch,GenerationStep_1,0.270000000000000017763568394003,5.000000000000000000000000000000,2271,146,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.085684067853014439508640975873,31,0
185,185_0,COMPLETED,BoTorch,GenerationStep_1,0.250000000000000000000000000000,5.000000000000000000000000000000,1235,196,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.079286917710023593897084026594,10,0
186,186_0,COMPLETED,BoTorch,GenerationStep_1,0.289999999999999980015985556747,5.000000000000000000000000000000,506,177,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.385365269962490986088710087643,47,0
187,187_0,COMPLETED,BoTorch,GenerationStep_1,0.289999999999999980015985556747,5.000000000000000000000000000000,1106,227,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.227374741495245696887295139277,51,0
188,188_0,COMPLETED,BoTorch,GenerationStep_1,0.280000000000000026645352591004,7.000000000000000000000000000000,4696,405,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.475627901776341954764859565330,21,0
189,189_0,COMPLETED,BoTorch,GenerationStep_1,0.289999999999999980015985556747,5.000000000000000000000000000000,1177,115,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.047988669003473378993351872168,77,0
190,190_0,COMPLETED,BoTorch,GenerationStep_1,0.280000000000000026645352591004,5.000000000000000000000000000000,1896,116,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,52,0
191,191_0,COMPLETED,BoTorch,GenerationStep_1,0.280000000000000026645352591004,6.000000000000000000000000000000,4803,406,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.861611395963166604161642680992,17,0
192,192_0,COMPLETED,BoTorch,GenerationStep_1,0.289999999999999980015985556747,5.000000000000000000000000000000,2677,149,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.369720258367998988457969744559,34,0
193,193_0,FAILED,BoTorch,GenerationStep_1,,,227,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,20,0
194,194_0,COMPLETED,BoTorch,GenerationStep_1,0.299999999999999988897769753748,5.000000000000000000000000000000,103,50,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.035929144042389518642899304268,83,0
195,195_0,COMPLETED,BoTorch,GenerationStep_1,0.280000000000000026645352591004,63.000000000000000000000000000000,2949,16,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,86,0
196,196_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,9.000000000000000000000000000000,2100,684,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,95,0
197,197_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,5.000000000000000000000000000000,820,20,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.324598512246576931250530151374,76,0
198,198_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,5.000000000000000000000000000000,1420,56,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.058620199606248854506951317944,48,0
199,199_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,1290,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,74,0
200,200_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,4631,1057,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,23,0
201,201_0,COMPLETED,BoTorch,GenerationStep_1,0.250000000000000000000000000000,5.000000000000000000000000000000,4476,179,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,8,0
202,202_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,6.000000000000000000000000000000,3259,1063,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,70,0
203,203_0,FAILED,BoTorch,GenerationStep_1,,,116,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,93,0
204,204_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,5.000000000000000000000000000000,746,101,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.900279244893964047946610662621,16,0
205,205_0,COMPLETED,BoTorch,GenerationStep_1,0.280000000000000026645352591004,19.000000000000000000000000000000,2841,680,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,93,0
206,206_0,COMPLETED,BoTorch,GenerationStep_1,0.289999999999999980015985556747,5.000000000000000000000000000000,211,250,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.382916465249165560713606737409,69,0
207,207_0,COMPLETED,BoTorch,GenerationStep_1,0.289999999999999980015985556747,6.000000000000000000000000000000,102,62,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.888301083342663666542193823261,13,0
208,208_0,COMPLETED,BoTorch,GenerationStep_1,0.289999999999999980015985556747,5.000000000000000000000000000000,2274,218,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.431236280571560826047061709687,23,0
209,209_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,4227,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,83,0
210,210_0,COMPLETED,BoTorch,GenerationStep_1,0.299999999999999988897769753748,5.000000000000000000000000000000,638,88,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,26,0
211,211_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,5.000000000000000000000000000000,1458,572,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,30,0
212,212_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,5.000000000000000000000000000000,1007,2849,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,55,0
213,213_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,100,0
214,214_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,6.000000000000000000000000000000,4295,961,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,32,0
215,215_0,COMPLETED,BoTorch,GenerationStep_1,0.260000000000000008881784197001,6.000000000000000000000000000000,1319,377,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,27,0
216,216_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.695656408354446975650375861733,1,0
217,217_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,7.000000000000000000000000000000,260,35,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.232961731823171480648682063475,30,0
218,218_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,13,3247,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,65,0
219,219_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,0
220,220_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,5.000000000000000000000000000000,4849,2357,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,46,0
221,221_0,COMPLETED,BoTorch,GenerationStep_1,0.280000000000000026645352591004,9.000000000000000000000000000000,794,104,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.727107063291117294845378182799,52,0
222,222_0,COMPLETED,BoTorch,GenerationStep_1,0.270000000000000017763568394003,24.000000000000000000000000000000,1511,139,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.159394122560123113752084123007,95,0
223,223_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,5.000000000000000000000000000000,362,1152,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,34,0
224,224_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,6.000000000000000000000000000000,558,81,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.901885126888456567506580086047,34,0
225,225_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,6.000000000000000000000000000000,3259,2483,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.463687280425557291074767363170,62,0
226,226_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,5.000000000000000000000000000000,1275,774,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,30,0
227,227_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,5.000000000000000000000000000000,4321,3478,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,72,0
228,228_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,31.000000000000000000000000000000,4194,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,25,0
229,229_0,FAILED,BoTorch,GenerationStep_1,,,3723,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.880921229656787985184962508356,100,0
230,230_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,6.000000000000000000000000000000,2577,942,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.489825622284360273628323056982,51,0
231,231_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,11.000000000000000000000000000000,4714,2956,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.650324417728416981354655490577,100,0
232,232_0,COMPLETED,BoTorch,GenerationStep_1,0.299999999999999988897769753748,6.000000000000000000000000000000,1702,14,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.954378277094710014694101118948,24,0
233,233_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,11.000000000000000000000000000000,4842,4907,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.353072574295450525294626231698,100,0
234,234_0,COMPLETED,BoTorch,GenerationStep_1,0.289999999999999980015985556747,6.000000000000000000000000000000,1089,240,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,28,0
235,235_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,10.000000000000000000000000000000,4339,4218,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.467407171884286543050990303527,100,0
236,236_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,5.000000000000000000000000000000,2805,183,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.666299687028531595345270943653,39,0
237,237_0,COMPLETED,BoTorch,GenerationStep_1,0.280000000000000026645352591004,25.000000000000000000000000000000,3729,87,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.252293833042468940153213452504,73,0
238,238_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,26.000000000000000000000000000000,1101,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,22,0
239,239_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,5.000000000000000000000000000000,2518,503,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.277470330084397975856091989044,49,0
240,240_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,17.000000000000000000000000000000,2825,82,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,65,0
241,241_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,35.000000000000000000000000000000,634,33,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.631324596088847722619163960189,69,0
242,242_0,COMPLETED,BoTorch,GenerationStep_1,0.289999999999999980015985556747,37.000000000000000000000000000000,3762,24,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.566011086661550089083050352201,67,0
243,243_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,152.000000000000000000000000000000,436,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.400514968399403814558468184259,42,0
244,244_0,RUNNING,BoTorch,GenerationStep_1,,,146,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,100,0
245,245_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,6.000000000000000000000000000000,1030,33,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.347921772237949400441436864639,15,0
246,246_0,FAILED,BoTorch,GenerationStep_1,,,54,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.312182606081352231885972514647,62,0
247,247_0,FAILED,BoTorch,GenerationStep_1,,,688,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,57,0
248,248_0,COMPLETED,BoTorch,GenerationStep_1,0.299999999999999988897769753748,8.000000000000000000000000000000,1599,31,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.289926911089947170196978731838,32,0
249,249_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,11.000000000000000000000000000000,1232,73,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.726211007832926913607707319898,70,0
250,250_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,19.000000000000000000000000000000,4965,77,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.872843444045444005752187877079,67,0
251,251_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,7.000000000000000000000000000000,4382,58,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,83,0
252,252_0,COMPLETED,BoTorch,GenerationStep_1,0.250000000000000000000000000000,8.000000000000000000000000000000,3813,260,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.473163792527433735290998129130,63,0
253,253_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,7.000000000000000000000000000000,437,226,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.328277884155798060916708891455,61,0
254,254_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,20.000000000000000000000000000000,4454,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,21,0
255,255_0,FAILED,BoTorch,GenerationStep_1,,,75,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,0
256,256_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,845.000000000000000000000000000000,3424,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,66,0
257,257_0,FAILED,BoTorch,GenerationStep_1,,,3784,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.778413862083676466596671161824,66,0
258,258_0,FAILED,BoTorch,GenerationStep_1,,,3442,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,100,0
259,259_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,1279,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.547296248348521863213989036012,11,0
260,260_0,COMPLETED,BoTorch,GenerationStep_1,0.270000000000000017763568394003,6.000000000000000000000000000000,4947,141,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.216125147570116277195850784665,20,0
261,261_0,FAILED,BoTorch,GenerationStep_1,,,316,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,50,0
262,262_0,COMPLETED,BoTorch,GenerationStep_1,0.250000000000000000000000000000,26.000000000000000000000000000000,316,114,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,89,0
263,263_0,COMPLETED,BoTorch,GenerationStep_1,0.270000000000000017763568394003,7.000000000000000000000000000000,2116,420,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,65,0
264,264_0,FAILED,BoTorch,GenerationStep_1,,,112,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.816611428958079255124857809278,1,0
265,265_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,5.000000000000000000000000000000,1531,37,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.477376398211201535826120334605,15,0
266,266_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,30.000000000000000000000000000000,560,49,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.768160504530043475313050294062,69,0
267,267_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,1266,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.459902178453173771099926625539,91,0
268,268_0,FAILED,BoTorch,GenerationStep_1,,,4310,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.209937522986656688317452790216,23,0
269,269_0,COMPLETED,BoTorch,GenerationStep_1,0.299999999999999988897769753748,5.000000000000000000000000000000,4626,109,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.325628215504493057075308115600,100,0
270,270_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,9.000000000000000000000000000000,1240,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,0
271,271_0,FAILED,BoTorch,GenerationStep_1,,,906,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.363611961148870843629765658989,100,0
272,272_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,9.000000000000000000000000000000,1496,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,64,0
273,273_0,FAILED,BoTorch,GenerationStep_1,,,4545,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.197803300226918832294131789240,100,0
274,274_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,56.000000000000000000000000000000,1786,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.811114037914740237944499767764,28,0
275,275_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,109.000000000000000000000000000000,3736,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.065212025876501697463361040263,38,0
276,276_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,39.000000000000000000000000000000,1,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,26,0
277,219_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,0
278,278_0,FAILED,BoTorch,GenerationStep_1,,,1533,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.448713901571537954193757968824,100,0
279,279_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,2356,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,45,0
280,280_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,617,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.713998424437527923203106183792,58,0
281,281_0,COMPLETED,BoTorch,GenerationStep_1,0.330000000000000015543122344752,10.000000000000000000000000000000,4777,9,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.629629926017700514151442803268,1,0
282,282_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,65.000000000000000000000000000000,3876,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,29,0
283,283_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,7.000000000000000000000000000000,127,39,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.545360777384448769389280187170,1,0
284,284_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,100,0
285,285_0,COMPLETED,BoTorch,GenerationStep_1,0.320000000000000006661338147751,123.000000000000000000000000000000,2129,3,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.659698864858789257858973087423,44,0
286,286_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,67.000000000000000000000000000000,573,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.545020045660146057464601199172,32,0
287,287_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,200.000000000000000000000000000000,612,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.273105701935475231323380285176,45,0
288,288_0,FAILED,BoTorch,GenerationStep_1,,,2041,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,70,0
289,289_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,13.000000000000000000000000000000,1,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,13,0
290,290_0,COMPLETED,BoTorch,GenerationStep_1,0.270000000000000017763568394003,9.000000000000000000000000000000,599,145,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,57,0
291,291_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,125.000000000000000000000000000000,4224,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,39,0
292,292_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,18.000000000000000000000000000000,1261,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,17,0
293,293_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,6.000000000000000000000000000000,2273,37,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.883820970997935884128082761890,53,0
294,294_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,9.000000000000000000000000000000,4753,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,74,0
295,295_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,2745.000000000000000000000000000000,4590,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,90,0
296,296_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,22.000000000000000000000000000000,2176,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.515749930961107549975963593170,20,0
297,297_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,7.000000000000000000000000000000,3552,104,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.731464318219737563708804373164,36,0
298,298_0,COMPLETED,BoTorch,GenerationStep_1,0.320000000000000006661338147751,53.000000000000000000000000000000,1476,2,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.579355205604045853107209040900,31,0
299,299_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,206.000000000000000000000000000000,4734,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.600452115884906878484628123260,45,0
300,300_0,COMPLETED,BoTorch,GenerationStep_1,0.299999999999999988897769753748,26.000000000000000000000000000000,1231,41,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.477188925212471359849075724924,67,0
301,301_0,FAILED,BoTorch,GenerationStep_1,,,1293,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,18,0
302,302_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,2134,4839,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.363190718403187617902005968062,100,0
303,219_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,0
304,304_0,FAILED,BoTorch,GenerationStep_1,,,2108,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,69,0
305,305_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,1300,4192,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.763515757114540893901732943050,31,0
306,306_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,8.000000000000000000000000000000,3867,5000,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,0
307,307_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,0
308,308_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,440,3853,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.462302754097468737715104225572,1,0
309,309_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,10.000000000000000000000000000000,1345,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,100,0
310,310_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,3077,5000,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.461609427480967893231422749523,100,0
311,311_0,COMPLETED,BoTorch,GenerationStep_1,0.299999999999999988897769753748,5.000000000000000000000000000000,2106,7,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.733145143272094235165070585936,85,0
312,312_0,FAILED,BoTorch,GenerationStep_1,,,3519,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,52,0
313,313_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,5.000000000000000000000000000000,4418,39,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.764133029017722398279488515982,27,0
314,314_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,4492,3286,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.715182219301570554215174979618,33,0
315,315_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,4586,5000,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,0
316,316_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,9.000000000000000000000000000000,4583,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,23,0
317,317_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,9.000000000000000000000000000000,434,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,100,0
318,318_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,5.000000000000000000000000000000,2019,5000,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,14,0
319,319_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,4185,5000,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,27,0
320,320_0,COMPLETED,BoTorch,GenerationStep_1,0.280000000000000026645352591004,9.000000000000000000000000000000,4125,311,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.461732418560638069315871234721,67,0
321,321_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,936,4916,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.421535344187127791748537219974,89,0
322,322_0,FAILED,BoTorch,GenerationStep_1,,,36,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,61,0
323,323_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,4443,5000,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.835247632289708219488488794013,29,0
324,324_0,COMPLETED,BoTorch,GenerationStep_1,0.299999999999999988897769753748,5.000000000000000000000000000000,4763,97,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.733968860528253941311049857177,100,0
325,325_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,8.000000000000000000000000000000,4873,4016,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.477409983722771824599107048925,1,0
326,326_0,COMPLETED,BoTorch,GenerationStep_1,0.299999999999999988897769753748,41.000000000000000000000000000000,2125,142,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.365545421451215990504834962849,100,0
327,327_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,1032,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,0
328,328_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,2000,5000,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.840759745262087299089159841969,47,0
329,329_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,11.000000000000000000000000000000,2306,5000,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,100,0
330,330_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,75.000000000000000000000000000000,4812,32,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.577234799879355220397769699048,87,0
331,331_0,FAILED,BoTorch,GenerationStep_1,,,4424,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.772411995471962486980999074149,1,0
332,332_0,FAILED,BoTorch,GenerationStep_1,,,1043,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,19,0
333,333_0,COMPLETED,BoTorch,GenerationStep_1,0.299999999999999988897769753748,29.000000000000000000000000000000,3384,179,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.179638654875846931480154466954,100,0
334,334_0,FAILED,BoTorch,GenerationStep_1,,,74,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,72,0
335,335_0,COMPLETED,BoTorch,GenerationStep_1,0.320000000000000006661338147751,6.000000000000000000000000000000,3912,22,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.547391370420526324203081003361,1,0
336,336_0,FAILED,BoTorch,GenerationStep_1,,,1326,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.577496586262243871701116404438,100,0
337,337_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,5.000000000000000000000000000000,1653,61,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.765161723443174346392936513439,1,0
338,338_0,COMPLETED,BoTorch,GenerationStep_1,0.299999999999999988897769753748,5.000000000000000000000000000000,3192,131,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.343715699582879452567141242980,1,0
339,339_0,FAILED,BoTorch,GenerationStep_1,,,2382,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,0
340,340_0,COMPLETED,BoTorch,GenerationStep_1,0.299999999999999988897769753748,5.000000000000000000000000000000,2590,60,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.423159075004206852721466702860,14,0
341,341_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,9.000000000000000000000000000000,2636,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.199396164300989831019705889048,1,0
342,342_0,FAILED,BoTorch,GenerationStep_1,,,3567,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.710257409133711825610646428686,12,0
343,343_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,9.000000000000000000000000000000,3373,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.279646833970687569426161189767,100,0
344,307_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,0
345,345_0,FAILED,BoTorch,GenerationStep_1,,,3241,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.622498596936500225851318646164,100,0
346,346_0,FAILED,BoTorch,GenerationStep_1,,,4472,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,83,0
347,347_0,FAILED,BoTorch,GenerationStep_1,,,3420,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,60,0
348,348_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,5.000000000000000000000000000000,234,33,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.560492350772682224047116505972,79,0
349,349_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,6.000000000000000000000000000000,3876,4,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.545218594996090155646584207716,18,0
350,350_0,COMPLETED,BoTorch,GenerationStep_1,0.299999999999999988897769753748,5.000000000000000000000000000000,162,39,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.133894583167972314186044968665,15,0
351,351_0,COMPLETED,BoTorch,GenerationStep_1,0.250000000000000000000000000000,11.000000000000000000000000000000,112,382,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.550695615147165806746443195152,87,0
352,352_0,FAILED,BoTorch,GenerationStep_1,,,363,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,46,0
353,353_0,FAILED,BoTorch,GenerationStep_1,,,1843,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,60,0
354,354_0,FAILED,BoTorch,GenerationStep_1,,,1536,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.468156124914070326248349829257,100,0
355,355_0,COMPLETED,BoTorch,GenerationStep_1,0.330000000000000015543122344752,9.000000000000000000000000000000,1534,26,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.139512761779722632704547891080,1,0
356,356_0,COMPLETED,BoTorch,GenerationStep_1,0.260000000000000008881784197001,12.000000000000000000000000000000,4179,378,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.632568230070260084652034038299,87,0
357,357_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,132.000000000000000000000000000000,2843,18,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.523013797308277017528155283799,85,0
358,358_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,1815,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.818486261389271052557603525202,100,0
359,359_0,COMPLETED,BoTorch,GenerationStep_1,0.330000000000000015543122344752,8.000000000000000000000000000000,1548,21,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.909007734282587742669079489133,1,0
360,360_0,RUNNING,BoTorch,GenerationStep_1,,,1553,57,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.728694883871712995038194549124,13,0
361,361_0,FAILED,BoTorch,GenerationStep_1,,,348,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,70,0
362,362_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,59,0
363,363_0,COMPLETED,BoTorch,GenerationStep_1,0.260000000000000008881784197001,7.000000000000000000000000000000,2301,245,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,50,0
364,364_0,RUNNING,BoTorch,GenerationStep_1,,,4746,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.610537560472126594746100636257,100,0
365,365_0,RUNNING,BoTorch,GenerationStep_1,,,2771,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.198414366044510265263411952219,13,0
366,366_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,306.000000000000000000000000000000,4544,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,50,0
367,367_0,RUNNING,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,0
368,307_0,RUNNING,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,0
369,369_0,FAILED,BoTorch,GenerationStep_1,,,2765,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,40,0
370,370_0,FAILED,BoTorch,GenerationStep_1,,,4122,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,81,0
371,371_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,6.000000000000000000000000000000,1938,15,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.222436697076042938503448453957,16,0
372,372_0,FAILED,BoTorch,GenerationStep_1,,,4606,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,57,0
373,373_0,COMPLETED,BoTorch,GenerationStep_1,0.250000000000000000000000000000,6.000000000000000000000000000000,4752,348,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.482591832317965763188283290219,16,0
374,374_0,FAILED,BoTorch,GenerationStep_1,,,2742,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,55,0
375,375_0,FAILED,BoTorch,GenerationStep_1,,,4768,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,0
376,376_0,FAILED,BoTorch,GenerationStep_1,,,736,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.496502344819158336619580040860,15,0
377,377_0,COMPLETED,BoTorch,GenerationStep_1,0.260000000000000008881784197001,8.000000000000000000000000000000,4960,312,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.815683235929098193750519385503,67,0
378,378_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,12.000000000000000000000000000000,1432,244,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.563422617013536131125306383183,88,0
379,379_0,FAILED,BoTorch,GenerationStep_1,,,2674,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.477134261569661821678067781249,100,0
380,380_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,16.000000000000000000000000000000,941,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.138808390401241293909961882491,18,0
381,381_0,FAILED,BoTorch,GenerationStep_1,,,1159,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,77,0
382,382_0,FAILED,BoTorch,GenerationStep_1,,,1097,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,16,0
383,383_0,FAILED,BoTorch,GenerationStep_1,,,1357,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,38,0
384,384_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,308.000000000000000000000000000000,1825,6,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.239255050432286481276733525192,79,0
385,385_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,62,0
386,386_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,9.000000000000000000000000000000,3136,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.161812870641093842216662324063,1,0
387,387_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,23.000000000000000000000000000000,3394,241,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.750127584005118808185841317027,100,0
388,388_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,5.000000000000000000000000000000,4899,42,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.570762202871930024450364271615,45,0
389,389_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,3962,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.543766858416138032517039846425,34,0
390,390_0,COMPLETED,BoTorch,GenerationStep_1,0.270000000000000017763568394003,7.000000000000000000000000000000,206,164,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,48,0
391,391_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,9.000000000000000000000000000000,5000,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,0
392,392_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,18.000000000000000000000000000000,4362,3,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.229036536995426365237449317647,31,0
393,53_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,0
394,394_0,FAILED,BoTorch,GenerationStep_1,,,4425,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,82,0
395,395_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,1,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,24,0
396,396_0,COMPLETED,BoTorch,GenerationStep_1,0.320000000000000006661338147751,97.000000000000000000000000000000,4526,8,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,56,0
397,397_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,7.000000000000000000000000000000,4970,48,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.249675316268317043499891383362,31,0
398,398_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,6.000000000000000000000000000000,1,436,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,48,0
399,399_0,FAILED,BoTorch,GenerationStep_1,,,3787,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,10,0
400,400_0,COMPLETED,BoTorch,GenerationStep_1,0.320000000000000006661338147751,7.000000000000000000000000000000,3005,48,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.825045789072616497783485556283,1,0
401,401_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,9.000000000000000000000000000000,5000,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,0
402,402_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,229.000000000000000000000000000000,246,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,47,0
403,403_0,COMPLETED,BoTorch,GenerationStep_1,0.260000000000000008881784197001,6.000000000000000000000000000000,204,824,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.644293539254635283519689892273,8,0
404,404_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,9.000000000000000000000000000000,2746,611,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,0
405,405_0,FAILED,BoTorch,GenerationStep_1,,,62,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,54,0
406,406_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,5000,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,0
407,407_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,5000,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,59,0
408,408_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,5.000000000000000000000000000000,73,61,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.688077668967535416300052020233,16,0
409,409_0,FAILED,BoTorch,GenerationStep_1,,,2863,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.689491498446315409509566052293,1,0
410,410_0,COMPLETED,BoTorch,GenerationStep_1,0.320000000000000006661338147751,10.000000000000000000000000000000,4831,2,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.326069201848254386355563383404,1,0
411,411_0,FAILED,BoTorch,GenerationStep_1,,,466,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.127679142969786635353202086662,1,0
412,412_0,FAILED,BoTorch,GenerationStep_1,,,479,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,74,0
413,413_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,11.000000000000000000000000000000,4957,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,9,0
414,414_0,FAILED,BoTorch,GenerationStep_1,,,906,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,90,0
415,415_0,COMPLETED,BoTorch,GenerationStep_1,0.289999999999999980015985556747,16.000000000000000000000000000000,469,27,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,57,0
416,416_0,COMPLETED,BoTorch,GenerationStep_1,0.299999999999999988897769753748,8.000000000000000000000000000000,5000,787,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,0
417,417_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,6.000000000000000000000000000000,5000,5000,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,63,0
418,418_0,COMPLETED,BoTorch,GenerationStep_1,0.289999999999999980015985556747,8.000000000000000000000000000000,1533,1148,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.731788111459780510337225223338,1,0
419,419_0,COMPLETED,BoTorch,GenerationStep_1,0.270000000000000017763568394003,8.000000000000000000000000000000,4624,56,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.279832030755599980853531860703,50,0
420,420_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,2195,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,60,0
421,421_0,COMPLETED,BoTorch,GenerationStep_1,0.270000000000000017763568394003,5.000000000000000000000000000000,374,13,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,12,0
422,422_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,9.000000000000000000000000000000,227,2,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.762247479394045579503824683343,16,0
423,423_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,9.000000000000000000000000000000,4715,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,88,0
424,424_0,FAILED,BoTorch,GenerationStep_1,,,2316,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,23,0
425,425_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,3530,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,47,0
426,426_0,FAILED,BoTorch,GenerationStep_1,,,580,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,0
427,427_0,FAILED,BoTorch,GenerationStep_1,,,3915,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.722797716093305120388379236829,1,0
428,428_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,4185,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.782995644266403223454631188361,80,0
429,429_0,COMPLETED,BoTorch,GenerationStep_1,0.299999999999999988897769753748,5.000000000000000000000000000000,1550,61,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.434753908207471229108165289290,87,0
430,430_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,97.000000000000000000000000000000,921,50,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.610494704928633002971594123665,100,0
431,431_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,1172,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,62,0
432,432_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,2694,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,36,0
433,433_0,FAILED,BoTorch,GenerationStep_1,,,4451,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,11,0
434,434_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,10.000000000000000000000000000000,1264,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,34,0
435,435_0,FAILED,BoTorch,GenerationStep_1,,,1509,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.690741322096838139543706347467,1,0
436,436_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,9.000000000000000000000000000000,4638,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.797432545156554706267115761875,90,0
437,437_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,4476,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.195316880677047166603443884014,57,0
438,438_0,COMPLETED,BoTorch,GenerationStep_1,0.299999999999999988897769753748,6.000000000000000000000000000000,2937,8,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.816556765858092337140305971843,14,0
439,439_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,4046,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,100,0
440,42_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,0
441,441_0,COMPLETED,BoTorch,GenerationStep_1,0.299999999999999988897769753748,6.000000000000000000000000000000,2797,79,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.212451283722012773669263197007,25,0
442,442_0,FAILED,BoTorch,GenerationStep_1,,,4956,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.878724183373862155477240776236,1,0
443,443_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,6.000000000000000000000000000000,1688,25,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.496239279969153068705622899870,61,0
444,444_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,10.000000000000000000000000000000,1861,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,65,0
445,445_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,10.000000000000000000000000000000,4219,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.480852327139594359906027420948,87,0
446,446_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,7.000000000000000000000000000000,3822,7,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.384415192768990443550336522094,10,0
447,447_0,COMPLETED,BoTorch,GenerationStep_1,0.320000000000000006661338147751,8.000000000000000000000000000000,1262,403,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,0
448,448_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,4972,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.511258729439110104486587715655,58,0
449,449_0,COMPLETED,BoTorch,GenerationStep_1,0.289999999999999980015985556747,5.000000000000000000000000000000,2942,30,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,15,0
450,450_0,FAILED,BoTorch,GenerationStep_1,,,4266,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.696058130448913958687739977904,1,0
451,451_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,9.000000000000000000000000000000,1394,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.522054469938055265565424178931,100,0
452,452_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,9.000000000000000000000000000000,1906,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.188134644210031565236818096309,90,0
453,453_0,FAILED,BoTorch,GenerationStep_1,,,592,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.827623578749214772187769995071,1,0
454,454_0,COMPLETED,BoTorch,GenerationStep_1,0.299999999999999988897769753748,5.000000000000000000000000000000,1051,72,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.646100446380325821316148449114,71,0
455,455_0,FAILED,BoTorch,GenerationStep_1,,,4158,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,21,0
456,456_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,2835,554,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.202352316164986306690209971748,1,0
457,457_0,FAILED,BoTorch,GenerationStep_1,,,2074,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,12,0
458,458_0,FAILED,BoTorch,GenerationStep_1,,,4939,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,26,0
459,459_0,FAILED,BoTorch,GenerationStep_1,,,2642,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,12,0
460,460_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,4906,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.836316785874441803727563637949,49,0
461,461_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,0
462,462_0,FAILED,BoTorch,GenerationStep_1,,,1515,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,27,0
463,463_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,9.000000000000000000000000000000,4735,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,15,0
464,464_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,1,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,0
465,465_0,COMPLETED,BoTorch,GenerationStep_1,0.330000000000000015543122344752,8.000000000000000000000000000000,320,103,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.186267942616064968719413741383,1,0
466,466_0,COMPLETED,BoTorch,GenerationStep_1,0.260000000000000008881784197001,5.000000000000000000000000000000,4480,44,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.807341615547999436053316912876,8,0
467,467_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,9.000000000000000000000000000000,3669,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,11,0
468,468_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,6.000000000000000000000000000000,978,14,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.821695471535179744471122376126,39,0
469,469_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,9.000000000000000000000000000000,3457,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,21,0
470,470_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,11.000000000000000000000000000000,4249,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.808261274990547340379976049007,38,0
471,471_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,7.000000000000000000000000000000,1203,2,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.193580423347774921438713136013,13,0
472,472_0,FAILED,BoTorch,GenerationStep_1,,,4368,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.111924469873505461059437493532,7,0
473,473_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,9.000000000000000000000000000000,3597,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.717288176809519395504821659415,9,0
474,474_0,FAILED,BoTorch,GenerationStep_1,,,4433,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.579577949188160190807650451461,11,0
475,475_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,10.000000000000000000000000000000,339,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.178202477836050920956267873407,1,0
476,476_0,FAILED,BoTorch,GenerationStep_1,,,4084,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,7,0
477,477_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,12.000000000000000000000000000000,4300,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.733184877557989889140799277811,11,0
478,478_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,4254,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.857040112332628112312704615761,1,0
479,479_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,9.000000000000000000000000000000,618,519,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.725790270828359451726896622858,1,0
480,480_0,FAILED,BoTorch,GenerationStep_1,,,4615,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,15,0
481,481_0,COMPLETED,BoTorch,GenerationStep_1,0.289999999999999980015985556747,8.000000000000000000000000000000,3611,1017,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.276457587742561350374614903558,1,0
482,482_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,5.000000000000000000000000000000,1472,823,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,6,0
483,483_0,FAILED,BoTorch,GenerationStep_1,,,4594,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,55,0
484,484_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,5.000000000000000000000000000000,2272,115,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,24,0
485,485_0,FAILED,BoTorch,GenerationStep_1,,,790,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,85,0
486,486_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,6.000000000000000000000000000000,3503,862,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.390601925146676520750332883836,10,0
487,487_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,5.000000000000000000000000000000,1785,1855,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,0
488,488_0,FAILED,BoTorch,GenerationStep_1,,,431,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.302815418079073139789869628657,33,0
489,489_0,FAILED,BoTorch,GenerationStep_1,,,2064,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,78,0
490,490_0,FAILED,BoTorch,GenerationStep_1,,,4319,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,24,0
491,491_0,FAILED,BoTorch,GenerationStep_1,,,754,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,16,0
492,492_0,COMPLETED,BoTorch,GenerationStep_1,0.250000000000000000000000000000,5.000000000000000000000000000000,2205,653,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.142081367102106531641325659621,31,0
493,493_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,6.000000000000000000000000000000,4077,835,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.610486324811809533130713134597,7,0
494,494_0,COMPLETED,BoTorch,GenerationStep_1,0.270000000000000017763568394003,7.000000000000000000000000000000,4186,772,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,0
495,495_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,6.000000000000000000000000000000,4292,1197,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,0
496,496_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,5.000000000000000000000000000000,3589,899,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,10,0
497,497_0,FAILED,BoTorch,GenerationStep_1,,,4644,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,32,0
498,498_0,FAILED,BoTorch,GenerationStep_1,,,4813,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.872006261063527632337866180023,1,0
499,499_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,6.000000000000000000000000000000,4846,716,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.762027116201940302175898978021,20,0
500,500_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,10.000000000000000000000000000000,2844,1650,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.379301726781176296032782602197,100,0
501,501_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,12.000000000000000000000000000000,3171,2375,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.761888403198094477097868093551,100,0
502,502_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,6.000000000000000000000000000000,733,772,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,0
503,503_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,11.000000000000000000000000000000,1426,2145,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.287334164004774961220789464278,100,0
504,504_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,3869,1043,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.547222266476389274103553361783,10,0
505,505_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,100,0
506,506_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,4454,1908,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,39,0
507,507_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,8.000000000000000000000000000000,4639,17,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.819715078107749794966707668209,27,0
508,508_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,14.000000000000000000000000000000,840,1931,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,100,0
509,509_0,COMPLETED,BoTorch,GenerationStep_1,0.309999999999999997779553950750,13.000000000000000000000000000000,4799,100,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.917838100680810842213475098106,56,0
</pre>
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			<script>
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			<h1>&nbsp;Errors</h1>
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			<button onclick='download_as_file("simple_pre_tab_tab_errors", "oo_errors.txt")'> Download &raquo;oo_errors.txt&laquo; as file</button>
<pre id='simple_pre_tab_tab_errors'><span style="background-color: black; color: white">
⚠ Job 3890206 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_TMDBalanced5s_ft_0_HoeffdingTreeClassifier_ACCURACY-RUNTIME/0/single_runs/3890206/3890206_0_result.pkl
has not produced any output (state: TIMEOUT)
Error stream produced:
----------------------------------------
slurmstepd: error: *** JOB 3890206 ON i7121 CANCELLED AT 2025-03-31T14:32:38 DUE TO TIME LIMIT ***



⚠ Job 3890219 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_TMDBalanced5s_ft_0_HoeffdingTreeClassifier_ACCURACY-RUNTIME/0/single_runs/3890219/3890219_0_result.pkl
has not produced any output (state: TIMEOUT)
Error stream produced:
----------------------------------------
slurmstepd: error: *** JOB 3890219 ON i7118 CANCELLED AT 2025-03-31T14:32:38 DUE TO TIME LIMIT ***



⚠ Job 3890254 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_TMDBalanced5s_ft_0_HoeffdingTreeClassifier_ACCURACY-RUNTIME/0/single_runs/3890254/3890254_0_result.pkl
has not produced any output (state: TIMEOUT)
Error stream produced:
----------------------------------------
slurmstepd: error: *** JOB 3890254 ON i7110 CANCELLED AT 2025-03-31T14:32:38 DUE TO TIME LIMIT ***



⚠ Job 3890296 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_TMDBalanced5s_ft_0_HoeffdingTreeClassifier_ACCURACY-RUNTIME/0/single_runs/3890296/3890296_0_result.pkl
has not produced any output (state: TIMEOUT)
Error stream produced:
----------------------------------------
slurmstepd: error: *** JOB 3890296 ON i7106 CANCELLED AT 2025-03-31T14:32:38 DUE TO TIME LIMIT ***



⚠ Job 3901166 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_TMDBalanced5s_ft_0_HoeffdingTreeClassifier_ACCURACY-RUNTIME/0/single_runs/3901166/3901166_0_result.pkl
has not produced any output (state: TIMEOUT)
Error stream produced:
----------------------------------------
slurmstepd: error: *** JOB 3901166 ON i7145 CANCELLED AT 2025-03-31T17:02:47 DUE TO TIME LIMIT ***


</span></pre><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("simple_pre_tab_tab_errors")'> Copy raw data to clipboard</button>
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			<h1>&nbsp;Args Overview</h1>
			<h2>Arguments Overview:                                                                                           </h2><table cellspacing="0" cellpadding="5"><thead><tr><th> Key</th><th>Value                                                                                                                                                    </th></tr></thead><tbody><tr><td> config_yaml</td><td>None                                                                                                                                                     </td></tr><tr><td> config_toml</td><td>None                                                                                                                                                     </td></tr><tr><td> config_json</td><td>None                                                                                                                                                     </td></tr><tr><td> num_random_steps</td><td>20                                                                                                                                                       </td></tr><tr><td> max_eval</td><td>500                                                                                                                                                      </td></tr><tr><td> run_program</td><td>[[&#039;bW9kdWxlIGxvYWQgR0NDY29yZS8xMC4zLjAgUHl0aG9uICYmIHNvdXJjZSAvZGF0YS9ob3JzZS93cy9zNDEyMjQ4NS1jb21wUGVyZkREL2JlbmNobWFyay92ZW52L2Jpbi9hY3RpdmF0ZSAmJiBw&hellip; </td></tr><tr><td> experiment_name</td><td>CDBD_TMDBalanced5s_ft_0_HoeffdingTreeClassifier_ACCURACY-RUNTIME                                                                                         </td></tr><tr><td> mem_gb</td><td>32                                                                                                                                                       </td></tr><tr><td> parameter</td><td>[[&#039;recent_samples_size&#039;, &#039;range&#039;, &#039;1&#039;, &#039;5000&#039;, &#039;int&#039;], [&#039;feature_id&#039;, &#039;fixed&#039;, &#039;0&#039;], [&#039;batch_size&#039;, &#039;range&#039;, &#039;1&#039;, &#039;5000&#039;, &#039;int&#039;], [&#039;divergence&#039;,         </td></tr><tr><td></td><td>&#039;choice&#039;, &quot;str\\(\\&#039;KL\\&#039;\\),str\\(\\&#039;H\\&#039;\\)&quot;], [&#039;detect_batch&#039;, &#039;choice&#039;, &#039;1,2,3&#039;], [&#039;statistic&#039;, &#039;choice&#039;,                                            </td></tr><tr><td></td><td>&quot;str\\(\\&#039;tstat\\&#039;\\),str\\(\\&#039;stdev\\&#039;\\)&quot;], [&#039;significance&#039;, &#039;range&#039;, &#039;0.001&#039;, &#039;0.999&#039;, &#039;float&#039;], [&#039;subsets&#039;, &#039;range&#039;, &#039;1&#039;, &#039;100&#039;, &#039;int&#039;]]             </td></tr><tr><td> continue_previous_job</td><td>None                                                                                                                                                     </td></tr><tr><td> maximize</td><td>False                                                                                                                                                    </td></tr><tr><td> experiment_constraints</td><td>None                                                                                                                                                     </td></tr><tr><td> stderr_to_stdout</td><td>False                                                                                                                                                    </td></tr><tr><td> run_dir</td><td>runs                                                                                                                                                     </td></tr><tr><td> seed</td><td>None                                                                                                                                                     </td></tr><tr><td> decimalrounding</td><td>12                                                                                                                                                       </td></tr><tr><td> enforce_sequential_optimization</td><td>False                                                                                                                                                    </td></tr><tr><td> verbose_tqdm</td><td>False                                                                                                                                                    </td></tr><tr><td> model</td><td>BOTORCH_MODULAR                                                                                                                                          </td></tr><tr><td> gridsearch</td><td>False                                                                                                                                                    </td></tr><tr><td> occ</td><td>False                                                                                                                                                    </td></tr><tr><td> show_sixel_scatter</td><td>False                                                                                                                                                    </td></tr><tr><td> show_sixel_general</td><td>False                                                                                                                                                    </td></tr><tr><td> show_sixel_trial_index_result</td><td>False                                                                                                                                                    </td></tr><tr><td> follow</td><td>False                                                                                                                                                    </td></tr><tr><td> send_anonymized_usage_stats</td><td>True                                                                                                                                                     </td></tr><tr><td> ui_url</td><td>None                                                                                                                                                     </td></tr><tr><td> root_venv_dir</td><td>/home/s4122485                                                                                                                                           </td></tr><tr><td> exclude</td><td>None                                                                                                                                                     </td></tr><tr><td> main_process_gb</td><td>8                                                                                                                                                        </td></tr><tr><td> pareto_front_confidence</td><td>1                                                                                                                                                        </td></tr><tr><td> max_nr_of_zero_results</td><td>50                                                                                                                                                       </td></tr><tr><td> disable_search_space_exhaustion_detection</td><td>False                                                                                                                                                    </td></tr><tr><td> abbreviate_job_names</td><td>False                                                                                                                                                    </td></tr><tr><td> orchestrator_file</td><td>None                                                                                                                                                     </td></tr><tr><td> checkout_to_latest_tested_version</td><td>False                                                                                                                                                    </td></tr><tr><td> live_share</td><td>False                                                                                                                                                    </td></tr><tr><td> disable_tqdm</td><td>False                                                                                                                                                    </td></tr><tr><td> workdir</td><td>False                                                                                                                                                    </td></tr><tr><td> max_parallelism</td><td>max_eval_times_thousand_plus_thousand                                                                                                                    </td></tr><tr><td> occ_type</td><td>euclid                                                                                                                                                   </td></tr><tr><td> result_names</td><td>[&#039;ACCURACY=max&#039;, &#039;RUNTIME=min&#039;]                                                                                                                          </td></tr><tr><td> minkowski_p</td><td>2                                                                                                                                                        </td></tr><tr><td> signed_weighted_euclidean_weights</td><td></td></tr><tr><td> generation_strategy</td><td>None                                                                                                                                                     </td></tr><tr><td> generate_all_jobs_at_once</td><td>True                                                                                                                                                     </td></tr><tr><td> revert_to_random_when_seemingly_exhausted</td><td>True                                                                                                                                                     </td></tr><tr><td> num_parallel_jobs</td><td>30                                                                                                                                                       </td></tr><tr><td> worker_timeout</td><td>60                                                                                                                                                       </td></tr><tr><td> slurm_use_srun</td><td>False                                                                                                                                                    </td></tr><tr><td> time</td><td>1440                                                                                                                                                     </td></tr><tr><td> partition</td><td>romeo                                                                                                                                                    </td></tr><tr><td> reservation</td><td>None                                                                                                                                                     </td></tr><tr><td> force_local_execution</td><td>False                                                                                                                                                    </td></tr><tr><td> slurm_signal_delay_s</td><td>0                                                                                                                                                        </td></tr><tr><td> nodes_per_job</td><td>1                                                                                                                                                        </td></tr><tr><td> cpus_per_task</td><td>1                                                                                                                                                        </td></tr><tr><td> account</td><td>None                                                                                                                                                     </td></tr><tr><td> gpus</td><td>0                                                                                                                                                        </td></tr><tr><td> run_mode</td><td>local                                                                                                                                                    </td></tr><tr><td> verbose</td><td>False                                                                                                                                                    </td></tr><tr><td> verbose_break_run_search_table</td><td>False                                                                                                                                                    </td></tr><tr><td> debug</td><td>False                                                                                                                                                    </td></tr><tr><td> no_sleep</td><td>False                                                                                                                                                    </td></tr><tr><td> tests</td><td>False                                                                                                                                                    </td></tr><tr><td> show_worker_percentage_table_at_end</td><td>False                                                                                                                                                    </td></tr><tr><td> auto_exclude_defective_hosts</td><td>False                                                                                                                                                    </td></tr><tr><td> run_tests_that_fail_on_taurus</td><td>False                                                                                                                                                    </td></tr><tr><td> raise_in_eval</td><td>False                                                                                                                                                    </td></tr><tr><td> show_ram_every_n_seconds</td><td>False                                                                                                                                                    </td></tr></tbody></table>
			<h1>&nbsp;Worker-Usage</h1>
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<pre id="pre_tab_worker_usage">1743371364.568506,30,0,0
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1743450041.4207063,30,13,43
1743450045.0734718,30,12,40
1743450045.2626884,30,12,40
1743450050.5722113,30,12,40
1743450054.4767845,30,11,37
1743450054.597658,30,11,37
1743450059.9027627,30,11,37
1743450060.0108924,30,11,37
1743450063.701492,30,10,33
1743450063.7883334,30,10,33
1743450069.06453,30,10,33
1743450069.1476264,30,10,33
1743450072.4171715,30,9,30
1743450072.5020084,30,9,30
1743450080.4873698,30,9,30
1743450086.0437896,30,9,30
1743450086.1326466,30,9,30
1743450089.8488617,30,8,27
1743450089.990291,30,8,27
1743450095.2725239,30,8,27
1743450095.356225,30,8,27
1743450098.6530194,30,7,23
1743450098.7435682,30,7,23
1743450104.0661697,30,7,23
1743450104.1937618,30,7,23
1743450107.8717682,30,6,20
1743450107.9619555,30,6,20
1743450113.2712593,30,6,20
1743450113.4085512,30,6,20
1743450117.086922,30,5,17
1743450117.2142022,30,5,17
1743450125.1883235,30,5,17
1743450130.4997559,30,5,17
1743450134.2227647,30,4,13
1743450134.310623,30,4,13
1743450139.6050034,30,4,13
1743450139.7646337,30,4,13
1743450143.4256244,30,3,10
1743450143.5506032,30,3,10
1743450151.5393999,30,3,10
1743450156.8837984,30,3,10
1743450156.9906762,30,3,10
1743450160.3189645,30,2,7
1743450160.5416665,30,2,7
1743450165.8709364,30,2,7
1743450165.9817975,30,2,7
1743450169.6917849,30,1,3
1743450169.7754092,30,1,3
1743450177.743114,30,1,3
1743450185.4285142,30,1,3
1743450190.7280905,30,1,3
1743450190.8232956,30,1,3
1743450194.5502777,30,0,0
</pre><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("pre_tab_worker_usage")'> Copy raw data to clipboard</button>
			<button onclick='download_as_file("pre_tab_worker_usage", "worker_usage.csv")'> Download &raquo;worker_usage.csv&laquo; as file</button>
			
			<h1>&nbsp;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 &raquo;cpu_ram_usage.csv&laquo; as file</button>
<pre id="pre_tab_main_worker_cpu_ram">timestamp,ram_usage_mb,cpu_usage_percent
1743371364,593.109375,2.3
1743371364,593.15625,5.5
1743371364,593.25390625,5.3
1743371364,593.25390625,7.5
1743371364,593.25390625,2.9
1743371364,593.25390625,5.4
1743371364,593.25390625,7.5
1743371475,608.69921875,2.7
1743371475,608.69921875,5.0
1743371475,608.69921875,3.7
1743371475,608.69921875,2.0
1743373504,671.3046875,4.1
1743373504,671.3046875,4.3
1743373504,671.3046875,3.8
1743373504,671.3046875,3.7
1743385188,685.55078125,4.3
1743385188,685.55078125,4.5
1743385188,685.55078125,4.4
1743385188,685.55078125,2.8
1743391115,689.796875,4.5
1743391115,689.796875,3.6
1743391115,689.796875,3.2
1743391115,689.796875,2.6
1743395940,702.2734375,4.7
1743395940,702.2734375,3.2
1743395940,702.2734375,3.8
1743395940,702.2734375,5.4
1743399947,706.83203125,4.8
1743399947,706.83203125,4.6
1743399947,706.83203125,4.6
1743399947,706.83203125,8.3
1743406886,734.4140625,4.8
1743406886,734.4140625,4.9
1743406886,734.4140625,4.6
1743406886,734.4140625,3.6
1743409565,725.63671875,5.3
1743409565,725.63671875,5.1
1743409565,725.63671875,5.1
1743409565,725.63671875,3.0
1743412435,799.9375,5.3
1743412435,799.9375,5.3
1743412435,799.9375,5.1
1743412435,799.9375,6.7
1743420701,767.07421875,5.3
1743420701,767.07421875,5.2
1743420701,767.07421875,5.1
1743420701,767.07421875,6.0
1743427019,777.1640625,6.1
1743427019,777.1640625,5.2
1743427019,777.1640625,5.1
1743427019,777.1640625,4.9
1743429686,780.734375,6.5
1743429686,780.734375,5.6
1743429686,780.734375,6.2
1743429686,780.734375,6.5
1743436366,825.33984375,6.6
1743436366,825.33984375,5.3
1743436366,825.33984375,5.5
1743436366,825.33984375,5.7
1743439827,781.80859375,6.8
1743439827,781.80859375,6.3
1743439827,781.80859375,6.5
1743439827,781.80859375,8.3
1743442553,784.62890625,7.0
1743442553,784.62890625,5.0
1743442553,784.62890625,5.8
1743442553,784.62890625,2.9
1743445546,788.89453125,6.4
1743445546,788.89453125,6.6
1743445546,788.89453125,7.2
1743445546,788.89453125,6.1
1743449961,814.94921875,8.1
1743449961,814.94921875,7.4
1743449961,814.94921875,7.5
1743449961,814.94921875,7.4
1743450197,819.171875,7.1
1743450197,819.171875,6.0
</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 &raquo;cpu_ram_usage.csv&laquo; as file</button>
			
			<h1>&nbsp;Parallel Plot</h1>
			<div class="invert_in_dark_mode" id="parallel-plot"></div>
			<h1>&nbsp;Scatter-2D</h1>
			<div class='invert_in_dark_mode' id='plotScatter2d'></div>
			<h1>&nbsp;Scatter-3D</h1>
			<div class='invert_in_dark_mode' id='plotScatter3d'></div>
			<h1>&nbsp;Job Status Distribution</h1>
			<div class="invert_in_dark_mode" id="plotJobStatusDistribution"></div>
			<h1>&nbsp;Boxplots</h1>
			<div class="invert_in_dark_mode" id="plotBoxplot"></div>
			<h1>&nbsp;Violin</h1>
			<div class="invert_in_dark_mode" id="plotViolin"></div>
			<h1>&nbsp;Histogram</h1>
			<div class="invert_in_dark_mode" id="plotHistogram"></div>
			<h1>&nbsp;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>&nbsp;Result-Pairs</h1>
			<div class="invert_in_dark_mode" id="plotResultPairs"></div>
	</body>
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