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			9
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
95	414	1	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
1743371378,1743371398,20,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 4152 feature_id 9 batch_size 2792 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.5191670401096344 subsets 72,4152,2792,str\(\'H\'\),2,str\(\'stdev\'\),0.5191670401096344,72,9,0.2,5,0,None,i7183,5,751.3203125,751.06640625,-1,0,3827914
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
1743371378,1743371398,20,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 1387 feature_id 9 batch_size 819 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.2880986645687372 subsets 48,1387,819,str\(\'KL\'\),2,str\(\'tstat\'\),0.2880986645687372,48,9,0.2,4,0,None,i7183,4,750.35546875,750.0572916666666,-1,0.15155526141628062,3827918
1743371392,1743371404,12,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 3429 feature_id 9 batch_size 1789 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.9069879042245448 subsets 12,3429,1789,str\(\'KL\'\),1,str\(\'stdev\'\),0.9069879042245448,12,9,0.2,3,0,None,i7182,3,750.38671875,750.2356770833334,-1,0,3827928
1743371392,1743371411,19,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 1172 feature_id 9 batch_size 4934 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.14588799856603146 subsets 82,1172,4934,str\(\'H\'\),3,str\(\'tstat\'\),0.14588799856603146,82,9,0.2,3,0,None,i7185,3,749.9375,749.7643229166666,-1,0,3827924
1743371404,1743371417,13,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 354 feature_id 9 batch_size 2244 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.41138083635270595 subsets 25,354,2244,str\(\'H\'\),3,str\(\'tstat\'\),0.41138083635270595,25,9,0.2,3,0,None,i7182,3,750.0546875,749.8802083333334,-1,0,3827937
1743371404,1743371423,19,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 2532 feature_id 9 batch_size 4177 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.6405147464610637 subsets 95,2532,4177,str\(\'KL\'\),1,str\(\'stdev\'\),0.6405147464610637,95,9,0.2,8,0,None,i7182,8,751.20703125,751.0638020833334,-1,0,3827935
1743371413,1743371426,13,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 4895 feature_id 9 batch_size 13 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.7827025812100619 subsets 35,4895,13,str\(\'H\'\),3,str\(\'stdev\'\),0.7827025812100619,35,9,0.2,3,0,None,i7183,3,750.67578125,750.4830729166666,-1,0.009596293845135672,3827948
1743371413,1743371433,20,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 2054 feature_id 9 batch_size 3275 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.02359804384596646 subsets 59,2054,3275,str\(\'KL\'\),1,str\(\'tstat\'\),0.02359804384596646,59,9,0.2,4,0,None,i7184,4,750.8359375,750.6432291666666,-1,0,3827942
1743371434,1743371447,13,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 4519 feature_id 9 batch_size 4620 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.9908605037629604 subsets 89,4519,4620,str\(\'KL\'\),3,str\(\'tstat\'\),0.9908605037629604,89,9,0.2,3,0,None,i7185,3,751.08984375,750.9140625,-1,0,3827955
1743371434,1743371453,19,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 2283 feature_id 9 batch_size 1475 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.19065524088218808 subsets 19,2283,1475,str\(\'H\'\),1,str\(\'stdev\'\),0.19065524088218808,19,9,0.2,5,0,None,i7183,5,751.2421875,751.1080729166666,-1,0,3827963
1743371434,1743371453,19,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 310 feature_id 9 batch_size 3087 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.36028529825620353 subsets 52,310,3087,str\(\'KL\'\),3,str\(\'stdev\'\),0.36028529825620353,52,9,0.2,3,0,None,i7182,3,749.9921875,749.8177083333334,-1,0,3827969
1743371456,1743371475,19,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 3054 feature_id 9 batch_size 1114 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.5678406361360103 subsets 29,3054,1114,str\(\'H\'\),2,str\(\'tstat\'\),0.5678406361360103,29,9,0.2,3,0,None,i7185,3,751.8203125,751.5221354166666,-1,0,3827974
1743371464,1743371483,19,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 3483 feature_id 9 batch_size 3581 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.8626782341022045 subsets 65,3483,3581,str\(\'H\'\),2,str\(\'tstat\'\),0.8626782341022045,65,9,0.2,3,0,None,i7184,3,750.28125,750.1263020833334,-1,0,3827987
1743371476,1743371495,19,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 660 feature_id 9 batch_size 319 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.06446738031320275 subsets 42,660,319,str\(\'KL\'\),2,str\(\'stdev\'\),0.06446738031320275,42,9,0.21,4,0,None,i7182,4,749.8828125,749.6171875,-1,0.07743216412971542,3827996
1743371495,1743371508,13,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 3932 feature_id 9 batch_size 1919 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.6930862288177013 subsets 5,3932,1919,str\(\'KL\'\),3,str\(\'tstat\'\),0.6930862288177013,5,9,0.2,3,0,None,i7181,3,750.09765625,749.9244791666666,-1,0,3828024
1743371495,1743371514,19,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 1773 feature_id 9 batch_size 3852 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.48746442412212493 subsets 76,1773,3852,str\(\'H\'\),1,str\(\'stdev\'\),0.48746442412212493,76,9,0.2,5,0,None,i7184,5,751.12890625,750.96875,-1,0,3828012
1743371525,1743371544,19,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 3844 feature_id 9 batch_size 3965 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.10302004255354405 subsets 47,3844,3965,str\(\'H\'\),1,str\(\'stdev\'\),0.10302004255354405,47,9,0.2,4,0,None,i7183,4,751.875,751.7057291666666,-1,0,3828043
1743371542,1743371561,19,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 865 feature_id 9 batch_size 3604 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.7335967444907874 subsets 7,865,3604,str\(\'H\'\),1,str\(\'tstat\'\),0.7335967444907874,7,9,0.2,3,0,None,i7181,3,751.78125,751.6158854166666,-1,0,3828073
1743371542,1743371567,25,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 3746 feature_id 9 batch_size 616 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.4635137632656842 subsets 87,3746,616,str\(\'KL\'\),3,str\(\'stdev\'\),0.4635137632656842,87,9,0.22,4,0,None,i7179,4,750.0390625,749.875,-1,0,3828089
1743371543,1743371569,26,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 1966 feature_id 9 batch_size 302 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.6809101503808052 subsets 94,1966,302,str\(\'H\'\),3,str\(\'stdev\'\),0.6809101503808052,94,9,0.21,4,0,None,i7163,4,750.27734375,750.1171875,-1,0.099933818663137,3828236
1743371544,1743371569,25,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 1705 feature_id 9 batch_size 2149 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.8406986287273467 subsets 74,1705,2149,str\(\'KL\'\),2,str\(\'tstat\'\),0.8406986287273467,74,9,0.2,5,0,None,i7182,5,749.984375,749.6796875,-1,0,3828056
1743371546,1743371571,25,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 967 feature_id 9 batch_size 1648 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.5566262977719307 subsets 67,967,1648,str\(\'KL\'\),2,str\(\'stdev\'\),0.5566262977719307,67,9,0.2,4,0,None,i7010,4,750.515625,750.2552083333334,-1,0,3828700
1743371546,1743371571,25,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 618 feature_id 9 batch_size 4260 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.7608380727171898 subsets 28,618,4260,str\(\'KL\'\),2,str\(\'stdev\'\),0.7608380727171898,28,9,0.2,3,0,None,i7156,3,750.65625,750.4817708333334,-1,0,3828304
1743371546,1743371572,26,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 3165 feature_id 9 batch_size 4754 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.2652690866775811 subsets 41,3165,4754,str\(\'H\'\),3,str\(\'tstat\'\),0.2652690866775811,41,9,0.2,3,0,None,i7135,3,751.00390625,750.8372395833334,-1,0,3828520
1743371548,1743371573,25,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 4587 feature_id 9 batch_size 1343 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.33732538034021853 subsets 61,4587,1343,str\(\'H\'\),2,str\(\'stdev\'\),0.33732538034021853,61,9,0.2,4,0,None,i7169,4,751.4296875,751.1731770833334,-1,0,3828175
1743371548,1743371573,25,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 4826 feature_id 9 batch_size 3290 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.3875584930162877 subsets 14,4826,3290,str\(\'KL\'\),1,str\(\'tstat\'\),0.3875584930162877,14,9,0.2,3,0,None,i7167,3,750.76171875,750.578125,-1,0,3828199
1743371549,1743371574,25,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 2371 feature_id 9 batch_size 4448 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.6054129709638655 subsets 34,2371,4448,str\(\'KL\'\),2,str\(\'tstat\'\),0.6054129709638655,34,9,0.2,3,0,None,i7174,3,750.3984375,750.2434895833334,-1,0,3828140
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 2849 feature_id 9 batch_size 2848 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.23020064254291356 subsets 21,2849,2848,str\(\'KL\'\),3,str\(\'stdev\'\),0.23020064254291356,21,9,0.2,3,0,None,i7177,3,749.81640625,749.6276041666666,-1,0,3828106
1743371553,1743371579,26,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 2737 feature_id 9 batch_size 2443 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.062022403437644244 subsets 54,2737,2443,str\(\'H\'\),2,str\(\'tstat\'\),0.062022403437644244,54,9,0.2,4,0,None,i7153,4,750.09765625,749.7890625,-1,0,3828340
1743371543,1743371581,38,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 47 feature_id 9 batch_size 1070 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.9659447735082358 subsets 100,47,1070,str\(\'H\'\),1,str\(\'tstat\'\),0.9659447735082358,100,9,0.22,16,0,None,i7176,16,751.1015625,750.953125,-1,0,3828124
1743375067,1743375080,13,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 3724 feature_id 9 batch_size 799 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.6432198238201787 subsets 92,3724,799,str\(\'KL\'\),3,str\(\'tstat\'\),0.6432198238201787,92,9,0.22,4,0,None,i7168,4,750.1640625,749.9166666666666,-1,0,3834793
1743375217,1743375237,20,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 4033 feature_id 9 batch_size 650 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 75,4033,650,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,75,9,0.22,4,0,None,i7167,4,751.015625,750.75390625,-1,0,3834843
1743375458,1743375471,13,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 2051 feature_id 9 batch_size 899 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.5697805726453924 subsets 96,2051,899,str\(\'KL\'\),3,str\(\'stdev\'\),0.5697805726453924,96,9,0.2,3,0,None,i7185,3,751.65234375,751.453125,-1,0,3834920
1743375638,1743375651,13,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 4579 feature_id 9 batch_size 903 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 100,4579,903,str\(\'KL\'\),3,str\(\'stdev\'\),0.001,100,9,0.2,3,0,None,i7183,3,751.1875,751.0013020833334,-1,0.23494374586366645,3834981
1743375848,1743375861,13,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 2554 feature_id 9 batch_size 816 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 85,2554,816,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,85,9,0.21,4,0,None,i7168,4,750.93359375,750.70703125,-1,0,3835055
1743376028,1743376041,13,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 3341 feature_id 9 batch_size 656 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 68,3341,656,str\(\'H\'\),3,str\(\'tstat\'\),0.999,68,9,0.22,4,0,None,i7179,4,750.05078125,749.8528645833334,-1,0,3835114
1743376118,1743376131,13,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 4184 feature_id 9 batch_size 928 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 96,4184,928,str\(\'KL\'\),3,str\(\'stdev\'\),0.999,96,9,0.2,3,0,None,i7176,3,751.00390625,750.83984375,-1,0.25976174718729317,3835144
1743376329,1743376342,13,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 2760 feature_id 9 batch_size 855 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 95,2760,855,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,95,9,0.2,3,0,None,i7181,3,750.68359375,750.4205729166666,-1,0,3835212
1743376569,1743376582,13,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 935 feature_id 9 batch_size 946 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.3697439799922159 subsets 94,935,946,str\(\'H\'\),3,str\(\'stdev\'\),0.3697439799922159,94,9,0.2,3,0,None,i7167,3,750.8125,750.62109375,-1,0.27763070814030444,3835299
1743376839,1743376852,13,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 490 feature_id 9 batch_size 816 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.8167330261974591 subsets 90,490,816,str\(\'KL\'\),3,str\(\'tstat\'\),0.8167330261974591,90,9,0.21,4,0,None,i7177,4,750.328125,750.0885416666666,-1,0,3835386
1743377080,1743377105,25,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 3694 feature_id 9 batch_size 858 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.6594948524059145 subsets 93,3694,858,str\(\'KL\'\),1,str\(\'stdev\'\),0.6594948524059145,93,9,0.22,12,0,None,i7178,12,751.2109375,751.1005859375,-1,0,3835464
1743377289,1743377302,13,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 205 feature_id 9 batch_size 881 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 97,205,881,str\(\'KL\'\),3,str\(\'stdev\'\),0.001,97,9,0.2,3,0,None,i7182,3,750.98046875,750.75390625,-1,0,3835531
1743377500,1743377519,19,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 3183 feature_id 9 batch_size 657 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 1,3183,657,str\(\'KL\'\),2,str\(\'stdev\'\),0.999,1,9,0.22,4,0,None,i7169,4,751.046875,750.7955729166666,-1,0,3835606
1743377620,1743377633,13,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 3104 feature_id 9 batch_size 816 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.68510446812638 subsets 100,3104,816,str\(\'KL\'\),3,str\(\'tstat\'\),0.68510446812638,100,9,0.21,4,0,None,i7169,4,751.80078125,751.5729166666666,-1,0,3835647
1743378011,1743378023,12,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 4598 feature_id 9 batch_size 976 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 92,4598,976,str\(\'H\'\),3,str\(\'stdev\'\),0.999,92,9,0.2,4,0,None,i7171,4,750.04296875,749.86328125,-1,0,3835775
1743378101,1743378120,19,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 6 feature_id 9 batch_size 195 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 44,6,195,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,44,9,0.24,7,0,None,i7183,7,750.234375,750.0546875,-1,0.12905360688285902,3835800
1743378311,1743378337,26,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 3306 feature_id 9 batch_size 851 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.3463444365701557 subsets 92,3306,851,str\(\'H\'\),1,str\(\'stdev\'\),0.3463444365701557,92,9,0.23,14,0,None,i7170,14,751.015625,750.8955078125,-1,0.18332230311052283,3835875
1743378523,1743378536,13,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 4449 feature_id 9 batch_size 749 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 80,4449,749,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,80,9,0.22,4,0,None,i7185,4,750.01953125,749.76953125,-1,0,3835940
1743378701,1743378714,13,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 3962 feature_id 9 batch_size 899 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 94,3962,899,str\(\'H\'\),3,str\(\'tstat\'\),0.999,94,9,0.21,4,0,None,i7168,4,750.4921875,750.2434895833334,-1,0,3836008
1743378912,1743378925,13,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 2700 feature_id 9 batch_size 729 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 69,2700,729,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,69,9,0.22,4,0,None,i7177,4,750.1171875,749.84375,-1,0,3836074
1743379062,1743379081,19,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 752 feature_id 9 batch_size 196 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 51,752,196,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,51,9,0.24,8,0,None,i7166,8,750.4375,750.2721354166666,-1,0.12971542025148908,3836124
1743379242,1743379255,13,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 803 feature_id 9 batch_size 809 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 100,803,809,str\(\'KL\'\),3,str\(\'stdev\'\),0.999,100,9,0.21,4,0,None,i7169,4,751.3125,751.0872395833334,-1,0,3836186
1743379483,1743379495,12,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 9 batch_size 321 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 63,5000,321,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,63,9,0.21,4,0,None,i7183,4,750.8671875,750.6419270833334,-1,0.08206485771012574,3836263
1743379573,1743379585,12,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 1460 feature_id 9 batch_size 856 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 83,1460,856,str\(\'H\'\),3,str\(\'tstat\'\),0.999,83,9,0.2,3,0,None,i7183,3,751.3359375,751.0859375,-1,0,3836294
1743379663,1743379688,25,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 77 feature_id 9 batch_size 816 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.5153479745212985 subsets 94,77,816,str\(\'KL\'\),1,str\(\'stdev\'\),0.5153479745212985,94,9,0.21,13,0,None,i7182,13,750.38671875,750.275390625,-1,0,3836325
1743379783,1743379796,13,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 9 batch_size 5000 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 62,1,5000,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,62,9,0.2,3,0,None,i7185,3,750.7421875,750.56640625,-1,0,3836362
1743379873,1743379886,13,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 3054 feature_id 9 batch_size 594 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 9,3054,594,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,9,9,0.22,4,0,None,i7185,4,751.0625,750.7721354166666,-1,0.19655857048312375,3836393
1743379933,1743379946,13,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 2881 feature_id 9 batch_size 967 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.2737989550032461 subsets 92,2881,967,str\(\'KL\'\),3,str\(\'tstat\'\),0.2737989550032461,92,9,0.21,4,0,None,i7183,4,751.21875,750.9856770833334,-1,0,3836417
1743380023,1743380049,26,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 4795 feature_id 9 batch_size 879 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.3132327171731461 subsets 99,4795,879,str\(\'KL\'\),1,str\(\'stdev\'\),0.3132327171731461,99,9,0.23,15,0,None,i7183,15,750.09375,749.98046875,-1,0,3836447
1743380083,1743380096,13,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 3208 feature_id 9 batch_size 1062 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 95,3208,1062,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,95,9,0.2,3,0,None,i7182,3,750.94140625,750.6666666666666,-1,0,3836469
1743388460,1743388473,13,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 1266 feature_id 9 batch_size 383 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 23,1266,383,str\(\'KL\'\),3,str\(\'stdev\'\),0.999,23,9,0.21,3,0,None,i7149,3,749.8515625,749.6432291666666,-1,0,3844956
1743388460,1743388473,13,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 629 feature_id 9 batch_size 294 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 40,629,294,str\(\'KL\'\),2,str\(\'stdev\'\),0.999,40,9,0.22,4,0,None,i7149,4,750.01171875,749.72265625,-1,0.11681005956320317,3844955
1743388462,1743388475,13,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 401 feature_id 9 batch_size 236 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 37,401,236,str\(\'H\'\),3,str\(\'stdev\'\),0.999,37,9,0.21,4,0,None,i7146,4,750.66015625,750.4361979166666,-1,0.11945731303772336,3844965
1743388462,1743388482,20,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 544 feature_id 9 batch_size 286 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 1,544,286,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,1,9,0.25,6,0,None,i7147,6,750.34375,750.1848958333334,-1,0.28491065519523495,3844957
1743388462,1743388482,20,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 542 feature_id 9 batch_size 243 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 52,542,243,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,52,9,0.21,5,0,None,i7147,5,750.71484375,750.40625,-1,0.14262078093977498,3844962
1743388462,1743388482,20,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 1283 feature_id 9 batch_size 293 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 14,1283,293,str\(\'H\'\),3,str\(\'stdev\'\),0.999,14,9,0.22,4,0,None,i7147,4,751.29296875,751.1184895833334,-1,0.09695565850430178,3844961
1743388462,1743388482,20,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 9 batch_size 5000 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 61,5000,5000,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,61,9,0.2,4,0,None,i7147,4,750.2265625,750.0885416666666,-1,0,3844958
1743388462,1743388482,20,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 131 feature_id 9 batch_size 4959 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.4313459873417986 subsets 63,131,4959,str\(\'KL\'\),1,str\(\'stdev\'\),0.4313459873417986,63,9,0.2,4,0,None,i7147,4,750.8125,750.6744791666666,-1,0,3844959
1743388480,1743388493,13,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 9 batch_size 317 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 51,1,317,str\(\'KL\'\),2,str\(\'stdev\'\),0.999,51,9,0.2,4,0,None,i7149,4,749.80859375,749.5611979166666,-1,0.10489741892786235,3844969
1743388480,1743388493,13,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 9 batch_size 5000 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 1,5000,5000,str\(\'H\'\),3,str\(\'tstat\'\),0.999,1,9,0.2,3,0,None,i7142,3,751.375,751.1666666666666,-1,0,3844974
1743388481,1743388494,13,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 456 feature_id 9 batch_size 117 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 25,456,117,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,25,9,0.23,4,0,None,i7184,4,750.1171875,749.859375,-1,0.03871608206485771,3844967
1743388485,1743388498,13,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 812 feature_id 9 batch_size 172 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 32,812,172,str\(\'H\'\),2,str\(\'tstat\'\),0.999,32,9,0.21,4,0,None,i7144,4,751.02734375,750.6822916666666,-1,0.056915949702183985,3844973
1743388480,1743388499,19,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 9 batch_size 5000 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 1,5000,5000,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,1,9,0.2,6,0,None,i7142,6,751.0859375,750.9700520833334,-1,0,3844976
1743388480,1743388499,19,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 9 batch_size 4369 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 1,5000,4369,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,1,9,0.2,6,0,None,i7144,6,750.96484375,750.8138020833334,-1,0,3844971
1743388492,1743388505,13,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 835 feature_id 9 batch_size 3860 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 100,835,3860,str\(\'KL\'\),3,str\(\'stdev\'\),0.001,100,9,0.2,3,0,None,i7147,3,749.890625,749.7174479166666,-1,0,3844982
1743388492,1743388505,13,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 9 batch_size 5000 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 1,5000,5000,str\(\'KL\'\),3,str\(\'stdev\'\),0.001,1,9,0.2,3,0,None,i7147,3,750.96875,750.7955729166666,-1,0,3844980
1743388492,1743388505,13,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 4006 feature_id 9 batch_size 847 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 27,4006,847,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,27,9,0.2,3,0,None,i7140,3,749.84375,749.6119791666666,-1,0,3844986
1743388492,1743388505,13,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 586 feature_id 9 batch_size 535 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 36,586,535,str\(\'KL\'\),2,str\(\'stdev\'\),0.999,36,9,0.22,4,0,None,i7140,4,750.4296875,750.1614583333334,-1,0,3844984
1743388492,1743388511,19,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 576 feature_id 9 batch_size 256 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 29,576,256,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,29,9,0.24,5,0,None,i7147,5,750.2734375,750.0859375,-1,0.18563864990072798,3844978
1743388500,1743388513,13,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 9 batch_size 5000 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 60,5000,5000,str\(\'KL\'\),2,str\(\'stdev\'\),0.001,60,9,0.2,3,0,None,i7142,3,750.4921875,750.3268229166666,-1,0,3844992
1743388500,1743388513,13,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 1738 feature_id 9 batch_size 5000 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 61,1738,5000,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,61,9,0.2,4,0,None,i7138,4,751.76953125,751.6171875,-1,0,3844994
1743388500,1743388513,13,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 3027 feature_id 9 batch_size 5000 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 63,3027,5000,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,63,9,0.2,4,0,None,i7135,4,750.4140625,750.2421875,-1,0,3844996
1743388500,1743388513,13,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 4138 feature_id 9 batch_size 5000 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.5455039738996219 subsets 24,4138,5000,str\(\'KL\'\),1,str\(\'stdev\'\),0.5455039738996219,24,9,0.2,3,0,None,i7133,3,750.76953125,750.6171875,-1,0,3844998
1743388500,1743388513,13,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 747 feature_id 9 batch_size 297 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.8502937973215028 subsets 15,747,297,str\(\'KL\'\),1,str\(\'stdev\'\),0.8502937973215028,15,9,0.23,4,0,None,i7153,4,750.53125,750.3619791666666,-1,0.22303110522832562,3844990
1743388500,1743388519,19,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 911 feature_id 9 batch_size 297 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 1,911,297,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,1,9,0.25,6,0,None,i7184,6,750.31640625,750.1796875,-1,0.3213103904698875,3844988
1743388520,1743388533,13,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 566 feature_id 9 batch_size 414 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 49,566,414,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,49,9,0.22,4,0,None,i7147,4,750.2265625,749.9088541666666,-1,0.1369953673064196,3845003
1743388520,1743388533,13,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 9 batch_size 4132 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 1,5000,4132,str\(\'H\'\),3,str\(\'tstat\'\),0.999,1,9,0.2,3,0,None,i7150,3,751.9453125,751.4622395833334,-1,0,3845001
1743388521,1743388534,13,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 9 batch_size 5000 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 1,5000,5000,str\(\'KL\'\),2,str\(\'tstat\'\),0.001,1,9,0.2,3,0,None,i7164,3,749.8828125,749.6875,-1,0,3844999
1743388520,1743388539,19,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 1183 feature_id 9 batch_size 202 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 35,1183,202,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,35,9,0.21,4,0,None,i7142,4,754.95703125,751.8580729166666,-1,0.07379219060225016,3845007
1743388520,1743388539,19,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 9 batch_size 5000 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.08537811992052806 subsets 1,1,5000,str\(\'KL\'\),1,str\(\'stdev\'\),0.08537811992052806,1,9,0.2,6,0,None,i7144,6,750.328125,750.2005208333334,-1,0,3845005
1743393025,1743393038,13,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 9 batch_size 630 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 18,5000,630,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,18,9,0.22,4,0,None,i7142,4,750.43359375,750.22265625,-1,0,3851662
1743393044,1743393057,13,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 9 batch_size 3273 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 28,5000,3273,str\(\'KL\'\),2,str\(\'tstat\'\),0.001,28,9,0.2,3,0,None,i7147,3,750.15234375,749.9661458333334,-1,0,3851670
1743393045,1743393058,13,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 434 feature_id 9 batch_size 402 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 1,434,402,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,1,9,0.22,4,0,None,i7163,4,750.02734375,749.8020833333334,-1,0.13302448709463932,3851665
1743393051,1743393070,19,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 9 batch_size 380 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 16,5000,380,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,16,9,0.23,4,0,None,i7144,4,751.87890625,751.6848958333334,-1,0.09298477829252151,3851679
1743393064,1743393078,14,module load GCCcore/10.3.0 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 9 batch_size 579 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 26,5000,579,str\(\'KL\'\),2,str\(\'stdev\'\),0.999,26,9,0.22,4,0,None,i7150,4,749.953125,749.68359375,-1,0,3851689
1743393080,1743393094,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4773 feature_id 9 batch_size 479 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 27,4773,479,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,27,9,0.22,3,0,None,i7143,3,751.22265625,750.9609375,-1,0,3851703
1743393081,1743393094,13,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 4461 feature_id 9 batch_size 842 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 18,4461,842,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,18,9,0.23,4,0,None,i7184,4,750.94140625,750.7395833333334,-1,0.1743878226340172,3851695
1743393085,1743393098,13,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 9 batch_size 2788 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 28,1,2788,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,28,9,0.2,3,0,None,i7141,3,750.87109375,750.6861979166666,-1,0.2610853739245533,3851714
1743393106,1743393119,13,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 9 batch_size 3975 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 34,5000,3975,str\(\'KL\'\),2,str\(\'tstat\'\),0.001,34,9,0.2,3,0,None,i7143,3,750.078125,749.8736979166666,-1,0,3851720
1743393111,1743393124,13,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 9 batch_size 3162 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 25,1,3162,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,25,9,0.2,3,0,None,i7139,3,751.30859375,751.1549479166666,-1,0,3851733
1743393125,1743393138,13,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 9 batch_size 675 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 19,5000,675,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,19,9,0.22,4,0,None,i7138,4,749.875,749.7278645833334,-1,0.008603573792190603,3851742
1743393145,1743393158,13,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 9 batch_size 3391 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 84,5000,3391,str\(\'H\'\),3,str\(\'stdev\'\),0.001,84,9,0.2,3,0,None,i7138,3,751.3046875,751.13671875,-1,0,3851761
1743393145,1743393158,13,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 9 batch_size 2242 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 29,5000,2242,str\(\'KL\'\),2,str\(\'stdev\'\),0.999,29,9,0.2,3,0,None,i7115,3,750.796875,750.53125,-1,0,3851782
1743393145,1743393158,13,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 344 feature_id 9 batch_size 3827 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 33,344,3827,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,33,9,0.2,3,0,None,i7078,3,751.3515625,751.15625,-1,0,3851792
1743393145,1743393159,14,module load GCCcore/10.3.0 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 9 batch_size 3881 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 23,1,3881,str\(\'H\'\),2,str\(\'tstat\'\),0.999,23,9,0.2,3,0,None,i7014,3,750.97265625,750.8046875,-1,0,3851843
1743393146,1743393159,13,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 9 batch_size 2897 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 25,5000,2897,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,25,9,0.2,3,0,None,i7002,3,751.1171875,750.7955729166666,-1,0,3851889
1743393146,1743393159,13,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 9 batch_size 381 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 40,1,381,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,40,9,0.21,3,0,None,i7019,3,749.9453125,749.7122395833334,-1,0,3851813
1743393140,1743393160,20,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 395 feature_id 9 batch_size 555 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 17,395,555,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,17,9,0.22,4,0,None,i7140,4,750.6484375,750.4361979166666,-1,0.07313037723362012,3851752
1743393145,1743393164,19,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 9 batch_size 2466 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 80,5000,2466,str\(\'KL\'\),3,str\(\'stdev\'\),0.001,80,9,0.2,3,0,None,i7028,3,750.7578125,750.5807291666666,-1,0,3851804
1743393146,1743393165,19,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 9 batch_size 384 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 15,5000,384,str\(\'H\'\),1,str\(\'stdev\'\),0.999,15,9,0.23,4,0,None,i7129,4,750.94140625,750.7708333333334,-1,0.10092653871608206,3851773
1743393146,1743393165,19,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 9 batch_size 511 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 24,5000,511,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,24,9,0.21,4,0,None,i7017,4,750.02734375,749.7161458333334,-1,0,3851824
1743393146,1743393165,19,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 9 batch_size 456 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 18,5000,456,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,18,9,0.24,4,0,None,i7015,4,750.2734375,750.1458333333334,-1,0.09298477829252151,3851835
1743393146,1743393165,19,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 9 batch_size 2500 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 1,5000,2500,str\(\'H\'\),3,str\(\'stdev\'\),0.999,1,9,0.2,3,0,None,i7007,3,750.7109375,750.5403645833334,-1,0,3851866
1743393146,1743393165,19,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 9 batch_size 3376 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 32,5000,3376,str\(\'KL\'\),2,str\(\'stdev\'\),0.999,32,9,0.2,3,0,None,i7004,3,751.2421875,751.05859375,-1,0,3851878
1743393146,1743393165,19,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 9 batch_size 2577 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 26,5000,2577,str\(\'H\'\),1,str\(\'tstat\'\),0.999,26,9,0.2,3,0,None,i7011,3,751.21484375,751.0390625,-1,0,3851854
1743393165,1743393177,12,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 9 batch_size 305 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 17,5000,305,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,17,9,0.22,4,0,None,i7115,4,751.875,751.6432291666666,-1,0.14592984778292523,3851897
1743393172,1743393185,13,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 9 batch_size 474 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 19,5000,474,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,19,9,0.22,4,0,None,i7133,4,750.453125,750.25,-1,0.15684976836532097,3851909
1743393185,1743393197,12,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 9 batch_size 497 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 14,5000,497,str\(\'H\'\),1,str\(\'tstat\'\),0.999,14,9,0.24,4,0,None,i7121,4,750.96875,750.7630208333334,-1,0.16446062210456652,3851919
1743393200,1743393213,13,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 9 batch_size 2404 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 27,1,2404,str\(\'KL\'\),2,str\(\'stdev\'\),0.001,27,9,0.2,3,0,None,i7133,3,751.265625,751.0013020833334,-1,0,3851929
1743393205,1743393218,13,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 9 batch_size 784 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 19,5000,784,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,19,9,0.22,4,0,None,i7044,4,750.171875,750.015625,-1,0,3851940
1743397703,1743397716,13,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 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 15,1,1,str\(\'H\'\),1,str\(\'stdev\'\),0.999,15,9,None,None,1,None,i7143,3857703
1743397709,1743397722,13,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 4917 feature_id 9 batch_size 3472 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 8,4917,3472,str\(\'H\'\),2,str\(\'stdev\'\),0.001,8,9,0.2,3,0,None,i7140,3,750.64453125,750.4947916666666,-1,0,3857714
1743397709,1743397722,13,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 1271 feature_id 9 batch_size 5000 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 12,1271,5000,str\(\'H\'\),2,str\(\'tstat\'\),0.999,12,9,0.2,3,0,None,i7139,3,750.41796875,750.21875,-1,0,3857716
1743397709,1743397722,13,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 3670 feature_id 9 batch_size 224 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 39,3670,224,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,39,9,0.22,4,0,None,i7183,4,750.3203125,750.0651041666666,-1,0.07412309728656519,3857706
1743397709,1743397722,13,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 2167 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 16,2167,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,16,9,None,None,1,None,i7142,3857709
1743397709,1743397722,13,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 3265 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 16,3265,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,16,9,None,None,1,None,i7142,3857711
1743397729,1743397742,13,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 2137 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 15,2137,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,15,9,None,None,1,None,i7170,3857719
1743397729,1743397742,13,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 3186 feature_id 9 batch_size 4442 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 22,3186,4442,str\(\'H\'\),1,str\(\'tstat\'\),0.999,22,9,0.2,3,0,None,i7144,3,750.4296875,750.26171875,-1,0,3857725
1743397729,1743397742,13,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 9 batch_size 568 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 39,5000,568,str\(\'KL\'\),3,str\(\'stdev\'\),0.999,39,9,0.22,4,0,None,i7164,4,751.21484375,750.984375,-1,0,3857722
1743397733,1743397746,13,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 278 feature_id 9 batch_size 3249 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 3,278,3249,str\(\'H\'\),2,str\(\'tstat\'\),0.999,3,9,0.2,3,0,None,i7141,3,750.34375,750.1848958333334,-1,0,3857737
1743397733,1743397746,13,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 850 feature_id 9 batch_size 3345 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 1,850,3345,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,1,9,0.2,4,0,None,i7142,4,751.26171875,751.0846354166666,-1,0,3857734
1743397734,1743397747,13,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 4191 feature_id 9 batch_size 3224 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 39,4191,3224,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,39,9,0.2,3,0,None,i7174,3,750.8125,750.6184895833334,-1,0,3857729
1743397734,1743397753,19,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 1934 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 39,1934,1,str\(\'H\'\),3,str\(\'tstat\'\),0.001,39,9,0.24,7,0,None,i7168,7,750.2734375,750.01953125,-1,0.0843812045003309,3857731
1743397749,1743397762,13,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 9 batch_size 3778 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 8,1,3778,str\(\'H\'\),2,str\(\'tstat\'\),0.001,8,9,0.2,3,0,None,i7179,3,750.66796875,750.5013020833334,-1,0,3857740
1743397749,1743397762,13,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 9 batch_size 4188 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 13,5000,4188,str\(\'H\'\),2,str\(\'stdev\'\),0.001,13,9,0.2,3,0,None,i7161,3,750.03125,749.8828125,-1,0,3857746
1743397749,1743397768,19,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 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 40,1,1,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,40,9,0.23,7,0,None,i7164,7,734.0625,733.7552083333334,-1,0.0843812045003309,3857743
1743397763,1743397776,13,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 4690 feature_id 9 batch_size 748 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 37,4690,748,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,37,9,0.22,4,0,None,i7171,4,749.84765625,749.6171875,-1,0,3857752
1743397763,1743397776,13,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 9 batch_size 538 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 37,5000,538,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,37,9,0.22,4,0,None,i7178,4,751.2890625,751.0364583333334,-1,0.17802779616148245,3857749
1743397763,1743397777,14,module load GCCcore/10.3.0 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 9 batch_size 5000 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 64,1,5000,str\(\'H\'\),3,str\(\'stdev\'\),0.001,64,9,0.2,4,0,None,i7142,4,751.171875,750.9869791666666,-1,0,3857758
1743397769,1743397782,13,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 9 batch_size 5000 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 15,1,5000,str\(\'H\'\),3,str\(\'stdev\'\),0.001,15,9,0.2,3,0,None,i7161,3,749.71875,749.546875,-1,0,3857765
1743397769,1743397782,13,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 9 batch_size 3046 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 39,5000,3046,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,39,9,0.2,3,0,None,i7161,3,750.46875,750.2825520833334,-1,0,3857767
1743397769,1743397782,13,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 441 feature_id 9 batch_size 4339 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 22,441,4339,str\(\'H\'\),1,str\(\'tstat\'\),0.001,22,9,0.2,3,0,None,i7170,3,751.3515625,751.1458333333334,-1,0,3857763
1743397763,1743397783,20,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 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 39,5000,1,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,39,9,0.24,7,0,None,i7163,7,751.64453125,751.37890625,-1,0.0843812045003309,3857755
1743397770,1743397783,13,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 4942 feature_id 9 batch_size 487 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 37,4942,487,str\(\'H\'\),3,str\(\'tstat\'\),0.001,37,9,0.21,4,0,None,i7158,4,750.02734375,749.8151041666666,-1,0.16115155526141628,3857769
1743397769,1743397788,19,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 434 feature_id 9 batch_size 729 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 16,434,729,str\(\'H\'\),1,str\(\'tstat\'\),0.999,16,9,0.22,5,0,None,i7179,5,751.38671875,751.2096354166666,-1,0.062210456651224356,3857761
1743397789,1743397802,13,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 9 batch_size 3575 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 58,1,3575,str\(\'H\'\),3,str\(\'tstat\'\),0.001,58,9,0.2,3,0,None,i7170,3,750.6875,750.515625,-1,0,3857777
1743397789,1743397802,13,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 2549 feature_id 9 batch_size 3514 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 12,2549,3514,str\(\'H\'\),3,str\(\'tstat\'\),0.001,12,9,0.2,3,0,None,i7176,3,751.546875,751.3684895833334,-1,0,3857774
1743397789,1743397802,13,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 823 feature_id 9 batch_size 370 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 18,823,370,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,18,9,0.23,4,0,None,i7178,4,750.484375,750.2786458333334,-1,0.19556585043017868,3857771
1743397789,1743397802,13,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 4388 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 14,4388,1,str\(\'H\'\),1,str\(\'stdev\'\),0.999,14,9,None,None,1,None,i7164,3857779
1743397794,1743397807,13,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 4139 feature_id 9 batch_size 998 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 17,4139,998,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,17,9,0.22,4,0,None,i7163,4,750.78515625,750.5729166666666,-1,0.32925215089344806,3857782
1743402454,1743402467,13,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 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 16,1,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,16,9,None,None,1,None,i7148,3864357
1743402454,1743402467,13,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 9 batch_size 2650 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 42,1,2650,str\(\'H\'\),3,str\(\'stdev\'\),0.999,42,9,0.2,3,0,None,i7137,3,750.2734375,750.1080729166666,-1,0,3864408
1743402455,1743402468,13,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 3780 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 18,3780,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,18,9,None,None,1,None,i7151,3864330
1743402455,1743402468,13,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 3634 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 17,3634,1,str\(\'H\'\),1,str\(\'stdev\'\),0.999,17,9,None,None,1,None,i7151,3864334
1743402455,1743402468,13,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 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 21,1,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,21,9,None,None,1,None,i7141,3864395
1743402454,1743402473,19,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 9 batch_size 91 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 12,5000,91,str\(\'KL\'\),3,str\(\'stdev\'\),0.001,12,9,0.23,4,0,None,i7148,4,750.39453125,750.2135416666666,-1,0.06121773659827928,3864353
1743402454,1743402473,19,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 9 batch_size 5000 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 77,1,5000,str\(\'KL\'\),2,str\(\'tstat\'\),0.001,77,9,0.2,3,0,None,i7148,3,749.87890625,749.703125,-1,0,3864355
1743402454,1743402473,19,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 9 batch_size 2069 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 26,5000,2069,str\(\'KL\'\),3,str\(\'stdev\'\),0.999,26,9,0.2,3,0,None,i7149,3,750.359375,750.1966145833334,-1,0,3864351
1743402454,1743402473,19,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 9 batch_size 3211 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 77,1,3211,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,77,9,0.2,3,0,None,i7143,3,750.3671875,750.1927083333334,-1,0,3864387
1743402454,1743402474,20,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 9 batch_size 1092 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 20,5000,1092,str\(\'KL\'\),3,str\(\'stdev\'\),0.999,20,9,0.2,3,0,None,i7146,3,749.98046875,749.7942708333334,-1,0,3864370
1743402454,1743402474,20,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 9 batch_size 5000 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 50,5000,5000,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,50,9,0.2,3,0,None,i7146,3,749.8671875,749.69140625,-1,0,3864373
1743402454,1743402474,20,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 9 batch_size 5000 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 23,1,5000,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,23,9,0.2,3,0,None,i7140,3,749.80078125,749.5963541666666,-1,0,3864400
1743402455,1743402474,19,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 442 feature_id 9 batch_size 208 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 15,442,208,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,15,9,0.21,4,0,None,i7142,4,750.359375,750.1067708333334,-1,0.06882859033752482,3864391
1743402455,1743402474,19,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 4571 feature_id 9 batch_size 3167 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 100,4571,3167,str\(\'H\'\),3,str\(\'tstat\'\),0.999,100,9,0.2,3,0,None,i7147,3,747.80859375,747.6575520833334,-1,0,3864359
1743402455,1743402474,19,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 3418 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 17,3418,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,17,9,None,None,1,None,i7147,3864364
1743402455,1743402474,19,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 4736 feature_id 9 batch_size 198 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 11,4736,198,str\(\'H\'\),3,str\(\'tstat\'\),0.001,11,9,0.21,4,0,None,i7147,4,749.90234375,749.6927083333334,-1,0.06551952349437459,3864362
1743402455,1743402474,19,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 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 17,5000,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,17,9,None,None,1,None,i7147,3864366
1743402455,1743402474,19,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 729 feature_id 9 batch_size 5000 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 53,729,5000,str\(\'H\'\),2,str\(\'tstat\'\),0.001,53,9,0.2,3,0,None,i7147,3,751.015625,750.8502604166666,-1,0,3864365
1743402455,1743402474,19,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 9 batch_size 2833 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 96,1,2833,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,96,9,0.2,3,0,None,i7144,3,751.22265625,751.0572916666666,-1,0,3864382
1743402455,1743402474,19,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 9 batch_size 696 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 14,5000,696,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,14,9,0.22,4,0,None,i7150,4,751.2109375,750.9869791666666,-1,0,3864346
1743402455,1743402474,19,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 9 batch_size 774 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 19,5000,774,str\(\'KL\'\),3,str\(\'stdev\'\),0.999,19,9,0.22,4,0,None,i7150,4,749.9375,749.7734375,-1,0,3864339
1743402455,1743402474,19,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 9 batch_size 5000 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 100,1,5000,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,100,9,0.2,3,0,None,i7145,3,750.484375,750.3255208333334,-1,0,3864379
1743402455,1743402475,20,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 2271 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 18,2271,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,18,9,None,None,1,None,i7152,3864325
1743402455,1743402475,20,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 9 batch_size 5000 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 100,5000,5000,str\(\'H\'\),3,str\(\'stdev\'\),0.999,100,9,0.2,3,0,None,i7139,3,745.82421875,745.6575520833334,-1,0,3864403
1743402458,1743402477,19,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 9 batch_size 971 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 20,5000,971,str\(\'H\'\),3,str\(\'tstat\'\),0.999,20,9,0.21,4,0,None,i7147,4,749.6328125,749.4140625,-1,0,3864363
1743402458,1743402477,19,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 1487 feature_id 9 batch_size 561 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 16,1487,561,str\(\'KL\'\),3,str\(\'stdev\'\),0.001,16,9,0.22,4,0,None,i7147,4,750.6328125,750.47265625,-1,0.18563864990072798,3864361
1743402454,1743402480,26,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 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 100,1,1,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,100,9,0.24,7,0,None,i7149,7,751.0546875,750.8502604166666,-1,0.0843812045003309,3864348
1743402455,1743402480,25,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 2097 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 83,2097,1,str\(\'H\'\),3,str\(\'stdev\'\),0.001,83,9,0.23,6,0,None,i7147,6,749.3515625,749.2018229166666,-1,0.0843812045003309,3864367
1743402455,1743402481,26,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 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 100,5000,1,str\(\'KL\'\),3,str\(\'stdev\'\),0.001,100,9,0.23,7,0,None,i7145,7,750.09765625,749.94140625,-1,0.0843812045003309,3864376
1743402455,1743402481,26,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 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 8,5000,1,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,8,9,0.24,7,0,None,i7150,7,749.76953125,749.56640625,-1,0.0843812045003309,3864343
1743407862,1743407875,13,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 9 batch_size 1598 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 75,1,1598,str\(\'KL\'\),3,str\(\'stdev\'\),0.001,75,9,0.2,3,0,None,i7143,3,749.97265625,749.8151041666666,-1,0,3872086
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 5000 feature_id 9 batch_size 1483 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 58,5000,1483,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,58,9,0.2,3,0,None,i7133,3,751.6484375,751.4231770833334,-1,0.3199867637326274,3872152
1743407858,1743407877,19,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 3213 feature_id 9 batch_size 694 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 36,3213,694,str\(\'H\'\),3,str\(\'stdev\'\),0.999,36,9,0.22,4,0,None,i7143,4,750.4921875,750.3333333333334,-1,0,3872089
1743407858,1743407877,19,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 9 batch_size 1902 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 85,1,1902,str\(\'H\'\),3,str\(\'stdev\'\),0.001,85,9,0.2,3,0,None,i7140,3,750.2421875,750.0924479166666,-1,0,3872102
1743407858,1743407877,19,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 9 batch_size 724 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 38,1,724,str\(\'H\'\),3,str\(\'stdev\'\),0.999,38,9,0.22,4,0,None,i7140,4,750.92578125,750.7513020833334,-1,0,3872100
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 4529 feature_id 9 batch_size 1650 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 97,4529,1650,str\(\'H\'\),3,str\(\'stdev\'\),0.001,97,9,0.2,3,0,None,i7138,3,750.7734375,750.6015625,-1,0,3872114
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 4681 feature_id 9 batch_size 1771 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 72,4681,1771,str\(\'H\'\),3,str\(\'stdev\'\),0.999,72,9,0.2,3,0,None,i7134,3,750.6640625,750.4947916666666,-1,0,3872145
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 4796 feature_id 9 batch_size 786 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 49,4796,786,str\(\'KL\'\),3,str\(\'stdev\'\),0.999,49,9,0.22,4,0,None,i7134,4,750.92578125,750.7408854166666,-1,0,3872149
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 1 feature_id 9 batch_size 1577 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 69,1,1577,str\(\'H\'\),3,str\(\'stdev\'\),0.999,69,9,0.2,3,0,None,i7144,3,749.9453125,749.7903645833334,-1,0,3872083
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 1860 feature_id 9 batch_size 624 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 35,1860,624,str\(\'KL\'\),3,str\(\'stdev\'\),0.999,35,9,0.22,4,0,None,i7137,4,749.8984375,749.7122395833334,-1,0,3872117
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 710 feature_id 9 batch_size 1613 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 66,710,1613,str\(\'KL\'\),3,str\(\'stdev\'\),0.999,66,9,0.2,3,0,None,i7139,3,750.09765625,749.94140625,-1,0,3872107
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 4722 feature_id 9 batch_size 1027 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 13,4722,1027,str\(\'H\'\),1,str\(\'tstat\'\),0.001,13,9,0.22,4,0,None,i7139,4,750.546875,750.34375,-1,0,3872106
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 767 feature_id 9 batch_size 266 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 15,767,266,str\(\'H\'\),1,str\(\'stdev\'\),0.999,15,9,0.23,4,0,None,i7139,4,751.46875,751.3411458333334,-1,0.2187293183322303,3872104
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 1624 feature_id 9 batch_size 57 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 15,1624,57,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,15,9,0.23,4,0,None,i7142,4,750.8671875,750.7044270833334,-1,0.03772336201191264,3872091
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 4097 feature_id 9 batch_size 2025 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 100,4097,2025,str\(\'H\'\),3,str\(\'stdev\'\),0.001,100,9,0.2,3,0,None,i7142,3,750.25390625,750.0768229166666,-1,0,3872094
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 5000 feature_id 9 batch_size 1498 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 56,5000,1498,str\(\'H\'\),3,str\(\'stdev\'\),0.999,56,9,0.2,3,0,None,i7142,3,750.140625,749.9791666666666,-1,0.3299139642620781,3872093
1743407860,1743407880,20,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 3347 feature_id 9 batch_size 227 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 13,3347,227,str\(\'H\'\),1,str\(\'tstat\'\),0.999,13,9,0.24,4,0,None,i7141,4,751.68359375,751.4856770833334,-1,0.16479152878888154,3872097
1743407860,1743407880,20,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 9 batch_size 1474 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 51,1,1474,str\(\'H\'\),3,str\(\'stdev\'\),0.001,51,9,0.2,3,0,None,i7141,3,749.85546875,749.6809895833334,-1,0.314030443414957,3872099
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 1352 feature_id 9 batch_size 4652 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 42,1352,4652,str\(\'KL\'\),2,str\(\'tstat\'\),0.001,42,9,0.2,3,0,None,i7132,3,750.60546875,750.4479166666666,-1,0,3872155
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 1 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 1,1,1,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,1,9,0.24,7,0,None,i7138,7,750.7109375,750.4856770833334,-1,0.0843812045003309,3872111
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 1 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 1,1,1,str\(\'KL\'\),3,str\(\'stdev\'\),0.001,1,9,0.23,7,0,None,i7137,7,751.18359375,751.0286458333334,-1,0.0843812045003309,3872116
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 1 feature_id 9 batch_size 165 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 15,1,165,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,15,9,0.25,5,0,None,i7139,5,750.3203125,750.1302083333334,-1,0.16379880873593647,3872109
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 597 feature_id 9 batch_size 1785 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 88,597,1785,str\(\'KL\'\),3,str\(\'stdev\'\),0.999,88,9,0.2,3,0,None,i7136,3,751.578125,751.4205729166666,-1,0,3872129
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 1 feature_id 9 batch_size 1449 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 72,1,1449,str\(\'KL\'\),3,str\(\'stdev\'\),0.999,72,9,0.2,3,0,None,i7136,3,750.80078125,750.6380208333334,-1,0.29748510919920584,3872121
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 1 feature_id 9 batch_size 2260 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 100,1,2260,str\(\'KL\'\),3,str\(\'stdev\'\),0.999,100,9,0.2,3,0,None,i7136,3,751.10546875,750.9427083333334,-1,0,3872124
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 4238 feature_id 9 batch_size 1555 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 38,4238,1555,str\(\'H\'\),3,str\(\'tstat\'\),0.001,38,9,0.2,3,0,None,i7136,3,751.15625,750.9856770833334,-1,0,3872127
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 5000 feature_id 9 batch_size 2986 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 24,5000,2986,str\(\'H\'\),1,str\(\'tstat\'\),0.001,24,9,0.2,3,0,None,i7135,3,750.59375,750.3984375,-1,0,3872135
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 4424 feature_id 9 batch_size 265 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 16,4424,265,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,16,9,0.24,4,0,None,i7135,4,750.546875,750.4140625,-1,0.2154202514890801,3872133
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 5000 feature_id 9 batch_size 663 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 28,5000,663,str\(\'H\'\),2,str\(\'stdev\'\),0.999,28,9,0.22,4,0,None,i7135,4,750.09765625,749.83984375,-1,0,3872138
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 3790 feature_id 9 batch_size 4682 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 41,3790,4682,str\(\'H\'\),1,str\(\'tstat\'\),0.001,41,9,0.2,3,0,None,i7135,3,750.83203125,750.66015625,-1,0,3872141
1743414801,1743414852,51,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 4716 feature_id 9 batch_size 1033 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 19,4716,1033,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,19,9,0.2,4,0,None,i7117,4,750.3828125,750.0716145833334,-1,0,3879312
1743414799,1743414857,58,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 4023 feature_id 9 batch_size 4297 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 80,4023,4297,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,80,9,0.2,4,0,None,i7119,4,750.9765625,750.80078125,-1,0,3879298
1743414805,1743414868,63,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 5000 feature_id 9 batch_size 1476 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 13,5000,1476,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,13,9,0.2,3,0,None,i7122,3,750.98828125,750.6822916666666,-1,0.31535407015221706,3879260
1743414805,1743414868,63,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 433 feature_id 9 batch_size 579 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 23,433,579,str\(\'KL\'\),3,str\(\'stdev\'\),0.999,23,9,0.22,4,0,None,i7122,4,751.0859375,750.8919270833334,-1,0,3879254
1743414801,1743414870,69,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 1 feature_id 9 batch_size 894 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 22,1,894,str\(\'KL\'\),3,str\(\'stdev\'\),0.999,22,9,0.2,3,0,None,i7127,3,750.66015625,750.4765625,-1,0,3879199
1743414801,1743414870,69,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 188 feature_id 9 batch_size 1224 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 15,188,1224,str\(\'KL\'\),2,str\(\'stdev\'\),0.999,15,9,0.2,3,0,None,i7127,3,750.51171875,750.26953125,-1,0,3879194
1743414919,1743414982,63,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 3673 feature_id 9 batch_size 341 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 23,3673,341,str\(\'KL\'\),3,str\(\'stdev\'\),0.001,23,9,0.21,4,0,None,i7124,4,749.64453125,749.484375,-1,0.015552614162806089,3879232
1743414919,1743414982,63,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 2276 feature_id 9 batch_size 5000 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 25,2276,5000,str\(\'KL\'\),2,str\(\'tstat\'\),0.001,25,9,0.2,3,0,None,i7124,3,750.62890625,750.453125,-1,0,3879222
1743414919,1743414982,63,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 4385 feature_id 9 batch_size 4088 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 27,4385,4088,str\(\'H\'\),3,str\(\'stdev\'\),0.001,27,9,0.2,3,0,None,i7124,3,750.6953125,750.5481770833334,-1,0,3879227
1743414928,1743414991,63,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 118 feature_id 9 batch_size 850 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 18,118,850,str\(\'KL\'\),2,str\(\'stdev\'\),0.999,18,9,0.2,3,0,None,i7126,3,749.6953125,749.4270833333334,-1,0,3879213
1743414928,1743414991,63,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 2257 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 19,2257,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,19,9,None,None,1,None,i7126,3879209
1743414928,1743414991,63,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 5000 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 18,5000,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,18,9,None,None,1,None,i7126,3879217
1743414928,1743414991,63,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 4888 feature_id 9 batch_size 1945 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 8,4888,1945,str\(\'H\'\),2,str\(\'tstat\'\),0.999,8,9,0.2,3,0,None,i7126,3,749.96875,749.6783854166666,-1,0,3879204
1743414951,1743415008,57,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 127 feature_id 9 batch_size 708 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 23,127,708,str\(\'KL\'\),3,str\(\'stdev\'\),0.999,23,9,0.22,4,0,None,i7115,4,751.0703125,750.8815104166666,-1,0,3879346
1743414951,1743415008,57,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 890 feature_id 9 batch_size 3409 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 21,890,3409,str\(\'H\'\),1,str\(\'stdev\'\),0.999,21,9,0.2,3,0,None,i7115,3,750.12109375,749.9791666666666,-1,0,3879340
1743414958,1743415015,57,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 4987 feature_id 9 batch_size 4124 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 46,4987,4124,str\(\'H\'\),3,str\(\'stdev\'\),0.999,46,9,0.2,3,0,None,i7123,3,749.65625,749.48828125,-1,0,3879237
1743414958,1743415015,57,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 4865 feature_id 9 batch_size 2162 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 9,4865,2162,str\(\'KL\'\),2,str\(\'stdev\'\),0.999,9,9,0.2,3,0,None,i7123,3,750.12109375,749.8567708333334,-1,0,3879242
1743414958,1743415015,57,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 992 feature_id 9 batch_size 4456 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 20,992,4456,str\(\'H\'\),3,str\(\'tstat\'\),0.999,20,9,0.2,3,0,None,i7123,3,750.64453125,750.4765625,-1,0,3879247
1743414971,1743415034,63,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 3427 feature_id 9 batch_size 2308 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 1,3427,2308,str\(\'H\'\),2,str\(\'stdev\'\),0.999,1,9,0.2,4,0,None,i7114,4,749.55859375,749.3190104166666,-1,0.10225016545334216,3879359
1743414979,1743415035,56,module load GCCcore/10.3.0 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 9 batch_size 4316 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 62,1,4316,str\(\'KL\'\),2,str\(\'tstat\'\),0.001,62,9,0.2,3,0,None,i7121,3,749.35546875,749.2005208333334,-1,0,3879272
1743414979,1743415035,56,module load GCCcore/10.3.0 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 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 20,5000,1,str\(\'H\'\),1,str\(\'stdev\'\),0.999,20,9,None,None,1,None,i7121,3879266
1743414971,1743415040,69,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 4315 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 18,4315,1,str\(\'H\'\),2,str\(\'stdev\'\),0.001,18,9,0.23,15,0,None,i7114,15,750.3359375,750.1455078125,-1,0.0843812045003309,3879352
1743414992,1743415043,51,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 551 feature_id 9 batch_size 1551 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 13,551,1551,str\(\'H\'\),2,str\(\'stdev\'\),0.999,13,9,0.2,3,0,None,i7116,3,751.11328125,750.859375,-1,0,3879333
1743414992,1743415043,51,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 5000 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 17,5000,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,17,9,None,None,1,None,i7116,3879320
1743414992,1743415049,57,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 2187 feature_id 9 batch_size 446 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 23,2187,446,str\(\'KL\'\),3,str\(\'stdev\'\),0.001,23,9,0.22,4,0,None,i7116,4,750.08984375,749.9036458333334,-1,0.14758438120450032,3879326
1743415000,1743415050,50,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 4305 feature_id 9 batch_size 2721 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 6,4305,2721,str\(\'KL\'\),2,str\(\'tstat\'\),0.001,6,9,0.2,3,0,None,i7120,3,749.77734375,749.4830729166666,-1,0,3879278
1743415000,1743415050,50,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 1 feature_id 9 batch_size 4521 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 63,1,4521,str\(\'H\'\),2,str\(\'tstat\'\),0.999,63,9,0.2,3,0,None,i7120,3,751.09765625,750.9296875,-1,0,3879291
1743415000,1743415050,50,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 1 feature_id 9 batch_size 4153 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 89,1,4153,str\(\'H\'\),3,str\(\'tstat\'\),0.999,89,9,0.2,3,0,None,i7120,3,751.1875,751.01953125,-1,0,3879284
1743415005,1743415056,51,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 4589 feature_id 9 batch_size 5000 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 34,4589,5000,str\(\'H\'\),1,str\(\'tstat\'\),0.999,34,9,0.2,4,0,None,i7113,4,751.26171875,751.0755208333334,-1,0,3879373
1743415005,1743415056,51,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 177 feature_id 9 batch_size 1162 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 24,177,1162,str\(\'KL\'\),3,str\(\'stdev\'\),0.999,24,9,0.2,3,0,None,i7113,3,750.03515625,749.8515625,-1,0,3879365
1743418989,1743419046,57,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 686 feature_id 9 batch_size 5000 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 89,686,5000,str\(\'KL\'\),2,str\(\'stdev\'\),0.999,89,9,0.2,3,0,None,i7070,3,751.19921875,751.0481770833334,-1,0,3886343
1743418989,1743419046,57,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 163 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 23,163,1,str\(\'H\'\),1,str\(\'stdev\'\),0.001,23,9,None,None,1,None,i7070,3886337
1743418998,1743419055,57,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 110 feature_id 9 batch_size 5000 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.04814258982104731 subsets 100,110,5000,str\(\'KL\'\),2,str\(\'stdev\'\),0.04814258982104731,100,9,0.2,4,0,None,i7069,4,749.484375,749.3020833333334,-1,0,3886349
1743419052,1743419102,50,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 1009 feature_id 9 batch_size 1125 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.3273115586402939 subsets 26,1009,1125,str\(\'KL\'\),3,str\(\'stdev\'\),0.3273115586402939,26,9,0.2,3,0,None,i7068,3,750.3515625,750.1653645833334,-1,0,3886373
1743419052,1743419102,50,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 3928 feature_id 9 batch_size 93 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.7749578225840483 subsets 20,3928,93,str\(\'H\'\),1,str\(\'stdev\'\),0.7749578225840483,20,9,0.22,4,0,None,i7068,4,750.98828125,750.8541666666666,-1,0,3886367
1743419052,1743419102,50,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 3871 feature_id 9 batch_size 615 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.4508417436193695 subsets 24,3871,615,str\(\'KL\'\),3,str\(\'stdev\'\),0.4508417436193695,24,9,0.22,4,0,None,i7068,4,750.8125,750.6419270833334,-1,0,3886364
1743419055,1743419111,56,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4175 feature_id 9 batch_size 1077 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.35797837953814915 subsets 27,4175,1077,str\(\'KL\'\),3,str\(\'tstat\'\),0.35797837953814915,27,9,0.2,3,0,None,i7066,3,751.125,750.8984375,-1,0,3886402
1743419055,1743419111,56,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4571 feature_id 9 batch_size 248 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.509546066750684 subsets 23,4571,248,str\(\'KL\'\),3,str\(\'stdev\'\),0.509546066750684,23,9,0.21,4,0,None,i7066,4,749.390625,749.2291666666666,-1,0.08206485771012574,3886391
1743419055,1743419111,56,module load GCCcore/10.3.0 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 9 batch_size 9 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.3546160393269794 subsets 22,4799,9,str\(\'H\'\),1,str\(\'stdev\'\),0.3546160393269794,22,9,0.22,5,0,None,i7066,5,750.87109375,750.7096354166666,-1,0.008603573792190603,3886399
1743419076,1743419114,38,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 186 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 31,186,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,31,9,None,None,1,None,i7095,3886302
1743419069,1743419120,51,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 1406 feature_id 9 batch_size 3300 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.4047164478142393 subsets 18,1406,3300,str\(\'KL\'\),2,str\(\'tstat\'\),0.4047164478142393,18,9,0.2,3,0,None,i7067,3,751.09765625,750.921875,-1,0,3886377
1743419069,1743419120,51,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 4752 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 19,4752,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,19,9,None,None,1,None,i7067,3886380
1743419076,1743419121,45,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 4429 feature_id 9 batch_size 825 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.41466325054459263 subsets 26,4429,825,str\(\'KL\'\),3,str\(\'stdev\'\),0.41466325054459263,26,9,0.2,4,0,None,i7095,4,750.0703125,749.8841145833334,-1,0.15751158173395102,3886295
1743419071,1743419121,50,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 4912 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 9,4912,1,str\(\'H\'\),1,str\(\'stdev\'\),0.001,9,9,None,None,1,None,i7081,3886331
1743419072,1743419123,51,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 1809 feature_id 9 batch_size 457 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.4763224761215777 subsets 24,1809,457,str\(\'KL\'\),3,str\(\'stdev\'\),0.4763224761215777,24,9,0.22,4,0,None,i7094,4,750.984375,750.81640625,-1,0.15122435473196558,3886309
1743419079,1743419124,45,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 4002 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.3848254716157996 subsets 18,4002,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.3848254716157996,18,9,None,None,1,None,i7096,3886281
1743419081,1743419131,50,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 320 feature_id 9 batch_size 210 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 1,320,210,str\(\'H\'\),1,str\(\'tstat\'\),0.001,1,9,0.25,6,0,None,i7065,6,749.80078125,749.6432291666666,-1,0.3113831899404368,3886406
1743419081,1743419131,50,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 16 feature_id 9 batch_size 5000 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.5274900276138061 subsets 70,16,5000,str\(\'KL\'\),2,str\(\'tstat\'\),0.5274900276138061,70,9,0.2,3,0,None,i7065,3,749.58203125,749.40625,-1,0,3886408
1743419081,1743419131,50,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 3212 feature_id 9 batch_size 3853 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 100,3212,3853,str\(\'KL\'\),2,str\(\'tstat\'\),0.001,100,9,0.2,3,0,None,i7065,3,750.2265625,750.05078125,-1,0,3886414
1743419081,1743419131,50,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 2690 feature_id 9 batch_size 5000 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.8510864052362835 subsets 1,2690,5000,str\(\'KL\'\),2,str\(\'stdev\'\),0.8510864052362835,1,9,0.2,3,0,None,i7065,3,751.125,750.94921875,-1,0,3886410
1743419081,1743419144,63,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 2127 feature_id 9 batch_size 432 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.31881126029673673 subsets 100,2127,432,str\(\'H\'\),2,str\(\'stdev\'\),0.31881126029673673,100,9,0.22,16,0,None,i7065,16,749.91015625,749.7158203125,-1,0.14295168762409,3886412
1743419052,1743419687,635,module load GCCcore/10.3.0 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 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 60,5000,1,str\(\'KL\'\),2,str\(\'tstat\'\),0.001,60,9,0.24,588,0,None,i7068,588,749.6171875,749.5524462090164,-1,0.0843812045003309,3886360
1743419079,1743419890,811,module load GCCcore/10.3.0 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 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 64,1232,1,str\(\'KL\'\),2,str\(\'stdev\'\),0.001,64,9,0.23,764,0,None,i7096,764,750.41015625,750.4003659018987,-1,0.0843812045003309,3886274
1743419069,1743420147,1078,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4688 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 70,4688,1,str\(\'H\'\),2,str\(\'tstat\'\),0.001,70,9,0.24,1031,0,None,i7067,1031,750.88671875,750.8475818452381,-1,0.0843812045003309,3886383
1743419069,1743420892,1823,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 70 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 80,70,1,str\(\'KL\'\),2,str\(\'stdev\'\),0.001,80,9,0.23,1771,0,None,i7067,1771,749.546875,749.5402627444134,-1,0.0843812045003309,3886388
1743418998,1743421468,2470,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3413 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 84,3413,1,str\(\'KL\'\),2,str\(\'stdev\'\),0.999,84,9,0.23,2414,0,None,i7069,2414,749.55078125,749.5474513319672,-1,0.0843812045003309,3886355
1743419076,1743422050,2974,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3381 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 90,3381,1,str\(\'KL\'\),2,str\(\'tstat\'\),0.001,90,9,0.24,2934,0,None,i7095,2934,751.05859375,751.0418470228041,-1,0.0843812045003309,3886288
1743424282,1743424295,13,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 4875 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 69,4875,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,69,9,None,None,1,None,i7157,3894477
1743424295,1743424308,13,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 4861 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 84,4861,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,84,9,None,None,1,None,i7171,3894484
1743424295,1743424308,13,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 3996 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 48,3996,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,48,9,None,None,1,None,i7171,3894483
1743424295,1743424308,13,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 1884 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 61,1884,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,61,9,None,None,1,None,i7175,3894479
1743424295,1743424308,13,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 70 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 37,70,1,str\(\'H\'\),1,str\(\'tstat\'\),0.001,37,9,None,None,1,None,i7175,3894480
1743424295,1743424308,13,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 4701 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 5,4701,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,5,9,None,None,1,None,i7173,3894481
1743424295,1743424309,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4804 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 75,4804,1,str\(\'H\'\),1,str\(\'stdev\'\),0.001,75,9,None,None,1,None,i7172,3894482
1743424296,1743424309,13,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 1227 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 79,1227,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,79,9,None,None,1,None,i7178,3894478
1743424296,1743424309,13,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 267 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 65,267,1,str\(\'H\'\),1,str\(\'stdev\'\),0.999,65,9,None,None,1,None,i7167,3894487
1743424302,1743424315,13,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 46 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 88,46,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,88,9,None,None,1,None,i7172,3894491
1743424303,1743424316,13,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 395 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 58,395,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,58,9,None,None,1,None,i7161,3894495
1743424302,1743424322,20,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 2639 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 55,2639,1,str\(\'H\'\),3,str\(\'stdev\'\),0.999,55,9,0.23,7,0,None,i7168,7,750.44140625,750.2747395833334,-1,0.0843812045003309,3894493
1743424302,1743424322,20,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 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 100,1,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,100,9,None,None,1,None,i7181,3894489
1743424303,1743424323,20,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 9 batch_size 1 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 4,1,1,str\(\'H\'\),2,str\(\'tstat\'\),0.999,4,9,0.23,10,0,None,i7155,10,750.83203125,750.53515625,-1,0.0843812045003309,3894497
1743424322,1743424336,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 983 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 92,983,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,92,9,None,None,1,None,i7183,3894499
1743424322,1743424336,14,module load GCCcore/10.3.0 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 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 6,5000,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,6,9,None,None,1,None,i7174,3894507
1743424322,1743424336,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3717 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 72,3717,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,72,9,None,None,1,None,i7178,3894502
1743424322,1743424336,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2304 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 35,2304,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,35,9,None,None,1,None,i7176,3894503
1743424325,1743424338,13,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 4349 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 73,4349,1,str\(\'H\'\),1,str\(\'tstat\'\),0.001,73,9,None,None,1,None,i7171,3894513
1743424325,1743424339,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4913 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 38,4913,1,str\(\'H\'\),1,str\(\'stdev\'\),0.999,38,9,None,None,1,None,i7167,3894515
1743424325,1743424339,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2420 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 67,2420,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,67,9,None,None,1,None,i7158,3894519
1743424327,1743424341,14,module load GCCcore/10.3.0 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 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 1,5000,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,1,9,None,None,1,None,i7175,3894505
1743424325,1743424345,20,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 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 1,1,1,str\(\'KL\'\),2,str\(\'tstat\'\),0.001,1,9,0.24,8,0,None,i7161,8,751.40234375,751.06640625,-1,0.0843812045003309,3894517
1743424342,1743424355,13,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 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 1,1,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,1,9,None,None,1,None,i7159,3894529
1743424343,1743424356,13,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 665 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 77,665,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,77,9,None,None,1,None,i7178,3894523
1743424325,1743424358,33,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1985 feature_id 9 batch_size 176 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 80,1985,176,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,80,9,0.24,24,0,None,i7171,24,750.34765625,750.2640625,-1,0.05823957643944408,3894512
1743424342,1743424361,19,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 1426 feature_id 9 batch_size 195 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 37,1426,195,str\(\'H\'\),1,str\(\'tstat\'\),0.001,37,9,0.22,4,0,None,i7168,4,750.83984375,750.6263020833334,-1,0.06452680344142951,3894527
1743424342,1743424362,20,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 2298 feature_id 9 batch_size 208 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 73,2298,208,str\(\'H\'\),1,str\(\'tstat\'\),0.001,73,9,0.21,8,0,None,i7176,8,750.94140625,750.7252604166666,-1,0,3894525
1743424342,1743424375,33,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 210 feature_id 9 batch_size 111 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 63,210,111,str\(\'H\'\),1,str\(\'tstat\'\),0.999,63,9,0.24,19,0,None,i7181,19,751.18359375,751.02734375,-1,0.18365320979483785,3894521
1743424325,1743424396,71,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 4824 feature_id 9 batch_size 77 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 82,4824,77,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,82,9,0.25,59,0,None,i7172,59,750.96484375,750.89208984375,-1,0.15387160820648577,3894510
1743427565,1743427585,20,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 9 batch_size 170 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 51,5000,170,str\(\'H\'\),1,str\(\'tstat\'\),0.999,51,9,0.24,7,0,None,i7182,7,751.703125,751.5078125,-1,0.013567174056915949,3898523
1743427566,1743427598,32,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 9 batch_size 582 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 100,1,582,str\(\'H\'\),2,str\(\'stdev\'\),0.999,100,9,0.22,16,0,None,i7185,16,750.49609375,750.275390625,-1,0,3898518
1743427584,1743427603,19,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 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 100,5000,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,100,9,None,None,1,None,i7179,3898543
1743427584,1743427604,20,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 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 1,5000,1,str\(\'KL\'\),2,str\(\'tstat\'\),0.001,1,9,0.24,7,0,None,i7183,7,750.50390625,750.2057291666666,-1,0.0843812045003309,3898538
1743427596,1743427609,13,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 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 65,1,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,65,9,None,None,1,None,i7177,3898556
1743427604,1743427623,19,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 9 batch_size 132 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 42,5000,132,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,42,9,0.24,6,0,None,i7169,6,750.8359375,750.6497395833334,-1,0.13103904698874919,3898567
1743427604,1743427624,20,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 9 batch_size 1 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 1,5000,1,str\(\'H\'\),2,str\(\'tstat\'\),0.001,1,9,0.24,8,0,None,i7185,8,751.50390625,751.1653645833334,-1,0.0843812045003309,3898558
1743427596,1743427640,44,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 1 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 24,1,1,str\(\'KL\'\),2,str\(\'tstat\'\),0.001,24,9,0.24,30,0,None,i7186,30,749.8203125,749.64765625,-1,0.0843812045003309,3898548
1743427626,1743427646,20,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 1059 feature_id 9 batch_size 1090 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 70,1059,1090,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,70,9,0.22,7,0,None,i7176,7,751.984375,751.7408854166666,-1,0,3898581
1743427626,1743427646,20,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 9 batch_size 1006 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 63,5000,1006,str\(\'H\'\),1,str\(\'stdev\'\),0.999,63,9,0.22,6,0,None,i7173,6,751.4375,751.2903645833334,-1,0.3328921244209133,3898584
1743427566,1743427648,82,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 1 feature_id 9 batch_size 73 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 88,1,73,str\(\'H\'\),1,str\(\'tstat\'\),0.999,88,9,0.25,71,0,None,i7172,71,750.15625,750.092578125,-1,0.14493712772998016,3898533
1743427631,1743427651,20,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 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 100,1,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,100,9,None,None,1,None,i7170,3898588
1743427624,1743427656,32,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 9 batch_size 171 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 67,1,171,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,67,9,0.24,17,0,None,i7180,17,749.953125,749.806640625,-1,0.16975512905360687,3898574
1743427625,1743427657,32,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 5000 feature_id 9 batch_size 81 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 64,5000,81,str\(\'H\'\),1,str\(\'tstat\'\),0.999,64,9,0.25,22,0,None,i7178,22,751.16796875,751.0265625,-1,0.18762409000661814,3898578
1743427645,1743427664,19,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 9 batch_size 8 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 53,5000,8,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,53,9,0.22,8,0,None,i7171,8,750.3828125,750.0729166666666,-1,0.007941760423560556,3898593
1743427646,1743427665,19,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 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 100,1,1,str\(\'H\'\),1,str\(\'tstat\'\),0.001,100,9,None,None,1,None,i7182,3898591
1743427646,1743427666,20,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 9 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 1,1,1,str\(\'H\'\),3,str\(\'tstat\'\),0.001,1,9,0.24,7,0,None,i7168,7,750.40625,747.7786458333334,-1,0.0843812045003309,3898604
1743427646,1743427671,25,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 9 batch_size 387 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 67,1,387,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,67,9,0.23,10,0,None,i7161,10,751.88671875,751.7395833333334,-1,0.12806088682991396,3898637
1743427645,1743427671,26,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 9 batch_size 322 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 61,5000,322,str\(\'H\'\),1,str\(\'stdev\'\),0.999,61,9,0.22,8,0,None,i7167,8,751.796875,751.6497395833334,-1,0.19093315684976836,3898612
1743427646,1743427672,26,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 9 batch_size 126 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 1,5000,126,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,1,9,0.26,6,0,None,i7162,6,751.08203125,750.91796875,-1,0.29748510919920584,3898631
1743427566,1743427674,108,module load GCCcore/10.3.0 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 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 36,5000,1,str\(\'KL\'\),2,str\(\'tstat\'\),0.001,36,9,0.24,97,0,None,i7177,97,751.3515625,751.2766927083334,-1,0.0843812045003309,3898528
1743427645,1743427677,32,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 9 batch_size 673 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 100,1,673,str\(\'H\'\),2,str\(\'stdev\'\),0.999,100,9,0.22,16,0,None,i7169,16,749.97265625,749.775390625,-1,0,3898600
1743427646,1743427685,39,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 1 feature_id 9 batch_size 263 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 81,1,263,str\(\'H\'\),1,str\(\'tstat\'\),0.999,81,9,0.24,21,0,None,i7168,21,750.7421875,746.01484375,-1,0.20880211780277963,3898607
1743427646,1743427703,57,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 5000 feature_id 9 batch_size 224 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 100,5000,224,str\(\'H\'\),1,str\(\'tstat\'\),0.999,100,9,0.24,40,0,None,i7164,40,751.0546875,750.947265625,-1,0.15387160820648577,3898624
1743427646,1743427716,70,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 1 feature_id 9 batch_size 84 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 100,1,84,str\(\'H\'\),2,str\(\'tstat\'\),0.999,100,9,0.22,56,0,None,i7160,56,751.2421875,743.8515625,-1,0.05559232296492389,3898644
1743427646,1743427729,83,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3331 feature_id 9 batch_size 166 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 100,3331,166,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,100,9,0.25,70,0,None,i7166,70,750.3046875,750.251171875,-1,0.16479152878888154,3898617
1743427595,1743427747,152,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3639 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 41,3639,1,str\(\'H\'\),2,str\(\'tstat\'\),0.001,41,9,0.24,139,0,None,i7182,139,750.22265625,750.166015625,-1,0.0843812045003309,3898550
1743427624,1743427789,165,module load GCCcore/10.3.0 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 9 batch_size 64 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 100,1,64,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,100,9,0.24,150,0,None,i7183,150,750.72265625,747.61328125,-1,0.16942422236929186,3898570
1743427645,1743427835,190,module load GCCcore/10.3.0 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 9 batch_size 1 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 44,5000,1,str\(\'H\'\),2,str\(\'tstat\'\),0.999,44,9,0.23,175,0,None,i7169,175,750.83984375,750.78828125,-1,0.0843812045003309,3898597
1743434852,1743434865,13,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 158 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 5,158,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,5,9,None,None,1,None,i7169,3906928
1743434853,1743434866,13,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 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 32,5000,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,32,9,None,None,1,None,i7138,3906978
1743434853,1743434866,13,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 4354 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 34,4354,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,34,9,None,None,1,None,i7149,3906945
1743434852,1743434872,20,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 3070 feature_id 9 batch_size 407 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 5,3070,407,str\(\'H\'\),1,str\(\'tstat\'\),0.999,5,9,0.23,5,0,None,i7143,5,751.15625,750.95703125,-1,0.14659166115155525,3906957
1743434852,1743434872,20,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 4349 feature_id 9 batch_size 788 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 40,4349,788,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,40,9,0.22,4,0,None,i7140,4,751.484375,751.26171875,-1,0,3906967
1743434853,1743434872,19,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 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 62,1,1,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,62,9,0.24,7,0,None,i7136,7,750.07421875,749.8489583333334,-1,0.0843812045003309,3906985
1743434853,1743434872,19,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 3123 feature_id 9 batch_size 603 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 41,3123,603,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,41,9,0.23,6,0,None,i7157,6,751.765625,751.59765625,-1,0.13666446062210458,3906937
1743434854,1743434873,19,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 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 76,1,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,76,9,None,None,1,None,i7141,3906963
1743434853,1743434879,26,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 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 39,1,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,39,9,None,None,1,None,i7139,3906972
1743434864,1743434883,19,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 4921 feature_id 9 batch_size 421 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 41,4921,421,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,41,9,0.23,5,0,None,i7135,5,751.5234375,751.3515625,-1,0.1743878226340172,3906995
1743434864,1743434890,26,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 1166 feature_id 9 batch_size 722 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 78,1166,722,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,78,9,0.22,12,0,None,i7177,12,751.28515625,751.1328125,-1,0.05526141628060887,3906989
1743434873,1743434892,19,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 3875 feature_id 9 batch_size 664 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 55,3875,664,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,55,9,0.21,5,0,None,i7134,5,749.86328125,749.67578125,-1,0,3907005
1743434873,1743434893,20,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 9 batch_size 518 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 34,5000,518,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,34,9,0.24,5,0,None,i7169,5,751.6328125,750.4895833333334,-1,0.024156187954996692,3907000
1743434891,1743434904,13,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 4960 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 5,4960,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,5,9,None,None,1,None,i7185,3907010
1743434891,1743434910,19,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 3052 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 48,3052,1,str\(\'H\'\),3,str\(\'tstat\'\),0.001,48,9,0.24,7,0,None,i7147,7,749.99609375,749.7330729166666,-1,0.0843812045003309,3907029
1743434891,1743434910,19,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 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 72,1,1,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,72,9,0.24,7,0,None,i7157,7,751.765625,751.5247395833334,-1,0.0843812045003309,3907024
1743434891,1743434917,26,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 9 batch_size 191 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 56,1,191,str\(\'H\'\),1,str\(\'tstat\'\),0.999,56,9,0.24,10,0,None,i7173,10,751.2265625,751.03515625,-1,0.1601588352084712,3907015
1743434894,1743434919,25,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 4740 feature_id 9 batch_size 827 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 78,4740,827,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,78,9,0.23,8,0,None,i7164,8,750.8125,750.6041666666666,-1,0,3907019
1743434911,1743434924,13,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 1880 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 47,1880,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,47,9,None,None,1,None,i7183,3907033
1743434911,1743434930,19,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 4873 feature_id 9 batch_size 329 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 32,4873,329,str\(\'H\'\),1,str\(\'tstat\'\),0.999,32,9,0.23,5,0,None,i7179,5,751.30859375,751.1119791666666,-1,0.10886829913964262,3907037
1743434921,1743434934,13,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 3097 feature_id 9 batch_size 670 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 5,3097,670,str\(\'H\'\),1,str\(\'tstat\'\),0.999,5,9,0.22,4,0,None,i7159,4,750.13671875,749.9309895833334,-1,0.003639973527465255,3907047
1743434921,1743434941,20,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 9 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 1,5000,1,str\(\'H\'\),3,str\(\'tstat\'\),0.001,1,9,0.24,7,0,None,i7176,7,749.73046875,749.4947916666666,-1,0.0843812045003309,3907042
1743434931,1743434944,13,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 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 1,1,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,1,9,None,None,1,None,i7144,3907059
1743434853,1743434948,95,module load GCCcore/10.3.0 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 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 34,1,1,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,34,9,0.23,81,0,None,i7144,81,751.9140625,751.8259943181819,-1,0.0843812045003309,3906951
1743434931,1743434950,19,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 4519 feature_id 9 batch_size 886 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 42,4519,886,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,42,9,0.23,5,0,None,i7183,5,751.03515625,750.8463541666666,-1,0,3907051
1743434931,1743434957,26,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 4075 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 12,4075,1,str\(\'H\'\),2,str\(\'tstat\'\),0.001,12,9,0.24,11,0,None,i7173,11,751.5078125,751.255859375,-1,0.0843812045003309,3907055
1743434950,1743434963,13,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 379 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 7,379,1,str\(\'H\'\),1,str\(\'tstat\'\),0.001,7,9,None,None,1,None,i7179,3907063
1743434951,1743434964,13,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 263 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 24,263,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,24,9,None,None,1,None,i7170,3907070
1743434950,1743434970,20,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 295 feature_id 9 batch_size 752 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 55,295,752,str\(\'H\'\),1,str\(\'tstat\'\),0.999,55,9,0.23,7,0,None,i7175,7,751.31640625,751.1080729166666,-1,0.08504301786896096,3907067
1743434951,1743434970,19,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 4936 feature_id 9 batch_size 821 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 53,4936,821,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,53,9,0.23,5,0,None,i7169,5,751.9609375,751.78515625,-1,0,3907073
1743439407,1743439433,26,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 524 feature_id 9 batch_size 35 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 8,524,35,str\(\'H\'\),1,str\(\'tstat\'\),0.001,8,9,0.22,3,0,None,i7147,3,750.28515625,750.0729166666666,-1,0.02316346790205162,3911995
1743439392,1743439486,94,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4974 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 4,4974,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,4,9,None,None,1,None,i7102,3911890
1743439430,1743439487,57,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 734 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 75,734,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,75,9,None,None,1,None,i7099,3911943
1743439437,1743439488,51,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 5000 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 46,5000,1,str\(\'H\'\),1,str\(\'tstat\'\),0.001,46,9,None,None,1,None,i7100,3911923
1743439432,1743439489,57,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 5000 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 33,5000,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,33,9,None,None,1,None,i7105,3911851
1743439445,1743439489,44,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 1219 feature_id 9 batch_size 2207 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 54,1219,2207,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,54,9,0.2,4,0,None,i7098,4,749.875,749.69921875,-1,0,3911957
1743439392,1743439493,101,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 50 feature_id 9 batch_size 441 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 25,50,441,str\(\'H\'\),1,str\(\'stdev\'\),0.999,25,9,0.24,5,0,None,i7102,5,751.375,751.2434895833334,-1,0.06816677696889477,3911894
1743439392,1743439493,101,module load GCCcore/10.3.0 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 9 batch_size 553 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 1,5000,553,str\(\'H\'\),1,str\(\'stdev\'\),0.999,1,9,0.25,6,0,None,i7102,6,751.33984375,751.2369791666666,-1,0.25347452018530775,3911901
1743439430,1743439494,64,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 350 feature_id 9 batch_size 111 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 24,350,111,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,24,9,0.23,4,0,None,i7099,4,750.859375,750.6536458333334,-1,0.03673064195896757,3911938
1743439430,1743439494,64,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 1 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 31,1,1,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,31,9,0.24,7,0,None,i7099,7,749.69921875,749.4752604166666,-1,0.0843812045003309,3911948
1743439437,1743439494,57,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 180 feature_id 9 batch_size 2183 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 91,180,2183,str\(\'H\'\),1,str\(\'tstat\'\),0.999,91,9,0.2,8,0,None,i7100,8,749.90625,749.71484375,-1,0,3911928
1743439437,1743439494,57,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 1 feature_id 9 batch_size 629 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 35,1,629,str\(\'H\'\),1,str\(\'stdev\'\),0.999,35,9,0.22,4,0,None,i7100,4,750.41015625,750.2760416666666,-1,0,3911933
1743439432,1743439495,63,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 148 feature_id 9 batch_size 1041 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 87,148,1041,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,87,9,0.22,11,0,None,i7105,11,749.8515625,749.7060546875,-1,0,3911857
1743439438,1743439495,57,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 1 feature_id 9 batch_size 603 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 40,1,603,str\(\'KL\'\),2,str\(\'stdev\'\),0.999,40,9,0.22,4,0,None,i7103,4,749.859375,749.5924479166666,-1,0,3911885
1743439439,1743439495,56,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3970 feature_id 9 batch_size 62 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 9,3970,62,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,9,9,0.23,4,0,None,i7103,4,751.34765625,751.1354166666666,-1,0.04103242885506287,3911880
1743439445,1743439495,50,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 362 feature_id 9 batch_size 88 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 33,362,88,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,33,9,0.24,6,0,None,i7098,6,751.375,751.18359375,-1,0.17471872931833224,3911962
1743439449,1743439499,50,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 4863 feature_id 9 batch_size 112 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 27,4863,112,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,27,9,0.23,4,0,None,i7097,4,751.21875,751.01171875,-1,0.037061548643282594,3911972
1743439449,1743439499,50,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 1731 feature_id 9 batch_size 2170 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 86,1731,2170,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,86,9,0.2,6,0,None,i7097,6,750.35546875,750.2291666666666,-1,0,3911967
1743439436,1743439499,63,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 2365 feature_id 9 batch_size 70 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 24,2365,70,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,24,9,0.25,5,0,None,i7101,5,751.41015625,751.2213541666666,-1,0.13898080741230973,3911907
1743439436,1743439499,63,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 124 feature_id 9 batch_size 41 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 36,124,41,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,36,9,0.24,8,0,None,i7101,8,750.203125,750.0221354166666,-1,0.14923891462607544,3911911
1743439436,1743439499,63,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 3589 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 69,3589,1,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,69,9,0.23,7,0,None,i7101,7,751.07421875,750.8567708333334,-1,0.0843812045003309,3911917
1743439445,1743439502,57,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 4043 feature_id 9 batch_size 1043 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 96,4043,1043,str\(\'H\'\),1,str\(\'tstat\'\),0.999,96,9,0.22,15,0,None,i7098,15,750.01171875,749.8798828125,-1,0,3911953
1743439441,1743439504,63,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 1 feature_id 9 batch_size 2 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 5,1,2,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,5,9,0.24,8,0,None,i7106,8,751.36328125,751.1809895833334,-1,0.16412971542025148,3911837
1743439441,1743439504,63,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 5000 feature_id 9 batch_size 956 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 1,5000,956,str\(\'H\'\),1,str\(\'tstat\'\),0.001,1,9,0.24,6,0,None,i7106,6,751.0859375,750.9244791666666,-1,0.2875579086697551,3911844
1743439449,1743439506,57,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 855 feature_id 9 batch_size 1175 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 85,855,1175,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,85,9,0.22,10,0,None,i7097,10,749.64453125,749.5107421875,-1,0,3911976
1743439443,1743439506,63,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 1133 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 79,1133,1,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,79,9,0.23,7,0,None,i7096,7,751.125,750.9088541666666,-1,0.0843812045003309,3911981
1743439443,1743439506,63,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 988 feature_id 9 batch_size 597 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 5,988,597,str\(\'H\'\),3,str\(\'stdev\'\),0.999,5,9,0.22,4,0,None,i7096,4,750.86328125,750.6888020833334,-1,0,3911986
1743439448,1743439512,64,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 4298 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 89,4298,1,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,89,9,0.23,7,0,None,i7104,7,750.1953125,749.9778645833334,-1,0.0843812045003309,3911873
1743439448,1743439512,64,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 2443 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 78,2443,1,str\(\'H\'\),3,str\(\'tstat\'\),0.999,78,9,0.23,7,0,None,i7104,7,751.078125,750.8671875,-1,0.0843812045003309,3911864
1743439448,1743439512,64,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 593 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 51,593,1,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,51,9,0.24,7,0,None,i7104,7,749.69921875,749.4934895833334,-1,0.0843812045003309,3911868
1743442472,1743442486,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2904 feature_id 9 batch_size 1054 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 29,2904,1054,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,29,9,0.22,4,0,None,i7137,4,749.98828125,749.7825520833334,-1,0,3915015
1743442493,1743442512,19,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 838 feature_id 9 batch_size 2549 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 75,838,2549,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,75,9,0.2,5,0,None,i7137,5,751.75,750.54296875,-1,0,3915032
1743442493,1743442512,19,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 786 feature_id 9 batch_size 2793 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 76,786,2793,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,76,9,0.2,5,0,None,i7132,5,750.94140625,750.8151041666666,-1,0.2627399073461284,3915035
1743442493,1743442512,19,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 4782 feature_id 9 batch_size 1201 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 31,4782,1201,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,31,9,0.22,4,0,None,i7132,4,750.66796875,750.4713541666666,-1,0,3915037
1743442482,1743442520,38,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 1877 feature_id 9 batch_size 119 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 75,1877,119,str\(\'H\'\),1,str\(\'tstat\'\),0.999,75,9,0.24,28,0,None,i7134,28,749.8515625,749.72265625,-1,0.1968894771674388,3915022
1743442482,1743442520,38,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 4817 feature_id 9 batch_size 528 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 100,4817,528,str\(\'H\'\),1,str\(\'stdev\'\),0.999,100,9,0.23,29,0,None,i7144,29,751.71484375,751.6265625,-1,0.03739245532759762,3915019
1743442482,1743442521,39,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 2441 feature_id 9 batch_size 430 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 100,2441,430,str\(\'H\'\),1,str\(\'stdev\'\),0.999,100,9,0.23,29,0,None,i7133,29,750.1640625,750.0609375,-1,0.19225678358702847,3915025
1743442512,1743442525,13,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 1425 feature_id 9 batch_size 1863 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 41,1425,1863,str\(\'H\'\),1,str\(\'tstat\'\),0.001,41,9,0.2,3,0,None,i7177,3,750.99609375,750.7747395833334,-1,0,3915039
1743442513,1743442526,13,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 559 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 75,559,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,75,9,None,None,1,None,i7130,3915055
1743442512,1743442531,19,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 4309 feature_id 9 batch_size 3092 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 78,4309,3092,str\(\'H\'\),1,str\(\'stdev\'\),0.999,78,9,0.2,6,0,None,i7134,6,750.171875,750.0130208333334,-1,0,3915045
1743442512,1743442531,19,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 1896 feature_id 9 batch_size 1810 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 75,1896,1810,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,75,9,0.2,5,0,None,i7150,5,750.09375,749.921875,-1,0,3915041
1743442512,1743442531,19,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 1416 feature_id 9 batch_size 2518 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 43,1416,2518,str\(\'H\'\),1,str\(\'stdev\'\),0.001,43,9,0.2,4,0,None,i7131,4,750.39453125,750.2682291666666,-1,0.171740569159497,3915047
1743442512,1743442532,20,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 229 feature_id 9 batch_size 2949 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 44,229,2949,str\(\'H\'\),1,str\(\'stdev\'\),0.999,44,9,0.2,4,0,None,i7131,4,749.890625,749.7369791666666,-1,0,3915051
1743442512,1743442532,20,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 1302 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 96,1302,1,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,96,9,0.24,7,0,None,i7145,7,750,749.7916666666666,-1,0.0843812045003309,3915043
1743442512,1743442532,20,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 2492 feature_id 9 batch_size 2491 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 73,2492,2491,str\(\'H\'\),1,str\(\'stdev\'\),0.999,73,9,0.2,5,0,None,i7131,5,750.82421875,750.7005208333334,-1,0,3915049
1743442513,1743442532,19,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 2958 feature_id 9 batch_size 1968 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 74,2958,1968,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,74,9,0.2,6,0,None,i7130,6,748.625,748.4375,-1,0,3915056
1743442513,1743442532,19,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 1065 feature_id 9 batch_size 2785 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 68,1065,2785,str\(\'H\'\),1,str\(\'stdev\'\),0.001,68,9,0.2,5,0,None,i7130,5,750.7421875,750.6184895833334,-1,0.2600926538716082,3915053
1743442493,1743442537,44,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 994 feature_id 9 batch_size 586 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 100,994,586,str\(\'H\'\),1,str\(\'tstat\'\),0.999,100,9,0.24,30,0,None,i7171,30,750.01953125,749.89140625,-1,0.114162806088683,3915029
1743442532,1743442545,13,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 4341 feature_id 9 batch_size 3527 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 69,4341,3527,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,69,9,0.2,4,0,None,i7171,4,750.58984375,750.4153645833334,-1,0,3915064
1743442532,1743442545,13,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 3328 feature_id 9 batch_size 3742 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 67,3328,3742,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,67,9,0.2,3,0,None,i7182,3,749.78515625,749.5924479166666,-1,0,3915059
1743442533,1743442546,13,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 1063 feature_id 9 batch_size 3059 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 43,1063,3059,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,43,9,0.2,3,0,None,i7177,3,751.66015625,751.4921875,-1,0,3915061
1743442533,1743442546,13,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 4378 feature_id 9 batch_size 3062 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 40,4378,3062,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,40,9,0.2,3,0,None,i7144,3,751.50390625,751.3203125,-1,0,3915068
1743442533,1743442553,20,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 4211 feature_id 9 batch_size 3122 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 70,4211,3122,str\(\'H\'\),1,str\(\'stdev\'\),0.001,70,9,0.2,5,0,None,i7163,5,750.375,750.25390625,-1,0,3915066
1743442533,1743442553,20,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 2480 feature_id 9 batch_size 3046 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 100,2480,3046,str\(\'H\'\),1,str\(\'stdev\'\),0.001,100,9,0.2,10,0,None,i7175,10,750.0390625,749.9153645833334,-1,0,3915062
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 2058 feature_id 9 batch_size 1990 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 62,2058,1990,str\(\'H\'\),2,str\(\'stdev\'\),0.001,62,9,0.2,4,0,None,i7173,4,750.67578125,750.37109375,-1,0,3915071
1743442541,1743442561,20,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 2016 feature_id 9 batch_size 2740 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 100,2016,2740,str\(\'H\'\),1,str\(\'tstat\'\),0.001,100,9,0.2,9,0,None,i7148,9,751.046875,750.8424479166666,-1,0,3915076
1743442542,1743442561,19,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 2294 feature_id 9 batch_size 2881 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 76,2294,2881,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,76,9,0.2,5,0,None,i7137,5,751.390625,751.2447916666666,-1,0,3915079
1743442542,1743442561,19,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 3596 feature_id 9 batch_size 3134 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 82,3596,3134,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,82,9,0.2,6,0,None,i7164,6,749.921875,749.7734375,-1,0,3915073
1743442543,1743442569,26,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 658 feature_id 9 batch_size 2724 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 100,658,2724,str\(\'H\'\),1,str\(\'stdev\'\),0.001,100,9,0.2,10,0,None,i7178,10,750.03125,749.919921875,-1,0.2399073461283918,3915070
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 1906 feature_id 9 batch_size 2580 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 73,1906,2580,str\(\'H\'\),1,str\(\'tstat\'\),0.001,73,9,0.2,5,0,None,i7177,5,750.08203125,749.8763020833334,-1,0,3915082
1743446082,1743446102,20,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 4980 feature_id 9 batch_size 601 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 53,4980,601,str\(\'H\'\),2,str\(\'stdev\'\),0.999,53,9,0.22,5,0,None,i7140,5,750.8671875,750.60546875,-1,0,3918182
1743446083,1743446102,19,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 4147 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 18,4147,1,str\(\'H\'\),3,str\(\'tstat\'\),0.001,18,9,0.24,7,0,None,i7136,7,750.91796875,750.6940104166666,-1,0.0843812045003309,3918185
1743446083,1743446102,19,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 2556 feature_id 9 batch_size 971 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 47,2556,971,str\(\'H\'\),1,str\(\'tstat\'\),0.001,47,9,0.22,5,0,None,i7135,5,750.67578125,750.47265625,-1,0.30244870946393115,3918188
1743446083,1743446102,19,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 2655 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 4,2655,1,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,4,9,0.24,7,0,None,i7152,7,750.45703125,750.2096354166666,-1,0.0843812045003309,3918180
1743446094,1743446107,13,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 3815 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 28,3815,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,28,9,None,None,1,None,i7141,3918191
1743446093,1743446113,20,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 3865 feature_id 9 batch_size 614 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 52,3865,614,str\(\'KL\'\),2,str\(\'stdev\'\),0.001,52,9,0.22,5,0,None,i7134,5,750.39453125,750.1471354166666,-1,0,3918198
1743446093,1743446113,20,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 4311 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 19,4311,1,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,19,9,0.24,7,0,None,i7134,7,751.4140625,751.1901041666666,-1,0.0843812045003309,3918195
1743446114,1743446127,13,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 3876 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 48,3876,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,48,9,None,None,1,None,i7140,3918210
1743446112,1743446132,20,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 2080 feature_id 9 batch_size 587 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 52,2080,587,str\(\'H\'\),2,str\(\'tstat\'\),0.999,52,9,0.23,5,0,None,i7150,5,751.94140625,751.63671875,-1,0,3918204
1743446112,1743446132,20,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 2275 feature_id 9 batch_size 651 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 53,2275,651,str\(\'H\'\),2,str\(\'stdev\'\),0.999,53,9,0.22,5,0,None,i7173,5,750.28515625,750.0299479166666,-1,0,3918201
1743446113,1743446132,19,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 632 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 66,632,1,str\(\'H\'\),3,str\(\'tstat\'\),0.001,66,9,0.24,8,0,None,i7141,8,750.23046875,749.9778645833334,-1,0.0843812045003309,3918207
1743446113,1743446133,20,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 4466 feature_id 9 batch_size 536 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 9,4466,536,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,9,9,0.23,5,0,None,i7137,5,748.6875,748.55859375,-1,0.04798146922567836,3918218
1743446115,1743446134,19,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 2231 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 27,2231,1,str\(\'H\'\),3,str\(\'tstat\'\),0.001,27,9,0.24,7,0,None,i7138,7,749.95703125,749.7552083333334,-1,0.0843812045003309,3918213
1743446113,1743446145,32,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 3411 feature_id 9 batch_size 66 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 57,3411,66,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,57,9,0.25,18,0,None,i7138,18,750.609375,750.4638671875,-1,0.1528788881535407,3918215
1743446133,1743446147,14,module load GCCcore/10.3.0 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 9 batch_size 599 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 56,2301,599,str\(\'H\'\),3,str\(\'tstat\'\),0.999,56,9,0.22,4,0,None,i7134,4,750.5,750.30078125,-1,0,3918230
1743446133,1743446153,20,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 4271 feature_id 9 batch_size 632 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 52,4271,632,str\(\'KL\'\),2,str\(\'stdev\'\),0.999,52,9,0.22,5,0,None,i7140,5,750.21484375,749.9609375,-1,0,3918224
1743446134,1743446153,19,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 2708 feature_id 9 batch_size 1008 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 59,2708,1008,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,59,9,0.22,5,0,None,i7171,5,750.90625,750.671875,-1,0,3918221
1743446134,1743446153,19,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 3360 feature_id 9 batch_size 561 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 52,3360,561,str\(\'KL\'\),2,str\(\'stdev\'\),0.999,52,9,0.22,5,0,None,i7135,5,750.34765625,750.0807291666666,-1,0.18563864990072798,3918228
1743446143,1743446162,19,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 2815 feature_id 9 batch_size 572 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 46,2815,572,str\(\'H\'\),1,str\(\'stdev\'\),0.999,46,9,0.23,6,0,None,i7150,6,750.578125,750.44140625,-1,0.0956320317670417,3918237
1743446143,1743446162,19,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 1354 feature_id 9 batch_size 610 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 52,1354,610,str\(\'H\'\),2,str\(\'stdev\'\),0.001,52,9,0.22,5,0,None,i7141,5,751.3125,751.0533854166666,-1,0,3918241
1743446143,1743446162,19,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 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 45,1,1,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,45,9,0.24,7,0,None,i7173,7,750.55859375,750.3125,-1,0.0843812045003309,3918233
1743446154,1743446167,13,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 2657 feature_id 9 batch_size 17 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 58,2657,17,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,58,9,0.21,4,0,None,i7179,4,750.33203125,750.1041666666666,-1,0.013567174056915949,3918243
1743446143,1743446169,26,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 2816 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 15,2816,1,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,15,9,0.23,16,0,None,i7141,16,750.234375,749.998046875,-1,0.0843812045003309,3918239
1743446143,1743446169,26,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 9 batch_size 984 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 81,4492,984,str\(\'H\'\),1,str\(\'stdev\'\),0.001,81,9,0.22,10,0,None,i7156,10,750.58203125,750.4361979166666,-1,0.31535407015221706,3918235
1743446154,1743446173,19,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 718 feature_id 9 batch_size 134 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 47,718,134,str\(\'H\'\),1,str\(\'tstat\'\),0.999,47,9,0.24,9,0,None,i7152,9,749.98046875,749.75390625,-1,0.17736598279285243,3918251
1743446173,1743446186,13,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 3599 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 45,3599,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,45,9,None,None,1,None,i7173,3918256
1743446173,1743446192,19,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 1231 feature_id 9 batch_size 406 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 47,1231,406,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,47,9,0.23,6,0,None,i7179,6,750.19140625,749.98046875,-1,0.14460622104566512,3918253
1743446173,1743446192,19,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 4807 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 4,4807,1,str\(\'H\'\),3,str\(\'tstat\'\),0.001,4,9,0.24,7,0,None,i7161,7,749.93359375,749.7122395833334,-1,0.0843812045003309,3918262
1743446173,1743446193,20,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 3129 feature_id 9 batch_size 1026 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 6,3129,1026,str\(\'H\'\),1,str\(\'tstat\'\),0.001,6,9,0.22,5,0,None,i7166,5,750.15625,749.9205729166666,-1,0,3918259
1743446154,1743446199,45,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 1936 feature_id 9 batch_size 301 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 95,1936,301,str\(\'H\'\),1,str\(\'tstat\'\),0.999,95,9,0.23,36,0,None,i7167,36,751.4140625,751.3203125,-1,0.23494374586366645,3918247
1743451060,1743451073,13,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 954 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 10,954,1,str\(\'H\'\),1,str\(\'stdev\'\),0.999,10,9,None,None,1,None,i7143,3926882
1743451061,1743451074,13,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 196 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 29,196,1,str\(\'H\'\),1,str\(\'stdev\'\),0.999,29,9,None,None,1,None,i7154,3926812
1743451062,1743451075,13,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 3513 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 11,3513,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,11,9,None,None,1,None,i7152,3926827
1743451063,1743451075,12,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 1096 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 29,1096,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,29,9,None,None,1,None,i7160,3926786
1743451062,1743451076,14,module load GCCcore/10.3.0 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 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 1,5000,1,str\(\'H\'\),1,str\(\'stdev\'\),0.999,1,9,None,None,1,None,i7150,3926831
1743451064,1743451076,12,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 3768 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 1,3768,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,1,9,None,None,1,None,i7153,3926817
1743451064,1743451076,12,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 4289 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 18,4289,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,18,9,None,None,1,None,i7153,3926820
1743451060,1743451079,19,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 2482 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 92,2482,1,str\(\'H\'\),3,str\(\'tstat\'\),0.001,92,9,0.24,7,0,None,i7148,7,749.83984375,749.6197916666666,-1,0.0843812045003309,3926839
1743451060,1743451079,19,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 955 feature_id 9 batch_size 615 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 64,955,615,str\(\'H\'\),1,str\(\'tstat\'\),0.999,64,9,0.23,8,0,None,i7146,8,750.125,749.94921875,-1,0.15254798146922569,3926857
1743451060,1743451080,20,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 3364 feature_id 9 batch_size 562 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.25299309124194425 subsets 4,3364,562,str\(\'H\'\),2,str\(\'stdev\'\),0.25299309124194425,4,9,0.22,4,0,None,i7138,4,748.64453125,748.3984375,-1,0.18596955658504302,3926913
1743451060,1743451080,20,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 3472 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 13,3472,1,str\(\'H\'\),3,str\(\'tstat\'\),0.001,13,9,0.24,7,0,None,i7157,7,749.921875,749.6822916666666,-1,0.0843812045003309,3926802
1743451060,1743451080,20,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 4429 feature_id 9 batch_size 1000 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 24,4429,1000,str\(\'H\'\),1,str\(\'tstat\'\),0.001,24,9,0.22,5,0,None,i7140,5,750.7578125,750.5572916666666,-1,0.3309066843150232,3926897
1743451061,1743451080,19,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 722 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 40,722,1,str\(\'H\'\),1,str\(\'stdev\'\),0.999,40,9,None,None,1,None,i7156,3926806
1743451062,1743451081,19,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 3928 feature_id 9 batch_size 596 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 15,3928,596,str\(\'H\'\),2,str\(\'tstat\'\),0.999,15,9,0.22,4,0,None,i7152,4,751.93359375,751.62890625,-1,0,3926822
1743451063,1743451082,19,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 3685 feature_id 9 batch_size 1041 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 36,3685,1041,str\(\'H\'\),1,str\(\'tstat\'\),0.001,36,9,0.22,4,0,None,i7139,4,750.26953125,750.0872395833334,-1,0,3926906
1743451063,1743451082,19,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 915 feature_id 9 batch_size 573 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 30,915,573,str\(\'H\'\),2,str\(\'tstat\'\),0.999,30,9,0.22,4,0,None,i7159,4,750.5,750.1744791666666,-1,0,3926791
1743451063,1743451083,20,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 1675 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 74,1675,1,str\(\'H\'\),3,str\(\'stdev\'\),0.001,74,9,0.23,7,0,None,i7147,7,751.21484375,751.0390625,-1,0.0843812045003309,3926845
1743451064,1743451083,19,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 4378 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 32,4378,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,32,9,None,None,1,None,i7144,3926878
1743451064,1743451083,19,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 4202 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 29,4202,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,29,9,None,None,1,None,i7144,3926875
1743451064,1743451083,19,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 530 feature_id 9 batch_size 624 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 61,530,624,str\(\'H\'\),3,str\(\'tstat\'\),0.999,61,9,0.22,4,0,None,i7141,4,750.28125,750.0703125,-1,0,3926894
1743451064,1743451083,19,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 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 48,5000,1,str\(\'H\'\),1,str\(\'stdev\'\),0.999,48,9,None,None,1,None,i7141,3926891
1743451060,1743451086,26,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 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 7,5000,1,str\(\'KL\'\),2,str\(\'stdev\'\),0.001,7,9,0.23,10,0,None,i7148,10,749.9375,749.6783854166666,-1,0.0843812045003309,3926832
1743451067,1743451086,19,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 484 feature_id 9 batch_size 493 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.44543255628631667 subsets 31,484,493,str\(\'KL\'\),1,str\(\'stdev\'\),0.44543255628631667,31,9,0.24,4,0,None,i7139,4,751.29296875,751.1354166666666,-1,0.16313699536730641,3926902
1743451062,1743451087,25,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 1644 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 98,1644,1,str\(\'H\'\),3,str\(\'tstat\'\),0.001,98,9,0.24,7,0,None,i7142,7,750.625,750.42578125,-1,0.0843812045003309,3926887
1743451062,1743451088,26,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 1136 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 7,1136,1,str\(\'KL\'\),2,str\(\'tstat\'\),0.001,7,9,0.24,11,0,None,i7155,11,749.94140625,749.689453125,-1,0.0843812045003309,3926808
1743451063,1743451089,26,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 136 feature_id 9 batch_size 806 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 74,136,806,str\(\'H\'\),1,str\(\'stdev\'\),0.001,74,9,0.21,8,0,None,i7147,8,750.60546875,750.4557291666666,-1,0,3926848
1743451063,1743451089,26,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 1587 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 86,1587,1,str\(\'H\'\),3,str\(\'tstat\'\),0.001,86,9,0.24,7,0,None,i7145,7,750.8984375,750.6796875,-1,0.0843812045003309,3926867
1743451063,1743451089,26,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 3855 feature_id 9 batch_size 481 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 71,3855,481,str\(\'H\'\),1,str\(\'tstat\'\),0.999,71,9,0.24,11,0,None,i7145,11,750.1796875,750.052734375,-1,0.15916611515552614,3926861
1743451064,1743451089,25,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 4660 feature_id 9 batch_size 290 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 23,4660,290,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,23,9,0.23,5,0,None,i7144,5,750.390625,750.2200520833334,-1,0.20218398411647914,3926870
1743451060,1743451092,32,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 1979 feature_id 9 batch_size 590 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 72,1979,590,str\(\'H\'\),1,str\(\'stdev\'\),0.999,72,9,0.23,12,0,None,i7158,12,751.7578125,751.6201171875,-1,0.11945731303772336,3926796
1743456839,1743456853,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2174 feature_id 9 batch_size 465 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 38,2174,465,str\(\'H\'\),2,str\(\'tstat\'\),0.001,38,9,0.22,4,0,None,i7152,4,751.5625,751.2513020833334,-1,0,3936588
1743456840,1743456853,13,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 963 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 44,963,1,str\(\'H\'\),1,str\(\'stdev\'\),0.001,44,9,None,None,1,None,i7147,3936595
1743456860,1743456873,13,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 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 29,5000,1,str\(\'H\'\),1,str\(\'stdev\'\),0.001,29,9,None,None,1,None,i7154,3936615
1743456860,1743456873,13,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 2931 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 12,2931,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,12,9,None,None,1,None,i7162,3936608
1743456856,1743456876,20,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 2407 feature_id 9 batch_size 516 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 40,2407,516,str\(\'KL\'\),2,str\(\'tstat\'\),0.001,40,9,0.21,5,0,None,i7181,5,750.5546875,750.2200520833334,-1,0,3936599
1743456885,1743456899,14,module load GCCcore/10.3.0 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 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 40,5000,1,str\(\'H\'\),1,str\(\'stdev\'\),0.999,40,9,None,None,1,None,i7162,3936637
1743456886,1743456905,19,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 4187 feature_id 9 batch_size 55 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 4,4187,55,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,4,9,0.25,5,0,None,i7181,5,750.34375,750.1783854166666,-1,0.1029119788219722,3936628
1743456900,1743456913,13,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 3722 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 1,3722,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,1,9,None,None,1,None,i7159,3936642
1743456901,1743456914,13,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 759 feature_id 9 batch_size 530 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 40,759,530,str\(\'KL\'\),2,str\(\'tstat\'\),0.001,40,9,0.21,4,0,None,i7148,4,751.2890625,750.9375,-1,0,3936648
1743456919,1743456932,13,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 1101 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 17,1101,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,17,9,None,None,1,None,i7159,3936669
1743456920,1743456939,19,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 1026 feature_id 9 batch_size 495 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 39,1026,495,str\(\'H\'\),2,str\(\'stdev\'\),0.001,39,9,0.21,4,0,None,i7181,4,750.546875,750.2734375,-1,0.16379880873593647,3936660
1743456946,1743456959,13,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 4792 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 36,4792,1,str\(\'H\'\),1,str\(\'stdev\'\),0.001,36,9,None,None,1,None,i7181,3936683
1743456940,1743456959,19,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 4383 feature_id 9 batch_size 197 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 44,4383,197,str\(\'H\'\),3,str\(\'tstat\'\),0.999,44,9,0.22,4,0,None,i7147,4,750.4921875,750.2421875,-1,0.13037723362011913,3936677
1743456946,1743456960,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 TMDBalanced5s 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3243 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 28,3243,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,28,9,None,None,1,None,i7141,3936689
1743456960,1743456973,13,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 3762 feature_id 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 9,3762,1,str\(\'H\'\),1,str\(\'stdev\'\),0.999,9,9,None,None,1,None,i7140,3936700
1743456960,1743456980,20,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 817 feature_id 9 batch_size 456 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 38,817,456,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,38,9,0.22,4,0,None,i7168,4,748.72265625,748.41015625,-1,0.15089344804765056,3936695
1743456980,1743456993,13,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 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 1,5000,1,str\(\'H\'\),1,str\(\'stdev\'\),0.001,1,9,None,None,1,None,i7174,3936712
1743456975,1743456995,20,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 3879 feature_id 9 batch_size 513 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 3,3879,513,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,3,9,0.22,5,0,None,i7147,5,751.2734375,751.09765625,-1,0.01753805426869623,3936705
1743456980,1743456999,19,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 72 feature_id 9 batch_size 451 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 38,72,451,str\(\'KL\'\),2,str\(\'tstat\'\),0.001,38,9,0.21,4,0,None,i7139,4,751.125,750.8059895833334,-1,0,3936718
1743457000,1743457013,13,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 1610 feature_id 9 batch_size 356 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 9,1610,356,str\(\'H\'\),1,str\(\'tstat\'\),0.001,9,9,0.22,4,0,None,i7137,4,750.78125,750.5625,-1,0.16313699536730641,3936733
1743457006,1743457019,13,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 302 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 9,302,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,9,9,None,None,1,None,i7139,3936740
1743457000,1743457020,20,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 2468 feature_id 9 batch_size 342 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 45,2468,342,str\(\'H\'\),3,str\(\'tstat\'\),0.001,45,9,0.21,4,0,None,i7181,4,750.33984375,750.1315104166666,-1,0.11317008603573792,3936723
1743457020,1743457033,13,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 893 feature_id 9 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 28,893,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,28,9,None,None,1,None,i7139,3936751
1743457020,1743457033,13,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 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 47,1,1,str\(\'H\'\),1,str\(\'tstat\'\),0.999,47,9,None,None,1,None,i7185,3936745
1743457036,1743457050,14,module load GCCcore/10.3.0 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 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 30,5000,1,str\(\'H\'\),1,str\(\'stdev\'\),0.999,30,9,None,None,1,None,i7181,3936756
1743457036,1743457055,19,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 9 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 30,5000,1,str\(\'H\'\),3,str\(\'tstat\'\),0.999,30,9,0.23,7,0,None,i7135,7,750.3046875,750.09375,-1,0.0843812045003309,3936764
1743457040,1743457060,20,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 42 feature_id 9 batch_size 153 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 35,42,153,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,35,9,0.25,6,0,None,i7139,6,750.3359375,750.1510416666666,-1,0.15188616810059563,3936770
1743457060,1743457073,13,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 9 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 48,5000,1,str\(\'H\'\),1,str\(\'stdev\'\),0.001,48,9,None,None,1,None,i7161,3936780
1743457060,1743457080,20,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 287 feature_id 9 batch_size 490 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 29,287,490,str\(\'H\'\),1,str\(\'tstat\'\),0.001,29,9,0.21,4,0,None,i7134,4,750.69921875,750.4986979166666,-1,0.16214427531436135,3936785
1743457061,1743457081,20,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 443 feature_id 9 batch_size 454 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 11,443,454,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,11,9,0.24,5,0,None,i7185,5,751.30078125,751.1575520833334,-1,0.08967571144937128,3936776

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_9_HoeffdingTreeClassifier_ACCURACY-RUNTIME
mem_gb	32
parameter	[['recent_samples_size', 'range', '1', '5000', 'int'], ['feature_id', 'fixed', '9'], ['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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				background-image: url("data:image/svg+xml;charset=utf-8,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 -0.5 15 17' shape-rendering='crispEdges'%3E%3Cpath stroke='%23e6eefc' d='M0 0h1'/%3E%3Cpath stroke='%23d1e0fd' d='M1 0h1M0 1h1m3 0h2M2 3h1M2 4h1'/%3E%3Cpath stroke='%23cad8f9' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23c4d3f7' d='M3 0h1M0 3h1M0 4h1'/%3E%3Cpath stroke='%23bfd0f8' d='M4 0h2M0 5h1'/%3E%3Cpath stroke='%23bdcef7' d='M6 0h1M0 6h1'/%3E%3Cpath stroke='%23baccf4' d='M7 0h1m6 2h1m-1 5h1m-1 1h1'/%3E%3Cpath stroke='%23b8cbf6' d='M8 0h1M0 7h1M0 8h1'/%3E%3Cpath stroke='%23b7caf5' d='M9 0h2M0 9h1'/%3E%3Cpath stroke='%23b5c8f7' d='M11 0h1'/%3E%3Cpath stroke='%23b3c7f5' d='M12 0h1'/%3E%3Cpath stroke='%23afc5f4' d='M13 0h1'/%3E%3Cpath stroke='%23dce6f9' d='M14 0h1'/%3E%3Cpath stroke='%23e1eafe' d='M1 1h1'/%3E%3Cpath stroke='%23dae6fe' d='M2 1h1M1 2h1'/%3E%3Cpath stroke='%23d4e1fc' d='M3 1h1M1 3h1M1 4h1'/%3E%3Cpath stroke='%23d0ddfc' d='M6 1h1M1 5h1'/%3E%3Cpath stroke='%23cedbfd' d='M7 1h1M4 2h2'/%3E%3Cpath stroke='%23cad9fd' d='M8 1h1M6 2h1M3 5h1'/%3E%3Cpath stroke='%23c8d8fb' d='M9 1h2'/%3E%3Cpath stroke='%23c5d6fc' d='M11 1h1M2 11h4'/%3E%3Cpath stroke='%23c2d3fc' d='M12 1h1m-2 1h1M1 11h1m0 1h2m-2 1h2'/%3E%3Cpath stroke='%23bccefa' d='M13 1h1m-1 1h1m-1 1h1m-1 1h1M3 15h4'/%3E%3Cpath stroke='%23b9c9f3' d='M14 1h1M3 16h4'/%3E%3Cpath stroke='%23d8e3fc' d='M2 2h1'/%3E%3Cpath stroke='%23d1defd' d='M3 2h1'/%3E%3Cpath stroke='%23c9d8fc' d='M7 2h1M4 3h3M4 4h3M3 6h1m1 0h2M1 7h1M1 8h1'/%3E%3Cpath stroke='%23c5d5fc' d='M8 2h1m-8 8h5'/%3E%3Cpath stroke='%23c5d3fc' d='M9 2h2'/%3E%3Cpath stroke='%23bed0fc' d='M12 2h1M8 3h1M8 4h1m-8 8h1m-1 1h1m0 1h1m1 0h3'/%3E%3Cpath stroke='%23cddbfc' d='M3 3h1M3 4h1M1 6h2'/%3E%3Cpath stroke='%23c8d5fb' d='M7 3h1M7 4h1'/%3E%3Cpath stroke='%23bbcefd' d='M9 3h4M9 4h4M8 5h1M7 6h1'/%3E%3Cpath stroke='%23bcccf3' d='M14 3h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23ceddfd' d='M2 5h1'/%3E%3Cpath stroke='%23c8d6fb' d='M4 5h4M1 9h3'/%3E%3Cpath stroke='%23bacdfc' d='M9 5h2m1 0h2M1 14h1'/%3E%3Cpath stroke='%23b9cdfb' d='M11 5h1M8 6h2m2 0h2m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%234d6185' d='M4 6h1m5 0h1M3 7h3m3 0h3M4 8h3m1 0h3M5 9h5m-4 1h3m-2 1h1'/%3E%3Cpath stroke='%23b7cdfc' d='M11 6h1m0 1h1m-1 1h1'/%3E%3Cpath stroke='%23cad8fd' d='M2 7h1M2 8h2'/%3E%3Cpath stroke='%23c1d3fb' d='M6 7h2M7 8h1M4 9h1'/%3E%3Cpath stroke='%23b6cefb' d='M8 7h1m2 1h1m-2 1h3m-2 1h2'/%3E%3Cpath stroke='%23b6cdfb' d='M13 9h1m-6 6h1'/%3E%3Cpath stroke='%23b9cbf3' d='M14 9h1'/%3E%3Cpath stroke='%23b4c8f6' d='M0 10h1'/%3E%3Cpath stroke='%23bdd3fb' d='M9 10h2m-4 4h1'/%3E%3Cpath stroke='%23b5cdfa' d='M13 10h1'/%3E%3Cpath stroke='%23b5c9f3' d='M14 10h1'/%3E%3Cpath stroke='%23b1c7f6' d='M0 11h1'/%3E%3Cpath stroke='%23c3d5fd' d='M6 11h1'/%3E%3Cpath stroke='%23bad4fc' d='M8 11h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b2cffb' d='M9 11h4m-2 3h1'/%3E%3Cpath stroke='%23b1cbfa' d='M13 11h1m-3 4h1'/%3E%3Cpath stroke='%23b3c8f5' d='M14 11h1m-7 5h3'/%3E%3Cpath stroke='%23adc3f6' d='M0 12h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c2d5fc' d='M4 12h4m-4 1h4'/%3E%3Cpath stroke='%23b7d3fc' d='M9 12h2m-2 1h2m-3 1h1'/%3E%3Cpath stroke='%23b3d1fc' d='M11 12h1m-1 1h1'/%3E%3Cpath stroke='%23afcdfb' d='M12 12h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23afcbfa' d='M13 12h1m-1 1h1'/%3E%3Cpath stroke='%23b2c8f4' d='M14 12h1m-1 1h1m-4 3h1'/%3E%3Cpath stroke='%23c1d2fb' d='M3 14h1'/%3E%3Cpath stroke='%23b6d1fb' d='M9 14h2'/%3E%3Cpath stroke='%23adc9f9' d='M13 14h1m-2 1h1'/%3E%3Cpath stroke='%23b1c6f3' d='M14 14h1m-3 2h1'/%3E%3Cpath stroke='%23abc1f4' d='M0 15h1'/%3E%3Cpath stroke='%23b7cbf9' d='M1 15h1'/%3E%3Cpath stroke='%23b9cefb' d='M2 15h1'/%3E%3Cpath stroke='%23b9cffb' d='M7 15h1'/%3E%3Cpath stroke='%23b2cdfb' d='M9 15h2'/%3E%3Cpath stroke='%23aec8f7' d='M13 15h1'/%3E%3Cpath stroke='%23b0c5f2' d='M14 15h1m-2 1h1'/%3E%3Cpath stroke='%23dbe3f8' d='M0 16h1'/%3E%3Cpath stroke='%23b7c6f1' d='M1 16h1'/%3E%3Cpath stroke='%23b8c9f2' d='M2 16h1m4 0h1'/%3E%3Cpath stroke='%23d9e3f6' d='M14 16h1'/%3E%3C/svg%3E");
				background-size: 15px;
				font-size: 11px;
				border: none;
				background-color: #fff;
				box-sizing: border-box;
				height: 21px;
				appearance: none;
				-webkit-appearance: none;
				-moz-appearance: none;
				position: relative;
				padding: 5px 32px 32px 5px;
				background-position: top 50% right 2px;
				background-repeat: no-repeat;
				border-radius: 0;
				border: 1px solid black;
			}
			

			body {
				font-variant: oldstyle-nums;
				font-family: 'IBM Plex Sans', 'Source Sans Pro', sans-serif;
				background-color: #fafafa;
				text-shadow: 0 0.05em 0.1em rgba(0,0,0,0.2);
				scroll-behavior: smooth;
				text-wrap: balance;
				text-rendering: optimizeLegibility;
				-webkit-font-smoothing: antialiased;
				-moz-osx-font-smoothing: grayscale;
				font-feature-settings: "ss02", "liga", "onum";
			}
			
			.marked_text {
				background-color: yellow;
			}
			
			.time_picker_container {
				font-variant: small-caps;
				width: 100%;
			}
			
			.time_picker_container > input {
				width: 50px;
			}
			
			#loader {
				display: grid;
				justify-content: center;
				align-items: center;
				height: 100%;
			}
			
			.no_linebreak {
				line-break: auto;
			}
			
			.dark_code_bg {
				background-color: #363636;
				color: white;
			}
			
			.code_bg {
				background-color: #C0C0C0;
			}
			
			#commands {
				line-break: anywhere;
			}
			
			.color_red {
				color: red;
			}
			
			.color_orange {
				color: orange;
			}
			
			table > tbody > tr:nth-child(odd) {
				background-color: #fafafa;
			}
			
			table > tbody > tr:nth-child(even) {
				background-color: #ddd;
			}
			
			table {
				border-collapse: collapse;
				margin: 0 0;
				min-width: 200px;
			}
			
			th {
				background-color: #4eae46;
				color: #ffffff;
				text-align: left;
				border: 0px;
			}
			
			.error_element {
				background-color: #e57373;
				border-radius: 10px;
				padding: 4px;
				display: none;
			}
			
			button {
				background-color: #4eae46;
				border: 1px solid #2A8387;
				border-radius: 4px;
				box-shadow: rgba(0, 0, 0, 0.12) 0 1px 1px;
				cursor: pointer;
				display: block;
				line-height: 100%;
				outline: 0;
				padding: 11px 15px 12px;
				text-align: center;
				transition: box-shadow .05s ease-in-out, opacity .05s ease-in-out;
				user-select: none;
				-webkit-user-select: none;
				touch-action: manipulation;
				font-family: 'IBM Plex Sans', 'Source Sans Pro', sans-serif;
			}
			
			button:hover {
				box-shadow: rgba(255, 255, 255, 0.3) 0 0 2px inset, rgba(0, 0, 0, 0.4) 0 1px 2px;
				text-decoration: none;
				transition-duration: .15s, .15s;
			}
			
			button:active {
				box-shadow: rgba(0, 0, 0, 0.15) 0 2px 4px inset, rgba(0, 0, 0, 0.4) 0 1px 1px;
			}
			
			button:disabled {
				cursor: not-allowed;
				opacity: .6;
			}
			
			button:disabled:active {
				pointer-events: none;
			}
			
			button:disabled:hover {
				box-shadow: none;
			}
			
			.half_width_td {
				vertical-align: baseline;
				width: 50%;
			}
			
			#scads_bar {
				width: 100%;
				margin: 0;
				padding: 0;
				user-select: none;
				user-drag: none;
				-webkit-user-drag: none;
				user-select: none;
				-moz-user-select: none;
				-webkit-user-select: none;
				-ms-user-select: none;
				display: -webkit-box;
			}
			
			.tab {
				display: inline-block;
				padding: 0px;
				margin: 0px;
				font-size: 16px;
				font-weight: bold;
				text-align: center;
				border-radius: 25px;
				text-decoration: none !important;
				transition: background-color 0.3s, color 0.3s;
				color: unset !important;
			}
			
			.tooltipster-base {
				border: 1px solid black;
				position: absolute;
				border-radius: 8px;
				padding: 2px;
				color: white;
				background-color: #61686f;
				width: 70%;
				min-width: 200px;
				pointer-events: none;
			}
			
			td {
				padding-top: 3px;
				padding-bottom: 3px;
			}
			
			.left_side {
				text-align: right;
			}
			
			.right_side {
				text-align: left;
			}
			
			.spinner {
				border: 8px solid rgba(0, 0, 0, 0.1);
				border-left: 8px solid #3498db;
				border-radius: 50%;
				width: 50px;
				height: 50px;
				animation: spin 1s linear infinite;
			}
			
			@keyframes spin {
				0% {
					transform: rotate(0deg);
				}
			
				100% {
					transform: rotate(360deg);
				}
			}
			
			#spinner-overlay {
				-webkit-text-stroke: 1px black;
				white !important;
				position: fixed;
				top: 0;
				left: 0;
				width: 100%;
				height: 100%;
				display: flex;
				justify-content: center;
				align-items: center;
				z-index: 9999;
			}
			
			#spinner-container {
				text-align: center;
				color: #fff;
				display: contents;
			}
			
			#spinner-text {
				font-size: 3vw;
				margin-left: 10px;
			}
			
			a, a:visited, a:active, a:hover, a:link {
				color: #007bff;
				text-decoration: none;
			}
			
			.copy-container {
				display: inline-block;
				position: relative;
				cursor: pointer;
				margin-left: 10px;
				color: blue;
			}
			
			.copy-container:hover {
				text-decoration: underline;
			}
			
			.clipboard-icon {
				position: absolute;
				top: 5px;
				right: 5px;
				font-size: 1.5em;
			}
			
			#main_tab {
				overflow: scroll;
				width: max-content;
			}
			
			.ui-tabs .ui-tabs-nav li {
				user-select: none;
			}
			
			.stacktrace_table {
				background-color: black !important;
				color: white !important;
			}
			
			#breadcrumb {
				user-select: none;
			}
			
			#statusBar {
				user-select: none;
			}
			
			.error_line {
				background-color: red !important;
				color: white !important;
			}
			
			.header_table {
				border: 0px !important;
				padding: 0px !important;
				width: revert !important;
				min-width: revert !important;
			}
			
			.img_auto_width {
				max-width: revert !important;
			}
			
			#main_dir_or_plot_view {
				display: inline-grid;
			}
			
			#refresh_button {
				width: 300px;
			}
			
			._share_link {
				color: black !important;
			}
			
			#footer_element {
				height: 30px;
				background-color: #f8f9fa;
				padding: 0px;
				text-align: center;
				border-top: 1px solid #dee2e6;
				width: 100%;
				box-sizing: border-box;
				position: fixed;
				bottom: 0;
				z-index: 2;
				margin-left: -9px;
				z-index: 99;
			}
			
			.switch {
				position: relative;
				display: inline-block;
				width: 50px;
				height: 26px;
			}
			
			.switch input {
				opacity: 0;
				width: 0;
				height: 0;
			}
			
			.slider {
				position: absolute;
				cursor: pointer;
				top: 0;
				left: 0;
				right: 0;
				bottom: 0;
				background-color: #ccc;
				transition: .4s;
				border-radius: 26px;
			}
			
			.slider:before {
				position: absolute;
				content: "";
				height: 20px;
				width: 20px;
				left: 3px;
				bottom: 3px;
				background-color: white;
				transition: .4s;
				border-radius: 50%;
			}
			
			input:checked + .slider {
				background-color: #444;
			}
			
			input:checked + .slider:before {
				transform: translateX(24px);
			}
			
			.mode-text {
				position: absolute;
				top: 5px;
				left: 65px;
				font-size: 14px;
				color: black;
				transition: .4s;
				width: 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 8h1'/%3E%3Cpath stroke='%23b5c8f7' d='M11 1h1'/%3E%3Cpath stroke='%23b3c7f5' d='M12 1h1'/%3E%3Cpath stroke='%23afc5f4' d='M13 1h1'/%3E%3Cpath stroke='%23dce6f9' d='M14 1h1'/%3E%3Cpath stroke='%23dfe2e1' d='M16 1h1'/%3E%3Cpath stroke='%23e1eafe' d='M3 2h1'/%3E%3Cpath stroke='%23dae6fe' d='M4 2h1M3 3h1'/%3E%3Cpath stroke='%23d4e1fc' d='M5 2h1M3 4h1'/%3E%3Cpath stroke='%23d1e0fd' d='M6 2h1M4 4h1'/%3E%3Cpath stroke='%23d0ddfc' d='M7 2h1M3 5h1'/%3E%3Cpath stroke='%23cedbfd' d='M8 2h1M6 3h1'/%3E%3Cpath stroke='%23cad9fd' d='M9 2h1M7 3h1M5 5h1'/%3E%3Cpath stroke='%23c8d8fb' d='M10 2h1'/%3E%3Cpath stroke='%23c5d6fc' d='M11 2h1m-8 8h1m1 0h1'/%3E%3Cpath stroke='%23c2d3fc' d='M12 2h1m-2 1h1m-9 7h1m0 1h1'/%3E%3Cpath stroke='%23bccefa' d='M13 2h1m-1 2h1m-9 9h2'/%3E%3Cpath stroke='%23b9c9f3' d='M14 2h1M5 14h3'/%3E%3Cpath stroke='%23cfd7dd' d='M16 2h1'/%3E%3Cpath stroke='%23d8e3fc' d='M4 3h1'/%3E%3Cpath stroke='%23d1defd' d='M5 3h1'/%3E%3Cpath stroke='%23c9d8fc' d='M8 3h1M6 4h2M5 6h2M3 7h1'/%3E%3Cpath stroke='%23c5d5fc' d='M9 3h1M3 9h1m3 0h1'/%3E%3Cpath stroke='%23c5d3fc' d='M10 3h1'/%3E%3Cpath stroke='%23bed0fc' d='M12 3h1M9 4h1m-7 7h1m0 1h1'/%3E%3Cpath stroke='%23bccdfa' d='M13 3h1'/%3E%3Cpath stroke='%23baccf4' d='M14 3h1'/%3E%3Cpath stroke='%23bdcbda' d='M16 3h1'/%3E%3Cpath stroke='%23c4d4f7' d='M2 4h1'/%3E%3Cpath stroke='%23cddbfc' d='M5 4h1M3 6h1'/%3E%3Cpath stroke='%23c8d5fb' d='M8 4h1'/%3E%3Cpath stroke='%23bbcefd' d='M10 4h3M9 5h1'/%3E%3Cpath stroke='%23bcccf3' d='M14 4h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b1c2d5' d='M16 4h1'/%3E%3Cpath stroke='%23bed0f8' d='M2 5h1'/%3E%3Cpath stroke='%23ceddfd' d='M4 5h1'/%3E%3Cpath stroke='%23c8d6fb' d='M6 5h2M3 8h2'/%3E%3Cpath stroke='%234d6185' d='M8 5h1M7 6h3M6 7h5M5 8h3m1 0h3M4 9h3m3 0h3m-8 1h1m5 0h1'/%3E%3Cpath stroke='%23bacdfc' d='M10 5h1m1 0h2M3 12h1'/%3E%3Cpath stroke='%23b9cdfb' d='M11 5h1m-2 1h1m1 0h2m-1 1h1'/%3E%3Cpath stroke='%23a8bbd4' d='M16 5h1'/%3E%3Cpath stroke='%23cddafc' d='M4 6h1'/%3E%3Cpath stroke='%23b7cdfc' d='M11 6h1m0 1h1'/%3E%3Cpath stroke='%23a4b8d3' d='M16 6h1'/%3E%3Cpath stroke='%23cad8fd' d='M4 7h2'/%3E%3Cpath stroke='%23b6cefb' d='M11 7h1m0 1h1'/%3E%3Cpath stroke='%23bacbf4' d='M14 7h1'/%3E%3Cpath stroke='%23a0b5d3' d='M16 7h1m-1 1h1m-1 5h1'/%3E%3Cpath stroke='%23c1d3fb' d='M8 8h1'/%3E%3Cpath stroke='%23b6cdfb' d='M13 8h1m-5 5h1'/%3E%3Cpath stroke='%23b9cbf3' d='M14 8h1'/%3E%3Cpath stroke='%23b4c8f6' d='M2 9h1'/%3E%3Cpath stroke='%23c2d5fc' d='M8 9h1m-1 1h1m-3 1h2'/%3E%3Cpath stroke='%23bdd3fb' d='M9 9h1m-2 3h1'/%3E%3Cpath stroke='%23b5cdfa' d='M13 9h1'/%3E%3Cpath stroke='%23b5c9f3' d='M14 9h1'/%3E%3Cpath stroke='%239fb5d2' d='M16 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b1c7f6' d='M2 10h1'/%3E%3Cpath stroke='%23c3d5fd' d='M7 10h1'/%3E%3Cpath stroke='%23bad4fc' d='M9 10h1m-1 1h1'/%3E%3Cpath stroke='%23b2cffb' d='M10 10h1m1 0h1m-2 2h1'/%3E%3Cpath stroke='%23b1cbfa' d='M13 10h1'/%3E%3Cpath stroke='%23b3c8f5' d='M14 10h1m-6 4h2'/%3E%3Cpath stroke='%23adc3f6' d='M2 11h1'/%3E%3Cpath stroke='%23c3d3fd' d='M5 11h1'/%3E%3Cpath stroke='%23c1d5fb' d='M8 11h1'/%3E%3Cpath stroke='%23b7d3fc' d='M10 11h1m-2 1h1'/%3E%3Cpath stroke='%23b3d1fc' d='M11 11h1'/%3E%3Cpath stroke='%23afcefb' d='M12 11h1'/%3E%3Cpath stroke='%23aecafa' d='M13 11h1'/%3E%3Cpath stroke='%23b1c8f3' d='M14 11h1'/%3E%3Cpath stroke='%23acc2f5' d='M2 12h1'/%3E%3Cpath stroke='%23c1d2fb' d='M5 12h1'/%3E%3Cpath stroke='%23bed1fc' d='M6 12h2'/%3E%3Cpath stroke='%23b6d1fb' d='M10 12h1'/%3E%3Cpath stroke='%23afccfb' d='M12 12h1'/%3E%3Cpath stroke='%23adc9f9' d='M13 12h1m-2 1h1'/%3E%3Cpath stroke='%23b1c5f3' d='M14 12h1'/%3E%3Cpath stroke='%23aac0f3' d='M2 13h1'/%3E%3Cpath stroke='%23b7cbf9' d='M3 13h1'/%3E%3Cpath stroke='%23b9cefb' d='M4 13h1'/%3E%3Cpath stroke='%23bbcef9' d='M7 13h1'/%3E%3Cpath stroke='%23b9cffb' d='M8 13h1'/%3E%3Cpath stroke='%23b2cdfb' d='M10 13h1'/%3E%3Cpath stroke='%23b0cbf9' d='M11 13h1'/%3E%3Cpath stroke='%23aec8f7' d='M13 13h1'/%3E%3Cpath stroke='%23b0c5f2' d='M14 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			: :-webkit-scrollbar-button: vertical: end{
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			}
			
			: :-webkit-scrollbar-button: horizontal: start{
				width: 17px;
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15h1'/%3E%3Cpath stroke='%23aec4e5' d='M15 15h1'/%3E%3Cpath stroke='%23edf1f3' d='M0 16h1'/%3E%3Cpath stroke='%23aac0e1' d='M1 16h1'/%3E%3Cpath stroke='%2394b1d9' d='M2 16h1'/%3E%3Cpath stroke='%2388a7d8' d='M3 16h1'/%3E%3Cpath stroke='%2383a4d3' d='M4 16h1'/%3E%3Cpath stroke='%237da0d4' d='M5 16h1m4 0h3'/%3E%3Cpath stroke='%237e9fd2' d='M6 16h1'/%3E%3Cpath stroke='%237c9fd3' d='M7 16h3'/%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: horizontal: end{
				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 2h1'/%3E%3Cpath stroke='%23b5c8f7' d='M11 2h1'/%3E%3Cpath stroke='%23b3c7f5' d='M12 2h1'/%3E%3Cpath stroke='%23afc5f4' d='M13 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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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			    ],
			    [
			        1743457031.9894395,
			        30,
			        9,
			        30
			    ],
			    [
			        1743457035.9576364,
			        30,
			        8,
			        27
			    ],
			    [
			        1743457036.0682373,
			        30,
			        8,
			        27
			    ],
			    [
			        1743457041.509835,
			        30,
			        8,
			        27
			    ],
			    [
			        1743457043.1066186,
			        30,
			        7,
			        23
			    ],
			    [
			        1743457047.5661807,
			        30,
			        6,
			        20
			    ],
			    [
			        1743457047.7923956,
			        30,
			        6,
			        20
			    ],
			    [
			        1743457053.3643203,
			        30,
			        6,
			        20
			    ],
			    [
			        1743457057.7601051,
			        30,
			        5,
			        17
			    ],
			    [
			        1743457057.9588745,
			        30,
			        5,
			        17
			    ],
			    [
			        1743457063.628694,
			        30,
			        5,
			        17
			    ],
			    [
			        1743457063.8095348,
			        30,
			        5,
			        17
			    ],
			    [
			        1743457065.2198064,
			        30,
			        4,
			        13
			    ],
			    [
			        1743457065.4093904,
			        30,
			        4,
			        13
			    ],
			    [
			        1743457069.4793994,
			        30,
			        3,
			        10
			    ],
			    [
			        1743457069.6118212,
			        30,
			        3,
			        10
			    ],
			    [
			        1743457075.2200754,
			        30,
			        3,
			        10
			    ],
			    [
			        1743457079.4892905,
			        30,
			        2,
			        7
			    ],
			    [
			        1743457079.7357237,
			        30,
			        2,
			        7
			    ],
			    [
			        1743457085.2308342,
			        30,
			        2,
			        7
			    ],
			    [
			        1743457085.387179,
			        30,
			        2,
			        7
			    ],
			    [
			        1743457086.8277934,
			        30,
			        1,
			        3
			    ],
			    [
			        1743457087.015214,
			        30,
			        1,
			        3
			    ],
			    [
			        1743457090.8204644,
			        30,
			        0,
			        0
			    ]
			];
			var tab_main_worker_cpu_ram_csv_json = [
			    [
			        1743371290,
			        595.6796875,
			        3
			    ],
			    [
			        1743371290,
			        595.71875,
			        4.1
			    ],
			    [
			        1743371290,
			        595.8125,
			        3.8
			    ],
			    [
			        1743371290,
			        595.8125,
			        2
			    ],
			    [
			        1743371290,
			        595.8125,
			        2.6
			    ],
			    [
			        1743371290,
			        595.8125,
			        3.4
			    ],
			    [
			        1743371290,
			        595.8125,
			        1.3
			    ],
			    [
			        1743371404,
			        614.59375,
			        1.9
			    ],
			    [
			        1743371404,
			        614.59375,
			        1.5
			    ],
			    [
			        1743371404,
			        614.59375,
			        1.6
			    ],
			    [
			        1743371404,
			        614.59375,
			        0
			    ],
			    [
			        1743372854,
			        675.82421875,
			        2.1
			    ],
			    [
			        1743372854,
			        675.82421875,
			        2.5
			    ],
			    [
			        1743372854,
			        675.82421875,
			        2.5
			    ],
			    [
			        1743372854,
			        675.82421875,
			        2.3
			    ],
			    [
			        1743381274,
			        691.765625,
			        5.1
			    ],
			    [
			        1743381274,
			        691.765625,
			        5
			    ],
			    [
			        1743381274,
			        691.765625,
			        4.9
			    ],
			    [
			        1743381274,
			        691.765625,
			        5.6
			    ],
			    [
			        1743390798,
			        695.75,
			        5.1
			    ],
			    [
			        1743390798,
			        695.8125,
			        1.9
			    ],
			    [
			        1743390799,
			        695.8125,
			        1.9
			    ],
			    [
			        1743390799,
			        695.8125,
			        2.7
			    ],
			    [
			        1743395846,
			        720.0546875,
			        5.6
			    ],
			    [
			        1743395846,
			        720.0546875,
			        4.9
			    ],
			    [
			        1743395846,
			        720.0546875,
			        5.1
			    ],
			    [
			        1743395846,
			        720.0546875,
			        5.1
			    ],
			    [
			        1743400892,
			        753.55078125,
			        5.7
			    ],
			    [
			        1743400892,
			        753.55078125,
			        5.2
			    ],
			    [
			        1743400892,
			        753.55078125,
			        5.4
			    ],
			    [
			        1743400892,
			        753.55078125,
			        5.7
			    ],
			    [
			        1743406867,
			        771.50390625,
			        5.5
			    ],
			    [
			        1743406867,
			        771.50390625,
			        4
			    ],
			    [
			        1743406867,
			        771.50390625,
			        4.1
			    ],
			    [
			        1743406867,
			        771.50390625,
			        2.4
			    ],
			    [
			        1743411954,
			        741.35546875,
			        5.5
			    ],
			    [
			        1743411954,
			        741.35546875,
			        6.5
			    ],
			    [
			        1743411954,
			        741.35546875,
			        6.8
			    ],
			    [
			        1743411954,
			        741.35546875,
			        7.9
			    ],
			    [
			        1743418208,
			        777.58984375,
			        4.9
			    ],
			    [
			        1743418208,
			        777.58984375,
			        5.8
			    ],
			    [
			        1743418208,
			        777.58984375,
			        5.7
			    ],
			    [
			        1743418208,
			        777.58984375,
			        2.9
			    ],
			    [
			        1743424303,
			        834.546875,
			        5.5
			    ],
			    [
			        1743424303,
			        834.546875,
			        5.5
			    ],
			    [
			        1743424303,
			        834.546875,
			        5.4
			    ],
			    [
			        1743424303,
			        834.546875,
			        5.4
			    ],
			    [
			        1743427582,
			        755.48828125,
			        6.2
			    ],
			    [
			        1743427582,
			        755.48828125,
			        4.7
			    ],
			    [
			        1743427582,
			        755.48828125,
			        5
			    ],
			    [
			        1743427582,
			        755.48828125,
			        5
			    ],
			    [
			        1743434922,
			        771.51171875,
			        5.9
			    ],
			    [
			        1743434922,
			        771.51171875,
			        6.9
			    ],
			    [
			        1743434922,
			        771.51171875,
			        6.4
			    ],
			    [
			        1743434922,
			        771.51171875,
			        6.2
			    ],
			    [
			        1743439358,
			        798.7890625,
			        6.2
			    ],
			    [
			        1743439358,
			        798.7890625,
			        5.3
			    ],
			    [
			        1743439358,
			        798.7890625,
			        5.6
			    ],
			    [
			        1743439358,
			        798.7890625,
			        2.4
			    ],
			    [
			        1743442502,
			        789.48046875,
			        6.3
			    ],
			    [
			        1743442502,
			        789.48046875,
			        5.8
			    ],
			    [
			        1743442502,
			        789.48046875,
			        6
			    ],
			    [
			        1743442502,
			        789.48046875,
			        6.3
			    ],
			    [
			        1743446194,
			        803.3046875,
			        6.3
			    ],
			    [
			        1743446194,
			        803.3046875,
			        5.7
			    ],
			    [
			        1743446194,
			        803.3046875,
			        5.8
			    ],
			    [
			        1743446194,
			        803.3046875,
			        4.7
			    ],
			    [
			        1743450962,
			        850.64453125,
			        7.8
			    ],
			    [
			        1743450962,
			        850.64453125,
			        9.2
			    ],
			    [
			        1743450962,
			        850.64453125,
			        9.6
			    ],
			    [
			        1743450962,
			        850.64453125,
			        10.4
			    ],
			    [
			        1743456875,
			        810.90234375,
			        8.8
			    ],
			    [
			        1743456875,
			        810.90234375,
			        8.1
			    ],
			    [
			        1743456876,
			        810.90234375,
			        7.7
			    ],
			    [
			        1743456876,
			        810.90234375,
			        9.8
			    ],
			    [
			        1743457093,
			        810.86328125,
			        8.2
			    ],
			    [
			        1743457093,
			        810.86328125,
			        9.5
			    ]
			];
			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>9</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>95</td>
			<td>414</td>
			<td>1</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_0,0.200000000000000011102230246252,5.000000000000000000000000000000,4152,2792,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.519167040109634436717556127405,72,9
1,1_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,4.000000000000000000000000000000,1387,819,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.288098664568737172775314547835,48,9
2,2_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,3.000000000000000000000000000000,1172,4934,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.145887998566031462654990491501,82,9
3,3_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,3.000000000000000000000000000000,3429,1789,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.906987904224544783104988709965,12,9
4,4_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,8.000000000000000000000000000000,2532,4177,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.640514746461063655402767835767,95,9
5,5_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,3.000000000000000000000000000000,354,2244,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.411380836352705947511765316449,25,9
6,6_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,4.000000000000000000000000000000,2054,3275,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.023598043845966459181040519866,59,9
7,7_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,3.000000000000000000000000000000,4895,13,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.782702581210061865135685366113,35,9
8,8_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,3.000000000000000000000000000000,4519,4620,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.990860503762960420637284641998,89,9
9,9_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,5.000000000000000000000000000000,2283,1475,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.190655240882188076190217884687,19,9
10,10_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,3.000000000000000000000000000000,310,3087,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.360285298256203534439379154719,52,9
11,11_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,3.000000000000000000000000000000,3054,1114,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.567840636136010323831158075336,29,9
12,12_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,3.000000000000000000000000000000,3483,3581,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.862678234102204455346907252533,65,9
13,13_0,COMPLETED,Sobol,GenerationStep_0,0.209999999999999992228438827624,4.000000000000000000000000000000,660,319,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.064467380313202746200396120457,42,9
14,14_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,5.000000000000000000000000000000,1773,3852,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.487464424122124928562271861665,76,9
15,15_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,3.000000000000000000000000000000,3932,1919,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.693086228817701321958111293497,5,9
16,16_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,4.000000000000000000000000000000,3844,3965,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.103020042553544050045744029376,47,9
17,17_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,5.000000000000000000000000000000,1705,2149,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.840698628727346686240196049766,74,9
18,18_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,3.000000000000000000000000000000,865,3604,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.733596744490787378012441877217,7,9
19,19_0,COMPLETED,Sobol,GenerationStep_0,0.220000000000000001110223024625,4.000000000000000000000000000000,3746,616,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.463513763265684219927464937427,87,9
20,20_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,3.000000000000000000000000000000,2849,2848,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.230200642542913558319384037532,21,9
21,21_0,COMPLETED,Sobol,GenerationStep_0,0.220000000000000001110223024625,16.000000000000000000000000000000,47,1070,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.965944773508235821068979021220,100,9
22,22_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,3.000000000000000000000000000000,2371,4448,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.605412970963865482154631081357,34,9
23,23_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,4.000000000000000000000000000000,4587,1343,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.337325380340218528019136101648,61,9
24,24_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,3.000000000000000000000000000000,4826,3290,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.387558493016287697319199878621,14,9
25,25_0,COMPLETED,Sobol,GenerationStep_0,0.209999999999999992228438827624,4.000000000000000000000000000000,1966,302,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.680910150380805156977714887034,94,9
26,26_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,3.000000000000000000000000000000,618,4260,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.760838072717189839444529297907,28,9
27,27_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,4.000000000000000000000000000000,2737,2443,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.062022403437644244017512562550,54,9
28,28_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,3.000000000000000000000000000000,3165,4754,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.265269086677581089617206089315,41,9
29,29_0,COMPLETED,Sobol,GenerationStep_0,0.200000000000000011102230246252,4.000000000000000000000000000000,967,1648,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.556626297771930733659928591806,67,9
30,30_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,3724,799,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.643219823820178726592189377698,92,9
31,31_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,4033,650,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,75,9
32,32_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,2051,899,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.569780572645392391351037986169,96,9
33,33_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,4579,903,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,100,9
34,34_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,4.000000000000000000000000000000,2554,816,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,85,9
35,35_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,3341,656,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,68,9
36,36_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,4184,928,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,96,9
37,37_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,2760,855,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,95,9
38,38_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,935,946,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.369743979992215920926668104585,94,9
39,39_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,4.000000000000000000000000000000,490,816,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.816733026197459133221911997680,90,9
40,40_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,12.000000000000000000000000000000,3694,858,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.659494852405914544490883599792,93,9
41,41_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,205,881,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,97,9
42,42_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,3183,657,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,9
43,43_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,4.000000000000000000000000000000,3104,816,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.685104468126380039549871980853,100,9
44,44_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,4598,976,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,92,9
45,45_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,7.000000000000000000000000000000,6,195,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,44,9
46,46_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,14.000000000000000000000000000000,3306,851,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.346344436570155678190019443718,92,9
47,47_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,4449,749,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,80,9
48,48_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,4.000000000000000000000000000000,3962,899,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,94,9
49,49_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,2700,729,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,69,9
50,50_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,8.000000000000000000000000000000,752,196,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,51,9
51,51_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,4.000000000000000000000000000000,803,809,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,100,9
52,52_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,4.000000000000000000000000000000,5000,321,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,63,9
53,53_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,1460,856,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,83,9
54,54_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,13.000000000000000000000000000000,77,816,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.515347974521298546335401624674,94,9
55,55_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,1,5000,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,62,9
56,56_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,3054,594,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,9,9
57,57_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,4.000000000000000000000000000000,2881,967,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.273798955003246080597278933055,92,9
58,58_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,15.000000000000000000000000000000,4795,879,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.313232717173146102407343960294,99,9
59,59_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,3208,1062,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,95,9
60,60_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,629,294,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,40,9
61,61_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,3.000000000000000000000000000000,1266,383,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,23,9
62,62_0,COMPLETED,BoTorch,GenerationStep_1,0.250000000000000000000000000000,6.000000000000000000000000000000,544,286,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,9
63,63_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,5000,5000,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,61,9
64,64_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,131,4959,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.431345987341798575709361784902,63,9
65,65_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,1283,293,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,14,9
66,66_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,5.000000000000000000000000000000,542,243,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,52,9
67,67_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,4.000000000000000000000000000000,401,236,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,37,9
68,68_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,4.000000000000000000000000000000,456,117,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,25,9
69,69_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,1,317,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,51,9
70,70_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,6.000000000000000000000000000000,5000,4369,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,9
71,71_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,4.000000000000000000000000000000,812,172,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,32,9
72,72_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,5000,5000,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,9
73,73_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,6.000000000000000000000000000000,5000,5000,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,9
74,74_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,5.000000000000000000000000000000,576,256,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,29,9
75,75_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,5000,5000,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,9
76,76_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,835,3860,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,100,9
77,77_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,586,535,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,36,9
78,78_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,4006,847,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,27,9
79,79_0,COMPLETED,BoTorch,GenerationStep_1,0.250000000000000000000000000000,6.000000000000000000000000000000,911,297,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,9
80,80_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,4.000000000000000000000000000000,747,297,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.850293797321502786701330478536,15,9
81,81_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,5000,5000,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,60,9
82,82_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,1738,5000,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,61,9
83,83_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,3027,5000,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,63,9
84,84_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,4138,5000,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.545503973899621907861501313164,24,9
85,85_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,5000,5000,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,9
86,86_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,5000,4132,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,9
87,87_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,566,414,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,49,9
88,88_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,6.000000000000000000000000000000,1,5000,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.085378119920528058872655208233,1,9
89,89_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,4.000000000000000000000000000000,1183,202,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,35,9
90,90_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,5000,630,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,18,9
91,91_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,434,402,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,9
92,92_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,5000,3273,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,28,9
93,93_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,4.000000000000000000000000000000,5000,380,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,16,9
94,94_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,5000,579,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,26,9
95,95_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,4.000000000000000000000000000000,4461,842,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,18,9
96,96_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,3.000000000000000000000000000000,4773,479,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,27,9
97,97_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,1,2788,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,28,9
98,98_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,5000,3975,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,34,9
99,99_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,1,3162,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,25,9
100,100_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,5000,675,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,19,9
101,101_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,395,555,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,17,9
102,102_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,5000,3391,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,84,9
103,103_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,4.000000000000000000000000000000,5000,384,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,15,9
104,104_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,5000,2242,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,29,9
105,105_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,344,3827,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,33,9
106,106_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,5000,2466,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,80,9
107,107_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,3.000000000000000000000000000000,1,381,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,40,9
108,108_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,4.000000000000000000000000000000,5000,511,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,24,9
109,109_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,4.000000000000000000000000000000,5000,456,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,18,9
110,110_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,1,3881,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,23,9
111,111_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,5000,2577,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,26,9
112,112_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,5000,2500,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,9
113,113_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,5000,3376,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,32,9
114,114_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,5000,2897,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,25,9
115,115_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,5000,305,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,17,9
116,116_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,5000,474,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,19,9
117,117_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,4.000000000000000000000000000000,5000,497,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,14,9
118,118_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,1,2404,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,27,9
119,119_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,5000,784,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,19,9
120,120_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,15,9
121,121_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,3670,224,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,39,9
122,122_0,FAILED,BoTorch,GenerationStep_1,,,2167,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,16,9
123,123_0,FAILED,BoTorch,GenerationStep_1,,,3265,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,16,9
124,124_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,4917,3472,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,8,9
125,125_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,1271,5000,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,12,9
126,126_0,FAILED,BoTorch,GenerationStep_1,,,2137,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,15,9
127,127_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,5000,568,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,39,9
128,128_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,3186,4442,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,22,9
129,129_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,4191,3224,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,39,9
130,130_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,7.000000000000000000000000000000,1934,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,39,9
131,131_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,850,3345,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,9
132,132_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,278,3249,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,3,9
133,133_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,1,3778,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,8,9
134,134_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,7.000000000000000000000000000000,1,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,40,9
135,135_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,5000,4188,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,13,9
136,136_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,5000,538,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,37,9
137,137_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,4690,748,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,37,9
138,138_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,7.000000000000000000000000000000,5000,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,39,9
139,139_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,1,5000,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,64,9
140,140_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,5.000000000000000000000000000000,434,729,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,16,9
141,141_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,441,4339,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,22,9
142,142_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,1,5000,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,15,9
143,143_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,5000,3046,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,39,9
144,144_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,4.000000000000000000000000000000,4942,487,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,37,9
145,145_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,4.000000000000000000000000000000,823,370,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,18,9
146,146_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,2549,3514,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,12,9
147,147_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,1,3575,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,58,9
148,148_0,FAILED,BoTorch,GenerationStep_1,,,4388,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,14,9
149,149_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,4139,998,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,17,9
150,150_0,FAILED,BoTorch,GenerationStep_1,,,2271,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,18,9
151,151_0,FAILED,BoTorch,GenerationStep_1,,,3780,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,18,9
152,152_0,FAILED,BoTorch,GenerationStep_1,,,3634,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,17,9
153,153_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,5000,774,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,19,9
154,154_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,7.000000000000000000000000000000,5000,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,8,9
155,155_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,5000,696,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,14,9
156,156_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,7.000000000000000000000000000000,1,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,100,9
157,157_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,5000,2069,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,26,9
158,158_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,4.000000000000000000000000000000,5000,91,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,12,9
159,159_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,1,5000,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,77,9
160,160_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,16,9
161,161_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,4571,3167,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,9
162,162_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,1487,561,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,16,9
163,163_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,4.000000000000000000000000000000,4736,198,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,11,9
164,164_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,4.000000000000000000000000000000,5000,971,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,20,9
165,165_0,FAILED,BoTorch,GenerationStep_1,,,3418,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,17,9
166,166_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,729,5000,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,53,9
167,167_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,17,9
168,168_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,6.000000000000000000000000000000,2097,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,83,9
169,169_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,5000,1092,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,20,9
170,170_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,5000,5000,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,50,9
171,171_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,7.000000000000000000000000000000,5000,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,100,9
172,172_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,1,5000,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,100,9
173,173_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,1,2833,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,96,9
174,174_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,1,3211,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,77,9
175,175_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,4.000000000000000000000000000000,442,208,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,15,9
176,176_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,21,9
177,177_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,1,5000,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,23,9
178,178_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,5000,5000,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,100,9
179,179_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,1,2650,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,42,9
180,180_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,1,1577,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,69,9
181,181_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,1,1598,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,75,9
182,182_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,3213,694,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,36,9
183,183_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,4.000000000000000000000000000000,1624,57,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,15,9
184,184_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,5000,1498,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,56,9
185,185_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,4097,2025,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,100,9
186,186_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,4.000000000000000000000000000000,3347,227,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,13,9
187,187_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,1,1474,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,51,9
188,188_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,1,724,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,38,9
189,189_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,1,1902,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,85,9
190,190_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,4.000000000000000000000000000000,767,266,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,15,9
191,191_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,4722,1027,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,13,9
192,192_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,710,1613,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,66,9
193,193_0,COMPLETED,BoTorch,GenerationStep_1,0.250000000000000000000000000000,5.000000000000000000000000000000,1,165,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,15,9
194,194_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,7.000000000000000000000000000000,1,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,9
195,195_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,4529,1650,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,97,9
196,196_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,7.000000000000000000000000000000,1,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,9
197,197_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,1860,624,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,35,9
198,198_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,1,1449,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,72,9
199,199_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,1,2260,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,100,9
200,200_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,4238,1555,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,38,9
201,201_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,597,1785,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,88,9
202,202_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,4.000000000000000000000000000000,4424,265,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,16,9
203,203_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,5000,2986,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,24,9
204,204_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,5000,663,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,28,9
205,205_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,3790,4682,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,41,9
206,206_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,4681,1771,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,72,9
207,207_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,4796,786,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,49,9
208,208_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,5000,1483,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,58,9
209,209_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,1352,4652,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,42,9
210,210_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,188,1224,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,15,9
211,211_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,1,894,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,22,9
212,212_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,4888,1945,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,8,9
213,213_0,FAILED,BoTorch,GenerationStep_1,,,2257,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,19,9
214,214_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,118,850,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,18,9
215,215_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,18,9
216,216_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,2276,5000,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,25,9
217,217_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,4385,4088,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,27,9
218,218_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,4.000000000000000000000000000000,3673,341,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,23,9
219,219_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,4987,4124,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,46,9
220,220_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,4865,2162,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,9,9
221,221_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,992,4456,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,20,9
222,222_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,433,579,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,23,9
223,223_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,5000,1476,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,13,9
224,224_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,20,9
225,225_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,1,4316,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,62,9
226,226_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,4305,2721,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,6,9
227,227_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,1,4153,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,89,9
228,228_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,1,4521,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,63,9
229,229_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,4023,4297,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,80,9
230,230_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,4716,1033,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,19,9
231,231_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,17,9
232,232_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,2187,446,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,23,9
233,233_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,551,1551,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,13,9
234,234_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,890,3409,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,21,9
235,235_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,127,708,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,23,9
236,236_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,15.000000000000000000000000000000,4315,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,18,9
237,237_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,3427,2308,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,9
238,238_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,177,1162,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,24,9
239,239_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,4589,5000,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,34,9
240,240_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,764.000000000000000000000000000000,1232,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,64,9
241,241_0,FAILED,BoTorch,GenerationStep_1,,,4002,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.384825471615799608038344103988,18,9
242,242_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,2934.000000000000000000000000000000,3381,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,90,9
243,243_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,4429,825,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.414663250544592631996465570410,26,9
244,244_0,FAILED,BoTorch,GenerationStep_1,,,186,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,31,9
245,245_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,1809,457,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.476322476121577687013797230975,24,9
246,246_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,9
247,247_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,100,9
248,248_0,FAILED,BoTorch,GenerationStep_1,,,4912,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,9,9
249,249_0,FAILED,BoTorch,GenerationStep_1,,,163,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,23,9
250,250_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,686,5000,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,89,9
251,251_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,110,5000,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.048142589821047312992341460358,100,9
252,252_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,2414.000000000000000000000000000000,3413,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,84,9
253,253_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,588.000000000000000000000000000000,5000,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,60,9
254,254_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,3871,615,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.450841743619369517137585035016,24,9
255,255_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,3928,93,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.774957822584048328096173463564,20,9
256,256_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,1009,1125,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.327311558640293875921400967854,26,9
257,257_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,1406,3300,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.404716447814239321800755533332,18,9
258,258_0,FAILED,BoTorch,GenerationStep_1,,,4752,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,19,9
259,259_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,1031.000000000000000000000000000000,4688,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,70,9
260,260_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,1771.000000000000000000000000000000,70,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,80,9
261,261_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,4.000000000000000000000000000000,4571,248,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.509546066750684034651897036383,23,9
262,262_0,FAILED,BoTorch,GenerationStep_1,,,1892,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.573161711927945849431864644430,96,9
263,263_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,5.000000000000000000000000000000,4799,9,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.354616039326979382018123487796,22,9
264,264_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,4175,1077,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.357978379538149149574621787906,27,9
265,265_0,COMPLETED,BoTorch,GenerationStep_1,0.250000000000000000000000000000,6.000000000000000000000000000000,320,210,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,9
266,266_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,16,5000,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.527490027613806145012631532154,70,9
267,267_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,2690,5000,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.851086405236283538577879426157,1,9
268,268_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,16.000000000000000000000000000000,2127,432,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.318811260296736731500999439959,100,9
269,269_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,3212,3853,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,100,9
270,270_0,FAILED,BoTorch,GenerationStep_1,,,4875,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,69,9
271,271_0,FAILED,BoTorch,GenerationStep_1,,,1227,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,79,9
272,272_0,FAILED,BoTorch,GenerationStep_1,,,1884,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,61,9
273,273_0,FAILED,BoTorch,GenerationStep_1,,,70,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,37,9
274,274_0,FAILED,BoTorch,GenerationStep_1,,,4701,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,5,9
275,275_0,FAILED,BoTorch,GenerationStep_1,,,4804,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,75,9
276,276_0,FAILED,BoTorch,GenerationStep_1,,,3996,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,48,9
277,277_0,FAILED,BoTorch,GenerationStep_1,,,4861,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,84,9
278,278_0,FAILED,BoTorch,GenerationStep_1,,,267,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,65,9
279,279_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,9
280,280_0,FAILED,BoTorch,GenerationStep_1,,,46,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,88,9
281,281_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,7.000000000000000000000000000000,2639,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,55,9
282,282_0,FAILED,BoTorch,GenerationStep_1,,,395,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,58,9
283,283_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,10.000000000000000000000000000000,1,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,4,9
284,284_0,FAILED,BoTorch,GenerationStep_1,,,983,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,92,9
285,285_0,FAILED,BoTorch,GenerationStep_1,,,3717,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,72,9
286,286_0,FAILED,BoTorch,GenerationStep_1,,,2304,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,35,9
287,287_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,9
288,288_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,6,9
289,289_0,COMPLETED,BoTorch,GenerationStep_1,0.250000000000000000000000000000,59.000000000000000000000000000000,4824,77,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,82,9
290,290_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,24.000000000000000000000000000000,1985,176,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,80,9
291,291_0,FAILED,BoTorch,GenerationStep_1,,,4349,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,73,9
292,292_0,FAILED,BoTorch,GenerationStep_1,,,4913,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,38,9
293,293_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,8.000000000000000000000000000000,1,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,9
294,294_0,FAILED,BoTorch,GenerationStep_1,,,2420,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,67,9
295,295_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,19.000000000000000000000000000000,210,111,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,63,9
296,296_0,FAILED,BoTorch,GenerationStep_1,,,665,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,77,9
297,297_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,8.000000000000000000000000000000,2298,208,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,73,9
298,298_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,1426,195,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,37,9
299,299_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,9
300,300_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,16.000000000000000000000000000000,1,582,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,100,9
301,301_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,7.000000000000000000000000000000,5000,170,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,51,9
302,302_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,97.000000000000000000000000000000,5000,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,36,9
303,303_0,COMPLETED,BoTorch,GenerationStep_1,0.250000000000000000000000000000,71.000000000000000000000000000000,1,73,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,88,9
304,304_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,7.000000000000000000000000000000,5000,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,9
305,305_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,9
306,306_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,30.000000000000000000000000000000,1,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,24,9
307,307_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,139.000000000000000000000000000000,3639,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,41,9
308,308_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,65,9
309,309_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,8.000000000000000000000000000000,5000,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,9
310,310_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,9
311,311_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,6.000000000000000000000000000000,5000,132,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,42,9
312,312_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,150.000000000000000000000000000000,1,64,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,9
313,313_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,17.000000000000000000000000000000,1,171,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,67,9
314,314_0,COMPLETED,BoTorch,GenerationStep_1,0.250000000000000000000000000000,22.000000000000000000000000000000,5000,81,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,64,9
315,315_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,7.000000000000000000000000000000,1059,1090,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,70,9
316,316_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,6.000000000000000000000000000000,5000,1006,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,63,9
317,317_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,9
318,318_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,100,9
319,319_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,8.000000000000000000000000000000,5000,8,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,53,9
320,320_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,175.000000000000000000000000000000,5000,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,44,9
321,321_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,16.000000000000000000000000000000,1,673,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,100,9
322,322_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,7.000000000000000000000000000000,1,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,9
323,323_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,21.000000000000000000000000000000,1,263,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,81,9
324,324_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,8.000000000000000000000000000000,5000,322,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,61,9
325,325_0,COMPLETED,BoTorch,GenerationStep_1,0.250000000000000000000000000000,70.000000000000000000000000000000,3331,166,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,9
326,326_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,40.000000000000000000000000000000,5000,224,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,9
327,327_0,COMPLETED,BoTorch,GenerationStep_1,0.260000000000000008881784197001,6.000000000000000000000000000000,5000,126,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,9
328,328_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,10.000000000000000000000000000000,1,387,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,67,9
329,329_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,56.000000000000000000000000000000,1,84,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,9
330,330_0,FAILED,BoTorch,GenerationStep_1,,,158,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,5,9
331,331_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,6.000000000000000000000000000000,3123,603,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,41,9
332,332_0,FAILED,BoTorch,GenerationStep_1,,,4354,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,34,9
333,333_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,81.000000000000000000000000000000,1,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,34,9
334,334_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,5.000000000000000000000000000000,3070,407,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,5,9
335,335_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,76,9
336,336_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,4349,788,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,40,9
337,337_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,39,9
338,338_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,32,9
339,339_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,7.000000000000000000000000000000,1,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,62,9
340,340_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,12.000000000000000000000000000000,1166,722,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,78,9
341,341_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,5.000000000000000000000000000000,4921,421,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,41,9
342,342_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,5.000000000000000000000000000000,5000,518,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,34,9
343,343_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,5.000000000000000000000000000000,3875,664,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,55,9
344,344_0,FAILED,BoTorch,GenerationStep_1,,,4960,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,5,9
345,345_0,RUNNING,BoTorch,GenerationStep_1,,,1,191,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,56,9
346,346_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,8.000000000000000000000000000000,4740,827,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,78,9
347,347_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,7.000000000000000000000000000000,1,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,72,9
348,348_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,7.000000000000000000000000000000,3052,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,48,9
349,349_0,FAILED,BoTorch,GenerationStep_1,,,1880,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,47,9
350,350_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,5.000000000000000000000000000000,4873,329,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,32,9
351,351_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,7.000000000000000000000000000000,5000,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,9
352,352_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,3097,670,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,5,9
353,353_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,5.000000000000000000000000000000,4519,886,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,42,9
354,354_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,11.000000000000000000000000000000,4075,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,12,9
355,299_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,9
356,356_0,FAILED,BoTorch,GenerationStep_1,,,379,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,7,9
357,357_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,7.000000000000000000000000000000,295,752,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,55,9
358,358_0,FAILED,BoTorch,GenerationStep_1,,,263,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,24,9
359,359_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,5.000000000000000000000000000000,4936,821,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,53,9
360,360_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,8.000000000000000000000000000000,1,2,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,5,9
361,361_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,6.000000000000000000000000000000,5000,956,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,9
362,362_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,33,9
363,363_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,11.000000000000000000000000000000,148,1041,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,87,9
364,364_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,7.000000000000000000000000000000,2443,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,78,9
365,365_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,7.000000000000000000000000000000,593,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,51,9
366,366_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,7.000000000000000000000000000000,4298,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,89,9
367,367_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,4.000000000000000000000000000000,3970,62,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,9,9
368,368_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,1,603,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,40,9
369,369_0,FAILED,BoTorch,GenerationStep_1,,,4974,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,4,9
370,370_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,5.000000000000000000000000000000,50,441,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,25,9
371,371_0,COMPLETED,BoTorch,GenerationStep_1,0.250000000000000000000000000000,6.000000000000000000000000000000,5000,553,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,9
372,372_0,COMPLETED,BoTorch,GenerationStep_1,0.250000000000000000000000000000,5.000000000000000000000000000000,2365,70,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,24,9
373,373_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,8.000000000000000000000000000000,124,41,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,36,9
374,374_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,7.000000000000000000000000000000,3589,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,69,9
375,375_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,46,9
376,376_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,8.000000000000000000000000000000,180,2183,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,91,9
377,377_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,1,629,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,35,9
378,378_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,4.000000000000000000000000000000,350,111,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,24,9
379,379_0,FAILED,BoTorch,GenerationStep_1,,,734,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,75,9
380,380_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,7.000000000000000000000000000000,1,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,31,9
381,381_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,15.000000000000000000000000000000,4043,1043,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,96,9
382,382_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,1219,2207,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,54,9
383,383_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,6.000000000000000000000000000000,362,88,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,33,9
384,384_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,6.000000000000000000000000000000,1731,2170,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,86,9
385,385_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,4.000000000000000000000000000000,4863,112,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,27,9
386,386_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,10.000000000000000000000000000000,855,1175,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,85,9
387,387_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,7.000000000000000000000000000000,1133,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,79,9
388,388_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,988,597,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,5,9
389,389_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,3.000000000000000000000000000000,524,35,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,8,9
390,390_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,2904,1054,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,29,9
391,391_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,29.000000000000000000000000000000,4817,528,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,100,9
392,392_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,28.000000000000000000000000000000,1877,119,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,75,9
393,393_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,29.000000000000000000000000000000,2441,430,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,100,9
394,394_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,30.000000000000000000000000000000,994,586,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,9
395,395_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,5.000000000000000000000000000000,838,2549,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,75,9
396,396_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,5.000000000000000000000000000000,786,2793,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,76,9
397,397_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,4782,1201,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,31,9
398,398_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,1425,1863,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,41,9
399,399_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,5.000000000000000000000000000000,1896,1810,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,75,9
400,400_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,7.000000000000000000000000000000,1302,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,96,9
401,401_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,6.000000000000000000000000000000,4309,3092,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,78,9
402,402_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,1416,2518,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,43,9
403,403_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,5.000000000000000000000000000000,2492,2491,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,73,9
404,404_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,229,2949,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,44,9
405,405_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,5.000000000000000000000000000000,1065,2785,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,68,9
406,406_0,FAILED,BoTorch,GenerationStep_1,,,559,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,75,9
407,407_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,6.000000000000000000000000000000,2958,1968,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,74,9
408,408_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,3328,3742,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,67,9
409,409_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,1063,3059,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,43,9
410,410_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,10.000000000000000000000000000000,2480,3046,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,100,9
411,411_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,4341,3527,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,69,9
412,412_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,5.000000000000000000000000000000,4211,3122,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,70,9
413,413_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,3.000000000000000000000000000000,4378,3062,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,40,9
414,414_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,10.000000000000000000000000000000,658,2724,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,100,9
415,415_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,4.000000000000000000000000000000,2058,1990,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,62,9
416,416_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,6.000000000000000000000000000000,3596,3134,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,82,9
417,417_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,9.000000000000000000000000000000,2016,2740,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,100,9
418,418_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,5.000000000000000000000000000000,2294,2881,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,76,9
419,419_0,COMPLETED,BoTorch,GenerationStep_1,0.200000000000000011102230246252,5.000000000000000000000000000000,1906,2580,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,73,9
420,420_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,7.000000000000000000000000000000,2655,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,4,9
421,421_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,5.000000000000000000000000000000,4980,601,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,53,9
422,422_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,7.000000000000000000000000000000,4147,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,18,9
423,423_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,5.000000000000000000000000000000,2556,971,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,47,9
424,424_0,FAILED,BoTorch,GenerationStep_1,,,3815,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,28,9
425,425_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,7.000000000000000000000000000000,4311,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,19,9
426,426_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,5.000000000000000000000000000000,3865,614,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,52,9
427,427_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,5.000000000000000000000000000000,2275,651,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,53,9
428,428_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,5.000000000000000000000000000000,2080,587,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,52,9
429,429_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,8.000000000000000000000000000000,632,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,66,9
430,430_0,FAILED,BoTorch,GenerationStep_1,,,3876,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,48,9
431,431_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,7.000000000000000000000000000000,2231,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,27,9
432,432_0,COMPLETED,BoTorch,GenerationStep_1,0.250000000000000000000000000000,18.000000000000000000000000000000,3411,66,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,57,9
433,433_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,5.000000000000000000000000000000,4466,536,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,9,9
434,434_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,5.000000000000000000000000000000,2708,1008,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,59,9
435,435_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,5.000000000000000000000000000000,4271,632,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,52,9
436,436_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,5.000000000000000000000000000000,3360,561,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,52,9
437,437_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,2301,599,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,56,9
438,438_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,7.000000000000000000000000000000,1,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,45,9
439,439_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,10.000000000000000000000000000000,4492,984,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,81,9
440,440_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,6.000000000000000000000000000000,2815,572,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,46,9
441,441_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,16.000000000000000000000000000000,2816,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,15,9
442,442_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,5.000000000000000000000000000000,1354,610,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,52,9
443,443_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,4.000000000000000000000000000000,2657,17,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,58,9
444,444_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,36.000000000000000000000000000000,1936,301,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,95,9
445,445_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,9.000000000000000000000000000000,718,134,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,47,9
446,446_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,6.000000000000000000000000000000,1231,406,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,47,9
447,447_0,FAILED,BoTorch,GenerationStep_1,,,3599,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,45,9
448,448_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,5.000000000000000000000000000000,3129,1026,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,6,9
449,449_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,7.000000000000000000000000000000,4807,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,4,9
450,450_0,FAILED,BoTorch,GenerationStep_1,,,1096,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,29,9
451,451_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,915,573,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,30,9
452,452_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,12.000000000000000000000000000000,1979,590,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,72,9
453,453_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,7.000000000000000000000000000000,3472,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,13,9
454,454_0,FAILED,BoTorch,GenerationStep_1,,,722,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,40,9
455,455_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,11.000000000000000000000000000000,1136,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,7,9
456,456_0,FAILED,BoTorch,GenerationStep_1,,,196,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,29,9
457,457_0,FAILED,BoTorch,GenerationStep_1,,,3768,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,9
458,458_0,FAILED,BoTorch,GenerationStep_1,,,4289,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,18,9
459,459_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,3928,596,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,15,9
460,460_0,FAILED,BoTorch,GenerationStep_1,,,3513,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,11,9
461,461_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,9
462,462_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,10.000000000000000000000000000000,5000,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,7,9
463,463_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,7.000000000000000000000000000000,2482,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,92,9
464,464_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,7.000000000000000000000000000000,1675,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,74,9
465,465_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,8.000000000000000000000000000000,136,806,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,74,9
466,466_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,8.000000000000000000000000000000,955,615,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,64,9
467,467_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,11.000000000000000000000000000000,3855,481,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,71,9
468,468_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,7.000000000000000000000000000000,1587,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,86,9
469,469_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,5.000000000000000000000000000000,4660,290,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,23,9
470,470_0,FAILED,BoTorch,GenerationStep_1,,,4202,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,29,9
471,471_0,FAILED,BoTorch,GenerationStep_1,,,4378,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,32,9
472,472_0,FAILED,BoTorch,GenerationStep_1,,,954,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,10,9
473,473_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,7.000000000000000000000000000000,1644,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,98,9
474,474_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,48,9
475,475_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,530,624,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,61,9
476,476_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,5.000000000000000000000000000000,4429,1000,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,24,9
477,477_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,4.000000000000000000000000000000,484,493,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.445432556286316672089498069909,31,9
478,478_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,3685,1041,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,36,9
479,479_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,3364,562,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.252993091241944245695094650728,4,9
480,480_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,2174,465,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,38,9
481,481_0,FAILED,BoTorch,GenerationStep_1,,,963,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,44,9
482,482_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,5.000000000000000000000000000000,2407,516,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,40,9
483,483_0,FAILED,BoTorch,GenerationStep_1,,,2931,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,12,9
484,484_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,29,9
485,485_0,COMPLETED,BoTorch,GenerationStep_1,0.250000000000000000000000000000,5.000000000000000000000000000000,4187,55,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,4,9
486,486_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,40,9
487,487_0,FAILED,BoTorch,GenerationStep_1,,,3722,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,9
488,488_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,4.000000000000000000000000000000,759,530,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,40,9
489,489_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,4.000000000000000000000000000000,1026,495,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,39,9
490,490_0,FAILED,BoTorch,GenerationStep_1,,,1101,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,17,9
491,491_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,4383,197,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,44,9
492,492_0,FAILED,BoTorch,GenerationStep_1,,,4792,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,36,9
493,493_0,FAILED,BoTorch,GenerationStep_1,,,3243,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,28,9
494,494_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,817,456,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,38,9
495,495_0,FAILED,BoTorch,GenerationStep_1,,,3762,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,9,9
496,496_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,5.000000000000000000000000000000,3879,513,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,3,9
497,497_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,9
498,498_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,4.000000000000000000000000000000,72,451,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,38,9
499,499_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,4.000000000000000000000000000000,2468,342,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,45,9
500,500_0,COMPLETED,BoTorch,GenerationStep_1,0.220000000000000001110223024625,4.000000000000000000000000000000,1610,356,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,9,9
501,501_0,FAILED,BoTorch,GenerationStep_1,,,302,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,9,9
502,502_0,FAILED,BoTorch,GenerationStep_1,,,1,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,47,9
503,503_0,FAILED,BoTorch,GenerationStep_1,,,893,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,28,9
504,504_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,30,9
505,505_0,COMPLETED,BoTorch,GenerationStep_1,0.230000000000000009992007221626,7.000000000000000000000000000000,5000,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,30,9
506,506_0,COMPLETED,BoTorch,GenerationStep_1,0.250000000000000000000000000000,6.000000000000000000000000000000,42,153,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,35,9
507,507_0,COMPLETED,BoTorch,GenerationStep_1,0.239999999999999991118215802999,5.000000000000000000000000000000,443,454,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,11,9
508,508_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,48,9
509,509_0,COMPLETED,BoTorch,GenerationStep_1,0.209999999999999992228438827624,4.000000000000000000000000000000,287,490,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,29,9
</pre>
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			<script>
				createTable(tab_results_csv_json, tab_results_headers_json, 'tab_results_csv_table');</script>
			
			<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 3886319 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_TMDBalanced5s_ft_9_HoeffdingTreeClassifier_ACCURACY-RUNTIME/0/single_runs/3886319/3886319_0_result.pkl
has not produced any output (state: TIMEOUT)
Error stream produced:
----------------------------------------
slurmstepd: error: *** JOB 3886319 ON i7081 CANCELLED AT 2025-03-31T14:02:38 DUE TO TIME LIMIT ***



⚠ Job 3886325 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_TMDBalanced5s_ft_9_HoeffdingTreeClassifier_ACCURACY-RUNTIME/0/single_runs/3886325/3886325_0_result.pkl
has not produced any output (state: TIMEOUT)
Error stream produced:
----------------------------------------
slurmstepd: error: *** JOB 3886325 ON i7081 CANCELLED AT 2025-03-31T14:02:38 DUE TO TIME LIMIT ***



⚠ Job 3886395 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_TMDBalanced5s_ft_9_HoeffdingTreeClassifier_ACCURACY-RUNTIME/0/single_runs/3886395/3886395_0_result.pkl
has not produced any output (state: TIMEOUT)
Error stream produced:
----------------------------------------
slurmstepd: error: *** JOB 3886395 ON i7066 CANCELLED AT 2025-03-31T14:02:38 DUE TO TIME LIMIT ***



⚠ Job 3898563 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_TMDBalanced5s_ft_9_HoeffdingTreeClassifier_ACCURACY-RUNTIME/0/single_runs/3898563/3898563_0_result.pkl
has not produced any output (state: TIMEOUT)
Error stream produced:
----------------------------------------
slurmstepd: error: *** JOB 3898563 ON i7172 CANCELLED AT 2025-03-31T16:26:46 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_9_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;9&#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">1743371290.1539762,30,0,0
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1743446200.8962972,30,4,13
1743446201.2413945,30,4,13
1743446202.698391,30,3,10
1743446202.9238894,30,3,10
1743446204.6397746,30,2,7
1743446204.9935732,30,2,7
1743446206.2168994,30,1,3
1743446206.4153595,30,1,3
1743446209.838465,30,0,0
1743446212.295936,30,0,0
1743446215.0182939,30,0,0
1743446456.5027342,30,0,0
1743446593.956676,30,0,0
1743446752.5347214,30,0,0
1743446858.981879,30,0,0
1743447010.1850412,30,0,0
1743447157.8666608,30,0,0
1743447298.7289424,30,0,0
1743447405.774921,30,0,0
1743447519.5462208,30,0,0
1743447683.5679877,30,0,0
1743447834.61579,30,0,0
1743447976.582759,30,0,0
1743448083.8361914,30,0,0
1743448251.730753,30,0,0
1743448402.578578,30,0,0
1743448630.6868684,30,0,0
1743448783.2806275,30,0,0
1743448965.2434857,30,0,0
1743449153.9692245,30,0,0
1743449313.0486493,30,0,0
1743449470.4260411,30,0,0
1743449604.8254914,30,0,0
1743449785.553985,30,0,0
1743449925.2361474,30,0,0
1743450051.6476517,30,0,0
1743450223.8019702,30,0,0
1743450390.9265509,30,0,0
1743450559.7289314,30,0,0
1743450726.172156,30,0,0
1743450883.3599286,30,0,0
1743450883.652094,30,0,0
1743450885.5234435,30,1,3
1743450885.6362166,30,1,3
1743450885.9638953,30,1,3
1743450887.8858144,30,2,7
1743450887.9597669,30,2,7
1743450888.2716253,30,2,7
1743450890.412477,30,3,10
1743450890.477416,30,3,10
1743450890.7721155,30,3,10
1743450892.4048004,30,4,13
1743450892.4733465,30,4,13
1743450892.813801,30,4,13
1743450894.37619,30,5,17
1743450894.4316733,30,5,17
1743450894.6096785,30,5,17
1743450896.3195713,30,6,20
1743450896.3723457,30,6,20
1743450896.6989634,30,6,20
1743450898.4789875,30,7,23
1743450898.6880174,30,7,23
1743450898.922393,30,7,23
1743450900.5857954,30,8,27
1743450900.6784108,30,8,27
1743450901.0274246,30,8,27
1743450903.005115,30,9,30
1743450903.062463,30,9,30
1743450903.3682818,30,9,30
1743450905.5395231,30,10,33
1743450905.7214665,30,10,33
1743450906.01165,30,10,33
1743450908.1153748,30,11,37
1743450908.1927104,30,11,37
1743450908.5088036,30,11,37
1743450910.597295,30,12,40
1743450910.6534255,30,12,40
1743450911.0083687,30,12,40
1743450913.243456,30,13,43
1743450913.65632,30,13,43
1743450914.0287368,30,13,43
1743450916.080069,30,14,47
1743450916.144418,30,14,47
1743450916.4148273,30,14,47
1743450918.452998,30,15,50
1743450918.5324008,30,15,50
1743450918.9773235,30,15,50
1743450921.115013,30,16,53
1743450921.630324,30,16,53
1743450921.909012,30,16,53
1743450924.014143,30,17,57
1743450924.2553258,30,17,57
1743450924.514395,30,17,57
1743450926.3248723,30,18,60
1743450926.4340837,30,18,60
1743450926.6265707,30,18,60
1743450928.3006382,30,19,63
1743450928.3574567,30,19,63
1743450928.5877821,30,19,63
1743450930.1922302,30,20,67
1743450930.3055367,30,20,67
1743450930.5358913,30,20,67
1743450932.31401,30,21,70
1743450932.3701832,30,21,70
1743450932.7219048,30,21,70
1743450934.3525374,30,22,73
1743450934.4214194,30,22,73
1743450934.783564,30,22,73
1743450936.5493603,30,23,77
1743450936.7034874,30,23,77
1743450937.01786,30,23,77
1743450938.9641132,30,24,80
1743450939.081079,30,24,80
1743450939.461579,30,24,80
1743450941.2788897,30,25,83
1743450941.3408473,30,25,83
1743450941.6133504,30,25,83
1743450943.331035,30,26,87
1743450943.392341,30,26,87
1743450943.6695373,30,26,87
1743450946.183208,30,27,90
1743450946.2630668,30,27,90
1743450946.5954475,30,27,90
1743450948.4411678,30,28,93
1743450948.5250816,30,28,93
1743450948.8965547,30,28,93
1743450950.9810917,30,29,97
1743450951.101308,30,29,97
1743450951.3708136,30,29,97
1743450954.280887,30,30,100
1743450957.9241362,30,30,100
1743450962.5034084,30,30,100
1743450970.3416607,30,30,100
1743450978.4860175,30,30,100
1743450986.5355732,30,30,100
1743450994.6460168,30,30,100
1743451002.7091522,30,30,100
1743451010.4279308,30,30,100
1743451018.9778721,30,30,100
1743451027.3051927,30,30,100
1743451035.0108736,30,30,100
1743451043.05767,30,30,100
1743451051.2100155,30,30,100
1743451059.3304024,30,30,100
1743451067.7742462,30,30,100
1743451075.9730957,30,30,100
1743451081.495232,30,30,100
1743451083.1553633,30,29,97
1743451083.4165106,30,29,97
1743451084.685436,30,28,93
1743451086.3407776,30,27,90
1743451088.0740936,30,26,87
1743451090.0877123,30,25,83
1743451091.6717553,30,24,80
1743451091.775847,30,24,80
1743451092.7963676,30,23,77
1743451094.0896788,30,22,73
1743451095.4140303,30,21,70
1743451095.5792768,30,21,70
1743451097.168981,30,20,67
1743451097.3450472,30,20,67
1743451098.6288762,30,19,63
1743451098.9672062,30,19,63
1743451100.4383526,30,18,60
1743451100.659494,30,18,60
1743451101.9912612,30,17,57
1743451102.1402435,30,17,57
1743451103.4439616,30,16,53
1743451103.713377,30,16,53
1743451105.4532347,30,15,50
1743451105.6219513,30,15,50
1743451106.9007862,30,14,47
1743451107.1007092,30,14,47
1743451108.2626073,30,13,43
1743451109.5987377,30,12,40
1743451111.1892438,30,11,37
1743451113.231926,30,10,33
1743451113.403495,30,10,33
1743451114.6152658,30,9,30
1743451116.3689005,30,8,27
1743451116.6440659,30,8,27
1743451117.9928725,30,7,23
1743451118.2167172,30,7,23
1743451119.5347137,30,6,20
1743451119.7289429,30,6,20
1743451121.0209372,30,5,17
1743451121.3562372,30,5,17
1743451123.1716871,30,4,13
1743451123.3237226,30,4,13
1743451126.7520096,30,3,10
1743451126.9245758,30,3,10
1743451132.4393086,30,3,10
1743451132.6545105,30,3,10
1743451134.454015,30,2,7
1743451134.6814415,30,2,7
1743451135.9845288,30,1,3
1743451136.1058967,30,1,3
1743451139.7673988,30,0,0
1743451142.3047838,30,0,0
1743451145.3531215,30,0,0
1743451356.376836,30,0,0
1743451516.8662167,30,0,0
1743451665.9644759,30,0,0
1743451824.7678342,30,0,0
1743451960.8448315,30,0,0
1743452103.8337753,30,0,0
1743452275.560458,30,0,0
1743452409.2538824,30,0,0
1743452542.618636,30,0,0
1743452705.2571387,30,0,0
1743452876.4305682,30,0,0
1743453046.6004715,30,0,0
1743453199.9135988,30,0,0
1743453352.434677,30,0,0
1743453537.0194626,30,0,0
1743453721.9887938,30,0,0
1743453988.8259714,30,0,0
1743454150.2413943,30,0,0
1743454383.8943036,30,0,0
1743454584.3906906,30,0,0
1743454873.5545118,30,0,0
1743455059.729958,30,0,0
1743455272.9414127,30,0,0
1743455455.6420107,30,0,0
1743455635.379792,30,0,0
1743455848.9707785,30,0,0
1743456050.967438,30,0,0
1743456303.5184715,30,0,0
1743456584.3512115,30,0,0
1743456794.7800605,30,0,0
1743456795.1653955,30,0,0
1743456797.1335058,30,1,3
1743456797.3526287,30,1,3
1743456797.6278222,30,1,3
1743456799.4635978,30,2,7
1743456799.5321825,30,2,7
1743456799.8967142,30,2,7
1743456801.780259,30,3,10
1743456801.852544,30,3,10
1743456802.1470163,30,3,10
1743456804.0599747,30,4,13
1743456804.1212819,30,4,13
1743456804.437767,30,4,13
1743456806.3295417,30,5,17
1743456806.4322827,30,5,17
1743456806.742126,30,5,17
1743456808.3724794,30,6,20
1743456808.429148,30,6,20
1743456808.7566717,30,6,20
1743456810.4208524,30,7,23
1743456810.5427077,30,7,23
1743456810.8237817,30,7,23
1743456812.454758,30,8,27
1743456812.5117502,30,8,27
1743456812.9173481,30,8,27
1743456814.6883085,30,9,30
1743456814.79741,30,9,30
1743456815.088644,30,9,30
1743456817.0981262,30,10,33
1743456817.2343273,30,10,33
1743456817.523121,30,10,33
1743456819.3886921,30,11,37
1743456819.4767973,30,11,37
1743456819.7550309,30,11,37
1743456821.6431546,30,12,40
1743456821.7018628,30,12,40
1743456822.0560253,30,12,40
1743456824.0207574,30,13,43
1743456824.0816205,30,13,43
1743456824.388028,30,13,43
1743456826.3386364,30,14,47
1743456826.4042537,30,14,47
1743456826.7219656,30,14,47
1743456828.4962935,30,15,50
1743456828.5519218,30,15,50
1743456828.8342743,30,15,50
1743456830.5242994,30,16,53
1743456830.5800433,30,16,53
1743456830.786236,30,16,53
1743456832.442595,30,17,57
1743456832.5519016,30,17,57
1743456832.910722,30,17,57
1743456834.4452498,30,18,60
1743456834.6450427,30,18,60
1743456834.832189,30,18,60
1743456836.8822298,30,19,63
1743456836.9444375,30,19,63
1743456837.159469,30,19,63
1743456839.0963824,30,20,67
1743456839.228349,30,20,67
1743456839.6203313,30,20,67
1743456841.7208173,30,21,70
1743456841.7932394,30,21,70
1743456842.0849965,30,21,70
1743456844.0794144,30,22,73
1743456844.1508405,30,22,73
1743456844.4249575,30,22,73
1743456846.4392107,30,23,77
1743456846.5265353,30,23,77
1743456846.8704786,30,23,77
1743456848.6163106,30,24,80
1743456848.725783,30,24,80
1743456849.0335526,30,24,80
1743456851.1051862,30,25,83
1743456851.1885629,30,25,83
1743456851.5743742,30,25,83
1743456853.3163407,30,26,87
1743456853.4316683,30,26,87
1743456853.7057269,30,26,87
1743456855.4741216,30,27,90
1743456855.5481706,30,27,90
1743456855.816433,30,27,90
1743456858.5951478,30,28,93
1743456858.7442675,30,28,93
1743456859.1750746,30,28,93
1743456861.0307026,30,29,97
1743456861.1272469,30,29,97
1743456861.3389194,30,29,97
1743456864.309412,30,30,100
1743456864.911436,30,30,100
1743456865.2216575,30,30,100
1743456866.620551,30,29,97
1743456871.224903,30,28,93
1743456871.4666584,30,28,93
1743456876.160424,30,28,93
1743456881.712978,30,28,93
1743456881.9284296,30,28,93
1743456883.197758,30,27,90
1743456884.806812,30,26,87
1743456888.9958305,30,25,83
1743456889.3423526,30,25,83
1743456897.2195764,30,25,83
1743456902.9594119,30,25,83
1743456907.2765198,30,24,80
1743456907.5731194,30,24,80
1743456913.1774852,30,24,80
1743456913.4113433,30,24,80
1743456915.2573254,30,23,77
1743456916.8894904,30,22,73
1743456917.0439618,30,22,73
1743456921.1830711,30,21,70
1743456921.519433,30,21,70
1743456929.4981186,30,21,70
1743456934.9103665,30,21,70
1743456939.20197,30,20,67
1743456939.3780868,30,20,67
1743456945.5172653,30,20,67
1743456945.7319303,30,20,67
1743456949.8186316,30,19,63
1743456950.1521807,30,19,63
1743456958.2510676,30,19,63
1743456963.9621086,30,19,63
1743456964.1483145,30,19,63
1743456965.4248111,30,18,60
1743456967.3300357,30,17,57
1743456971.9720044,30,16,53
1743456972.1981285,30,16,53
1743456977.887216,30,16,53
1743456982.3666341,30,15,50
1743456982.7143826,30,15,50
1743456988.3051817,30,15,50
1743456988.582558,30,15,50
1743456991.9451556,30,14,47
1743456992.0442169,30,14,47
1743456997.5427842,30,14,47
1743456997.7051408,30,14,47
1743456999.5623672,30,13,43
1743457001.4580958,30,12,40
1743457001.664432,30,12,40
1743457005.777492,30,11,37
1743457005.922659,30,11,37
1743457013.9444299,30,11,37
1743457019.6549308,30,11,37
1743457019.8213847,30,11,37
1743457021.3232381,30,10,33
1743457025.8128338,30,9,30
1743457026.0291915,30,9,30
1743457031.6823094,30,9,30
1743457031.9894395,30,9,30
1743457035.9576364,30,8,27
1743457036.0682373,30,8,27
1743457041.509835,30,8,27
1743457043.1066186,30,7,23
1743457047.5661807,30,6,20
1743457047.7923956,30,6,20
1743457053.3643203,30,6,20
1743457057.7601051,30,5,17
1743457057.9588745,30,5,17
1743457063.628694,30,5,17
1743457063.8095348,30,5,17
1743457065.2198064,30,4,13
1743457065.4093904,30,4,13
1743457069.4793994,30,3,10
1743457069.6118212,30,3,10
1743457075.2200754,30,3,10
1743457079.4892905,30,2,7
1743457079.7357237,30,2,7
1743457085.2308342,30,2,7
1743457085.387179,30,2,7
1743457086.8277934,30,1,3
1743457087.015214,30,1,3
1743457090.8204644,30,0,0
</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
1743371290,595.6796875,3.0
1743371290,595.71875,4.1
1743371290,595.8125,3.8
1743371290,595.8125,2.0
1743371290,595.8125,2.6
1743371290,595.8125,3.4
1743371290,595.8125,1.3
1743371404,614.59375,1.9
1743371404,614.59375,1.5
1743371404,614.59375,1.6
1743371404,614.59375,0.0
1743372854,675.82421875,2.1
1743372854,675.82421875,2.5
1743372854,675.82421875,2.5
1743372854,675.82421875,2.3
1743381274,691.765625,5.1
1743381274,691.765625,5.0
1743381274,691.765625,4.9
1743381274,691.765625,5.6
1743390798,695.75,5.1
1743390798,695.8125,1.9
1743390799,695.8125,1.9
1743390799,695.8125,2.7
1743395846,720.0546875,5.6
1743395846,720.0546875,4.9
1743395846,720.0546875,5.1
1743395846,720.0546875,5.1
1743400892,753.55078125,5.7
1743400892,753.55078125,5.2
1743400892,753.55078125,5.4
1743400892,753.55078125,5.7
1743406867,771.50390625,5.5
1743406867,771.50390625,4.0
1743406867,771.50390625,4.1
1743406867,771.50390625,2.4
1743411954,741.35546875,5.5
1743411954,741.35546875,6.5
1743411954,741.35546875,6.8
1743411954,741.35546875,7.9
1743418208,777.58984375,4.9
1743418208,777.58984375,5.8
1743418208,777.58984375,5.7
1743418208,777.58984375,2.9
1743424303,834.546875,5.5
1743424303,834.546875,5.5
1743424303,834.546875,5.4
1743424303,834.546875,5.4
1743427582,755.48828125,6.2
1743427582,755.48828125,4.7
1743427582,755.48828125,5.0
1743427582,755.48828125,5.0
1743434922,771.51171875,5.9
1743434922,771.51171875,6.9
1743434922,771.51171875,6.4
1743434922,771.51171875,6.2
1743439358,798.7890625,6.2
1743439358,798.7890625,5.3
1743439358,798.7890625,5.6
1743439358,798.7890625,2.4
1743442502,789.48046875,6.3
1743442502,789.48046875,5.8
1743442502,789.48046875,6.0
1743442502,789.48046875,6.3
1743446194,803.3046875,6.3
1743446194,803.3046875,5.7
1743446194,803.3046875,5.8
1743446194,803.3046875,4.7
1743450962,850.64453125,7.8
1743450962,850.64453125,9.2
1743450962,850.64453125,9.6
1743450962,850.64453125,10.4
1743456875,810.90234375,8.8
1743456875,810.90234375,8.1
1743456876,810.90234375,7.7
1743456876,810.90234375,9.8
1743457093,810.86328125,8.2
1743457093,810.86328125,9.5
</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>
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