OmniOpt2

Setting	Value
Max. nr. evaluations	50090
Max. nr. evaluations (from arguments)	50000
Number random steps	20
Nr. of workers (parameter)	20
Main process memory (GB)	8
Worker memory (GB)	32
Nr. imported jobs	90

Name	Type	Lower bound	Upper bound	Values	Type	Log Scale?
recent_samples_size	int	1	5000		int	No
n_samples	int	1	5000		int	No
confidence	choice			0.25, 0.1, 0.05, 0.025, 0.01, 0.005, 0.001
feature_proportion	float	0.001	0.999		float	No
n_clusters	int	1	50		int	No

Failed	Succeeded	Running	Total
2	534	1	537

name	min/max
ACCURACY	max
RUNTIME	min

start_time,end_time,run_time,program_string,recent_samples_size,n_samples,feature_proportion,n_clusters,confidence,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
1746192995,1746193015,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1730 n_samples 318 confidence 0.1 feature_proportion 0.999 n_clusters 43,1730,318,0.999,43,0.1,0.57,3,0,None,i7180,3,642.05078125,636.0299479166666,-1,0.954,4903194
1746193424,1746193437,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2310 n_samples 252 confidence 0.1 feature_proportion 0.999 n_clusters 50,2310,252,0.999,50,0.1,0.56,1,0,None,i7176,1,640.1640625,635.39453125,-1,0.882,4903307
1746193965,1746193978,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 713 confidence 0.05 feature_proportion 0.001 n_clusters 42,1,713,0.001,42,0.05,0.55,1,0,None,i7174,1,636.859375,634.7473958333334,-1,0.0005,4903441
1746194163,1746194176,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2552 n_samples 491 confidence 0.025 feature_proportion 0.999 n_clusters 50,2552,491,0.999,50,0.025,0.55,1,0,None,i7172,1,639.4140625,635.8997395833334,-1,0.982,4903489
1746194632,1746194663,31,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 3092 confidence 0.05 feature_proportion 0.999 n_clusters 16,1,3092,0.999,16,0.05,0.55,0,0,None,i7171,0,632.9921875,632.9453125,-1,0,4903576
1746195123,1746195136,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1368 n_samples 450 confidence 0.1 feature_proportion 0.999 n_clusters 50,1368,450,0.999,50,0.1,0.55,2,0,None,i7171,2,641.79296875,635.6979166666666,-1,0.9,4903682
1746195704,1746195717,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2038 n_samples 326 confidence 0.25 feature_proportion 0.999 n_clusters 1,2038,326,0.999,1,0.25,0.55,1,0,None,i7176,1,641.00390625,636.3411458333334,-1,0.978,4903795
1746195874,1746195886,12,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4385 n_samples 162 confidence 0.1 feature_proportion 0.999 n_clusters 50,4385,162,0.999,50,0.1,0.57,4,0,None,i7169,4,637.21875,635.0611979166666,-1,0.972,4903831
1746196204,1746196217,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4722 n_samples 15 confidence 0.1 feature_proportion 0.999 n_clusters 50,4722,15,0.999,50,0.1,None,None,1,None,i7174,,,,,,4903881
1746196464,1746196502,38,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3916 n_samples 283 confidence 0.25 feature_proportion 0.999 n_clusters 50,3916,283,0.999,50,0.25,0.56,4,0,None,i7168,4,641.62109375,636.2864583333334,-1,0.9905,4903939
1746196655,1746196668,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 3974 confidence 0.01 feature_proportion 0.999 n_clusters 50,1,3974,0.999,50,0.01,0.55,0,0,None,i7168,0,634.16015625,634.1106770833334,-1,0,4903971
1746197074,1746197087,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3179 n_samples 287 confidence 0.1 feature_proportion 0.999 n_clusters 1,3179,287,0.999,1,0.1,0.56,2,0,None,i7173,2,638.671875,635.3229166666666,-1,0.861,4904050
1746197554,1746197567,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1782 n_samples 377 confidence 0.025 feature_proportion 0.999 n_clusters 1,1782,377,0.999,1,0.025,0.56,2,0,None,i7169,2,640.71484375,636.0611979166666,-1,0.9425,4904143
1746197843,1746197856,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3168 n_samples 276 confidence 0.025 feature_proportion 0.999 n_clusters 1,3168,276,0.999,1,0.025,0.56,2,0,None,i7167,2,641.359375,636.703125,-1,0.966,4904196
1746198069,1746198100,31,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3225 n_samples 237 confidence 0.025 feature_proportion 0.999 n_clusters 50,3225,237,0.999,50,0.025,0.56,2,0,None,i7166,2,640.19921875,635.4453125,-1,0.948,4904235
1746198283,1746198296,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 1545 confidence 0.25 feature_proportion 0.999 n_clusters 1,1,1545,0.999,1,0.25,0.55,0,0,None,i7166,0,639.94921875,635.3567708333334,-1,0,4904275
1746198754,1746198767,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 149 confidence 0.025 feature_proportion 0.999 n_clusters 50,5000,149,0.999,50,0.025,0.57,5,0,None,i7167,5,636.890625,634.7109375,-1,0.9685,4904362
1746199043,1746199056,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 3260 confidence 0.005 feature_proportion 0.001 n_clusters 50,5000,3260,0.001,50,0.005,0.55,0,0,None,i7166,0,632.95703125,632.90625,-1,0,4904422
1746199223,1746199236,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 4696 confidence 0.025 feature_proportion 0.001 n_clusters 50,1,4696,0.001,50,0.025,0.55,0,0,None,i7166,0,633.02734375,632.9479166666666,-1,0,4904457
1746199474,1746199487,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 2204 confidence 0.05 feature_proportion 0.999 n_clusters 1,1,2204,0.999,1,0.05,0.55,0,0,None,i7164,0,632.5625,632.4661458333334,-1,0,4904519
1746199865,1746199878,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2965 n_samples 309 confidence 0.01 feature_proportion 0.999 n_clusters 1,2965,309,0.999,1,0.01,0.56,2,0,None,i7164,2,642.1875,636.2096354166666,-1,0.927,4904605
1746200124,1746200137,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3514 n_samples 4083 confidence 0.025 feature_proportion 0.999 n_clusters 1,3514,4083,0.999,1,0.025,0.55,0,0,None,i7179,0,634.03515625,633.984375,-1,0,4904659
1746200485,1746200505,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4312 n_samples 241 confidence 0.025 feature_proportion 0.999 n_clusters 1,4312,241,0.999,1,0.025,0.57,4,0,None,i7178,4,640.21484375,635.67578125,-1,0.964,4904739
1746200704,1746200718,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2543 n_samples 318 confidence 0.025 feature_proportion 0.999 n_clusters 50,2543,318,0.999,50,0.025,0.56,2,0,None,i7178,2,642.2734375,636.2044270833334,-1,0.954,4904796
1746200915,1746200928,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 977 confidence 0.025 feature_proportion 0.999 n_clusters 1,1,977,0.999,1,0.025,0.55,1,0,None,i7183,1,639.71875,636.2486979166666,-1,0.0005,4904844
1746201144,1746201157,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 2623 confidence 0.01 feature_proportion 0.999 n_clusters 50,1,2623,0.999,50,0.01,0.55,0,0,None,i7179,0,632.73046875,632.7005208333334,-1,0,4904900
1746201425,1746201438,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 4176 confidence 0.1 feature_proportion 0.999 n_clusters 50,1,4176,0.999,50,0.1,0.55,0,0,None,i7178,0,632.7578125,632.6861979166666,-1,0,4904961
1746201575,1746201588,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 4642 confidence 0.25 feature_proportion 0.999 n_clusters 50,5000,4642,0.999,50,0.25,0.55,0,0,None,i7178,0,633.85546875,633.8268229166666,-1,0,4904992
1746201905,1746201918,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 3768 confidence 0.25 feature_proportion 0.001 n_clusters 1,1,3768,0.001,1,0.25,0.55,0,0,None,i7178,0,633.6640625,633.6145833333334,-1,0,4905054
1746202237,1746202257,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2280 n_samples 340 confidence 0.01 feature_proportion 0.999 n_clusters 1,2280,340,0.999,1,0.01,0.55,2,0,None,i7178,2,639.0703125,635.7369791666666,-1,0.85,4905113
1746202526,1746202540,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 2600 confidence 0.005 feature_proportion 0.001 n_clusters 50,1,2600,0.001,50,0.005,0.55,0,0,None,i7181,0,633.5234375,633.4856770833334,-1,0,4905163
1746202772,1746202785,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 5000 confidence 0.1 feature_proportion 0.001 n_clusters 1,1,5000,0.001,1,0.1,0.55,0,0,None,i7175,0,632.93359375,632.8828125,-1,0,4905206
1746203009,1746203029,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2446 n_samples 312 confidence 0.1 feature_proportion 0.999 n_clusters 50,2446,312,0.999,50,0.1,0.56,2,0,None,i7183,2,640.3671875,635.0403645833334,-1,0.936,4905239
1746203226,1746203239,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 2165 confidence 0.005 feature_proportion 0.001 n_clusters 50,1,2165,0.001,50,0.005,0.55,0,0,None,i7176,0,632.55859375,632.5286458333334,-1,0,4905279
1746203544,1746203557,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 4566 confidence 0.001 feature_proportion 0.999 n_clusters 1,1,4566,0.999,1,0.001,0.55,0,0,None,i7175,0,632.95703125,632.90625,-1,0,4905338
1746203848,1746203861,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3278 n_samples 3689 confidence 0.025 feature_proportion 0.999 n_clusters 50,3278,3689,0.999,50,0.025,0.55,0,0,None,i7174,0,632.5390625,632.4635416666666,-1,0,4905394
1746204005,1746204018,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3653 n_samples 261 confidence 0.1 feature_proportion 0.999 n_clusters 50,3653,261,0.999,50,0.1,0.56,2,0,None,i7173,2,641.546875,635.4973958333334,-1,0.9135,4905429
1746204206,1746204219,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 3047 confidence 0.1 feature_proportion 0.999 n_clusters 50,1,3047,0.999,50,0.1,0.55,0,0,None,i7173,0,633.0703125,633,-1,0,4905469
1746204446,1746204459,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3465 n_samples 4756 confidence 0.01 feature_proportion 0.999 n_clusters 1,3465,4756,0.999,1,0.01,0.55,0,0,None,i7173,0,634.5,634.4309895833334,-1,0,4905512
1746204686,1746204699,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 1448 confidence 0.001 feature_proportion 0.001 n_clusters 50,1,1448,0.001,50,0.001,0.55,1,0,None,i7173,1,636.9609375,635.0078125,-1,0,4905569
1746205027,1746205040,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 1956 confidence 0.001 feature_proportion 0.999 n_clusters 50,1,1956,0.999,50,0.001,0.55,0,0,None,i7173,0,642.953125,636.8450520833334,-1,0,4905633
1746205175,1746205188,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 4267 confidence 0.005 feature_proportion 0.001 n_clusters 1,1,4267,0.001,1,0.005,0.55,0,0,None,i7172,0,633.1171875,633.06640625,-1,0,4905661
1746205416,1746205429,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4206 n_samples 260 confidence 0.1 feature_proportion 0.999 n_clusters 50,4206,260,0.999,50,0.1,0.57,3,0,None,i7181,3,640.984375,636.23828125,-1,0.91,4905710
1746205776,1746205789,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 4348 confidence 0.01 feature_proportion 0.999 n_clusters 50,5000,4348,0.999,50,0.01,0.55,0,0,None,i7172,0,632.859375,632.80859375,-1,0,4905786
1746206026,1746206039,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2135 n_samples 3548 confidence 0.01 feature_proportion 0.999 n_clusters 50,2135,3548,0.999,50,0.01,0.55,0,0,None,i7179,0,632.859375,632.8072916666666,-1,0,4905830
1746206345,1746206359,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 1808 confidence 0.01 feature_proportion 0.999 n_clusters 1,1,1808,0.999,1,0.01,0.55,0,0,None,i7180,0,640.4375,635.8190104166666,-1,0,4905890
1746206605,1746206617,12,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2248 n_samples 347 confidence 0.005 feature_proportion 0.999 n_clusters 1,2248,347,0.999,1,0.005,0.55,1,0,None,i7171,1,640.65625,635.9713541666666,-1,0.8675,4905943
1746206905,1746206917,12,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 4325 confidence 0.025 feature_proportion 0.999 n_clusters 50,1,4325,0.999,50,0.025,0.55,0,0,None,i7176,0,632.91015625,632.859375,-1,0,4905998
1746207094,1746207107,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4338 n_samples 340 confidence 0.025 feature_proportion 0.999 n_clusters 50,4338,340,0.999,50,0.025,0.56,2,0,None,i7169,2,641.53515625,636.7877604166666,-1,0.85,4906034
1746207304,1746207317,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 4289 confidence 0.005 feature_proportion 0.001 n_clusters 1,5000,4289,0.001,1,0.005,0.55,0,0,None,i7179,0,632.91796875,632.8880208333334,-1,0,4906070
1746207584,1746207597,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 3549 confidence 0.005 feature_proportion 0.001 n_clusters 50,5000,3549,0.001,50,0.005,0.55,0,0,None,i7169,0,632.69921875,632.6692708333334,-1,0,4906131
1746207985,1746207998,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1699 n_samples 339 confidence 0.025 feature_proportion 0.999 n_clusters 50,1699,339,0.999,50,0.025,0.56,2,0,None,i7182,2,641.94140625,635.90625,-1,0.8475,4906199
1746208285,1746208298,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 3072 confidence 0.05 feature_proportion 0.001 n_clusters 1,5000,3072,0.001,1,0.05,0.55,0,0,None,i7182,0,633.96484375,633.8671875,-1,0,4906256
1746208485,1746208498,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 3842 confidence 0.005 feature_proportion 0.001 n_clusters 50,1,3842,0.001,50,0.005,0.55,0,0,None,i7179,0,633.58203125,633.53125,-1,0,4906297
1746208885,1746208898,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 1191 confidence 0.005 feature_proportion 0.001 n_clusters 50,5000,1191,0.001,50,0.005,0.55,1,0,None,i7179,1,636.69921875,634.64453125,-1,0,4906373
1746209246,1746209265,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3485 n_samples 351 confidence 0.025 feature_proportion 0.999 n_clusters 50,3485,351,0.999,50,0.025,0.56,2,0,None,i7180,2,639.109375,635.65234375,-1,0.8775,4906462
1746209506,1746209519,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3866 n_samples 271 confidence 0.025 feature_proportion 0.999 n_clusters 50,3866,271,0.999,50,0.025,0.56,2,0,None,i7179,2,642.28515625,636.234375,-1,0.9485,4906533
1746209786,1746209800,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1989 n_samples 322 confidence 0.025 feature_proportion 0.999 n_clusters 50,1989,322,0.999,50,0.025,0.57,3,0,None,i7180,3,641.59765625,635.5065104166666,-1,0.966,4906595
1746210204,1746210224,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 4604 confidence 0.1 feature_proportion 0.001 n_clusters 1,5000,4604,0.001,1,0.1,0.55,0,0,None,i7183,0,633.46484375,633.4348958333334,-1,0,4906690
1746210346,1746210359,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 5000 confidence 0.25 feature_proportion 0.999 n_clusters 50,1,5000,0.999,50,0.25,0.55,0,0,None,i7176,0,632.9765625,632.92578125,-1,0,4906729
1746210566,1746210579,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 2611 confidence 0.025 feature_proportion 0.999 n_clusters 1,1,2611,0.999,1,0.025,0.55,0,0,None,i7179,0,634.625,634.57421875,-1,0,4906776
1746210866,1746210879,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4963 n_samples 203 confidence 0.1 feature_proportion 0.999 n_clusters 50,4963,203,0.999,50,0.1,0.57,3,0,None,i7179,3,642.62109375,636.5963541666666,-1,0.9135,4906839
1746211116,1746211130,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 3662 confidence 0.001 feature_proportion 0.999 n_clusters 50,1,3662,0.999,50,0.001,0.55,0,0,None,i7179,0,633.91015625,633.859375,-1,0,4906902
1746211347,1746211360,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 2332 confidence 0.1 feature_proportion 0.999 n_clusters 1,1,2332,0.999,1,0.1,0.55,0,0,None,i7185,0,633.1796875,633.09375,-1,0,4906950
1746211607,1746211620,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 2683 confidence 0.025 feature_proportion 0.001 n_clusters 50,5000,2683,0.001,50,0.025,0.55,0,0,None,i7185,0,634.609375,634.51953125,-1,0,4907014
1746211807,1746211827,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 237 confidence 0.1 feature_proportion 0.999 n_clusters 50,5000,237,0.999,50,0.1,0.57,4,0,None,i7186,4,640.32421875,635.7109375,-1,0.948,4907059
1746211986,1746212000,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 2586 confidence 0.1 feature_proportion 0.001 n_clusters 1,1,2586,0.001,1,0.1,0.55,0,0,None,i7181,0,633.87109375,633.8411458333334,-1,0,4907093
1746212258,1746212271,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 3230 confidence 0.005 feature_proportion 0.999 n_clusters 1,1,3230,0.999,1,0.005,0.55,0,0,None,i7184,0,633.8515625,633.7864583333334,-1,0,4907146
1746212468,1746212481,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 3145 confidence 0.025 feature_proportion 0.999 n_clusters 1,1,3145,0.999,1,0.025,0.55,0,0,None,i7185,0,633.61328125,633.5833333333334,-1,0,4907193
1746212708,1746212721,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 3977 confidence 0.05 feature_proportion 0.999 n_clusters 1,1,3977,0.999,1,0.05,0.55,0,0,None,i7185,0,632.82421875,632.7044270833334,-1,0,4907245
1746212887,1746212900,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 3115 confidence 0.01 feature_proportion 0.999 n_clusters 1,5000,3115,0.999,1,0.01,0.55,0,0,None,i7183,0,634.57421875,634.5234375,-1,0,4907285
1746213007,1746213020,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 2156 confidence 0.005 feature_proportion 0.999 n_clusters 1,5000,2156,0.999,1,0.005,0.55,0,0,None,i7185,0,633.69140625,633.6614583333334,-1,0,4907313
1746213156,1746213170,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 4001 confidence 0.025 feature_proportion 0.001 n_clusters 50,1,4001,0.001,50,0.025,0.55,0,0,None,i7183,0,634.56640625,634.515625,-1,0,4907348
1746213307,1746213320,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3965 n_samples 2349 confidence 0.1 feature_proportion 0.999 n_clusters 50,3965,2349,0.999,50,0.1,0.55,0,0,None,i7181,0,633.59765625,633.546875,-1,0,4907380
1746213487,1746213501,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 3917 confidence 0.025 feature_proportion 0.999 n_clusters 1,5000,3917,0.999,1,0.025,0.55,0,0,None,i7186,0,632.53515625,632.4075520833334,-1,0,4907418
1746213728,1746213748,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2970 n_samples 430 confidence 0.1 feature_proportion 0.999 n_clusters 50,2970,430,0.999,50,0.1,0.56,2,0,None,i7186,2,642.15625,636.1184895833334,-1,0.86,4907474
1746214058,1746214078,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1998 n_samples 354 confidence 0.025 feature_proportion 0.001 n_clusters 50,1998,354,0.001,50,0.025,0.56,4,0,None,i7186,4,640.3125,634.9635416666666,-1,0.92,4907553
1746214247,1746214260,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 4742 confidence 0.001 feature_proportion 0.001 n_clusters 50,5000,4742,0.001,50,0.001,0.55,0,0,None,i7180,0,633.52734375,633.4895833333334,-1,0,4907599
1746214407,1746214420,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 3161 confidence 0.001 feature_proportion 0.999 n_clusters 50,5000,3161,0.999,50,0.001,0.55,0,0,None,i7176,0,632.75390625,632.7044270833334,-1,0,4907640
1746214667,1746214680,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 4688 confidence 0.025 feature_proportion 0.999 n_clusters 50,5000,4688,0.999,50,0.025,0.55,0,0,None,i7176,0,633.57421875,633.5247395833334,-1,0,4907703
1746215067,1746215079,12,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 1380 confidence 0.1 feature_proportion 0.999 n_clusters 50,1,1380,0.999,50,0.1,0.55,0,0,None,i7176,0,642.7890625,636.72265625,-1,0,4907800
1746215377,1746215397,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 170 confidence 0.025 feature_proportion 0.999 n_clusters 50,5000,170,0.999,50,0.025,0.58,4,0,None,i7180,4,633.8046875,632.9778645833334,-1,0.935,4907865
1746215648,1746215668,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4164 n_samples 252 confidence 0.025 feature_proportion 0.999 n_clusters 50,4164,252,0.999,50,0.025,0.57,3,0,None,i7184,3,640.2578125,635.4739583333334,-1,0.882,4907930
1746215988,1746216001,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 3734 confidence 0.025 feature_proportion 0.001 n_clusters 1,5000,3734,0.001,1,0.025,0.55,0,0,None,i7185,0,633.671875,633.6419270833334,-1,0,4908010
1746216218,1746216231,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 1483 confidence 0.01 feature_proportion 0.999 n_clusters 50,5000,1483,0.999,50,0.01,0.55,1,0,None,i7183,1,643.27734375,637.2057291666666,-1,0,4908069
1746216577,1746216590,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 1224 confidence 0.25 feature_proportion 0.999 n_clusters 1,1,1224,0.999,1,0.25,0.55,1,0,None,i7186,1,638.765625,635.43359375,-1,0,4908143
1746216894,1746216907,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3626 n_samples 5000 confidence 0.005 feature_proportion 0.999 n_clusters 1,3626,5000,0.999,1,0.005,0.55,0,0,None,i7186,0,634.02734375,633.9869791666666,-1,0,4908215
1746217040,1746217059,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4062 n_samples 295 confidence 0.05 feature_proportion 0.999 n_clusters 50,4062,295,0.999,50,0.05,0.57,3,0,None,i7179,3,642.3203125,636.2200520833334,-1,0.885,4908255
1746217350,1746217370,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3807 n_samples 389 confidence 0.1 feature_proportion 0.999 n_clusters 50,3807,389,0.999,50,0.1,0.56,2,0,None,i7179,2,638.7578125,635.3424479166666,-1,0.9725,4908328
1746217608,1746217621,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 2827 confidence 0.1 feature_proportion 0.999 n_clusters 50,5000,2827,0.999,50,0.1,0.55,0,0,None,i7175,0,633.8359375,633.8059895833334,-1,0,4908399
1746218127,1746218141,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2685 n_samples 341 confidence 0.05 feature_proportion 0.999 n_clusters 50,2685,341,0.999,50,0.05,0.56,2,0,None,i7184,2,641.3359375,636.62109375,-1,0.8525,4908508
1746218307,1746218320,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2169 n_samples 384 confidence 0.005 feature_proportion 0.999 n_clusters 50,2169,384,0.999,50,0.005,0.55,1,0,None,i7176,1,641.078125,636.3372395833334,-1,0.96,4908556
1746218590,1746218603,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 3979 confidence 0.001 feature_proportion 0.999 n_clusters 50,5000,3979,0.999,50,0.001,0.55,0,0,None,i7175,0,634.296875,634.24609375,-1,0,4908631
1746218860,1746218873,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 1704 confidence 0.005 feature_proportion 0.999 n_clusters 1,1,1704,0.999,1,0.005,0.55,0,0,None,i7175,0,641.0390625,636.3736979166666,-1,0,4908697
1746219128,1746219141,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 1391 confidence 0.005 feature_proportion 0.999 n_clusters 1,5000,1391,0.999,1,0.005,0.55,0,0,None,i7175,0,640.6796875,636.01171875,-1,0,4908765
1746219428,1746219441,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 4644 confidence 0.01 feature_proportion 0.999 n_clusters 1,1,4644,0.999,1,0.01,0.55,0,0,None,i7184,0,633.24609375,633.1875,-1,0,4908836
1746219631,1746219644,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 3452 confidence 0.01 feature_proportion 0.999 n_clusters 1,1,3452,0.999,1,0.01,0.55,0,0,None,i7181,0,633.8984375,633.8684895833334,-1,0,4908884
1746220061,1746220074,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2631 n_samples 2793 confidence 0.005 feature_proportion 0.001 n_clusters 1,2631,2793,0.001,1,0.005,0.55,0,0,None,i7183,0,633.53125,633.46484375,-1,0,4908986
1746220348,1746220361,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 1857 confidence 0.005 feature_proportion 0.999 n_clusters 50,5000,1857,0.999,50,0.005,0.55,0,0,None,i7173,0,642.67578125,636.6184895833334,-1,0,4909063
1746220529,1746220542,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 687 n_samples 2246 confidence 0.001 feature_proportion 0.001 n_clusters 1,687,2246,0.001,1,0.001,0.55,0,0,None,i7173,0,632.671875,632.6432291666666,-1,0,4909105
1746220870,1746220883,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 2651 confidence 0.005 feature_proportion 0.001 n_clusters 50,5000,2651,0.001,50,0.005,0.55,0,0,None,i7184,0,634.15234375,634.1223958333334,-1,0,4909184
1746221069,1746221082,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2528 n_samples 2690 confidence 0.025 feature_proportion 0.999 n_clusters 50,2528,2690,0.999,50,0.025,0.55,0,0,None,i7181,0,633.06640625,633.0364583333334,-1,0,4909235
1746221380,1746221399,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1791 n_samples 389 confidence 0.1 feature_proportion 0.999 n_clusters 50,1791,389,0.999,50,0.1,0.56,2,0,None,i7183,2,642.1171875,635.9921875,-1,0.9725,4909314
1746221488,1746221514,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1864 n_samples 1333 confidence 0.1 feature_proportion 0.999 n_clusters 50,1864,1333,0.999,50,0.1,0.55,1,0,None,i7172,1,643.43359375,636.1484375,-1,0,4909341
1746221729,1746221742,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2681 n_samples 371 confidence 0.05 feature_proportion 0.999 n_clusters 50,2681,371,0.999,50,0.05,0.56,2,0,None,i7186,2,642.27734375,636.2421875,-1,0.9275,4909390
1746222008,1746222021,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 3532 confidence 0.025 feature_proportion 0.999 n_clusters 1,1,3532,0.999,1,0.025,0.55,0,0,None,i7180,0,633.22265625,633.171875,-1,0,4909454
1746222149,1746222162,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2503 n_samples 3747 confidence 0.1 feature_proportion 0.999 n_clusters 1,2503,3747,0.999,1,0.1,0.55,0,0,None,i7180,0,633.50390625,633.453125,-1,0,4909483
1746222369,1746222382,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2209 n_samples 5000 confidence 0.25 feature_proportion 0.001 n_clusters 50,2209,5000,0.001,50,0.25,0.55,0,0,None,i7179,0,633.55078125,633.5208333333334,-1,0,4909535
1746222699,1746222712,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 2729 confidence 0.05 feature_proportion 0.999 n_clusters 50,1,2729,0.999,50,0.05,0.55,0,0,None,i7184,0,633.21875,633.1692708333334,-1,0,4909603
1746223030,1746223043,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1884 n_samples 3485 confidence 0.005 feature_proportion 0.999 n_clusters 1,1884,3485,0.999,1,0.005,0.55,0,0,None,i7184,0,632.67578125,632.6263020833334,-1,0,4909670
1746223362,1746223382,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 5000 confidence 0.025 feature_proportion 0.999 n_clusters 50,1,5000,0.999,50,0.025,0.55,0,0,None,i7180,0,633.84375,633.8138020833334,-1,0,4909745
1746223650,1746223663,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 4426 confidence 0.05 feature_proportion 0.001 n_clusters 1,1,4426,0.001,1,0.05,0.55,0,0,None,i7185,0,634.51953125,634.4895833333334,-1,0,4909809
1746223900,1746223913,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3521 n_samples 4341 confidence 0.1 feature_proportion 0.999 n_clusters 1,3521,4341,0.999,1,0.1,0.55,0,0,None,i7178,0,630.671875,630.6432291666666,-1,0,4909858
1746224189,1746224202,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3577 n_samples 412 confidence 0.1 feature_proportion 0.999 n_clusters 50,3577,412,0.999,50,0.1,0.56,2,0,None,i7182,2,642.4609375,636.4205729166666,-1,0.824,4909912
1746224505,1746224518,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2552 n_samples 2021 confidence 0.005 feature_proportion 0.999 n_clusters 1,2552,2021,0.999,1,0.005,0.55,0,0,None,i7176,0,632.3984375,632.2721354166666,-1,0,4909981
1746224853,1746224872,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3509 n_samples 302 confidence 0.1 feature_proportion 0.999 n_clusters 50,3509,302,0.999,50,0.1,0.57,3,0,None,i7176,3,641.7421875,635.72265625,-1,0.906,4910046
1746225313,1746225333,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 5000 confidence 0.01 feature_proportion 0.001 n_clusters 50,5000,5000,0.001,50,0.01,0.55,0,0,None,i7173,0,633.6953125,633.6666666666666,-1,0,4910146
1746225761,1746225774,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 3261 confidence 0.025 feature_proportion 0.001 n_clusters 50,1,3261,0.001,50,0.025,0.55,0,0,None,i7185,0,633.54296875,633.4921875,-1,0,4910236
1746226131,1746226144,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1705 n_samples 401 confidence 0.1 feature_proportion 0.999 n_clusters 50,1705,401,0.999,50,0.1,0.56,2,0,None,i7186,2,641.15625,636.41015625,-1,0.802,4910315
1746226290,1746226310,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4585 n_samples 229 confidence 0.1 feature_proportion 0.999 n_clusters 50,4585,229,0.999,50,0.1,0.57,4,0,None,i7186,4,635.37109375,634.6783854166666,-1,0.916,4910346
1746226590,1746226603,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1905 n_samples 4777 confidence 0.1 feature_proportion 0.999 n_clusters 50,1905,4777,0.999,50,0.1,0.55,0,0,None,i7180,0,632.67578125,632.625,-1,0,4910413
1746226849,1746226862,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1249 n_samples 394 confidence 0.05 feature_proportion 0.999 n_clusters 50,1249,394,0.999,50,0.05,0.56,2,0,None,i7172,2,639.4921875,634.7434895833334,-1,0.985,4910477
1746227429,1746227442,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 1757 confidence 0.1 feature_proportion 0.999 n_clusters 1,5000,1757,0.999,1,0.1,0.55,0,0,None,i7186,0,640.17578125,634.2604166666666,-1,0,4910588
1746227610,1746227623,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 2360 confidence 0.005 feature_proportion 0.999 n_clusters 1,1,2360,0.999,1,0.005,0.55,0,0,None,i7174,0,632.61328125,632.5638020833334,-1,0,4910627
1746227853,1746227866,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 3575 confidence 0.25 feature_proportion 0.001 n_clusters 50,5000,3575,0.001,50,0.25,0.55,0,0,None,i7183,0,633.82421875,633.7734375,-1,0,4910670
1746228574,1746228587,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 4166 confidence 0.005 feature_proportion 0.001 n_clusters 50,5000,4166,0.001,50,0.005,0.55,0,0,None,i7183,0,633.25,633.19921875,-1,0,4910810
1746228999,1746229012,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 2969 confidence 0.01 feature_proportion 0.001 n_clusters 50,1,2969,0.001,50,0.01,0.55,0,0,None,i7182,0,633.84765625,633.796875,-1,0,4910889
1746229449,1746229462,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 4453 confidence 0.001 feature_proportion 0.999 n_clusters 1,5000,4453,0.999,1,0.001,0.55,0,0,None,i7182,0,633.3125,633.26171875,-1,0,4910981
1746229830,1746229843,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3898 n_samples 3068 confidence 0.005 feature_proportion 0.001 n_clusters 50,3898,3068,0.001,50,0.005,0.55,0,0,None,i7180,0,634.390625,634.33984375,-1,0,4911061
1746230650,1746230663,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3203 n_samples 1773 confidence 0.001 feature_proportion 0.999 n_clusters 1,3203,1773,0.999,1,0.001,0.55,0,0,None,i7184,0,640.19921875,635.54296875,-1,0,4911222
1746231069,1746231082,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3835 n_samples 4557 confidence 0.005 feature_proportion 0.999 n_clusters 1,3835,4557,0.999,1,0.005,0.55,0,0,None,i7184,0,633.21875,632.0104166666666,-1,0,4911314
1746231520,1746231533,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 2289 confidence 0.005 feature_proportion 0.999 n_clusters 50,5000,2289,0.999,50,0.005,0.55,0,0,None,i7185,0,633.75390625,633.703125,-1,0,4911419
1746232149,1746232162,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 1172 confidence 0.1 feature_proportion 0.999 n_clusters 1,5000,1172,0.999,1,0.1,0.55,1,0,None,i7181,1,639.546875,634.953125,-1,0,4911566
1746232569,1746232582,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2867 n_samples 3744 confidence 0.25 feature_proportion 0.999 n_clusters 50,2867,3744,0.999,50,0.25,0.55,0,0,None,i7179,0,633.1171875,633.06640625,-1,0,4911660
1746233352,1746233365,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 1968 confidence 0.005 feature_proportion 0.999 n_clusters 1,1,1968,0.999,1,0.005,0.55,0,0,None,i7179,0,639.48828125,636.1145833333334,-1,0,4911826
1746233609,1746233622,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2983 n_samples 288 confidence 0.1 feature_proportion 0.999 n_clusters 50,2983,288,0.999,50,0.1,0.56,2,0,None,i7179,2,641.76953125,635.71875,-1,0.864,4911884
1746234189,1746234202,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 3388 confidence 0.25 feature_proportion 0.999 n_clusters 50,1,3388,0.999,50,0.25,0.55,0,0,None,i7176,0,632.81640625,632.765625,-1,0,4912019
1746234849,1746234862,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 3352 confidence 0.001 feature_proportion 0.001 n_clusters 1,5000,3352,0.001,1,0.001,0.55,0,0,None,i7182,0,632.55859375,632.5,-1,0,4912175
1746235612,1746235631,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 132 confidence 0.05 feature_proportion 0.999 n_clusters 50,5000,132,0.999,50,0.05,0.58,5,0,None,i7183,5,637.03125,634.8606770833334,-1,0.99,4912334
1746236070,1746236083,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 5000 confidence 0.001 feature_proportion 0.001 n_clusters 1,5000,5000,0.001,1,0.001,0.55,0,0,None,i7174,0,633.69921875,633.6705729166666,-1,0,4912435
1746236590,1746236603,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3843 n_samples 3943 confidence 0.01 feature_proportion 0.001 n_clusters 50,3843,3943,0.001,50,0.01,0.55,0,0,None,i7175,0,633.31640625,633.24609375,-1,0,4912549
1746237010,1746237023,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3578 n_samples 309 confidence 0.025 feature_proportion 0.999 n_clusters 50,3578,309,0.999,50,0.025,0.57,2,0,None,i7175,2,642.25390625,636.2447916666666,-1,0.927,4912644
1746237711,1746237724,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 1599 confidence 0.005 feature_proportion 0.999 n_clusters 50,1,1599,0.999,50,0.005,0.55,1,0,None,i7184,1,641.63671875,635.6145833333334,-1,0,4912793
1746238150,1746238169,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 89 confidence 0.05 feature_proportion 0.999 n_clusters 50,5000,89,0.999,50,0.05,0.57,7,0,None,i7183,7,636.7109375,634.6940104166666,-1,0.979,4912889
1746238529,1746238543,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 4833 confidence 0.25 feature_proportion 0.999 n_clusters 1,1,4833,0.999,1,0.25,0.55,0,0,None,i7181,0,632.52734375,632.4440104166666,-1,0,4912972
1746239201,1746239221,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 96 confidence 0.1 feature_proportion 0.999 n_clusters 50,5000,96,0.999,50,0.1,0.57,7,0,None,i7186,7,640.15625,635.3450520833334,-1,0.96,4913135
1746239730,1746239743,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4625 n_samples 4854 confidence 0.025 feature_proportion 0.001 n_clusters 50,4625,4854,0.001,50,0.025,0.55,0,0,None,i7186,0,633.87109375,633.8216145833334,-1,0,4913243
1746240030,1746240043,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1881 n_samples 320 confidence 0.05 feature_proportion 0.999 n_clusters 1,1881,320,0.999,1,0.05,0.57,3,0,None,i7180,3,639.12890625,635.69921875,-1,0.96,4913310
1746240461,1746240474,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 4435 confidence 0.1 feature_proportion 0.999 n_clusters 50,5000,4435,0.999,50,0.1,0.55,0,0,None,i7180,0,633.18359375,633.1223958333334,-1,0,4913407
1746240809,1746240822,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 2982 confidence 0.025 feature_proportion 0.999 n_clusters 50,5000,2982,0.999,50,0.025,0.55,0,0,None,i7182,0,633.61328125,633.5625,-1,0,4913486
1746241092,1746241105,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 2942 confidence 0.01 feature_proportion 0.999 n_clusters 1,1,2942,0.999,1,0.01,0.55,0,0,None,i7180,0,632.62890625,632.5989583333334,-1,0,4913551
1746241433,1746241452,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 129 confidence 0.05 feature_proportion 0.999 n_clusters 50,5000,129,0.999,50,0.05,0.58,4,0,None,i7179,4,637.375,635.1640625,-1,0.9675,4913626
1746242013,1746242033,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 127 confidence 0.025 feature_proportion 0.999 n_clusters 50,5000,127,0.999,50,0.025,0.58,5,0,None,i7179,5,637.15234375,635.0026041666666,-1,0.9525,4913755
1746242555,1746242574,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 1312 confidence 0.005 feature_proportion 0.999 n_clusters 1,1,1312,0.999,1,0.005,0.55,1,0,None,i7178,1,641.265625,636.6197916666666,-1,0,4913892
1746243074,1746243087,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 987 n_samples 331 confidence 0.1 feature_proportion 0.999 n_clusters 1,987,331,0.999,1,0.1,0.56,2,0,None,i7180,2,641.08203125,636.4192708333334,-1,0.993,4914016
1746243390,1746243409,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 112 confidence 0.05 feature_proportion 0.999 n_clusters 50,5000,112,0.999,50,0.05,0.58,6,0,None,i7176,6,640.14453125,635.34375,-1,0.952,4914091
1746243914,1746243928,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2925 n_samples 2996 confidence 0.05 feature_proportion 0.999 n_clusters 1,2925,2996,0.999,1,0.05,0.55,0,0,None,i7180,0,633.76953125,633.7395833333334,-1,0,4914204
1746244293,1746244312,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 124 confidence 0.025 feature_proportion 0.999 n_clusters 50,5000,124,0.999,50,0.025,0.58,6,0,None,i7174,6,635.640625,634.8255208333334,-1,0.992,4914284
1746244670,1746244683,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 4186 confidence 0.025 feature_proportion 0.999 n_clusters 1,5000,4186,0.999,1,0.025,0.55,0,0,None,i7175,0,632.75390625,632.6744791666666,-1,0,4914366
1746245197,1746245217,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 136 confidence 0.025 feature_proportion 0.999 n_clusters 50,5000,136,0.999,50,0.025,0.58,5,0,None,i7174,5,636.78125,634.9661458333334,-1,0.952,4914459
1746245591,1746245604,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 2093 confidence 0.1 feature_proportion 0.999 n_clusters 1,1,2093,0.999,1,0.1,0.55,0,0,None,i7186,0,631.39453125,631.3294270833334,-1,0,4914539
1746246211,1746246224,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 1333 confidence 0.05 feature_proportion 0.001 n_clusters 50,5000,1333,0.001,50,0.05,0.55,1,0,None,i7179,1,641.6953125,635.7591145833334,-1,0,4914654
1746246700,1746246720,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 120 confidence 0.025 feature_proportion 0.999 n_clusters 50,5000,120,0.999,50,0.025,0.58,5,0,None,i7186,5,640.23046875,635.4322916666666,-1,0.96,4914742
1746247171,1746247184,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 3046 confidence 0.005 feature_proportion 0.001 n_clusters 1,1,3046,0.001,1,0.005,0.55,0,0,None,i7180,0,632.97265625,632.921875,-1,0,4914840
1746247950,1746247963,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 113 confidence 0.025 feature_proportion 0.999 n_clusters 50,5000,113,0.999,50,0.025,0.58,5,0,None,i7172,5,640.21875,635.3919270833334,-1,0.9605,4914988
1746248431,1746248444,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 2222 confidence 0.1 feature_proportion 0.001 n_clusters 50,5000,2222,0.001,50,0.1,0.55,0,0,None,i7180,0,634.2421875,634.1549479166666,-1,0,4915072
1746248830,1746248843,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1996 n_samples 318 confidence 0.1 feature_proportion 0.999 n_clusters 50,1996,318,0.999,50,0.1,0.57,2,0,None,i7181,2,640.58984375,635.8606770833334,-1,0.954,4915141
1746249213,1746249226,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 1354 confidence 0.025 feature_proportion 0.999 n_clusters 1,5000,1354,0.999,1,0.025,0.55,0,0,None,i7185,0,640.69921875,636.0859375,-1,0,4915212
1746249572,1746249585,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4348 n_samples 2478 confidence 0.025 feature_proportion 0.999 n_clusters 1,4348,2478,0.999,1,0.025,0.55,0,0,None,i7186,0,634.5078125,634.4388020833334,-1,0,4915272
1746250414,1746250427,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 3751 confidence 0.1 feature_proportion 0.001 n_clusters 50,1,3751,0.001,50,0.1,0.55,0,0,None,i7186,0,634.15625,634.1263020833334,-1,0,4915437
1746251085,1746251098,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 3502 confidence 0.025 feature_proportion 0.001 n_clusters 50,5000,3502,0.001,50,0.025,0.55,0,0,None,i7183,0,633.578125,633.52734375,-1,0,4915573
1746251740,1746251753,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4568 n_samples 2809 confidence 0.1 feature_proportion 0.001 n_clusters 1,4568,2809,0.001,1,0.1,0.55,0,0,None,i7182,0,634.1015625,634.05078125,-1,0,4915718
1746252552,1746252565,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4724 n_samples 237 confidence 0.025 feature_proportion 0.999 n_clusters 50,4724,237,0.999,50,0.025,0.57,3,0,None,i7180,3,640.484375,635.7434895833334,-1,0.948,4915902
1746253533,1746253546,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 3841 confidence 0.1 feature_proportion 0.001 n_clusters 50,5000,3841,0.001,50,0.1,0.55,0,0,None,i7180,0,633.296875,633.25390625,-1,0,4916128
1746254172,1746254185,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 744 n_samples 634 confidence 0.1 feature_proportion 0.999 n_clusters 50,744,634,0.999,50,0.1,0.55,1,0,None,i7180,1,637.8046875,635.5716145833334,-1,0.689,4916264
1746255514,1746255533,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 107 confidence 0.025 feature_proportion 0.999 n_clusters 50,5000,107,0.999,50,0.025,0.58,6,0,None,i7178,6,635.28125,633.4140625,-1,0.963,4916533
1746256481,1746256500,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 104 confidence 0.025 feature_proportion 0.999 n_clusters 50,5000,104,0.999,50,0.025,0.58,6,0,None,i7176,6,640.11328125,635.2955729166666,-1,0.988,4916737
1746257013,1746257033,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 183 confidence 0.025 feature_proportion 0.999 n_clusters 50,5000,183,0.999,50,0.025,0.58,4,0,None,i7175,4,640.16796875,635.2591145833334,-1,0.915,4917340
1746257651,1746257664,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4926 n_samples 221 confidence 0.025 feature_proportion 0.999 n_clusters 50,4926,221,0.999,50,0.025,0.57,4,0,None,i7169,4,633.44140625,632.6380208333334,-1,0.9945,4917474
1746258355,1746258393,38,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3047 n_samples 295 confidence 0.025 feature_proportion 0.999 n_clusters 50,3047,295,0.999,50,0.025,0.56,2,0,None,i7167,2,640.234375,634.8619791666666,-1,0.885,4917617
1746258874,1746258886,12,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2742 n_samples 296 confidence 0.005 feature_proportion 0.999 n_clusters 50,2742,296,0.999,50,0.005,0.56,2,0,None,i7169,2,643.5859375,636.1705729166666,-1,0.888,4917731
1746259511,1746259524,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 3221 confidence 0.025 feature_proportion 0.999 n_clusters 1,5000,3221,0.999,1,0.025,0.55,0,0,None,i7183,0,633.53515625,633.484375,-1,0,4917858
1746260454,1746260474,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 168 confidence 0.025 feature_proportion 0.999 n_clusters 50,5000,168,0.999,50,0.025,0.57,5,0,None,i7186,5,635.8515625,635.0247395833334,-1,0.924,4918057
1746260923,1746260936,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2358 n_samples 4885 confidence 0.1 feature_proportion 0.999 n_clusters 1,2358,4885,0.999,1,0.1,0.55,0,0,None,i7179,0,634.03515625,633.984375,-1,0,4918169
1746261492,1746261505,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 2512 confidence 0.025 feature_proportion 0.001 n_clusters 50,1,2512,0.001,50,0.025,0.55,0,0,None,i7186,0,634.45703125,634.40625,-1,0,4918290
1746262053,1746262067,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 4137 confidence 0.25 feature_proportion 0.001 n_clusters 50,1,4137,0.001,50,0.25,0.55,0,0,None,i7180,0,632.7734375,632.7018229166666,-1,0,4918424
1746262473,1746262493,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 165 confidence 0.05 feature_proportion 0.999 n_clusters 50,5000,165,0.999,50,0.05,0.57,5,0,None,i7184,5,636.93359375,634.7565104166666,-1,0.99,4918526
1746262812,1746262826,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2306 n_samples 301 confidence 0.05 feature_proportion 0.999 n_clusters 50,2306,301,0.999,50,0.05,0.55,1,0,None,i7184,1,641,636.2877604166666,-1,0.903,4918601
1746263232,1746263245,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 2539 confidence 0.005 feature_proportion 0.999 n_clusters 1,5000,2539,0.999,1,0.005,0.55,0,0,None,i7166,0,634.015625,633.96484375,-1,0,4918860
1746263952,1746263972,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 160 confidence 0.025 feature_proportion 0.999 n_clusters 50,5000,160,0.999,50,0.025,0.57,5,0,None,i7167,5,639.98046875,635.1419270833334,-1,0.96,4919097
1746264394,1746264414,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 4416 confidence 0.1 feature_proportion 0.001 n_clusters 1,1,4416,0.001,1,0.1,0.55,0,0,None,i7184,0,632.7890625,632.7591145833334,-1,0,4919232
1746264793,1746264806,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1990 n_samples 599 confidence 0.1 feature_proportion 0.999 n_clusters 50,1990,599,0.999,50,0.1,0.55,2,0,None,i7183,2,635.99609375,633.8307291666666,-1,0.8985,4919369
1746265318,1746265338,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 143 confidence 0.025 feature_proportion 0.999 n_clusters 50,5000,143,0.999,50,0.025,0.58,4,0,None,i7169,4,639.71875,635.07421875,-1,0.9295,4919532
1746265915,1746265928,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4269 n_samples 267 confidence 0.025 feature_proportion 0.999 n_clusters 50,4269,267,0.999,50,0.025,0.57,3,0,None,i7176,3,639.140625,635.7591145833334,-1,0.9345,4919699
1746266335,1746266348,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 589 confidence 0.025 feature_proportion 0.999 n_clusters 50,5000,589,0.999,50,0.025,0.55,2,0,None,i7175,2,641.9609375,635.80078125,-1,0.8835,4919849
1746266836,1746266850,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1178 n_samples 312 confidence 0.025 feature_proportion 0.999 n_clusters 50,1178,312,0.999,50,0.025,0.56,2,0,None,i7175,2,642.5078125,636.3984375,-1,0.936,4919985
1746267357,1746267370,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2814 n_samples 3352 confidence 0.25 feature_proportion 0.001 n_clusters 50,2814,3352,0.001,50,0.25,0.55,0,0,None,i7184,0,632.59765625,632.51171875,-1,0,4920136
1746267934,1746267947,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2242 n_samples 4241 confidence 0.025 feature_proportion 0.001 n_clusters 1,2242,4241,0.001,1,0.025,0.55,0,0,None,i7183,0,633.08984375,633.0390625,-1,0,4920314
1746268694,1746268707,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 692 n_samples 322 confidence 0.1 feature_proportion 0.999 n_clusters 50,692,322,0.999,50,0.1,0.57,2,0,None,i7182,2,642.1953125,636.14453125,-1,0.966,4920543
1746269374,1746269387,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1345 n_samples 2845 confidence 0.025 feature_proportion 0.999 n_clusters 50,1345,2845,0.999,50,0.025,0.55,0,0,None,i7186,0,633.4609375,633.41015625,-1,0,4920721
1746269833,1746269846,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2865 n_samples 4879 confidence 0.025 feature_proportion 0.999 n_clusters 1,2865,4879,0.999,1,0.025,0.55,0,0,None,i7180,0,632.03125,632.0013020833334,-1,0,4920818
1746270234,1746270247,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 3835 confidence 0.1 feature_proportion 0.001 n_clusters 1,1,3835,0.001,1,0.1,0.55,0,0,None,i7180,0,633.2421875,633.19140625,-1,0,4920938
1746270823,1746270836,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1104 n_samples 315 confidence 0.1 feature_proportion 0.999 n_clusters 50,1104,315,0.999,50,0.1,0.56,2,0,None,i7181,2,639.1796875,634.4583333333334,-1,0.945,4921128
1746271783,1746271796,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 660 confidence 0.1 feature_proportion 0.999 n_clusters 50,1,660,0.999,50,0.1,0.55,1,0,None,i7176,1,642.28125,636.1536458333334,-1,0.001,4921381
1746272580,1746272593,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 212 confidence 0.025 feature_proportion 0.999 n_clusters 50,5000,212,0.999,50,0.025,0.57,3,0,None,i7183,3,634.75,634.1471354166666,-1,0.954,4921637
1746273574,1746273587,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3538 n_samples 285 confidence 0.1 feature_proportion 0.999 n_clusters 50,3538,285,0.999,50,0.1,0.56,2,0,None,i7169,2,641.40234375,635.2994791666666,-1,0.9975,4921859
1746274424,1746274437,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 4466 confidence 0.025 feature_proportion 0.999 n_clusters 50,1,4466,0.999,50,0.025,0.55,0,0,None,i7183,0,633.0703125,633.01953125,-1,0,4922018
1746275330,1746275343,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 2984 confidence 0.025 feature_proportion 0.001 n_clusters 50,1,2984,0.001,50,0.025,0.55,0,0,None,i7175,0,632.84375,632.7578125,-1,0,4922243
1746276103,1746276116,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 1307 confidence 0.025 feature_proportion 0.999 n_clusters 1,1,1307,0.999,1,0.025,0.55,0,0,None,i7167,0,639.35546875,634.7825520833334,-1,0,4922410
1746276755,1746276769,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2546 n_samples 2025 confidence 0.1 feature_proportion 0.001 n_clusters 1,2546,2025,0.001,1,0.1,0.55,0,0,None,i7176,0,633.015625,632.9635416666666,-1,0,4922532
1746277416,1746277429,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 282 n_samples 317 confidence 0.025 feature_proportion 0.999 n_clusters 50,282,317,0.999,50,0.025,0.55,1,0,None,i7186,1,639.05859375,634.3541666666666,-1,0.705,4922681
1746278435,1746278448,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 3384 confidence 0.1 feature_proportion 0.001 n_clusters 1,1,3384,0.001,1,0.1,0.55,0,0,None,i7166,0,632.55859375,632.5286458333334,-1,0,4922930
1746279275,1746279288,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 4680 confidence 0.025 feature_proportion 0.001 n_clusters 1,1,4680,0.001,1,0.025,0.55,0,0,None,i7183,0,632.79296875,632.7421875,-1,0,4923091
1746279855,1746279868,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2724 n_samples 5000 confidence 0.1 feature_proportion 0.001 n_clusters 50,2724,5000,0.001,50,0.1,0.55,0,0,None,i7183,0,631.953125,631.9231770833334,-1,0,4923262
1746280415,1746280428,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4570 n_samples 5000 confidence 0.1 feature_proportion 0.999 n_clusters 50,4570,5000,0.999,50,0.1,0.55,0,0,None,i7185,0,633.48046875,633.4296875,-1,0,4923408
1746280895,1746280908,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1556 n_samples 2758 confidence 0.1 feature_proportion 0.001 n_clusters 50,1556,2758,0.001,50,0.1,0.55,0,0,None,i7179,0,633.79296875,633.7408854166666,-1,0,4923544
1746282075,1746282088,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 3951 confidence 0.001 feature_proportion 0.999 n_clusters 1,1,3951,0.999,1,0.001,0.55,0,0,None,i7184,0,631.890625,631.7864583333334,-1,0,4923819
1746283042,1746283055,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 2587 confidence 0.001 feature_proportion 0.001 n_clusters 1,5000,2587,0.001,1,0.001,0.55,0,0,None,i7181,0,632.41796875,632.2916666666666,-1,0,4924046
1746283516,1746283529,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2384 n_samples 2544 confidence 0.1 feature_proportion 0.999 n_clusters 1,2384,2544,0.999,1,0.1,0.55,0,0,None,i7176,0,631.89453125,631.8424479166666,-1,0,4924138
1746284617,1746284636,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4377 n_samples 258 confidence 0.025 feature_proportion 0.999 n_clusters 50,4377,258,0.999,50,0.025,0.57,3,0,None,i7186,3,641.12890625,635.1067708333334,-1,0.903,4924409
1746285936,1746285949,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 380 n_samples 313 confidence 0.1 feature_proportion 0.999 n_clusters 50,380,313,0.999,50,0.1,0.56,2,0,None,i7186,2,641.88671875,635.859375,-1,0.816,4924664
1746286776,1746286789,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 1817 confidence 0.1 feature_proportion 0.999 n_clusters 1,1,1817,0.999,1,0.1,0.55,0,0,None,i7183,0,639.484375,634.8919270833334,-1,0,4924859
1746287385,1746287398,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2198 n_samples 5000 confidence 0.05 feature_proportion 0.999 n_clusters 1,2198,5000,0.999,1,0.05,0.55,0,0,None,i7180,0,632.94921875,632.9192708333334,-1,0,4924979
1746288536,1746288550,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 1278 confidence 0.025 feature_proportion 0.001 n_clusters 50,1,1278,0.001,50,0.025,0.55,1,0,None,i7175,1,638.93359375,634.3255208333334,-1,0,4925255
1746289666,1746289679,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2857 n_samples 292 confidence 0.025 feature_proportion 0.999 n_clusters 50,2857,292,0.999,50,0.025,0.56,2,0,None,i7183,2,640.078125,635.3684895833334,-1,0.876,4925508
1746290279,1746290298,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 602 n_samples 314 confidence 0.025 feature_proportion 0.999 n_clusters 1,602,314,0.999,1,0.025,0.57,2,0,None,i7184,2,639.23046875,634.52734375,-1,0.929,4925668
1746291217,1746291230,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1496 n_samples 3817 confidence 0.025 feature_proportion 0.999 n_clusters 1,1496,3817,0.999,1,0.025,0.55,0,0,None,i7182,0,633.796875,633.7669270833334,-1,0,4925858
1746291856,1746291869,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 3216 confidence 0.1 feature_proportion 0.001 n_clusters 50,5000,3216,0.001,50,0.1,0.55,0,0,None,i7181,0,632.11328125,632.0638020833334,-1,0,4925987
1746292681,1746292695,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 4575 confidence 0.025 feature_proportion 0.999 n_clusters 1,1,4575,0.999,1,0.025,0.55,0,0,None,i7170,0,631.9140625,631.86328125,-1,0,4926166
1746293506,1746293519,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 318 confidence 0.1 feature_proportion 0.999 n_clusters 1,1,318,0.999,1,0.1,0.55,1,0,None,i7175,1,638.45703125,635.1015625,-1,0.0025,4926378
1746294240,1746294253,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2556 n_samples 297 confidence 0.1 feature_proportion 0.999 n_clusters 50,2556,297,0.999,50,0.1,0.57,1,0,None,i7169,1,640.265625,635.5481770833334,-1,0.891,4926569
1746294700,1746294713,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1905 n_samples 4134 confidence 0.1 feature_proportion 0.001 n_clusters 50,1905,4134,0.001,50,0.1,0.55,0,0,None,i7183,0,632.0390625,631.98828125,-1,0,4926668
1746295438,1746295452,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 1370 confidence 0.1 feature_proportion 0.999 n_clusters 1,5000,1370,0.999,1,0.1,0.55,1,0,None,i7174,1,637.43359375,632.8880208333334,-1,0,4926861
1746296327,1746296340,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 697 confidence 0.025 feature_proportion 0.999 n_clusters 50,1,697,0.999,50,0.025,0.55,1,0,None,i7185,1,639.04296875,635.6223958333334,-1,0.0005,4927040
1746297500,1746297513,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 2080 confidence 0.01 feature_proportion 0.999 n_clusters 50,1,2080,0.999,50,0.01,0.55,0,0,None,i7183,0,632,631.94921875,-1,0,4927289
1746298357,1746298370,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3009 n_samples 4086 confidence 0.025 feature_proportion 0.001 n_clusters 50,3009,4086,0.001,50,0.025,0.55,0,0,None,i7181,0,633.28125,633.2513020833334,-1,0,4927465
1746299019,1746299032,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 4725 confidence 0.05 feature_proportion 0.001 n_clusters 50,1,4725,0.001,50,0.05,0.55,0,0,None,i7179,0,633.1015625,633.05078125,-1,0,4927628
1746299919,1746299932,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4572 n_samples 256 confidence 0.025 feature_proportion 0.999 n_clusters 50,4572,256,0.999,50,0.025,0.57,3,0,None,i7185,3,637.93359375,634.4921875,-1,0.896,4927911
1746300798,1746300811,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2546 n_samples 295 confidence 0.1 feature_proportion 0.999 n_clusters 1,2546,295,0.999,1,0.1,0.57,2,0,None,i7179,2,639.23828125,634.6119791666666,-1,0.885,4928099
1746301377,1746301390,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 2901 confidence 0.005 feature_proportion 0.999 n_clusters 1,1,2901,0.999,1,0.005,0.55,0,0,None,i7176,0,632.1171875,632.0677083333334,-1,0,4928226
1746302259,1746302272,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 3111 confidence 0.025 feature_proportion 0.001 n_clusters 50,5000,3111,0.001,50,0.025,0.55,0,0,None,i7184,0,632.8828125,632.83203125,-1,0,4928427
1746303359,1746303372,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 3690 confidence 0.1 feature_proportion 0.001 n_clusters 1,5000,3690,0.001,1,0.1,0.55,0,0,None,i7184,0,631.890625,631.8606770833334,-1,0,4928646
1746303998,1746304012,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 5000 confidence 0.01 feature_proportion 0.001 n_clusters 50,1,5000,0.001,50,0.01,0.55,0,0,None,i7181,0,631.89453125,631.8645833333334,-1,0,4928783
1746304910,1746304923,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 349 n_samples 4592 confidence 0.25 feature_proportion 0.999 n_clusters 50,349,4592,0.999,50,0.25,0.55,0,0,None,i7175,0,632.09765625,632.0677083333334,-1,0,4928966
1746306077,1746306090,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4000 n_samples 261 confidence 0.1 feature_proportion 0.999 n_clusters 1,4000,261,0.999,1,0.1,0.57,3,0,None,i7180,3,640.3984375,635.66015625,-1,0.9135,4929231
1746306758,1746306771,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1768 n_samples 4355 confidence 0.01 feature_proportion 0.999 n_clusters 50,1768,4355,0.999,50,0.01,0.55,0,0,None,i7180,0,633.17578125,633.125,-1,0,4929368
1746307786,1746307800,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2406 n_samples 2238 confidence 0.01 feature_proportion 0.999 n_clusters 50,2406,2238,0.999,50,0.01,0.55,0,0,None,i7179,0,632.1015625,632.05078125,-1,0,4929663
1746308987,1746309000,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 3990 confidence 0.005 feature_proportion 0.999 n_clusters 50,1,3990,0.999,50,0.005,0.55,0,0,None,i7184,0,632.98828125,632.8932291666666,-1,0,4929899
1746310697,1746310710,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 4821 confidence 0.1 feature_proportion 0.999 n_clusters 50,1,4821,0.999,50,0.1,0.55,0,0,None,i7181,0,632.52734375,632.4440104166666,-1,0,4930265
1746311677,1746311690,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3247 n_samples 274 confidence 0.025 feature_proportion 0.999 n_clusters 50,3247,274,0.999,50,0.025,0.57,2,0,None,i7183,2,628.85546875,624.2708333333334,-1,0.959,4930457
1746312777,1746312791,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2693 n_samples 3139 confidence 0.025 feature_proportion 0.001 n_clusters 1,2693,3139,0.001,1,0.025,0.55,0,0,None,i7179,0,632.6796875,632.62890625,-1,0,4930695
1746313637,1746313656,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 1543 confidence 0.25 feature_proportion 0.999 n_clusters 50,5000,1543,0.999,50,0.25,0.55,0,0,None,i7179,0,639.01953125,634.2395833333334,-1,0,4930877
1746314577,1746314590,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4233 n_samples 2977 confidence 0.25 feature_proportion 0.999 n_clusters 1,4233,2977,0.999,1,0.25,0.55,0,0,None,i7175,0,633.52734375,633.45703125,-1,0,4931100
1746315457,1746315470,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2146 n_samples 3248 confidence 0.025 feature_proportion 0.999 n_clusters 50,2146,3248,0.999,50,0.025,0.55,0,0,None,i7175,0,632.1640625,632.1080729166666,-1,0,4931303
1746316337,1746316350,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2675 n_samples 289 confidence 0.1 feature_proportion 0.999 n_clusters 1,2675,289,0.999,1,0.1,0.56,2,0,None,i7176,2,639.83203125,635.1510416666666,-1,0.867,4931476
1746317477,1746317490,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 156 confidence 0.025 feature_proportion 0.999 n_clusters 50,5000,156,0.999,50,0.025,0.57,4,0,None,i7169,4,641.80859375,635.6315104166666,-1,0.936,4931769
1746318638,1746318651,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3183 n_samples 1421 confidence 0.025 feature_proportion 0.999 n_clusters 50,3183,1421,0.999,50,0.025,0.55,1,0,None,i7184,1,640.8515625,636.0794270833334,-1,0,4932003
1746319157,1746319170,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4557 n_samples 2916 confidence 0.25 feature_proportion 0.001 n_clusters 1,4557,2916,0.001,1,0.25,0.55,0,0,None,i7180,0,633.90234375,632.6419270833334,-1,0,4932106
1746320099,1746320112,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2484 n_samples 2507 confidence 0.1 feature_proportion 0.999 n_clusters 50,2484,2507,0.999,50,0.1,0.55,0,0,None,i7183,0,632.2578125,632.2213541666666,-1,0,4932343
1746321298,1746321312,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 2178 confidence 0.25 feature_proportion 0.001 n_clusters 50,1,2178,0.001,50,0.25,0.55,0,0,None,i7184,0,632.21484375,632.1848958333334,-1,0,4932566
1746322538,1746322551,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1960 n_samples 301 confidence 0.1 feature_proportion 0.999 n_clusters 1,1960,301,0.999,1,0.1,0.57,2,0,None,i7180,2,640.30078125,635.6354166666666,-1,0.903,4932828
1746324234,1746324247,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 5000 confidence 0.025 feature_proportion 0.001 n_clusters 1,1,5000,0.001,1,0.025,0.55,0,0,None,i7180,0,632.01171875,631.9609375,-1,0,4933181
1746325158,1746325171,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2475 n_samples 1250 confidence 0.005 feature_proportion 0.999 n_clusters 1,2475,1250,0.999,1,0.005,0.55,0,0,None,i7173,0,638.3671875,635.0442708333334,-1,0,4933400
1746326159,1746326178,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 153 confidence 0.025 feature_proportion 0.999 n_clusters 1,5000,153,0.999,1,0.025,0.57,5,0,None,i7181,5,636.61328125,634.5234375,-1,0.9945,4933665
1746328338,1746328351,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 2432 confidence 0.05 feature_proportion 0.001 n_clusters 50,1,2432,0.001,50,0.05,0.55,0,0,None,i7184,0,632.0078125,631.9583333333334,-1,0,4934107
1746329479,1746329499,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4386 n_samples 242 confidence 0.1 feature_proportion 0.999 n_clusters 50,4386,242,0.999,50,0.1,0.57,3,0,None,i7181,3,637.65625,634.3815104166666,-1,0.968,4934318
1746330919,1746330932,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 4351 confidence 0.025 feature_proportion 0.999 n_clusters 1,5000,4351,0.999,1,0.025,0.55,0,0,None,i7178,0,632.69921875,632.61328125,-1,0,4934625
1746332199,1746332212,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 4413 confidence 0.25 feature_proportion 0.001 n_clusters 50,5000,4413,0.001,50,0.25,0.55,0,0,None,i7180,0,632.484375,632.4544270833334,-1,0,4934859
1746333289,1746333302,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 4794 confidence 0.025 feature_proportion 0.001 n_clusters 1,1,4794,0.001,1,0.025,0.55,0,0,None,i7183,0,633.546875,633.49609375,-1,0,4935094
1746334849,1746334862,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 1708 confidence 0.005 feature_proportion 0.001 n_clusters 1,5000,1708,0.001,1,0.005,0.55,0,0,None,i7176,0,639.4609375,634.9075520833334,-1,0,4935416
1746335959,1746335972,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 515 n_samples 314 confidence 0.1 feature_proportion 0.999 n_clusters 1,515,314,0.999,1,0.1,0.56,2,0,None,i7186,2,640.95703125,634.9791666666666,-1,0.8855,4935699
1746337239,1746337253,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 2559 confidence 0.25 feature_proportion 0.999 n_clusters 50,1,2559,0.999,50,0.25,0.55,0,0,None,i7182,0,631.88671875,631.8567708333334,-1,0,4936016
1746338201,1746338214,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 2572 confidence 0.01 feature_proportion 0.001 n_clusters 1,5000,2572,0.001,1,0.01,0.55,0,0,None,i7180,0,632.0078125,631.95703125,-1,0,4936209
1746339661,1746339674,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 310 n_samples 4248 confidence 0.025 feature_proportion 0.001 n_clusters 50,310,4248,0.001,50,0.025,0.55,0,0,None,i7186,0,633.1640625,633.1145833333334,-1,0,4936496
1746341020,1746341033,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 3868 confidence 0.01 feature_proportion 0.999 n_clusters 50,5000,3868,0.999,50,0.01,0.55,0,0,None,i7186,0,631.92578125,631.875,-1,0,4936789
1746341921,1746341934,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 699 n_samples 5000 confidence 0.005 feature_proportion 0.001 n_clusters 1,699,5000,0.001,1,0.005,0.55,0,0,None,i7181,0,632.48046875,632.4505208333334,-1,0,4936971
1746342941,1746342954,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3099 n_samples 4888 confidence 0.25 feature_proportion 0.001 n_clusters 1,3099,4888,0.001,1,0.25,0.55,0,0,None,i7181,0,632.109375,632.0598958333334,-1,0,4937192
1746344092,1746344105,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 2605 confidence 0.001 feature_proportion 0.001 n_clusters 1,1,2605,0.001,1,0.001,0.55,0,0,None,i7186,0,630.5859375,630.4817708333334,-1,0,4937405
1746344871,1746344884,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4030 n_samples 4095 confidence 0.1 feature_proportion 0.001 n_clusters 1,4030,4095,0.001,1,0.1,0.55,0,0,None,i7180,0,632.94140625,632.8515625,-1,0,4937582
1746346361,1746346374,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 4028 confidence 0.1 feature_proportion 0.001 n_clusters 50,5000,4028,0.001,50,0.1,0.55,0,0,None,i7179,0,631.93359375,631.8828125,-1,0,4937858
1746347441,1746347454,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 3514 confidence 0.005 feature_proportion 0.999 n_clusters 50,1,3514,0.999,50,0.005,0.55,0,0,None,i7179,0,632.96484375,632.9140625,-1,0,4938061
1746348463,1746348476,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 2480 confidence 0.01 feature_proportion 0.999 n_clusters 1,1,2480,0.999,1,0.01,0.55,0,0,None,i7174,0,633.06640625,632.9635416666666,-1,0,4938281
1746349541,1746349554,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 5000 confidence 0.05 feature_proportion 0.001 n_clusters 50,1,5000,0.001,50,0.05,0.55,0,0,None,i7175,0,631.88671875,631.8567708333334,-1,0,4938550
1746350922,1746350935,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 2211 confidence 0.1 feature_proportion 0.001 n_clusters 50,1,2211,0.001,50,0.1,0.55,0,0,None,i7174,0,631.7421875,631.6927083333334,-1,0,4938849
1746352241,1746352261,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 152 confidence 0.1 feature_proportion 0.999 n_clusters 50,5000,152,0.999,50,0.1,0.57,5,0,None,i7181,5,633.0625,632.1731770833334,-1,0.988,4939098
1746354222,1746354235,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 3189 confidence 0.1 feature_proportion 0.001 n_clusters 1,1,3189,0.001,1,0.1,0.55,0,0,None,i7180,0,632.80078125,632.75,-1,0,4939489
1746356572,1746356586,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 3371 confidence 0.025 feature_proportion 0.001 n_clusters 50,1,3371,0.001,50,0.025,0.55,0,0,None,i7181,0,633.1796875,633.0989583333334,-1,0,4939938
1746358483,1746358496,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 4806 confidence 0.1 feature_proportion 0.001 n_clusters 1,5000,4806,0.001,1,0.1,0.55,0,0,None,i7183,0,633.0703125,633.01953125,-1,0,4940777
1746359802,1746359815,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 3457 confidence 0.025 feature_proportion 0.001 n_clusters 1,5000,3457,0.001,1,0.025,0.55,0,0,None,i7181,0,632.22265625,632.1731770833334,-1,0,4941017
1746361943,1746361956,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 701 confidence 0.1 feature_proportion 0.999 n_clusters 1,1,701,0.999,1,0.1,0.55,1,0,None,i7181,1,641.65625,635.5846354166666,-1,0.0005,4941476
1746363642,1746363655,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 1 confidence 0.025 feature_proportion 0.1719046850106064 n_clusters 50,5000,1,0.1719046850106064,50,0.025,None,None,1,None,i7183,,,,,,4941826
1746364732,1746364745,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 2925 confidence 0.025 feature_proportion 0.999 n_clusters 1,5000,2925,0.999,1,0.025,0.55,0,0,None,i7179,0,633.265625,633.2356770833334,-1,0,4942021
1746365962,1746365976,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 4831 confidence 0.005 feature_proportion 0.999 n_clusters 1,5000,4831,0.999,1,0.005,0.55,0,0,None,i7184,0,633.10546875,633.0546875,-1,0,4942230
1746366714,1746366728,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 274 n_samples 4430 confidence 0.025 feature_proportion 0.001 n_clusters 50,274,4430,0.001,50,0.025,0.55,0,0,None,i7184,0,633.75390625,633.703125,-1,0,4942397
1746367944,1746367957,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4203 n_samples 3949 confidence 0.25 feature_proportion 0.001 n_clusters 50,4203,3949,0.001,50,0.25,0.55,0,0,None,i7180,0,632.30078125,632.25,-1,0,4942643
1746368874,1746368887,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4542 n_samples 3346 confidence 0.1 feature_proportion 0.999 n_clusters 1,4542,3346,0.999,1,0.1,0.55,0,0,None,i7179,0,633.47265625,633.37109375,-1,0,4942806
1746370424,1746370437,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 1178 confidence 0.05 feature_proportion 0.999 n_clusters 1,1,1178,0.999,1,0.05,0.55,1,0,None,i7183,1,635.10546875,633.1067708333334,-1,0,4943103
1746372104,1746372118,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 3367 confidence 0.05 feature_proportion 0.999 n_clusters 1,5000,3367,0.999,1,0.05,0.55,0,0,None,i7179,0,632.7421875,632.6575520833334,-1,0,4943450
1746373704,1746373718,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1805 n_samples 4380 confidence 0.05 feature_proportion 0.999 n_clusters 50,1805,4380,0.999,50,0.05,0.55,0,0,None,i7179,0,633.609375,633.55859375,-1,0,4943725
1746374825,1746374838,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4588 n_samples 2415 confidence 0.025 feature_proportion 0.999 n_clusters 1,4588,2415,0.999,1,0.025,0.55,0,0,None,i7175,0,632.17578125,632.125,-1,0,4943935
1746375445,1746375458,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 729 n_samples 310 confidence 0.001 feature_proportion 0.999 n_clusters 50,729,310,0.999,50,0.001,0.56,2,0,None,i7183,2,640.375,635.66015625,-1,0.93,4944047
1746376605,1746376618,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1575 n_samples 4908 confidence 0.25 feature_proportion 0.001 n_clusters 1,1575,4908,0.001,1,0.25,0.55,0,0,None,i7185,0,633.33203125,633.3020833333334,-1,0,4944248
1746378324,1746378338,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1438 n_samples 304 confidence 0.1 feature_proportion 0.999 n_clusters 50,1438,304,0.999,50,0.1,0.57,2,0,None,i7176,2,643.37890625,635.9557291666666,-1,0.912,4944562
1746381405,1746381418,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1777 n_samples 278 confidence 0.1 feature_proportion 0.999 n_clusters 50,1777,278,0.999,50,0.1,0.56,3,0,None,i7183,3,639.96875,635.2721354166666,-1,0.973,4945176
1746383346,1746383360,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1316 n_samples 1849 confidence 0.1 feature_proportion 0.999 n_clusters 1,1316,1849,0.999,1,0.1,0.55,0,0,None,i7184,0,639.9765625,635.3333333333334,-1,0,4945519
1746385465,1746385478,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4552 n_samples 242 confidence 0.025 feature_proportion 0.999 n_clusters 50,4552,242,0.999,50,0.025,0.57,3,0,None,i7185,3,641.2890625,635.44140625,-1,0.968,4945951
1746387586,1746387599,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 38 n_samples 5000 confidence 0.01 feature_proportion 0.999 n_clusters 1,38,5000,0.999,1,0.01,0.55,0,0,None,i7179,0,631.83203125,631.7174479166666,-1,0,4946361
1746390107,1746390126,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4811 n_samples 277 confidence 0.005 feature_proportion 0.999 n_clusters 1,4811,277,0.999,1,0.005,0.56,3,0,None,i7183,3,641.60546875,635.5651041666666,-1,0.9695,4946846
1746392507,1746392520,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1322 n_samples 2459 confidence 0.1 feature_proportion 0.999 n_clusters 1,1322,2459,0.999,1,0.1,0.55,0,0,None,i7181,0,633.87890625,633.828125,-1,0,4947255
1746395035,1746395048,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3701 n_samples 4570 confidence 0.025 feature_proportion 0.001 n_clusters 1,3701,4570,0.001,1,0.025,0.55,0,0,None,i7182,0,633.37109375,633.2630208333334,-1,0,4947732
1746397750,1746397763,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1783 n_samples 1640 confidence 0.005 feature_proportion 0.999 n_clusters 1,1783,1640,0.999,1,0.005,0.55,0,0,None,i7184,0,639.0859375,634.4700520833334,-1,0,4948210
1746398936,1746398949,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 5000 confidence 0.025 feature_proportion 0.001 n_clusters 50,5000,5000,0.001,50,0.025,0.55,0,0,None,i7184,0,632.33984375,632.2903645833334,-1,0,4948440
1746400737,1746400750,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3617 n_samples 3302 confidence 0.01 feature_proportion 0.001 n_clusters 50,3617,3302,0.001,50,0.01,0.55,0,0,None,i7186,0,632.53125,632.4479166666666,-1,0,4948776
1746402849,1746402862,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 3574 confidence 0.005 feature_proportion 0.999 n_clusters 1,5000,3574,0.999,1,0.005,0.55,0,0,None,i7180,0,633.4453125,633.34765625,-1,0,4949123
1746405597,1746405610,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1628 n_samples 3057 confidence 0.005 feature_proportion 0.999 n_clusters 1,1628,3057,0.999,1,0.005,0.55,0,0,None,i7176,0,632.51171875,632.4817708333334,-1,0,4949628
1746406609,1746406629,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1149 n_samples 301 confidence 0.025 feature_proportion 0.999 n_clusters 1,1149,301,0.999,1,0.025,0.57,2,0,None,i7180,2,640.296875,635.5768229166666,-1,0.903,4949825
1746407990,1746408003,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3573 n_samples 3751 confidence 0.005 feature_proportion 0.001 n_clusters 1,3573,3751,0.001,1,0.005,0.55,0,0,None,i7178,0,633.1328125,633.0833333333334,-1,0,4950088
1746409129,1746409141,12,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 321 confidence 0.1 feature_proportion 0.999 n_clusters 50,1,321,0.999,50,0.1,0.55,1,0,None,i7175,1,640.37109375,635.5924479166666,-1,0.0025,4950319
1746410367,1746410380,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3700 n_samples 1798 confidence 0.005 feature_proportion 0.999 n_clusters 50,3700,1798,0.999,50,0.005,0.55,0,0,None,i7183,0,640.5,635.7955729166666,-1,0,4950537
1746411267,1746411280,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2975 n_samples 3889 confidence 0.005 feature_proportion 0.999 n_clusters 1,2975,3889,0.999,1,0.005,0.55,0,0,None,i7182,0,633.38671875,633.3359375,-1,0,4950699
1746412488,1746412501,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 2905 confidence 0.005 feature_proportion 0.001 n_clusters 50,5000,2905,0.001,50,0.005,0.55,0,0,None,i7183,0,632.47265625,632.4427083333334,-1,0,4950921
1746413448,1746413461,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 4375 confidence 0.005 feature_proportion 0.001 n_clusters 50,1,4375,0.001,50,0.005,0.55,0,0,None,i7185,0,633.08203125,633.03125,-1,0,4951101
1746415809,1746415821,12,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1525 n_samples 284 confidence 0.1 feature_proportion 0.999 n_clusters 1,1525,284,0.999,1,0.1,0.56,2,0,None,i7185,2,641.4140625,635.4388020833334,-1,0.994,4951530
1746418048,1746418061,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 952 n_samples 636 confidence 0.1 feature_proportion 0.999 n_clusters 1,952,636,0.999,1,0.1,0.55,2,0,None,i7178,2,640.4453125,635.6471354166666,-1,0.794,4951962
1746420478,1746420492,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3791 n_samples 2521 confidence 0.25 feature_proportion 0.001 n_clusters 1,3791,2521,0.001,1,0.25,0.55,0,0,None,i7181,0,632.53125,632.4427083333334,-1,0,4952457
1746422308,1746422321,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2411 n_samples 5000 confidence 0.005 feature_proportion 0.001 n_clusters 1,2411,5000,0.001,1,0.005,0.55,0,0,None,i7176,0,632.59765625,632.546875,-1,0,4952792
1746424852,1746424866,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3975 n_samples 2919 confidence 0.1 feature_proportion 0.001 n_clusters 1,3975,2919,0.001,1,0.1,0.55,0,0,None,i7181,0,631.87109375,631.7682291666666,-1,0,4953229
1746427012,1746427025,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3367 n_samples 1300 confidence 0.005 feature_proportion 0.999 n_clusters 1,3367,1300,0.999,1,0.005,0.55,0,0,None,i7185,0,637.37890625,634.0494791666666,-1,0,4953580
1746430313,1746430326,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 317 confidence 0.05 feature_proportion 0.999 n_clusters 1,1,317,0.999,1,0.05,0.55,1,0,None,i7181,1,639.89453125,635.1705729166666,-1,0.0025,4954221
1746431310,1746431330,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 246 n_samples 320 confidence 0.05 feature_proportion 0.999 n_clusters 50,246,320,0.999,50,0.05,0.55,2,0,None,i7184,2,640.16015625,635.4270833333334,-1,0.615,4954888
1746433891,1746433904,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3889 n_samples 290 confidence 0.025 feature_proportion 0.999 n_clusters 50,3889,290,0.999,50,0.025,0.56,2,0,None,i7183,2,640.01171875,635.3020833333334,-1,0.87,4955367
1746436074,1746436087,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1072 n_samples 2131 confidence 0.005 feature_proportion 0.999 n_clusters 1,1072,2131,0.999,1,0.005,0.55,0,0,None,i7180,0,633.859375,633.8294270833334,-1,0,4956245
1746438251,1746438271,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3803 n_samples 1327 confidence 0.1 feature_proportion 0.999 n_clusters 1,3803,1327,0.999,1,0.1,0.55,1,0,None,i7184,1,637.33984375,633.94921875,-1,0,4956625
1746439628,1746439647,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2378 n_samples 2227 confidence 0.1 feature_proportion 0.999 n_clusters 50,2378,2227,0.999,50,0.1,0.55,0,0,None,i7186,0,633.421875,633.3697916666666,-1,0,4956893
1746441024,1746441043,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2440 n_samples 4689 confidence 0.05 feature_proportion 0.001 n_clusters 50,2440,4689,0.001,50,0.05,0.55,0,0,None,i7181,0,632.08203125,632.0325520833334,-1,0,4957155
1746442947,1746442966,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 947 n_samples 644 confidence 0.025 feature_proportion 0.999 n_clusters 1,947,644,0.999,1,0.025,0.55,1,0,None,i7176,1,642.0078125,635.9752604166666,-1,0.7955,4957472
1746445074,1746445088,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1495 n_samples 3957 confidence 0.01 feature_proportion 0.001 n_clusters 50,1495,3957,0.001,50,0.01,0.55,0,0,None,i7182,0,632.42578125,632.375,-1,0,4957825
1746450405,1746450424,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4992 n_samples 1867 confidence 0.001 feature_proportion 0.999 n_clusters 1,4992,1867,0.999,1,0.001,0.55,1,0,None,i7186,1,640.1640625,635.5052083333334,-1,0,4958956
1746452065,1746452084,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 70 n_samples 2243 confidence 0.25 feature_proportion 0.001 n_clusters 1,70,2243,0.001,1,0.25,0.55,0,0,None,i7186,0,633.421875,633.3919270833334,-1,0,4959233
1746454338,1746454351,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1627 n_samples 282 confidence 0.025 feature_proportion 0.999 n_clusters 50,1627,282,0.999,50,0.025,0.56,3,0,None,i7182,3,641.57421875,635.5520833333334,-1,0.987,4959806
1746456396,1746456416,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1094 n_samples 336 confidence 0.005 feature_proportion 0.999 n_clusters 1,1094,336,0.999,1,0.005,0.56,2,0,None,i7184,2,639.45703125,634.2421875,-1,0.84,4960135
1746458104,1746458117,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4050 n_samples 1254 confidence 0.1 feature_proportion 0.999 n_clusters 50,4050,1254,0.999,50,0.1,0.55,1,0,None,i7181,1,638.94921875,635.5169270833334,-1,0,4960498
1746462147,1746462160,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3359 n_samples 2485 confidence 0.001 feature_proportion 0.001 n_clusters 50,3359,2485,0.001,50,0.001,0.55,0,0,None,i7180,0,632.76171875,632.7109375,-1,0,4961263
1746465448,1746465467,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 630 n_samples 3356 confidence 0.025 feature_proportion 0.999 n_clusters 1,630,3356,0.999,1,0.025,0.55,0,0,None,i7186,0,633.0625,633.0325520833334,-1,0,4961865
1746468155,1746468175,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 877 n_samples 339 confidence 0.05 feature_proportion 0.999 n_clusters 1,877,339,0.999,1,0.05,0.56,2,0,None,i7178,2,640.34765625,635.6653645833334,-1,0.8475,4962304
1746470503,1746470517,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 914 n_samples 3950 confidence 0.1 feature_proportion 0.999 n_clusters 1,914,3950,0.999,1,0.1,0.55,0,0,None,i7183,0,633.34375,633.28125,-1,0,4962680
1746472524,1746472537,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3915 n_samples 4761 confidence 0.1 feature_proportion 0.001 n_clusters 1,3915,4761,0.001,1,0.1,0.55,0,0,None,i7181,0,633.8125,633.7825520833334,-1,0,4963044
1746474144,1746474157,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1261 n_samples 4275 confidence 0.1 feature_proportion 0.999 n_clusters 50,1261,4275,0.999,50,0.1,0.55,0,0,None,i7181,0,631.73046875,631.6223958333334,-1,0,4963318
1746476645,1746476658,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1184 n_samples 1350 confidence 0.001 feature_proportion 0.001 n_clusters 1,1184,1350,0.001,1,0.001,0.55,1,0,None,i7181,1,639.58203125,635.0286458333334,-1,0,4963758
1746480024,1746480037,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 645 n_samples 1299 confidence 0.005 feature_proportion 0.001 n_clusters 1,645,1299,0.001,1,0.005,0.55,0,0,None,i7179,0,641.73046875,635.8333333333334,-1,0,4964318
1746482555,1746482568,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3489 n_samples 3112 confidence 0.1 feature_proportion 0.999 n_clusters 50,3489,3112,0.999,50,0.1,0.55,0,0,None,i7184,0,632.0546875,632.0247395833334,-1,0,4964721
1746484945,1746484958,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3791 n_samples 4797 confidence 0.025 feature_proportion 0.999 n_clusters 50,3791,4797,0.999,50,0.025,0.55,0,0,None,i7182,0,632.6171875,632.56640625,-1,0,4965134
1746489214,1746489228,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 813 n_samples 304 confidence 0.025 feature_proportion 0.999 n_clusters 50,813,304,0.999,50,0.025,0.56,2,0,None,i7179,2,640.0625,635.33203125,-1,0.912,4965870
1746490446,1746490459,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4579 n_samples 2543 confidence 0.05 feature_proportion 0.999 n_clusters 50,4579,2543,0.999,50,0.05,0.55,0,0,None,i7184,0,632.078125,632.0481770833334,-1,0,4966074
1746492485,1746492498,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3296 n_samples 3480 confidence 0.001 feature_proportion 0.001 n_clusters 1,3296,3480,0.001,1,0.001,0.55,0,0,None,i7185,0,633.2421875,633.2122395833334,-1,0,4966476
1746495267,1746495280,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 922 n_samples 1962 confidence 0.25 feature_proportion 0.999 n_clusters 50,922,1962,0.999,50,0.25,0.55,0,0,None,i7185,0,642.09765625,636.0755208333334,-1,0,4966936
1746497765,1746497778,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 957 n_samples 604 confidence 0.025 feature_proportion 0.999 n_clusters 1,957,604,0.999,1,0.025,0.55,1,0,None,i7183,1,639.16796875,634.375,-1,0.7805,4967327
1746500018,1746500031,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3732 n_samples 4270 confidence 0.005 feature_proportion 0.999 n_clusters 50,3732,4270,0.999,50,0.005,0.55,0,0,None,i7184,0,633.43359375,633.3932291666666,-1,0,4967694
1746501967,1746501987,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4222 n_samples 283 confidence 0.1 feature_proportion 0.999 n_clusters 50,4222,283,0.999,50,0.1,0.56,3,0,None,i7180,3,640.9140625,634.9127604166666,-1,0.9905,4968031
1746503450,1746503463,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3982 n_samples 3707 confidence 0.1 feature_proportion 0.001 n_clusters 1,3982,3707,0.001,1,0.1,0.55,0,0,None,i7185,0,632.26171875,632.2317708333334,-1,0,4968251
1746504570,1746504626,56,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2788 n_samples 2917 confidence 0.1 feature_proportion 0.001 n_clusters 50,2788,2917,0.001,50,0.1,0.55,0,0,None,i7176,0,631.94921875,631.8984375,-1,0,4968440
1746506330,1746506343,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2572 n_samples 4355 confidence 0.1 feature_proportion 0.999 n_clusters 50,2572,4355,0.999,50,0.1,0.55,0,0,None,i7181,0,633.23046875,633.1809895833334,-1,0,4968732
1746508388,1746508401,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1074 n_samples 5000 confidence 0.001 feature_proportion 0.999 n_clusters 50,1074,5000,0.999,50,0.001,0.55,0,0,None,i7180,0,632.75390625,632.6705729166666,-1,0,4969075
1746514174,1746514187,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1122 n_samples 4575 confidence 0.1 feature_proportion 0.001 n_clusters 1,1122,4575,0.001,1,0.1,0.55,0,0,None,i7185,0,633.0859375,633,-1,0,4970062
1746516176,1746516207,31,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 2527 confidence 0.1 feature_proportion 0.999 n_clusters 1,5000,2527,0.999,1,0.1,0.55,0,0,None,i7179,0,632.1484375,632.1184895833334,-1,0,4970395
1746517750,1746517763,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1591 n_samples 4690 confidence 0.025 feature_proportion 0.001 n_clusters 50,1591,4690,0.001,50,0.025,0.55,0,0,None,i7186,0,633.40625,633.3567708333334,-1,0,4970676
1746520242,1746520261,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4899 n_samples 94 confidence 0.025 feature_proportion 0.999 n_clusters 50,4899,94,0.999,50,0.025,0.57,7,0,None,i7181,7,641.859375,635.7213541666666,-1,0.987,4971087
1746522724,1746522743,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1333 n_samples 1313 confidence 0.05 feature_proportion 0.999 n_clusters 50,1333,1313,0.999,50,0.05,0.55,1,0,None,i7179,1,642.19140625,636.1666666666666,-1,0,4971478
1746524200,1746524213,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4357 n_samples 4234 confidence 0.25 feature_proportion 0.999 n_clusters 17,4357,4234,0.999,17,0.25,0.55,0,0,None,i7175,0,633.296875,633.24609375,-1,0,4971754
1746526855,1746526874,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4022 n_samples 2148 confidence 0.001 feature_proportion 0.001 n_clusters 50,4022,2148,0.001,50,0.001,0.55,0,0,None,i7179,0,633.921875,633.87109375,-1,0,4972195
1746529760,1746529779,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 1801 confidence 0.001 feature_proportion 0.999 n_clusters 50,1,1801,0.999,50,0.001,0.55,0,0,None,i7179,0,641.3515625,635.3138020833334,-1,0,4972755
1746532465,1746532485,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1022 n_samples 593 confidence 0.1 feature_proportion 0.999 n_clusters 1,1022,593,0.999,1,0.1,0.55,1,0,None,i7184,1,637.3203125,633.8815104166666,-1,0.8075,4973329
1746534360,1746534380,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3848 n_samples 248 confidence 0.025 feature_proportion 0.999 n_clusters 1,3848,248,0.999,1,0.025,0.57,3,0,None,i7184,3,635.0390625,632.9518229166666,-1,0.992,4973690
1746536658,1746536677,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 758 n_samples 3005 confidence 0.01 feature_proportion 0.001 n_clusters 50,758,3005,0.001,50,0.01,0.55,0,0,None,i7184,0,632.48828125,632.4583333333334,-1,0,4974139
1746538439,1746538458,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4882 n_samples 187 confidence 0.025 feature_proportion 0.999 n_clusters 50,4882,187,0.999,50,0.025,0.58,4,0,None,i7184,4,637.80859375,632.9283854166666,-1,0.935,4974470
1746541628,1746541672,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1082 n_samples 4120 confidence 0.01 feature_proportion 0.999 n_clusters 1,1082,4120,0.999,1,0.01,0.55,0,0,None,i7181,0,633.20703125,633.1575520833334,-1,0,4975049
1746543946,1746543972,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2989 n_samples 3239 confidence 0.1 feature_proportion 0.999 n_clusters 1,2989,3239,0.999,1,0.1,0.55,0,0,None,i7186,0,633.51171875,633.4127604166666,-1,0,4975419
1746546904,1746546923,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1074 n_samples 337 confidence 0.25 feature_proportion 0.999 n_clusters 1,1074,337,0.999,1,0.25,0.56,2,0,None,i7182,2,638.71484375,633.9986979166666,-1,0.8425,4975916
1746550354,1746550373,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3735 n_samples 1226 confidence 0.25 feature_proportion 0.999 n_clusters 50,3735,1226,0.999,50,0.25,0.55,1,0,None,i7186,1,641.8046875,635.7747395833334,-1,0,4976436
1746554471,1746554490,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1299 n_samples 2328 confidence 0.005 feature_proportion 0.001 n_clusters 1,1299,2328,0.001,1,0.005,0.55,0,0,None,i7181,0,632.1328125,632.0078125,-1,0,4977100
1746557282,1746557295,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 874 n_samples 4898 confidence 0.025 feature_proportion 0.999 n_clusters 50,874,4898,0.999,50,0.025,0.55,0,0,None,i7179,0,633.47265625,633.421875,-1,0,4977549
1746559906,1746559919,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 970 n_samples 556 confidence 0.025 feature_proportion 0.999 n_clusters 1,970,556,0.999,1,0.025,0.55,1,0,None,i7185,1,639.203125,634.4674479166666,-1,0.763,4977969
1746565225,1746565245,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4344 n_samples 286 confidence 0.025 feature_proportion 0.999 n_clusters 50,4344,286,0.999,50,0.025,0.56,3,0,None,i7179,3,640.3359375,635.6315104166666,-1,0.858,4978844
1746568634,1746568647,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 2120 confidence 0.1 feature_proportion 0.999 n_clusters 1,5000,2120,0.999,1,0.1,0.55,0,0,None,i7185,0,633.13671875,633.0859375,-1,0,4979337
1746571423,1746571437,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3432 n_samples 2679 confidence 0.01 feature_proportion 0.001 n_clusters 50,3432,2679,0.001,50,0.01,0.55,0,0,None,i7183,0,632.86328125,632.8125,-1,0,4979801
1746574624,1746574638,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3287 n_samples 1212 confidence 0.025 feature_proportion 0.999 n_clusters 50,3287,1212,0.999,50,0.025,0.55,1,0,None,i7180,1,641.76171875,635.7526041666666,-1,0,4980328
1746576151,1746576171,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4967 n_samples 1675 confidence 0.005 feature_proportion 0.999 n_clusters 1,4967,1675,0.999,1,0.005,0.55,0,0,None,i7179,0,640.7890625,636.1236979166666,-1,0,4980568
1746578729,1746578749,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1063 n_samples 336 confidence 0.025 feature_proportion 0.999 n_clusters 1,1063,336,0.999,1,0.025,0.56,2,0,None,i7184,2,641.3671875,635.38671875,-1,0.84,4981000
1746580489,1746580509,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1740 n_samples 273 confidence 0.1 feature_proportion 0.999 n_clusters 50,1740,273,0.999,50,0.1,0.56,3,0,None,i7186,3,638.71875,635.35546875,-1,0.9555,4981264
1746583488,1746583502,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1331 n_samples 4900 confidence 0.005 feature_proportion 0.999 n_clusters 50,1331,4900,0.999,50,0.005,0.55,0,0,None,i7183,0,633.05859375,632.9752604166666,-1,0,4981745
1746586532,1746586557,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1062 n_samples 4136 confidence 0.025 feature_proportion 0.999 n_clusters 1,1062,4136,0.999,1,0.025,0.55,0,0,None,i7184,0,632.625,632.57421875,-1,0,4982175
1746589748,1746589767,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1014 n_samples 337 confidence 0.05 feature_proportion 0.999 n_clusters 1,1014,337,0.999,1,0.05,0.56,2,0,None,i7186,2,641.015625,635.0182291666666,-1,0.8425,4982700
1746592267,1746592287,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 953 n_samples 349 confidence 0.005 feature_proportion 0.999 n_clusters 1,953,349,0.999,1,0.005,0.56,2,0,None,i7180,2,639.140625,634.4674479166666,-1,0.8725,4983075
1746594859,1746594878,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1801 n_samples 2937 confidence 0.1 feature_proportion 0.001 n_clusters 1,1801,2937,0.001,1,0.1,0.55,0,0,None,i7183,0,633.2890625,633.2591145833334,-1,0,4983473
1746599024,1746599037,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4042 n_samples 2219 confidence 0.1 feature_proportion 0.001 n_clusters 1,4042,2219,0.001,1,0.1,0.55,0,0,None,i7179,0,632.13671875,632.0859375,-1,0,4984107
1746602292,1746602311,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1696 n_samples 277 confidence 0.1 feature_proportion 0.999 n_clusters 1,1696,277,0.999,1,0.1,0.56,3,0,None,i7180,3,641.94921875,635.890625,-1,0.9695,4984632
1746604521,1746604540,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1881 n_samples 1669 confidence 0.1 feature_proportion 0.001 n_clusters 1,1881,1669,0.001,1,0.1,0.55,0,0,None,i7184,0,638.38671875,635.0989583333334,-1,0,4984990
1746606467,1746606487,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4537 n_samples 282 confidence 0.025 feature_proportion 0.999 n_clusters 50,4537,282,0.999,50,0.025,0.56,3,0,None,i7186,3,640.8203125,634.76953125,-1,0.987,4985310
1746609533,1746609552,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1046 n_samples 345 confidence 0.025 feature_proportion 0.999 n_clusters 50,1046,345,0.999,50,0.025,0.56,2,0,None,i7183,2,640.3359375,635.5729166666666,-1,0.8625,4985821
1746613596,1746613609,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1004 n_samples 2558 confidence 0.01 feature_proportion 0.001 n_clusters 50,1004,2558,0.001,50,0.01,0.55,0,0,None,i7182,0,632.26171875,632.2317708333334,-1,0,4986434
1746617302,1746617321,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 984 n_samples 554 confidence 0.1 feature_proportion 0.999 n_clusters 50,984,554,0.999,50,0.1,0.55,1,0,None,i7182,1,639.69921875,633.6328125,-1,0.769,4987087
1746621164,1746621183,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3254 n_samples 3337 confidence 0.025 feature_proportion 0.001 n_clusters 50,3254,3337,0.001,50,0.025,0.55,0,0,None,i7178,0,631.95703125,631.9166666666666,-1,0,4987663
1746625661,1746625680,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3872 n_samples 3959 confidence 0.25 feature_proportion 0.999 n_clusters 1,3872,3959,0.999,1,0.25,0.55,0,0,None,i7183,0,633.26171875,633.1744791666666,-1,0,4988319
1746628615,1746628635,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 984 n_samples 342 confidence 0.01 feature_proportion 0.999 n_clusters 50,984,342,0.999,50,0.01,0.56,2,0,None,i7180,2,639.9765625,635.1705729166666,-1,0.855,4988758
1746632089,1746632108,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 1983 confidence 0.1 feature_proportion 0.001 n_clusters 50,5000,1983,0.001,50,0.1,0.55,0,0,None,i7184,0,641.78515625,635.7981770833334,-1,0,4989278
1746635208,1746635241,33,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3342 n_samples 4327 confidence 0.25 feature_proportion 0.001 n_clusters 1,3342,4327,0.001,1,0.25,0.55,0,0,None,i7175,0,632.328125,632.27734375,-1,0,4991154
1746639457,1746639470,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 771 n_samples 348 confidence 0.005 feature_proportion 0.999 n_clusters 1,771,348,0.999,1,0.005,0.56,2,0,None,i7182,2,638.828125,634.1393229166666,-1,0.87,4992967
1746642220,1746642233,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 772 n_samples 354 confidence 0.001 feature_proportion 0.999 n_clusters 1,772,354,0.999,1,0.001,0.56,2,0,None,i7183,2,640.921875,634.9440104166666,-1,0.885,4993367
1746648312,1746648331,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1664 n_samples 3567 confidence 0.005 feature_proportion 0.001 n_clusters 50,1664,3567,0.001,50,0.005,0.55,0,0,None,i7185,0,632.46484375,632.3736979166666,-1,0,4994258
1746650479,1746650493,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2903 n_samples 5000 confidence 0.025 feature_proportion 0.001 n_clusters 50,2903,5000,0.001,50,0.025,0.55,0,0,None,i7181,0,633.50390625,633.4505208333334,-1,0,4994569
1746651694,1746651714,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3824 n_samples 3918 confidence 0.1 feature_proportion 0.001 n_clusters 1,3824,3918,0.001,1,0.1,0.55,0,0,None,i7178,0,632.86328125,632.7565104166666,-1,0,4994747
1746654029,1746654042,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4081 n_samples 2818 confidence 0.001 feature_proportion 0.001 n_clusters 1,4081,2818,0.001,1,0.001,0.55,0,0,None,i7183,0,633.453125,633.4231770833334,-1,0,4995089
1746657493,1746657506,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3883 n_samples 3561 confidence 0.25 feature_proportion 0.001 n_clusters 1,3883,3561,0.001,1,0.25,0.55,0,0,None,i7185,0,633.828125,633.77734375,-1,0,4995601
1746662752,1746662771,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4445 n_samples 270 confidence 0.025 feature_proportion 0.999 n_clusters 50,4445,270,0.999,50,0.025,0.57,3,0,None,i7181,3,641.98046875,635.8671875,-1,0.945,4996453
1746666277,1746666303,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 332 confidence 0.005 feature_proportion 0.999 n_clusters 50,1,332,0.999,50,0.005,0.55,1,0,None,i7182,1,640.30859375,635.5755208333334,-1,0.0025,4996909
1746671203,1746671222,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 959 n_samples 3070 confidence 0.25 feature_proportion 0.001 n_clusters 1,959,3070,0.001,1,0.25,0.55,0,0,None,i7172,0,632.80078125,632.7513020833334,-1,0,4997632
1746677274,1746677287,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 760 n_samples 347 confidence 0.25 feature_proportion 0.999 n_clusters 1,760,347,0.999,1,0.25,0.56,2,0,None,i7181,2,641.390625,635.3854166666666,-1,0.8675,4998462
1746681150,1746681170,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 920 n_samples 513 confidence 0.1 feature_proportion 0.999 n_clusters 50,920,513,0.999,50,0.1,0.55,2,0,None,i7184,2,641.88671875,635.8567708333334,-1,0.7165,4998979
1746684804,1746684817,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 975 n_samples 1242 confidence 0.25 feature_proportion 0.001 n_clusters 1,975,1242,0.001,1,0.25,0.55,1,0,None,i7181,1,637.69140625,634.4622395833334,-1,0,4999517
1746687807,1746687820,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1006 n_samples 3841 confidence 0.1 feature_proportion 0.001 n_clusters 50,1006,3841,0.001,50,0.1,0.55,0,0,None,i7181,0,633.76171875,633.7317708333334,-1,0,4999920
1746690201,1746690215,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 4441 confidence 0.25 feature_proportion 0.999 n_clusters 50,1,4441,0.999,50,0.25,0.55,0,0,None,i7179,0,633.07421875,632.9505208333334,-1,0,5000224
1746693528,1746693542,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3428 n_samples 4509 confidence 0.01 feature_proportion 0.001 n_clusters 50,3428,4509,0.001,50,0.01,0.55,0,0,None,i7183,0,632.76953125,632.7395833333334,-1,0,5000723
1746695987,1746696000,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3745 n_samples 261 confidence 0.025 feature_proportion 0.999 n_clusters 1,3745,261,0.999,1,0.025,0.56,2,0,None,i7183,2,638.83984375,635.4895833333334,-1,0.9135,5001101
1746700189,1746700202,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 320 n_samples 386 confidence 0.025 feature_proportion 0.999 n_clusters 1,320,386,0.999,1,0.025,0.55,1,0,None,i7179,1,641.625,635.65234375,-1,0.64,5001671
1746704962,1746704975,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 435 n_samples 388 confidence 0.025 feature_proportion 0.999 n_clusters 1,435,388,0.999,1,0.025,0.56,1,0,None,i7184,1,638.89453125,634.1966145833334,-1,0.7995,5002418
1746709614,1746709627,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3844 n_samples 5000 confidence 0.1 feature_proportion 0.001 n_clusters 50,3844,5000,0.001,50,0.1,0.55,0,0,None,i7183,0,633.83984375,633.7890625,-1,0,5003066
1746714311,1746714324,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1804 n_samples 4573 confidence 0.025 feature_proportion 0.001 n_clusters 1,1804,4573,0.001,1,0.025,0.55,0,0,None,i7183,0,632.05859375,632.0078125,-1,0,5003697
1746715712,1746715725,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4311 n_samples 4321 confidence 0.05 feature_proportion 0.999 n_clusters 1,4311,4321,0.999,1,0.05,0.55,0,0,None,i7182,0,633.26953125,633.21875,-1,0,5004033
1746720231,1746720244,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3547 n_samples 1719 confidence 0.01 feature_proportion 0.999 n_clusters 1,3547,1719,0.999,1,0.01,0.55,0,0,None,i7181,0,641.76953125,635.8177083333334,-1,0,5004803
1746724552,1746724566,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1108 n_samples 3491 confidence 0.005 feature_proportion 0.999 n_clusters 1,1108,3491,0.999,1,0.005,0.55,0,0,None,i7179,0,633.56640625,633.48046875,-1,0,5005418
1746727882,1746727896,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1213 n_samples 3568 confidence 0.25 feature_proportion 0.001 n_clusters 50,1213,3568,0.001,50,0.25,0.55,0,0,None,i7184,0,633.87890625,633.8489583333334,-1,0,5005931
1746730133,1746730146,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1584 n_samples 285 confidence 0.025 feature_proportion 0.999 n_clusters 1,1584,285,0.999,1,0.025,0.56,2,0,None,i7182,2,641.5703125,635.62890625,-1,0.9975,5006257
1746733981,1746734001,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2130 n_samples 3361 confidence 0.1 feature_proportion 0.001 n_clusters 1,2130,3361,0.001,1,0.1,0.55,0,0,None,i7184,0,632.52734375,631.33203125,-1,0,5006799
1746736613,1746736626,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4956 n_samples 193 confidence 0.1 feature_proportion 0.999 n_clusters 1,4956,193,0.999,1,0.1,0.57,4,0,None,i7183,4,633.10546875,632.3255208333334,-1,0.965,5007224
1746741026,1746741039,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2741 n_samples 1251 confidence 0.01 feature_proportion 0.999 n_clusters 50,2741,1251,0.999,50,0.01,0.55,1,0,None,i7183,1,641.80078125,635.8125,-1,0,5007876
1746743730,1746743744,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 338 confidence 0.025 feature_proportion 0.999 n_clusters 1,1,338,0.999,1,0.025,0.55,1,0,None,i7186,1,641.5,635.4934895833334,-1,0.002,5008262
1746746853,1746746872,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3020 n_samples 2504 confidence 0.025 feature_proportion 0.001 n_clusters 1,3020,2504,0.001,1,0.025,0.55,0,0,None,i7180,0,631.85546875,631.8255208333334,-1,0,5008676
1746751177,1746751190,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1078 n_samples 5000 confidence 0.1 feature_proportion 0.001 n_clusters 50,1078,5000,0.001,50,0.1,0.55,0,0,None,i7182,0,633.2734375,633.22265625,-1,0,5009270
1746756522,1746756535,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1534 n_samples 2213 confidence 0.05 feature_proportion 0.999 n_clusters 50,1534,2213,0.999,50,0.05,0.55,0,0,None,i7183,0,632.265625,632.1744791666666,-1,0,5010019
1746762273,1746762286,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3642 n_samples 2254 confidence 0.25 feature_proportion 0.001 n_clusters 1,3642,2254,0.001,1,0.25,0.55,0,0,None,i7183,0,633.09375,633.0091145833334,-1,0,5010863
1746767353,1746767366,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1322 n_samples 4562 confidence 0.05 feature_proportion 0.999 n_clusters 1,1322,4562,0.999,1,0.05,0.55,0,0,None,i7176,0,632.1640625,632.11328125,-1,0,5011558
1746772333,1746772346,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 1129 confidence 0.005 feature_proportion 0.001 n_clusters 1,1,1129,0.001,1,0.005,0.55,0,0,None,i7182,0,636.890625,633.6627604166666,-1,0,5012272
1746777769,1746777789,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4584 n_samples 261 confidence 0.025 feature_proportion 0.999 n_clusters 50,4584,261,0.999,50,0.025,0.57,3,0,None,i7183,3,638.5703125,635.2278645833334,-1,0.9135,5013018
1746784045,1746784064,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 867 n_samples 351 confidence 0.025 feature_proportion 0.999 n_clusters 1,867,351,0.999,1,0.025,0.56,2,0,None,i7186,2,640.75390625,636.06640625,-1,0.8775,5013881
1746788716,1746788729,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 3351 n_samples 280 confidence 0.05 feature_proportion 0.999 n_clusters 1,3351,280,0.999,1,0.05,0.57,2,0,None,i7181,2,641.63671875,635.6588541666666,-1,0.98,5014607
1746791775,1746791789,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4103 n_samples 4223 confidence 0.025 feature_proportion 0.001 n_clusters 50,4103,4223,0.001,50,0.025,0.55,0,0,None,i7184,0,632.54296875,632.4934895833334,-1,0,5015171
1746796707,1746796726,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1280 n_samples 3744 confidence 0.01 feature_proportion 0.999 n_clusters 1,1280,3744,0.999,1,0.01,0.55,0,0,None,i7182,0,631.859375,631.8268229166666,-1,0,5015959

Key	Value
config_yaml	None
config_toml	None
config_json	None
num_random_steps	20
max_eval	50000
run_program	None
experiment_name	None
mem_gb	32
parameter	None
continue_previous_job	/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CSDDM_OutdoorObjects_HoeffdingTreeClassifier_ACCURACY-RUNTIME/0/
experiment_constraints	None
run_dir	runs
seed	None
decimalrounding	4
enforce_sequential_optimization	False
verbose_tqdm	False
model	None
gridsearch	False
occ	False
show_sixel_scatter	False
show_sixel_general	False
show_sixel_trial_index_result	False
follow	False
send_anonymized_usage_stats	False
ui_url	None
root_venv_dir	/home/s4122485
exclude	None
main_process_gb	8
pareto_front_confidence	1
max_nr_of_zero_results	10
abbreviate_job_names	False
orchestrator_file	None
checkout_to_latest_tested_version	False
live_share	False
disable_tqdm	False
workdir	False
occ_type	euclid
result_names	['RESULT=min']
minkowski_p	2
signed_weighted_euclidean_weights
generation_strategy	None
generate_all_jobs_at_once	False
revert_to_random_when_seemingly_exhausted	True
load_data_from_existing_jobs	[]
n_estimators_randomforest	100
external_generator	None
username	None
max_failed_jobs	None
num_parallel_jobs	20
worker_timeout	120
slurm_use_srun	False
time
partition
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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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 4833 confidence 0.25 feature_proportion 0.999 n_clusters 1",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 3841 confidence 0.1 feature_proportion 0.001 n_clusters 50",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 660 confidence 0.1 feature_proportion 0.999 n_clusters 50",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 1817 confidence 0.1 feature_proportion 0.999 n_clusters 1",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 4028 confidence 0.1 feature_proportion 0.001 n_clusters 50",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 1 n_samples 3514 confidence 0.005 feature_proportion 0.999 n_clusters 50",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 5000 n_samples 2925 confidence 0.025 feature_proportion 0.999 n_clusters 1",
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			        13.9
			    ],
			    [
			        1746503456,
			        906.79296875,
			        13.5
			    ],
			    [
			        1746503456,
			        906.79296875,
			        11.8
			    ],
			    [
			        1746554475,
			        931.94921875,
			        15.9
			    ],
			    [
			        1746554475,
			        931.94921875,
			        14.9
			    ],
			    [
			        1746554475,
			        931.94921875,
			        15.5
			    ],
			    [
			        1746554475,
			        931.94921875,
			        15.6
			    ],
			    [
			        1746613597,
			        946.296875,
			        15.8
			    ],
			    [
			        1746613597,
			        946.296875,
			        15.8
			    ],
			    [
			        1746613597,
			        946.296875,
			        15.7
			    ],
			    [
			        1746613597,
			        946.296875,
			        13.6
			    ],
			    [
			        1746687812,
			        957.00390625,
			        22
			    ],
			    [
			        1746687812,
			        957.00390625,
			        21.6
			    ],
			    [
			        1746687812,
			        957.00390625,
			        21.2
			    ],
			    [
			        1746687812,
			        957.00390625,
			        24.6
			    ],
			    [
			        1746762277,
			        999.28125,
			        18.6
			    ],
			    [
			        1746762277,
			        999.28125,
			        15.9
			    ],
			    [
			        1746762277,
			        999.28125,
			        16.4
			    ],
			    [
			        1746762277,
			        999.28125,
			        18.7
			    ]
			];
			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) &&
						tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
					);
			
					if (numericColumns.length < 2) {
						console.error("Not enough columns for Scatter-Plots");
						return;
					}
			
					for (let i = 0; i < numericColumns.length; i++) {
						for (let j = i + 1; j < numericColumns.length; j++) {
							let xCol = numericColumns[i];
							let yCol = numericColumns[j];
			
							let xIndex = tab_results_headers_json.indexOf(xCol);
							let yIndex = tab_results_headers_json.indexOf(yCol);
			
							let data = tab_results_csv_json.map(row => ({
								x: parseFloat(row[xIndex]),
								y: parseFloat(row[yIndex]),
								result: row[resultIndex] !== "" ? parseFloat(row[resultIndex]) : null
							}));
			
							data = data.filter(d => d.result >= minResult && d.result <= maxResult);
			
							let layoutTitle = `${xCol} (x) vs ${yCol} (y), result: ${selectedResult}`;
							let layout = {
								title: layoutTitle,
								xaxis: {
									title: get_axis_title_data(xCol)
								},
								yaxis: {
									title: get_axis_title_data(yCol)
								},
								showlegend: false
							};
							let subDiv = document.createElement("div");
			
							let spinnerContainer = document.createElement("div");
							spinnerContainer.style.display = "flex";
							spinnerContainer.style.alignItems = "center";
							spinnerContainer.style.justifyContent = "center";
							spinnerContainer.style.width = layout.width + "px";
							spinnerContainer.style.height = layout.height + "px";
							spinnerContainer.style.position = "relative";
			
							let spinner = document.createElement("div");
							spinner.className = "spinner";
							spinner.style.width = "40px";
							spinner.style.height = "40px";
			
							let loadingText = document.createElement("span");
							loadingText.innerText = `Loading ${layoutTitle}`;
							loadingText.style.marginLeft = "10px";
			
							spinnerContainer.appendChild(spinner);
							spinnerContainer.appendChild(loadingText);
			
							plotDiv.appendChild(spinnerContainer);
			
							await new Promise(resolve => setTimeout(resolve, 50));
			
							let colors = data.map(d => {
								if (d.result === null) {
									return 'rgb(0, 0, 0)';
								} else {
									let norm = (d.result - minResult) / (maxResult - minResult);
									if (invertColor) {
										norm = 1 - norm;
									}
									return `rgb(${Math.round(255 * norm)}, ${Math.round(255 * (1 - norm))}, 0)`;
								}
							});
			
							let trace = {
								x: data.map(d => d.x),
								y: data.map(d => d.y),
								mode: 'markers',
								marker: {
									size: get_marker_size(),
									color: data.map(d => d.result !== null ? d.result : null),
									colorscale: invertColor ? [
										[0, 'red'],
										[1, 'green']
									] : [
										[0, 'green'],
										[1, 'red']
									],
									colorbar: {
										title: 'Result',
										tickvals: [minResult, maxResult],
										ticktext: [`${minResult}`, `${maxResult}`]
									},
									symbol: data.map(d => d.result === null ? 'x' : 'circle'),
								},
								text: data.map(d => d.result !== null ? `Result: ${d.result}` : 'No result'),
								type: 'scatter',
								showlegend: false
							};
			
							try {
								plotDiv.replaceChild(subDiv, spinnerContainer);
							} catch (err) {
								//
							}
							Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
						}
					}
				}
			
				$("#plotScatter2d").data("loaded", "true");
			}
			
			function plotScatter3d() {
				if ($("#plotScatter3d").data("loaded") == "true") {
					return;
				}
			
				var plotDiv = document.getElementById("plotScatter3d");
				if (!plotDiv) {
					console.error("Div element with id 'plotScatter3d' not found");
					return;
				}
				plotDiv.innerHTML = "";
			
				var minInput3d = document.getElementById("minValue3d");
				var maxInput3d = document.getElementById("maxValue3d");
			
				if (!minInput3d || !maxInput3d) {
					minInput3d = document.createElement("input");
					minInput3d.id = "minValue3d";
					minInput3d.type = "number";
					minInput3d.placeholder = "Min Value";
					minInput3d.step = "any";
			
					maxInput3d = document.createElement("input");
					maxInput3d.id = "maxValue3d";
					maxInput3d.type = "number";
					maxInput3d.placeholder = "Max Value";
					maxInput3d.step = "any";
			
					var inputContainer3d = document.createElement("div");
					inputContainer3d.style.marginBottom = "10px";
					inputContainer3d.appendChild(minInput3d);
					inputContainer3d.appendChild(maxInput3d);
					plotDiv.appendChild(inputContainer3d);
				}
			
				var select3d = document.getElementById("select3dScatter");
				if (result_names.length > 1 && !select3d) {
					if (!select3d) {
						select3d = document.createElement("select");
						select3d.id = "select3dScatter";
						select3d.style.marginBottom = "10px";
						select3d.innerHTML = result_names.map(name => `<option value="${name}">${name}</option>`).join("");
			
						select3d.addEventListener("change", updatePlots3d);
			
						plotDiv.appendChild(select3d);
					}
				}
			
				minInput3d.addEventListener("input", updatePlots3d);
				maxInput3d.addEventListener("input", updatePlots3d);
			
				updatePlots3d();
			
				async function updatePlots3d() {
					var selectedResult = select3d ? select3d.value : result_names[0];
					var minValue3d = parseFloat(minInput3d.value);
					var maxValue3d = parseFloat(maxInput3d.value);
			
					if (isNaN(minValue3d)) minValue3d = -Infinity;
					if (isNaN(maxValue3d)) maxValue3d = Infinity;
			
					while (plotDiv.children.length > 2) {
						plotDiv.removeChild(plotDiv.lastChild);
					}
			
					var resultIndex = tab_results_headers_json.findIndex(header =>
						header.toLowerCase() === selectedResult.toLowerCase()
					);
					var resultValues = tab_results_csv_json.map(row => row[resultIndex]);
			
					var minResult = Math.min(...resultValues.filter(value => value !== null && value !== ""));
					var maxResult = Math.max(...resultValues.filter(value => value !== null && value !== ""));
			
					if (minValue3d !== -Infinity) minResult = Math.max(minResult, minValue3d);
					if (maxValue3d !== Infinity) maxResult = Math.min(maxResult, maxValue3d);
			
					var invertColor = result_min_max[result_names.indexOf(selectedResult)] === "max";
			
					var numericColumns = tab_results_headers_json.filter(col =>
						!special_col_names.includes(col) && !result_names.includes(col) &&
						tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
					);
			
					if (numericColumns.length < 3) {
						console.error("Not enough columns for 3D scatter plots");
						return;
					}
			
					for (let i = 0; i < numericColumns.length; i++) {
						for (let j = i + 1; j < numericColumns.length; j++) {
							for (let k = j + 1; k < numericColumns.length; k++) {
								let xCol = numericColumns[i];
								let yCol = numericColumns[j];
								let zCol = numericColumns[k];
			
								let xIndex = tab_results_headers_json.indexOf(xCol);
								let yIndex = tab_results_headers_json.indexOf(yCol);
								let zIndex = tab_results_headers_json.indexOf(zCol);
			
								let data = tab_results_csv_json.map(row => ({
									x: parseFloat(row[xIndex]),
									y: parseFloat(row[yIndex]),
									z: parseFloat(row[zIndex]),
									result: row[resultIndex] !== "" ? parseFloat(row[resultIndex]) : null
								}));
			
								data = data.filter(d => d.result >= minResult && d.result <= maxResult);
			
								let layoutTitle = `${xCol} (x) vs ${yCol} (y) vs ${zCol} (z), result: ${selectedResult}`;
								let layout = {
									title: layoutTitle,
									scene: {
										xaxis: {
											title: get_axis_title_data(xCol)
										},
										yaxis: {
											title: get_axis_title_data(yCol)
										},
										zaxis: {
											title: get_axis_title_data(zCol)
										}
									},
									showlegend: false
								};
			
								let spinnerContainer = document.createElement("div");
								spinnerContainer.style.display = "flex";
								spinnerContainer.style.alignItems = "center";
								spinnerContainer.style.justifyContent = "center";
								spinnerContainer.style.width = layout.width + "px";
								spinnerContainer.style.height = layout.height + "px";
								spinnerContainer.style.position = "relative";
			
								let spinner = document.createElement("div");
								spinner.className = "spinner";
								spinner.style.width = "40px";
								spinner.style.height = "40px";
			
								let loadingText = document.createElement("span");
								loadingText.innerText = `Loading ${layoutTitle}`;
								loadingText.style.marginLeft = "10px";
			
								spinnerContainer.appendChild(spinner);
								spinnerContainer.appendChild(loadingText);
			
								plotDiv.appendChild(spinnerContainer);
			
								await new Promise(resolve => setTimeout(resolve, 50));
			
								let colors = data.map(d => {
									if (d.result === null) {
										return 'rgb(0, 0, 0)';
									} else {
										let norm = (d.result - minResult) / (maxResult - minResult);
										if (invertColor) {
											norm = 1 - norm;
										}
										return `rgb(${Math.round(255 * norm)}, ${Math.round(255 * (1 - norm))}, 0)`;
									}
								});
			
								let trace = {
									x: data.map(d => d.x),
									y: data.map(d => d.y),
									z: data.map(d => d.z),
									mode: 'markers',
									marker: {
										size: get_marker_size(),
										color: data.map(d => d.result !== null ? d.result : null),
										colorscale: invertColor ? [
											[0, 'red'],
											[1, 'green']
										] : [
											[0, 'green'],
											[1, 'red']
										],
										colorbar: {
											title: 'Result',
											tickvals: [minResult, maxResult],
											ticktext: [`${minResult}`, `${maxResult}`]
										},
									},
									text: data.map(d => d.result !== null ? `Result: ${d.result}` : 'No result'),
									type: 'scatter3d',
									showlegend: false
								};
			
								let subDiv = document.createElement("div");
								try {
									plotDiv.replaceChild(subDiv, spinnerContainer);
								} catch (err) {
									//
								}
								Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
							}
						}
					}
				}
			
				$("#plotScatter3d").data("loaded", "true");
			}
			
			async function plot_worker_cpu_ram() {
				if($("#worker_cpu_ram_pre").data("loaded") == "true") {
					return;
				}
			
				const logData = $("#worker_cpu_ram_pre").text();
				const regex = /^Unix-Timestamp: (\d+), Hostname: ([\w-]+), CPU: ([\d.]+)%, RAM: ([\d.]+) MB \/ ([\d.]+) MB$/;
			
				const hostData = {};
			
				logData.split("\n").forEach(line => {
					line = line.trim();
					const match = line.match(regex);
					if (match) {
						const timestamp = new Date(parseInt(match[1]) * 1000);
						const hostname = match[2];
						const cpu = parseFloat(match[3]);
						const ram = parseFloat(match[4]);
			
						if (!hostData[hostname]) {
							hostData[hostname] = { timestamps: [], cpuUsage: [], ramUsage: [] };
						}
			
						hostData[hostname].timestamps.push(timestamp);
						hostData[hostname].cpuUsage.push(cpu);
						hostData[hostname].ramUsage.push(ram);
					}
				});
			
				if (!Object.keys(hostData).length) {
					console.log("No valid data found");
					return;
				}
			
				const container = document.getElementById("cpuRamWorkerChartContainer");
				container.innerHTML = "";
			
				var i = 1;
			
				Object.entries(hostData).forEach(([hostname, { timestamps, cpuUsage, ramUsage }], index) => {
					const chartId = `workerChart_${index}`;
					const chartDiv = document.createElement("div");
					chartDiv.id = chartId;
					chartDiv.style.marginBottom = "40px";
					container.appendChild(chartDiv);
			
					const cpuTrace = {
						x: timestamps,
						y: cpuUsage,
						mode: "lines+markers",
						name: "CPU Usage (%)",
						yaxis: "y1",
						line: {
							color: "red"
						}
					};
			
					const ramTrace = {
						x: timestamps,
						y: ramUsage,
						mode: "lines+markers",
						name: "RAM Usage (MB)",
						yaxis: "y2",
						line: {
							color: "blue"
						}
					};
			
					const layout = {
						title: `Worker CPU and RAM Usage - ${hostname}`,
						xaxis: {
							title: get_axis_title_data("Timestamp", "date")
						},
						yaxis: {
							title: get_axis_title_data("CPU Usage (%)"),
							side: "left",
							color: "red"
						},
						yaxis2: {
							title: get_axis_title_data("RAM Usage (MB)"),
							side: "right",
							overlaying: "y",
							color: "blue"
						},
						showlegend: true
					};
			
					Plotly.newPlot(chartId, [cpuTrace, ramTrace], add_default_layout_data(layout));
					i++;
				});
			
				$("#plot_worker_cpu_ram_button").remove();
				$("#worker_cpu_ram_pre").data("loaded", "true");
			}
			
			function load_log_file(log_nr, filename) {
				var pre_id = `single_run_${log_nr}_pre`;
			
				if (!$("#" + pre_id).data("loaded")) {
					const params = new URLSearchParams(window.location.search);
			
					const user_id = params.get('user_id');
					const experiment_name = params.get('experiment_name');
					const run_nr = params.get('run_nr');
			
					var url = `get_log?user_id=${user_id}&experiment_name=${experiment_name}&run_nr=${run_nr}&filename=${filename}`;
			
					fetch(url)
						.then(response => response.json())
						.then(data => {
							if (data.data) {
								$("#" + pre_id).html(data.data);
								$("#" + pre_id).data("loaded", true);
							} else {
								log(`No 'data' key found in response.`);
							}
			
							$("#spinner_log_" + log_nr).remove();
						})
						.catch(error => {
							log(`Error loading log: ${error}`);
							$("#spinner_log_" + log_nr).remove();
						});
				}
			}
			
			function load_debug_log () {
				var pre_id = `here_debuglogs_go`;
			
				if (!$("#" + pre_id).data("loaded")) {
					const params = new URLSearchParams(window.location.search);
			
					const user_id = params.get('user_id');
					const experiment_name = params.get('experiment_name');
					const run_nr = params.get('run_nr');
			
					var url = `get_debug_log?user_id=${user_id}&experiment_name=${experiment_name}&run_nr=${run_nr}`;
			
					fetch(url)
						.then(response => response.json())
						.then(data => {
							$("#debug_log_spinner").remove();
			
							if (data.data) {
								try {
									$("#" + pre_id).html(data.data);
								} catch (err) {
									$("#" + pre_id).text(`Error loading data: ${err}`);
								}
			
								$("#" + pre_id).data("loaded", true);
			
								if (typeof apply_theme_based_on_system_preferences === 'function') {
									apply_theme_based_on_system_preferences();
								}
							} else {
								log(`No 'data' key found in response.`);
							}
						})
						.catch(error => {
							log(`Error loading log: ${error}`);
							$("#debug_log_spinner").remove();
						});
				}
			}
			
			function plotBoxplot() {
				if ($("#plotBoxplot").data("loaded") == "true") {
					return;
				}
				var numericColumns = tab_results_headers_json.filter(col =>
					!special_col_names.includes(col) && !result_names.includes(col) &&
					tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
				);
			
				if (numericColumns.length < 1) {
					console.error("Not enough numeric columns for Boxplot");
					return;
				}
			
				var resultIndex = tab_results_headers_json.findIndex(function(header) {
					return result_names.includes(header.toLowerCase());
				});
				var resultValues = tab_results_csv_json.map(row => row[resultIndex]);
				var minResult = Math.min(...resultValues.filter(value => value !== null && value !== ""));
				var maxResult = Math.max(...resultValues.filter(value => value !== null && value !== ""));
			
				var plotDiv = document.getElementById("plotBoxplot");
				plotDiv.innerHTML = "";
			
				let traces = numericColumns.map(col => {
					let index = tab_results_headers_json.indexOf(col);
					let data = tab_results_csv_json.map(row => parseFloat(row[index]));
			
					return {
						y: data,
						type: 'box',
						name: col,
						boxmean: 'sd',
						marker: {
							color: 'rgb(0, 255, 0)'
						},
					};
				});
			
				let layout = {
					title: 'Boxplot of Numerical Columns',
					xaxis: {
						title: get_axis_title_data("Columns")
					},
					yaxis: {
						title: get_axis_title_data("Value")
					},
					showlegend: false
				};
			
				Plotly.newPlot(plotDiv, traces, add_default_layout_data(layout));
				$("#plotBoxplot").data("loaded", "true");
			}
			
			function plotHeatmap() {
				if ($("#plotHeatmap").data("loaded") === "true") {
					return;
				}
			
				var numericColumns = tab_results_headers_json.filter(col => {
					if (special_col_names.includes(col) || result_names.includes(col)) {
						return false;
					}
					let index = tab_results_headers_json.indexOf(col);
					return tab_results_csv_json.every(row => {
						let value = parseFloat(row[index]);
						return !isNaN(value) && isFinite(value);
					});
				});
			
				if (numericColumns.length < 2) {
					console.error("Not enough valid numeric columns for Heatmap");
					return;
				}
			
				var columnData = numericColumns.map(col => {
					let index = tab_results_headers_json.indexOf(col);
					return tab_results_csv_json.map(row => parseFloat(row[index]));
				});
			
				var dataMatrix = numericColumns.map((_, i) =>
					numericColumns.map((_, j) => {
						let values = columnData[i].map((val, index) => (val + columnData[j][index]) / 2);
						return values.reduce((a, b) => a + b, 0) / values.length;
					})
				);
			
				var trace = {
					z: dataMatrix,
					x: numericColumns,
					y: numericColumns,
					colorscale: 'Viridis',
					type: 'heatmap'
				};
			
				var layout = {
					xaxis: {
						title: get_axis_title_data("Columns")
					},
					yaxis: {
						title: get_axis_title_data("Columns")
					},
					showlegend: false
				};
			
				var plotDiv = document.getElementById("plotHeatmap");
				plotDiv.innerHTML = "";
			
				Plotly.newPlot(plotDiv, [trace], add_default_layout_data(layout));
				$("#plotHeatmap").data("loaded", "true");
			}
			
			function plotHistogram() {
				if ($("#plotHistogram").data("loaded") == "true") {
					return;
				}
			
				var numericColumns = tab_results_headers_json.filter(col =>
					!special_col_names.includes(col) && !result_names.includes(col) &&
					tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
				);
			
				if (numericColumns.length < 1) {
					console.error("Not enough columns for Histogram");
					return;
				}
			
				var plotDiv = document.getElementById("plotHistogram");
				plotDiv.innerHTML = "";
			
				const colorPalette = ['#ff9999', '#66b3ff', '#99ff99', '#ffcc99', '#c2c2f0', '#ffb3e6'];
			
				let traces = numericColumns.map((col, index) => {
					let data = tab_results_csv_json.map(row => parseFloat(row[tab_results_headers_json.indexOf(col)]));
			
					return {
						x: data,
						type: 'histogram',
						name: col,
						opacity: 0.7,
						marker: {
							color: colorPalette[index % colorPalette.length]
						},
						autobinx: true
					};
				});
			
				let layout = {
					title: 'Histogram of Numerical Columns',
					xaxis: {
						title: get_axis_title_data("Value")
					},
					yaxis: {
						title: get_axis_title_data("Frequency")
					},
					showlegend: true,
					barmode: 'overlay'
				};
			
				Plotly.newPlot(plotDiv, traces, add_default_layout_data(layout));
				$("#plotHistogram").data("loaded", "true");
			}
			
			function plotViolin() {
				if ($("#plotViolin").data("loaded") == "true") {
					return;
				}
				var numericColumns = tab_results_headers_json.filter(col =>
					!special_col_names.includes(col) && !result_names.includes(col) &&
					tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
				);
			
				if (numericColumns.length < 1) {
					console.error("Not enough columns for Violin Plot");
					return;
				}
			
				var plotDiv = document.getElementById("plotViolin");
				plotDiv.innerHTML = "";
			
				let traces = numericColumns.map(col => {
					let index = tab_results_headers_json.indexOf(col);
					let data = tab_results_csv_json.map(row => parseFloat(row[index]));
			
					return {
						y: data,
						type: 'violin',
						name: col,
						box: {
							visible: true
						},
						line: {
							color: 'rgb(0, 255, 0)'
						},
						marker: {
							color: 'rgb(0, 255, 0)'
						},
						meanline: {
							visible: true
						},
					};
				});
			
				let layout = {
					title: 'Violin Plot of Numerical Columns',
					yaxis: {
						title: get_axis_title_data("Value")
					},
					xaxis: {
						title: get_axis_title_data("Columns")
					},
					showlegend: false
				};
			
				Plotly.newPlot(plotDiv, traces, add_default_layout_data(layout));
				$("#plotViolin").data("loaded", "true");
			}
			
			function plotExitCodesPieChart() {
				if ($("#plotExitCodesPieChart").data("loaded") == "true") {
					return;
				}
			
				var exitCodes = tab_job_infos_csv_json.map(row => row[tab_job_infos_headers_json.indexOf("exit_code")]);
			
				var exitCodeCounts = exitCodes.reduce(function(counts, exitCode) {
					counts[exitCode] = (counts[exitCode] || 0) + 1;
					return counts;
				}, {});
			
				var labels = Object.keys(exitCodeCounts);
				var values = Object.values(exitCodeCounts);
			
				var plotDiv = document.getElementById("plotExitCodesPieChart");
				plotDiv.innerHTML = "";
			
				var trace = {
					labels: labels,
					values: values,
					type: 'pie',
					hoverinfo: 'label+percent',
					textinfo: 'label+value',
					marker: {
						colors: ['#ff9999','#66b3ff','#99ff99','#ffcc99','#c2c2f0']
					}
				};
			
				var layout = {
					title: 'Exit Code Distribution',
					showlegend: true
				};
			
				Plotly.newPlot(plotDiv, [trace], add_default_layout_data(layout));
				$("#plotExitCodesPieChart").data("loaded", "true");
			}
			
			function plotResultEvolution() {
				if ($("#plotResultEvolution").data("loaded") == "true") {
					return;
				}
			
				result_names.forEach(resultName => {
					var relevantColumns = tab_results_headers_json.filter(col =>
						!special_col_names.includes(col) && !col.startsWith("OO_Info") && col.toLowerCase() !== resultName.toLowerCase()
					);
			
					var xColumnIndex = tab_results_headers_json.indexOf("trial_index");
					var resultIndex = tab_results_headers_json.indexOf(resultName);
			
					let data = tab_results_csv_json.map(row => ({
						x: row[xColumnIndex],
						y: parseFloat(row[resultIndex])
					}));
			
					data.sort((a, b) => a.x - b.x);
			
					let xData = data.map(item => item.x);
					let yData = data.map(item => item.y);
			
					let trace = {
						x: xData,
						y: yData,
						mode: 'lines+markers',
						name: resultName,
						line: {
							shape: 'linear'
						},
						marker: {
							size: get_marker_size()
						}
					};
			
					let layout = {
						title: `Evolution of ${resultName} over time`,
						xaxis: {
							title: get_axis_title_data("Trial-Index")
						},
						yaxis: {
							title: get_axis_title_data(resultName)
						},
						showlegend: true
					};
			
					let subDiv = document.createElement("div");
					document.getElementById("plotResultEvolution").appendChild(subDiv);
			
					Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
				});
			
				$("#plotResultEvolution").data("loaded", "true");
			}
			
			function plotResultPairs() {
				if ($("#plotResultPairs").data("loaded") == "true") {
					return;
				}
			
				var plotDiv = document.getElementById("plotResultPairs");
				plotDiv.innerHTML = "";
			
				for (let i = 0; i < result_names.length; i++) {
					for (let j = i + 1; j < result_names.length; j++) {
						let xName = result_names[i];
						let yName = result_names[j];
			
						let xIndex = tab_results_headers_json.indexOf(xName);
						let yIndex = tab_results_headers_json.indexOf(yName);
			
						let data = tab_results_csv_json
							.filter(row => row[xIndex] !== "" && row[yIndex] !== "")
							.map(row => ({
								x: parseFloat(row[xIndex]),
								y: parseFloat(row[yIndex]),
								status: row[tab_results_headers_json.indexOf("trial_status")]
							}));
			
						let colors = data.map(d => d.status === "COMPLETED" ? 'green' : (d.status === "FAILED" ? 'red' : 'gray'));
			
						let trace = {
							x: data.map(d => d.x),
							y: data.map(d => d.y),
							mode: 'markers',
							marker: {
								size: get_marker_size(),
								color: colors
							},
							text: data.map(d => `Status: ${d.status}`),
							type: 'scatter',
							showlegend: false
						};
			
						let layout = {
							xaxis: {
								title: get_axis_title_data(xName)
							},
							yaxis: {
								title: get_axis_title_data(yName)
							},
							showlegend: false
						};
			
						let subDiv = document.createElement("div");
						plotDiv.appendChild(subDiv);
			
						Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
					}
				}
			
				$("#plotResultPairs").data("loaded", "true");
			}
			
			function add_up_down_arrows_for_scrolling () {
				const upArrow = document.createElement('div');
				const downArrow = document.createElement('div');
			
				const style = document.createElement('style');
				style.innerHTML = `
					.scroll-arrow {
						position: fixed;
						right: 10px;
						z-index: 100;
						cursor: pointer;
						font-size: 25px;
						display: none;
						background-color: green;
						color: white;
						padding: 5px;
						outline: 2px solid white;
						box-shadow: 0 0 10px rgba(0, 0, 0, 0.5);
						transition: background-color 0.3s, transform 0.3s;
					}
					.scroll-arrow:hover {
						background-color: darkgreen;
						transform: scale(1.1);
					}
					#up-arrow {
						top: 10px;
					}
					#down-arrow {
						bottom: 10px;
					}
				`;
				document.head.appendChild(style);
			
				upArrow.id = "up-arrow";
				upArrow.classList.add("scroll-arrow");
				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();
			}
			
			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();;
				plotResultEvolution();;
				plotExitCodesPieChart();

				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> Max. nr. evaluations</td><td>50090 </td></tr><tr><td> Max. nr. evaluations (from arguments)</td><td>50000 </td></tr><tr><td> Number random steps</td><td>20    </td></tr><tr><td> Nr. of workers (parameter)</td><td>20    </td></tr><tr><td> Main process memory (GB)</td><td>8     </td></tr><tr><td> Worker memory (GB)</td><td>32    </td></tr><tr><td> Nr. imported jobs</td><td>90    </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>int</td><td>1</td><td>5000</td><td></td><td>int</td><td>No         </td></tr><tr><td> n_samples</td><td>int</td><td>1</td><td>5000</td><td></td><td>int</td><td>No         </td></tr><tr><td> confidence</td><td>choice</td><td></td><td></td><td>0.25, 0.1, 0.05, 0.025, 0.01, 0.005, 0.001</td><td></td><td></td></tr><tr><td> feature_proportion</td><td>float</td><td>0.001</td><td>0.999</td><td></td><td>float</td><td>No         </td></tr><tr><td> n_clusters</td><td>int</td><td>1</td><td>50</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>2</td>
			<td>534</td>
			<td>1</td>
			<td>537</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>
			<br>
			<h2>Git-Version</h2>
			<tt>Commit: 2223ae6553abdd3e288f4b391080b763a7a48477
			</tt>
			<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,n_samples,feature_proportion,n_clusters,confidence
0,0_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,0.000000000000000000000000000000,3595,4132,0.701485616922378540927240919700,18,0.1
1,1_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,1.000000000000000000000000000000,2420,464,0.214044812804087991597867812743,41,0.05
2,2_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,0.000000000000000000000000000000,400,3614,0.348608805460855375457640548120,32,0.05
3,3_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,0.000000000000000000000000000000,4213,2438,0.859198473686352381939457245608,11,0.25
4,4_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,0.000000000000000000000000000000,4463,2646,0.098108189797028899636899268444,31,0.01
5,5_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,0.000000000000000000000000000000,776,1316,0.616492829488590410313975098688,3,0.05
6,6_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,0.000000000000000000000000000000,1407,4612,0.946087049866095153305423082202,20,0.005
7,7_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,1.000000000000000000000000000000,2732,785,0.466441229296848169916245296918,47,0.1
8,8_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,0.000000000000000000000000000000,3003,3236,0.766061342881992457520823336381,45,0.01
9,9_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,5.000000000000000000000000000000,1767,1906,0.255229925846680971712743257740,24,0.025
10,10_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,0.000000000000000000000000000000,1051,4040,0.183160878134891402790884740170,6,0.005
11,11_0,COMPLETED,Sobol,SOBOL,0.570000000000000062172489379009,3.000000000000000000000000000000,4807,213,0.670359921360388355537907045800,29,0.05
12,12_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,0.000000000000000000000000000000,3863,4713,0.435559294825419773822261504392,8,0.001
13,13_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,1.000000000000000000000000000000,120,1044,0.914959559516981268956214989885,35,0.1
14,14_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,0.000000000000000000000000000000,2065,3012,0.523357743496075222822128125699,43,0.01
15,15_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,0.000000000000000000000000000000,3329,1837,0.004727547926828265523191419106,15,0.25
16,16_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,0.000000000000000000000000000000,3243,2859,0.579029498932883135431382015668,14,0.025
17,17_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,1.000000000000000000000000000000,1996,1688,0.068441737959161405568941916044,41,0.05
18,18_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,0.000000000000000000000000000000,187,4867,0.495129268409684297758133197931,37,0.005
19,19_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,0.000000000000000000000000000000,3952,1193,0.982571960261091614796669091447,9,0.01
20,20_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,0.000000000000000000000000000000,4875,3882,0.246639386871829624503504874156,26,0.005
21,21_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,6.000000000000000000000000000000,1140,50,0.726283300189301317395518253761,5,0.001
22,22_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,0.000000000000000000000000000000,1680,3394,0.833437586447223988095345248439,24,0.1
23,23_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,0.000000000000000000000000000000,2933,2070,0.315051046939566758986472905235,47,0.01
24,24_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,0.000000000000000000000000000000,2585,4463,0.889191303519532127985769420775,50,0.005
25,25_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,1.000000000000000000000000000000,1399,631,0.401994167545810354713609058308,21,0.001
26,26_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,0.000000000000000000000000000000,787,2795,0.037314262481406332283562221619,2,0.25
27,27_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,0.000000000000000000000000000000,4608,1470,0.548147579332813661423529083550,29,0.1
28,28_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,0.000000000000000000000000000000,4224,3450,0.283925348589196824278246822360,12,0.1
29,29_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,0.000000000000000000000000000000,545,2279,0.802553636906668588224533777975,35,0.25
30,30_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,5000,0.704670638813436278624635633605,31,0.05
31,31_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,3715,0.767975833195619794757647014194,5,0.05
32,32_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,3391,0.678035718940829257306290855922,8,0.025
33,33_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,5000,985,0.810293179614616110306712926104,1,0.05
34,34_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1257,2759,0.001000000000000000020816681712,8,0.025
35,35_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,3580,0.001000000000000000020816681712,8,0.025
36,36_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,5000,0.518090888827096973656693990051,10,0.025
37,37_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1355,2357,0.001000000000000000020816681712,7,0.025
38,38_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,5000,1952,0.593295082353993419310711487924,2,0.05
39,39_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,5000,0.001000000000000000020816681712,14,0.001
40,40_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.570000000000000062172489379009,4.000000000000000000000000000000,5000,165,0.998999999999999999111821580300,1,0.05
41,41_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,4878,0.998999999999999999111821580300,20,0.05
42,42_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,2713,0.706766054422214073937880129961,6,0.05
43,43_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,2328,0.998999999999999999111821580300,1,0.05
44,44_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,4476,0.001000000000000000020816681712,8,0.025
45,45_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,2193,0.998999999999999999111821580300,5,0.05
46,46_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,5000,0.001000000000000000020816681712,50,0.05
47,47_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,1291,961,0.001000000000000000020816681712,32,0.001
48,48_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,4052,0.998999999999999999111821580300,14,0.05
49,49_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,5000,963,0.352614184300036159758207077175,50,0.05
50,50_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,5000,381,0.998999999999999999111821580300,7,0.05
51,51_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,3.000000000000000000000000000000,5000,502,0.001000000000000000020816681712,49,0.05
52,52_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,4901,0.001000000000000000020816681712,10,0.05
53,53_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.570000000000000062172489379009,3.000000000000000000000000000000,5000,232,0.998999999999999999111821580300,6,0.05
54,54_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2126,1227,0.998999999999999999111821580300,6,0.025
55,55_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,3.000000000000000000000000000000,5000,374,0.001000000000000000020816681712,50,0.05
56,56_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,5000,1191,0.001000000000000000020816681712,50,0.025
57,57_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,5000,0.998999999999999999111821580300,20,0.05
58,58_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,5000,0.998999999999999999111821580300,3,0.05
59,59_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1615,5000,0.998999999999999999111821580300,16,0.001
60,60_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.570000000000000062172489379009,3.000000000000000000000000000000,3909,207,0.998999999999999999111821580300,50,0.025
61,61_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,1,243,0.998999999999999999111821580300,50,0.1
62,62_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3050,1407,0.683247280720495009376236339449,2,0.001
63,63_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,660,220,0.998999999999999999111821580300,50,0.25
64,64_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,1,249,0.998999999999999999111821580300,50,0.025
65,65_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,1,315,0.998999999999999999111821580300,49,0.05
66,66_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,4948,2222,0.036471601709381018530109486164,42,0.001
67,67_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.570000000000000062172489379009,3.000000000000000000000000000000,5000,209,0.998999999999999999111821580300,1,0.025
68,68_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3132,3052,0.818287020120799346578621680237,7,0.001
69,69_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,843,2529,0.964153182313869705488684758166,11,0.001
70,70_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2869,3907,0.423153675989766164811101134546,19,0.001
71,71_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.570000000000000062172489379009,2.000000000000000000000000000000,2321,214,0.998999999999999999111821580300,50,0.025
72,72_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2000,4311,0.001000000000000000020816681712,18,0.001
73,73_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,4040,1442,0.457271417793322143552359193563,4,0.25
74,74_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,2896,0.998999999999999999111821580300,20,0.001
75,75_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2425,4095,0.465109776116715833982340200237,35,0.001
76,76_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.570000000000000062172489379009,3.000000000000000000000000000000,5000,210,0.998999999999999999111821580300,1,0.25
77,77_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1148,3293,0.001000000000000000020816681712,1,0.001
78,78_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3921,2057,0.998999999999999999111821580300,25,0.25
79,79_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,4313,2498,0.001000000000000000020816681712,13,0.025
80,80_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2426,2467,0.001000000000000000020816681712,32,0.001
81,81_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,874,3333,0.001000000000000000020816681712,49,0.001
82,82_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,750,2990,0.001000000000000000020816681712,46,0.001
83,83_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,1,280,0.998999999999999999111821580300,50,0.025
84,84_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1448,2649,0.998999999999999999111821580300,38,0.001
85,85_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.570000000000000062172489379009,3.000000000000000000000000000000,5000,198,0.998999999999999999111821580300,50,0.025
86,86_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,4719,1525,0.001000000000000000020816681712,1,0.001
87,87_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1183,4380,0.001000000000000000020816681712,19,0.25
88,88_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,4813,3502,0.998999999999999999111821580300,50,0.001
89,89_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2795,1340,0.001000000000000000020816681712,1,0.001
90,90_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,3.000000000000000000000000000000,1730,318,0.998999999999999999111821580300,43,0.1
91,91_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,1.000000000000000000000000000000,2310,252,0.998999999999999999111821580300,50,0.1
92,92_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,1,713,0.001000000000000000020816681712,42,0.05
93,93_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,2552,491,0.998999999999999999111821580300,50,0.025
94,94_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,3092,0.998999999999999999111821580300,16,0.05
95,95_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,1368,450,0.998999999999999999111821580300,50,0.1
96,96_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,2038,326,0.998999999999999999111821580300,1,0.25
97,97_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,4.000000000000000000000000000000,4385,162,0.998999999999999999111821580300,50,0.1
98,98_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4722,15,0.998999999999999999111821580300,50,0.1
99,99_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,4.000000000000000000000000000000,3916,283,0.998999999999999999111821580300,50,0.25
100,100_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,3974,0.998999999999999999111821580300,50,0.01
101,101_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,3179,287,0.998999999999999999111821580300,1,0.1
102,102_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,1782,377,0.998999999999999999111821580300,1,0.025
103,103_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,3168,276,0.998999999999999999111821580300,1,0.025
104,104_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,3225,237,0.998999999999999999111821580300,50,0.025
105,105_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,1545,0.998999999999999999111821580300,1,0.25
106,106_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,5.000000000000000000000000000000,5000,149,0.998999999999999999111821580300,50,0.025
107,107_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,3260,0.001000000000000000020816681712,50,0.005
108,108_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,4696,0.001000000000000000020816681712,50,0.025
109,109_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,2204,0.998999999999999999111821580300,1,0.05
110,110_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,2965,309,0.998999999999999999111821580300,1,0.01
111,111_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3514,4083,0.998999999999999999111821580300,1,0.025
112,112_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,4.000000000000000000000000000000,4312,241,0.998999999999999999111821580300,1,0.025
113,113_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,2543,318,0.998999999999999999111821580300,50,0.025
114,114_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,1,977,0.998999999999999999111821580300,1,0.025
115,115_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,2623,0.998999999999999999111821580300,50,0.01
116,116_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,4176,0.998999999999999999111821580300,50,0.1
117,117_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,4642,0.998999999999999999111821580300,50,0.25
118,118_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,3768,0.001000000000000000020816681712,1,0.25
119,119_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,2280,340,0.998999999999999999111821580300,1,0.01
120,120_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,2600,0.001000000000000000020816681712,50,0.005
121,121_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,5000,0.001000000000000000020816681712,1,0.1
122,122_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,2446,312,0.998999999999999999111821580300,50,0.1
123,123_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,2165,0.001000000000000000020816681712,50,0.005
124,124_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,4566,0.998999999999999999111821580300,1,0.001
125,125_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3278,3689,0.998999999999999999111821580300,50,0.025
126,126_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,3653,261,0.998999999999999999111821580300,50,0.1
127,127_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,3047,0.998999999999999999111821580300,50,0.1
128,128_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3465,4756,0.998999999999999999111821580300,1,0.01
129,129_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,1,1448,0.001000000000000000020816681712,50,0.001
130,130_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,1956,0.998999999999999999111821580300,50,0.001
131,131_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,4267,0.001000000000000000020816681712,1,0.005
132,132_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,3.000000000000000000000000000000,4206,260,0.998999999999999999111821580300,50,0.1
133,133_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,4348,0.998999999999999999111821580300,50,0.01
134,134_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2135,3548,0.998999999999999999111821580300,50,0.01
135,135_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,1808,0.998999999999999999111821580300,1,0.01
136,136_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,2248,347,0.998999999999999999111821580300,1,0.005
137,137_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,4325,0.998999999999999999111821580300,50,0.025
138,138_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,4338,340,0.998999999999999999111821580300,50,0.025
139,139_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,4289,0.001000000000000000020816681712,1,0.005
140,140_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,3549,0.001000000000000000020816681712,50,0.005
141,141_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,1699,339,0.998999999999999999111821580300,50,0.025
142,142_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,3072,0.001000000000000000020816681712,1,0.05
143,143_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,3842,0.001000000000000000020816681712,50,0.005
144,144_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,5000,1191,0.001000000000000000020816681712,50,0.005
145,145_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,3485,351,0.998999999999999999111821580300,50,0.025
146,146_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,3866,271,0.998999999999999999111821580300,50,0.025
147,147_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,3.000000000000000000000000000000,1989,322,0.998999999999999999111821580300,50,0.025
148,148_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,4604,0.001000000000000000020816681712,1,0.1
149,149_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,5000,0.998999999999999999111821580300,50,0.25
150,150_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,2611,0.998999999999999999111821580300,1,0.025
151,151_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,3.000000000000000000000000000000,4963,203,0.998999999999999999111821580300,50,0.1
152,152_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,3662,0.998999999999999999111821580300,50,0.001
153,153_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,2332,0.998999999999999999111821580300,1,0.1
154,154_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,2683,0.001000000000000000020816681712,50,0.025
155,155_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,4.000000000000000000000000000000,5000,237,0.998999999999999999111821580300,50,0.1
156,156_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,2586,0.001000000000000000020816681712,1,0.1
157,157_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,3230,0.998999999999999999111821580300,1,0.005
158,158_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,3145,0.998999999999999999111821580300,1,0.025
159,159_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,3977,0.998999999999999999111821580300,1,0.05
160,160_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,3115,0.998999999999999999111821580300,1,0.01
161,161_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,2156,0.998999999999999999111821580300,1,0.005
162,162_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,4001,0.001000000000000000020816681712,50,0.025
163,163_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3965,2349,0.998999999999999999111821580300,50,0.1
164,164_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,3917,0.998999999999999999111821580300,1,0.025
165,165_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,2970,430,0.998999999999999999111821580300,50,0.1
166,166_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,4.000000000000000000000000000000,1998,354,0.001000000000000000020816681712,50,0.025
167,167_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,4742,0.001000000000000000020816681712,50,0.001
168,168_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,3161,0.998999999999999999111821580300,50,0.001
169,169_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,4688,0.998999999999999999111821580300,50,0.025
170,170_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,1380,0.998999999999999999111821580300,50,0.1
171,171_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.579999999999999960031971113494,4.000000000000000000000000000000,5000,170,0.998999999999999999111821580300,50,0.025
172,172_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,3.000000000000000000000000000000,4164,252,0.998999999999999999111821580300,50,0.025
173,173_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,3734,0.001000000000000000020816681712,1,0.025
174,174_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,5000,1483,0.998999999999999999111821580300,50,0.01
175,175_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,1,1224,0.998999999999999999111821580300,1,0.25
176,176_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3626,5000,0.998999999999999999111821580300,1,0.005
177,177_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,3.000000000000000000000000000000,4062,295,0.998999999999999999111821580300,50,0.05
178,178_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,3807,389,0.998999999999999999111821580300,50,0.1
179,179_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,2827,0.998999999999999999111821580300,50,0.1
180,180_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,2685,341,0.998999999999999999111821580300,50,0.05
181,181_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,2169,384,0.998999999999999999111821580300,50,0.005
182,182_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,3979,0.998999999999999999111821580300,50,0.001
183,183_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,1704,0.998999999999999999111821580300,1,0.005
184,184_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,1391,0.998999999999999999111821580300,1,0.005
185,185_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,4644,0.998999999999999999111821580300,1,0.01
186,186_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,3452,0.998999999999999999111821580300,1,0.01
187,187_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2631,2793,0.001000000000000000020816681712,1,0.005
188,188_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,1857,0.998999999999999999111821580300,50,0.005
189,189_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,687,2246,0.001000000000000000020816681712,1,0.001
190,190_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,2651,0.001000000000000000020816681712,50,0.005
191,191_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2528,2690,0.998999999999999999111821580300,50,0.025
192,192_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,1791,389,0.998999999999999999111821580300,50,0.1
193,193_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,1864,1333,0.998999999999999999111821580300,50,0.1
194,194_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,2681,371,0.998999999999999999111821580300,50,0.05
195,195_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,3532,0.998999999999999999111821580300,1,0.025
196,196_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2503,3747,0.998999999999999999111821580300,1,0.1
197,197_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2209,5000,0.001000000000000000020816681712,50,0.25
198,198_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,2729,0.998999999999999999111821580300,50,0.05
199,199_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1884,3485,0.998999999999999999111821580300,1,0.005
200,200_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,5000,0.998999999999999999111821580300,50,0.025
201,201_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,4426,0.001000000000000000020816681712,1,0.05
202,202_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3521,4341,0.998999999999999999111821580300,1,0.1
203,203_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,3577,412,0.998999999999999999111821580300,50,0.1
204,204_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2552,2021,0.998999999999999999111821580300,1,0.005
205,205_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,3.000000000000000000000000000000,3509,302,0.998999999999999999111821580300,50,0.1
206,206_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,5000,0.001000000000000000020816681712,50,0.01
207,207_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,3261,0.001000000000000000020816681712,50,0.025
208,208_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,1705,401,0.998999999999999999111821580300,50,0.1
209,209_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,4.000000000000000000000000000000,4585,229,0.998999999999999999111821580300,50,0.1
210,210_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1905,4777,0.998999999999999999111821580300,50,0.1
211,211_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,1249,394,0.998999999999999999111821580300,50,0.05
212,212_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,1757,0.998999999999999999111821580300,1,0.1
213,213_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,2360,0.998999999999999999111821580300,1,0.005
214,214_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,3575,0.001000000000000000020816681712,50,0.25
215,215_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,4166,0.001000000000000000020816681712,50,0.005
216,216_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,2969,0.001000000000000000020816681712,50,0.01
217,217_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,4453,0.998999999999999999111821580300,1,0.001
218,218_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3898,3068,0.001000000000000000020816681712,50,0.005
219,219_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3203,1773,0.998999999999999999111821580300,1,0.001
220,220_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3835,4557,0.998999999999999999111821580300,1,0.005
221,221_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,2289,0.998999999999999999111821580300,50,0.005
222,222_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,5000,1172,0.998999999999999999111821580300,1,0.1
223,223_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2867,3744,0.998999999999999999111821580300,50,0.25
224,224_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,1968,0.998999999999999999111821580300,1,0.005
225,225_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,2983,288,0.998999999999999999111821580300,50,0.1
226,226_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,3388,0.998999999999999999111821580300,50,0.25
227,227_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,3352,0.001000000000000000020816681712,1,0.001
228,228_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.579999999999999960031971113494,5.000000000000000000000000000000,5000,132,0.998999999999999999111821580300,50,0.05
229,229_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,5000,0.001000000000000000020816681712,1,0.001
230,230_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3843,3943,0.001000000000000000020816681712,50,0.01
231,231_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,2.000000000000000000000000000000,3578,309,0.998999999999999999111821580300,50,0.025
232,232_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,1,1599,0.998999999999999999111821580300,50,0.005
233,233_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,7.000000000000000000000000000000,5000,89,0.998999999999999999111821580300,50,0.05
234,234_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,4833,0.998999999999999999111821580300,1,0.25
235,235_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,7.000000000000000000000000000000,5000,96,0.998999999999999999111821580300,50,0.1
236,236_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,4625,4854,0.001000000000000000020816681712,50,0.025
237,237_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,3.000000000000000000000000000000,1881,320,0.998999999999999999111821580300,1,0.05
238,238_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,4435,0.998999999999999999111821580300,50,0.1
239,239_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,2982,0.998999999999999999111821580300,50,0.025
240,240_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,2942,0.998999999999999999111821580300,1,0.01
241,241_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.579999999999999960031971113494,4.000000000000000000000000000000,5000,129,0.998999999999999999111821580300,50,0.05
242,242_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.579999999999999960031971113494,5.000000000000000000000000000000,5000,127,0.998999999999999999111821580300,50,0.025
243,243_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,1,1312,0.998999999999999999111821580300,1,0.005
244,244_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,987,331,0.998999999999999999111821580300,1,0.1
245,245_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.579999999999999960031971113494,6.000000000000000000000000000000,5000,112,0.998999999999999999111821580300,50,0.05
246,246_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2925,2996,0.998999999999999999111821580300,1,0.05
247,247_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.579999999999999960031971113494,6.000000000000000000000000000000,5000,124,0.998999999999999999111821580300,50,0.025
248,248_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,4186,0.998999999999999999111821580300,1,0.025
249,249_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.579999999999999960031971113494,5.000000000000000000000000000000,5000,136,0.998999999999999999111821580300,50,0.025
250,250_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,2093,0.998999999999999999111821580300,1,0.1
251,251_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,5000,1333,0.001000000000000000020816681712,50,0.05
252,252_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.579999999999999960031971113494,5.000000000000000000000000000000,5000,120,0.998999999999999999111821580300,50,0.025
253,253_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,3046,0.001000000000000000020816681712,1,0.005
254,254_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.579999999999999960031971113494,5.000000000000000000000000000000,5000,113,0.998999999999999999111821580300,50,0.025
255,255_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,2222,0.001000000000000000020816681712,50,0.1
256,256_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,2.000000000000000000000000000000,1996,318,0.998999999999999999111821580300,50,0.1
257,257_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,1354,0.998999999999999999111821580300,1,0.025
258,258_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,4348,2478,0.998999999999999999111821580300,1,0.025
259,259_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,3751,0.001000000000000000020816681712,50,0.1
260,260_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,3502,0.001000000000000000020816681712,50,0.025
261,261_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,4568,2809,0.001000000000000000020816681712,1,0.1
262,262_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,3.000000000000000000000000000000,4724,237,0.998999999999999999111821580300,50,0.025
263,263_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,3841,0.001000000000000000020816681712,50,0.1
264,264_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,744,634,0.998999999999999999111821580300,50,0.1
265,265_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.579999999999999960031971113494,6.000000000000000000000000000000,5000,107,0.998999999999999999111821580300,50,0.025
266,266_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.579999999999999960031971113494,6.000000000000000000000000000000,5000,104,0.998999999999999999111821580300,50,0.025
267,267_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.579999999999999960031971113494,4.000000000000000000000000000000,5000,183,0.998999999999999999111821580300,50,0.025
268,268_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,4.000000000000000000000000000000,4926,221,0.998999999999999999111821580300,50,0.025
269,269_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,3047,295,0.998999999999999999111821580300,50,0.025
270,270_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,2742,296,0.998999999999999999111821580300,50,0.005
271,271_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,3221,0.998999999999999999111821580300,1,0.025
272,272_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,5.000000000000000000000000000000,5000,168,0.998999999999999999111821580300,50,0.025
273,273_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2358,4885,0.998999999999999999111821580300,1,0.1
274,274_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,2512,0.001000000000000000020816681712,50,0.025
275,275_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,4137,0.001000000000000000020816681712,50,0.25
276,276_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,5.000000000000000000000000000000,5000,165,0.998999999999999999111821580300,50,0.05
277,277_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,2306,301,0.998999999999999999111821580300,50,0.05
278,278_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,2539,0.998999999999999999111821580300,1,0.005
279,279_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,5.000000000000000000000000000000,5000,160,0.998999999999999999111821580300,50,0.025
280,280_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,4416,0.001000000000000000020816681712,1,0.1
281,281_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,1990,599,0.998999999999999999111821580300,50,0.1
282,282_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.579999999999999960031971113494,4.000000000000000000000000000000,5000,143,0.998999999999999999111821580300,50,0.025
283,283_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,3.000000000000000000000000000000,4269,267,0.998999999999999999111821580300,50,0.025
284,284_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,5000,589,0.998999999999999999111821580300,50,0.025
285,285_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,1178,312,0.998999999999999999111821580300,50,0.025
286,286_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2814,3352,0.001000000000000000020816681712,50,0.25
287,287_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2242,4241,0.001000000000000000020816681712,1,0.025
288,288_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,2.000000000000000000000000000000,692,322,0.998999999999999999111821580300,50,0.1
289,289_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1345,2845,0.998999999999999999111821580300,50,0.025
290,290_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2865,4879,0.998999999999999999111821580300,1,0.025
291,291_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,3835,0.001000000000000000020816681712,1,0.1
292,292_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,1104,315,0.998999999999999999111821580300,50,0.1
293,293_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,1,660,0.998999999999999999111821580300,50,0.1
294,294_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,3.000000000000000000000000000000,5000,212,0.998999999999999999111821580300,50,0.025
295,295_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,3538,285,0.998999999999999999111821580300,50,0.1
296,296_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,4466,0.998999999999999999111821580300,50,0.025
297,297_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,2984,0.001000000000000000020816681712,50,0.025
298,298_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,1307,0.998999999999999999111821580300,1,0.025
299,299_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2546,2025,0.001000000000000000020816681712,1,0.1
300,300_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,282,317,0.998999999999999999111821580300,50,0.025
301,301_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,3384,0.001000000000000000020816681712,1,0.1
302,302_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,4680,0.001000000000000000020816681712,1,0.025
303,303_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2724,5000,0.001000000000000000020816681712,50,0.1
304,304_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,4570,5000,0.998999999999999999111821580300,50,0.1
305,305_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1556,2758,0.001000000000000000020816681712,50,0.1
306,306_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,3951,0.998999999999999999111821580300,1,0.001
307,307_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,2587,0.001000000000000000020816681712,1,0.001
308,308_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2384,2544,0.998999999999999999111821580300,1,0.1
309,309_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,3.000000000000000000000000000000,4377,258,0.998999999999999999111821580300,50,0.025
310,310_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,380,313,0.998999999999999999111821580300,50,0.1
311,311_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,1817,0.998999999999999999111821580300,1,0.1
312,312_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2198,5000,0.998999999999999999111821580300,1,0.05
313,313_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,1,1278,0.001000000000000000020816681712,50,0.025
314,314_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,2857,292,0.998999999999999999111821580300,50,0.025
315,315_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,2.000000000000000000000000000000,602,314,0.998999999999999999111821580300,1,0.025
316,316_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1496,3817,0.998999999999999999111821580300,1,0.025
317,317_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,3216,0.001000000000000000020816681712,50,0.1
318,318_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,4575,0.998999999999999999111821580300,1,0.025
319,319_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,1,318,0.998999999999999999111821580300,1,0.1
320,320_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,1.000000000000000000000000000000,2556,297,0.998999999999999999111821580300,50,0.1
321,321_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1905,4134,0.001000000000000000020816681712,50,0.1
322,322_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,5000,1370,0.998999999999999999111821580300,1,0.1
323,323_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,1,697,0.998999999999999999111821580300,50,0.025
324,324_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,2080,0.998999999999999999111821580300,50,0.01
325,325_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3009,4086,0.001000000000000000020816681712,50,0.025
326,326_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,4725,0.001000000000000000020816681712,50,0.05
327,327_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,3.000000000000000000000000000000,4572,256,0.998999999999999999111821580300,50,0.025
328,328_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,2.000000000000000000000000000000,2546,295,0.998999999999999999111821580300,1,0.1
329,329_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,2901,0.998999999999999999111821580300,1,0.005
330,330_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,3111,0.001000000000000000020816681712,50,0.025
331,331_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,3690,0.001000000000000000020816681712,1,0.1
332,332_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,5000,0.001000000000000000020816681712,50,0.01
333,333_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,349,4592,0.998999999999999999111821580300,50,0.25
334,334_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,3.000000000000000000000000000000,4000,261,0.998999999999999999111821580300,1,0.1
335,335_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1768,4355,0.998999999999999999111821580300,50,0.01
336,336_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2406,2238,0.998999999999999999111821580300,50,0.01
337,337_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,3990,0.998999999999999999111821580300,50,0.005
338,338_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,4821,0.998999999999999999111821580300,50,0.1
339,339_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,2.000000000000000000000000000000,3247,274,0.998999999999999999111821580300,50,0.025
340,340_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2693,3139,0.001000000000000000020816681712,1,0.025
341,341_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,1543,0.998999999999999999111821580300,50,0.25
342,342_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,4233,2977,0.998999999999999999111821580300,1,0.25
343,343_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2146,3248,0.998999999999999999111821580300,50,0.025
344,344_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,2675,289,0.998999999999999999111821580300,1,0.1
345,345_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,4.000000000000000000000000000000,5000,156,0.998999999999999999111821580300,50,0.025
346,346_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,3183,1421,0.998999999999999999111821580300,50,0.025
347,347_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,4557,2916,0.001000000000000000020816681712,1,0.25
348,348_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2484,2507,0.998999999999999999111821580300,50,0.1
349,349_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,2178,0.001000000000000000020816681712,50,0.25
350,350_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,2.000000000000000000000000000000,1960,301,0.998999999999999999111821580300,1,0.1
351,351_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,5000,0.001000000000000000020816681712,1,0.025
352,352_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2475,1250,0.998999999999999999111821580300,1,0.005
353,353_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,5.000000000000000000000000000000,5000,153,0.998999999999999999111821580300,1,0.025
354,354_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,2432,0.001000000000000000020816681712,50,0.05
355,355_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,3.000000000000000000000000000000,4386,242,0.998999999999999999111821580300,50,0.1
356,356_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,4351,0.998999999999999999111821580300,1,0.025
357,357_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,4413,0.001000000000000000020816681712,50,0.25
358,358_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,4794,0.001000000000000000020816681712,1,0.025
359,359_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,1708,0.001000000000000000020816681712,1,0.005
360,360_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,515,314,0.998999999999999999111821580300,1,0.1
361,361_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,2559,0.998999999999999999111821580300,50,0.25
362,362_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,2572,0.001000000000000000020816681712,1,0.01
363,363_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,310,4248,0.001000000000000000020816681712,50,0.025
364,364_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,3868,0.998999999999999999111821580300,50,0.01
365,365_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,699,5000,0.001000000000000000020816681712,1,0.005
366,366_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3099,4888,0.001000000000000000020816681712,1,0.25
367,367_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,2605,0.001000000000000000020816681712,1,0.001
368,368_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,4030,4095,0.001000000000000000020816681712,1,0.1
369,369_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,4028,0.001000000000000000020816681712,50,0.1
370,370_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,3514,0.998999999999999999111821580300,50,0.005
371,371_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,2480,0.998999999999999999111821580300,1,0.01
372,372_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,5000,0.001000000000000000020816681712,50,0.05
373,373_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,2211,0.001000000000000000020816681712,50,0.1
374,374_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,5.000000000000000000000000000000,5000,152,0.998999999999999999111821580300,50,0.1
375,375_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,3189,0.001000000000000000020816681712,1,0.1
376,376_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,3371,0.001000000000000000020816681712,50,0.025
377,377_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,4806,0.001000000000000000020816681712,1,0.1
378,378_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,3457,0.001000000000000000020816681712,1,0.025
379,379_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,1,701,0.998999999999999999111821580300,1,0.1
380,380_0,FAILED,BoTorch,BOTORCH_MODULAR,,,5000,1,0.171904685010606406159183734417,50,0.025
381,381_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,2925,0.998999999999999999111821580300,1,0.025
382,382_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,4831,0.998999999999999999111821580300,1,0.005
383,383_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,274,4430,0.001000000000000000020816681712,50,0.025
384,384_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,4203,3949,0.001000000000000000020816681712,50,0.25
385,385_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,4542,3346,0.998999999999999999111821580300,1,0.1
386,386_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,1,1178,0.998999999999999999111821580300,1,0.05
387,387_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,3367,0.998999999999999999111821580300,1,0.05
388,388_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1805,4380,0.998999999999999999111821580300,50,0.05
389,389_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,4588,2415,0.998999999999999999111821580300,1,0.025
390,390_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,729,310,0.998999999999999999111821580300,50,0.001
391,391_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1575,4908,0.001000000000000000020816681712,1,0.25
392,392_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,2.000000000000000000000000000000,1438,304,0.998999999999999999111821580300,50,0.1
393,393_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,3.000000000000000000000000000000,1777,278,0.998999999999999999111821580300,50,0.1
394,394_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1316,1849,0.998999999999999999111821580300,1,0.1
395,395_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,3.000000000000000000000000000000,4552,242,0.998999999999999999111821580300,50,0.025
396,396_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,38,5000,0.998999999999999999111821580300,1,0.01
397,397_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,3.000000000000000000000000000000,4811,277,0.998999999999999999111821580300,1,0.005
398,398_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1322,2459,0.998999999999999999111821580300,1,0.1
399,399_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3701,4570,0.001000000000000000020816681712,1,0.025
400,400_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1783,1640,0.998999999999999999111821580300,1,0.005
401,401_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,5000,0.001000000000000000020816681712,50,0.025
402,402_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3617,3302,0.001000000000000000020816681712,50,0.01
403,403_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,3574,0.998999999999999999111821580300,1,0.005
404,404_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1628,3057,0.998999999999999999111821580300,1,0.005
405,405_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,2.000000000000000000000000000000,1149,301,0.998999999999999999111821580300,1,0.025
406,406_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3573,3751,0.001000000000000000020816681712,1,0.005
407,407_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,1,321,0.998999999999999999111821580300,50,0.1
408,408_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3700,1798,0.998999999999999999111821580300,50,0.005
409,409_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2975,3889,0.998999999999999999111821580300,1,0.005
410,410_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,2905,0.001000000000000000020816681712,50,0.005
411,411_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,4375,0.001000000000000000020816681712,50,0.005
412,412_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,1525,284,0.998999999999999999111821580300,1,0.1
413,413_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,952,636,0.998999999999999999111821580300,1,0.1
414,414_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3791,2521,0.001000000000000000020816681712,1,0.25
415,415_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2411,5000,0.001000000000000000020816681712,1,0.005
416,416_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3975,2919,0.001000000000000000020816681712,1,0.1
417,417_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3367,1300,0.998999999999999999111821580300,1,0.005
418,418_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,1,317,0.998999999999999999111821580300,1,0.05
419,419_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,246,320,0.998999999999999999111821580300,50,0.05
420,420_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,3889,290,0.998999999999999999111821580300,50,0.025
421,421_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1072,2131,0.998999999999999999111821580300,1,0.005
422,422_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,3803,1327,0.998999999999999999111821580300,1,0.1
423,423_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2378,2227,0.998999999999999999111821580300,50,0.1
424,424_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2440,4689,0.001000000000000000020816681712,50,0.05
425,425_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,947,644,0.998999999999999999111821580300,1,0.025
426,426_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1495,3957,0.001000000000000000020816681712,50,0.01
427,427_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,4992,1867,0.998999999999999999111821580300,1,0.001
428,428_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,70,2243,0.001000000000000000020816681712,1,0.25
429,429_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,3.000000000000000000000000000000,1627,282,0.998999999999999999111821580300,50,0.025
430,430_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,1094,336,0.998999999999999999111821580300,1,0.005
431,431_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,4050,1254,0.998999999999999999111821580300,50,0.1
432,432_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3359,2485,0.001000000000000000020816681712,50,0.001
433,433_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,630,3356,0.998999999999999999111821580300,1,0.025
434,434_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,877,339,0.998999999999999999111821580300,1,0.05
435,435_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,914,3950,0.998999999999999999111821580300,1,0.1
436,436_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3915,4761,0.001000000000000000020816681712,1,0.1
437,437_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1261,4275,0.998999999999999999111821580300,50,0.1
438,438_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,1184,1350,0.001000000000000000020816681712,1,0.001
439,439_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,645,1299,0.001000000000000000020816681712,1,0.005
440,440_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3489,3112,0.998999999999999999111821580300,50,0.1
441,441_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3791,4797,0.998999999999999999111821580300,50,0.025
442,442_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,813,304,0.998999999999999999111821580300,50,0.025
443,443_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,4579,2543,0.998999999999999999111821580300,50,0.05
444,444_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3296,3480,0.001000000000000000020816681712,1,0.001
445,445_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,922,1962,0.998999999999999999111821580300,50,0.25
446,446_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,957,604,0.998999999999999999111821580300,1,0.025
447,447_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3732,4270,0.998999999999999999111821580300,50,0.005
448,448_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,3.000000000000000000000000000000,4222,283,0.998999999999999999111821580300,50,0.1
449,449_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3982,3707,0.001000000000000000020816681712,1,0.1
450,450_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2788,2917,0.001000000000000000020816681712,50,0.1
451,451_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2572,4355,0.998999999999999999111821580300,50,0.1
452,452_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1074,5000,0.998999999999999999111821580300,50,0.001
453,453_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1122,4575,0.001000000000000000020816681712,1,0.1
454,454_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,2527,0.998999999999999999111821580300,1,0.1
455,455_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1591,4690,0.001000000000000000020816681712,50,0.025
456,456_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,7.000000000000000000000000000000,4899,94,0.998999999999999999111821580300,50,0.025
457,457_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,1333,1313,0.998999999999999999111821580300,50,0.05
458,458_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,4357,4234,0.998999999999999999111821580300,17,0.25
459,459_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,4022,2148,0.001000000000000000020816681712,50,0.001
460,460_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,1801,0.998999999999999999111821580300,50,0.001
461,461_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,1022,593,0.998999999999999999111821580300,1,0.1
462,462_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,3.000000000000000000000000000000,3848,248,0.998999999999999999111821580300,1,0.025
463,463_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,758,3005,0.001000000000000000020816681712,50,0.01
464,464_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.579999999999999960031971113494,4.000000000000000000000000000000,4882,187,0.998999999999999999111821580300,50,0.025
465,465_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1082,4120,0.998999999999999999111821580300,1,0.01
466,466_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2989,3239,0.998999999999999999111821580300,1,0.1
467,467_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,1074,337,0.998999999999999999111821580300,1,0.25
468,468_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,3735,1226,0.998999999999999999111821580300,50,0.25
469,469_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1299,2328,0.001000000000000000020816681712,1,0.005
470,470_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,874,4898,0.998999999999999999111821580300,50,0.025
471,471_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,970,556,0.998999999999999999111821580300,1,0.025
472,472_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,3.000000000000000000000000000000,4344,286,0.998999999999999999111821580300,50,0.025
473,473_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,2120,0.998999999999999999111821580300,1,0.1
474,474_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3432,2679,0.001000000000000000020816681712,50,0.01
475,475_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,3287,1212,0.998999999999999999111821580300,50,0.025
476,476_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,4967,1675,0.998999999999999999111821580300,1,0.005
477,477_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,1063,336,0.998999999999999999111821580300,1,0.025
478,478_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,3.000000000000000000000000000000,1740,273,0.998999999999999999111821580300,50,0.1
479,479_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1331,4900,0.998999999999999999111821580300,50,0.005
480,480_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1062,4136,0.998999999999999999111821580300,1,0.025
481,481_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,1014,337,0.998999999999999999111821580300,1,0.05
482,482_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,953,349,0.998999999999999999111821580300,1,0.005
483,483_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1801,2937,0.001000000000000000020816681712,1,0.1
484,484_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,4042,2219,0.001000000000000000020816681712,1,0.1
485,485_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,3.000000000000000000000000000000,1696,277,0.998999999999999999111821580300,1,0.1
486,486_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1881,1669,0.001000000000000000020816681712,1,0.1
487,487_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,3.000000000000000000000000000000,4537,282,0.998999999999999999111821580300,50,0.025
488,488_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,1046,345,0.998999999999999999111821580300,50,0.025
489,489_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1004,2558,0.001000000000000000020816681712,50,0.01
490,490_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,984,554,0.998999999999999999111821580300,50,0.1
491,491_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3254,3337,0.001000000000000000020816681712,50,0.025
492,492_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3872,3959,0.998999999999999999111821580300,1,0.25
493,493_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,984,342,0.998999999999999999111821580300,50,0.01
494,494_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,5000,1983,0.001000000000000000020816681712,50,0.1
495,495_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3342,4327,0.001000000000000000020816681712,1,0.25
496,496_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,771,348,0.998999999999999999111821580300,1,0.005
497,497_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,772,354,0.998999999999999999111821580300,1,0.001
498,498_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1664,3567,0.001000000000000000020816681712,50,0.005
499,499_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2903,5000,0.001000000000000000020816681712,50,0.025
500,500_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3824,3918,0.001000000000000000020816681712,1,0.1
501,501_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,4081,2818,0.001000000000000000020816681712,1,0.001
502,502_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3883,3561,0.001000000000000000020816681712,1,0.25
503,503_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,3.000000000000000000000000000000,4445,270,0.998999999999999999111821580300,50,0.025
504,504_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,1,332,0.998999999999999999111821580300,50,0.005
505,505_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,959,3070,0.001000000000000000020816681712,1,0.25
506,506_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,760,347,0.998999999999999999111821580300,1,0.25
507,507_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,920,513,0.998999999999999999111821580300,50,0.1
508,508_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,975,1242,0.001000000000000000020816681712,1,0.25
509,509_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1006,3841,0.001000000000000000020816681712,50,0.1
510,510_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,4441,0.998999999999999999111821580300,50,0.25
511,511_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3428,4509,0.001000000000000000020816681712,50,0.01
512,512_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,3745,261,0.998999999999999999111821580300,1,0.025
513,513_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,320,386,0.998999999999999999111821580300,1,0.025
514,514_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,1.000000000000000000000000000000,435,388,0.998999999999999999111821580300,1,0.025
515,515_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3844,5000,0.001000000000000000020816681712,50,0.1
516,516_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1804,4573,0.001000000000000000020816681712,1,0.025
517,517_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,4311,4321,0.998999999999999999111821580300,1,0.05
518,518_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3547,1719,0.998999999999999999111821580300,1,0.01
519,519_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1108,3491,0.998999999999999999111821580300,1,0.005
520,520_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1213,3568,0.001000000000000000020816681712,50,0.25
521,521_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,1584,285,0.998999999999999999111821580300,1,0.025
522,522_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,2130,3361,0.001000000000000000020816681712,1,0.1
523,523_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,4.000000000000000000000000000000,4956,193,0.998999999999999999111821580300,1,0.1
524,524_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,2741,1251,0.998999999999999999111821580300,50,0.01
525,525_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,1.000000000000000000000000000000,1,338,0.998999999999999999111821580300,1,0.025
526,526_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3020,2504,0.001000000000000000020816681712,1,0.025
527,527_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1078,5000,0.001000000000000000020816681712,50,0.1
528,528_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1534,2213,0.998999999999999999111821580300,50,0.05
529,529_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,3642,2254,0.001000000000000000020816681712,1,0.25
530,530_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1322,4562,0.998999999999999999111821580300,1,0.05
531,531_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,1,1129,0.001000000000000000020816681712,1,0.005
532,532_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,3.000000000000000000000000000000,4584,261,0.998999999999999999111821580300,50,0.025
533,533_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,2.000000000000000000000000000000,867,351,0.998999999999999999111821580300,1,0.025
534,534_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,2.000000000000000000000000000000,3351,280,0.998999999999999999111821580300,1,0.05
535,535_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,0.000000000000000000000000000000,4103,4223,0.001000000000000000020816681712,50,0.025
536,536_0,RUNNING,BoTorch,BOTORCH_MODULAR,,,1280,3744,0.998999999999999999111821580300,1,0.01
</pre>
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			<h1>&nbsp;Errors</h1>
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<pre id='simple_pre_tab_tab_errors'><span style="background-color: black; color: white">
/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CSDDM_OutdoorObjects_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4903881/4903881_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CSDDM_OutdoorObjects_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4941826/4941826_0_log.err not found

</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>50000                                                                                                                               </td></tr><tr><td> run_program</td><td>None                                                                                                                                </td></tr><tr><td> experiment_name</td><td>None                                                                                                                                </td></tr><tr><td> mem_gb</td><td>32                                                                                                                                  </td></tr><tr><td> parameter</td><td>None                                                                                                                                </td></tr><tr><td> continue_previous_job</td><td>/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CSDDM_OutdoorObjects_HoeffdingTreeClassifier_ACCURACY-RUNTIME/0/ </td></tr><tr><td> experiment_constraints</td><td>None                                                                                                                                </td></tr><tr><td> run_dir</td><td>runs                                                                                                                                </td></tr><tr><td> seed</td><td>None                                                                                                                                </td></tr><tr><td> decimalrounding</td><td>4                                                                                                                                   </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>None                                                                                                                                </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>False                                                                                                                               </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>10                                                                                                                                  </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> occ_type</td><td>euclid                                                                                                                              </td></tr><tr><td> result_names</td><td>[&#039;RESULT=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>False                                                                                                                               </td></tr><tr><td> revert_to_random_when_seemingly_exhausted</td><td>True                                                                                                                                </td></tr><tr><td> load_data_from_existing_jobs</td><td>[]                                                                                                                                  </td></tr><tr><td> n_estimators_randomforest</td><td>100                                                                                                                                 </td></tr><tr><td> external_generator</td><td>None                                                                                                                                </td></tr><tr><td> username</td><td>None                                                                                                                                </td></tr><tr><td> max_failed_jobs</td><td>None                                                                                                                                </td></tr><tr><td> num_parallel_jobs</td><td>20                                                                                                                                  </td></tr><tr><td> worker_timeout</td><td>120                                                                                                                                 </td></tr><tr><td> slurm_use_srun</td><td>False                                                                                                                               </td></tr><tr><td> time</td><td></td></tr><tr><td> partition</td><td></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">1746192490.4836555,20,0,0
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1746666240.4333248,20,1,5
1746666242.6108825,20,2,10
1746666244.8139954,20,2,10
1746666256.482221,20,1,5
1746666256.6523051,20,1,5
1746671190.329715,20,1,5
1746671191.3456836,20,1,5
1746671193.584829,20,2,10
1746671195.4965696,20,2,10
1746671209.066795,20,1,5
1746671209.2072494,20,1,5
1746677252.8157277,20,1,5
1746677253.7952354,20,1,5
1746677255.6887774,20,2,10
1746677257.5347478,20,2,10
1746677269.5861297,20,1,5
1746677269.7451284,20,1,5
1746681119.9533064,20,1,5
1746681120.7542763,20,1,5
1746681122.6347153,20,2,10
1746681124.5105257,20,2,10
1746681137.9086583,20,1,5
1746681138.0113952,20,1,5
1746684780.9119344,20,1,5
1746684781.663028,20,1,5
1746684783.7304251,20,2,10
1746684785.5949793,20,2,10
1746684799.1544778,20,1,5
1746684799.2938411,20,1,5
1746687787.7147212,20,1,5
1746687788.3694565,20,1,5
1746687790.412409,20,2,10
1746687791.779882,20,2,10
1746687802.7649684,20,1,5
1746687803.0297759,20,1,5
1746687813.1724412,20,1,5
1746687825.521603,20,1,5
1746687831.8414187,20,1,5
1746687839.756938,20,0,0
1746687848.2717738,20,0,0
1746690186.4682539,20,0,0
1746690187.0144672,20,0,0
1746690188.8104475,20,1,5
1746690196.0804121,20,1,5
1746693510.147389,20,1,5
1746693510.6887147,20,1,5
1746693512.3687098,20,2,10
1746693513.5475862,20,2,10
1746693525.4315772,20,1,5
1746693525.5360906,20,1,5
1746695968.270252,20,1,5
1746695968.9077258,20,1,5
1746695970.6186318,20,2,10
1746695972.1022813,20,2,10
1746695983.225373,20,1,5
1746695983.3417833,20,1,5
1746700163.4703603,20,1,5
1746700164.4218557,20,1,5
1746700166.5581634,20,2,10
1746700168.3789868,20,2,10
1746700182.266332,20,1,5
1746700182.426148,20,1,5
1746704945.5488806,20,1,5
1746704946.3851855,20,1,5
1746704948.5009944,20,2,10
1746704950.3147814,20,2,10
1746704963.3432114,20,1,5
1746704963.4940946,20,1,5
1746709604.3728251,20,1,5
1746709605.4459975,20,1,5
1746709607.5868993,20,2,10
1746709609.4417353,20,2,10
1746709623.4371479,20,1,5
1746709623.5970178,20,1,5
1746714290.6923876,20,1,5
1746714291.3631256,20,1,5
1746714294.2628496,20,2,10
1746714295.7156117,20,2,10
1746714307.2941325,20,1,5
1746714307.6672554,20,1,5
1746715696.729906,20,1,5
1746715697.5284913,20,1,5
1746715699.5636246,20,2,10
1746715701.3681767,20,2,10
1746715715.9015772,20,1,5
1746715716.0378027,20,1,5
1746720221.2869084,20,1,5
1746720222.2673044,20,1,5
1746720224.541807,20,2,10
1746720226.5098593,20,2,10
1746720240.3929734,20,1,5
1746720240.504515,20,1,5
1746724540.9959452,20,1,5
1746724541.8189805,20,1,5
1746724543.7579503,20,2,10
1746724545.6958928,20,2,10
1746724571.111709,20,1,5
1746724571.3470802,20,1,5
1746727873.4907346,20,1,5
1746727874.311768,20,1,5
1746727876.5160854,20,2,10
1746727878.4685993,20,2,10
1746727892.6458087,20,1,5
1746727892.929957,20,1,5
1746730122.9924662,20,1,5
1746730123.7258956,20,1,5
1746730125.318943,20,2,10
1746730126.6108084,20,2,10
1746730137.7170749,20,1,5
1746730137.8406117,20,1,5
1746733966.6109061,20,1,5
1746733967.2787583,20,1,5
1746733969.3746562,20,2,10
1746733970.478386,20,2,10
1746733982.3943875,20,1,5
1746733982.479896,20,1,5
1746736583.3325589,20,1,5
1746736583.8895197,20,1,5
1746736585.350726,20,2,10
1746736585.838051,20,2,10
1746736596.2762535,20,1,5
1746736596.330384,20,1,5
1746741004.2938406,20,1,5
1746741004.9962273,20,1,5
1746741006.6885986,20,2,10
1746741008.1510963,20,2,10
1746741021.0803416,20,1,5
1746741021.1971703,20,1,5
1746743697.7302084,20,1,5
1746743698.3369684,20,1,5
1746743700.3707335,20,2,10
1746743701.8062465,20,2,10
1746743714.306335,20,1,5
1746743714.4541821,20,1,5
1746746826.4798849,20,1,5
1746746827.343882,20,1,5
1746746829.4947143,20,2,10
1746746831.1000564,20,2,10
1746746842.8809578,20,1,5
1746746843.0137002,20,1,5
1746751160.5124083,20,1,5
1746751161.4651387,20,1,5
1746751163.5783925,20,2,10
1746751165.595565,20,2,10
1746751179.6149716,20,1,5
1746751179.7702816,20,1,5
1746756499.0749235,20,1,5
1746756499.8555472,20,1,5
1746756501.7821882,20,2,10
1746756503.5754404,20,2,10
1746756517.8421433,20,1,5
1746756517.9783266,20,1,5
1746762248.8313177,20,1,5
1746762249.6684659,20,1,5
1746762251.7332222,20,2,10
1746762253.6198263,20,2,10
1746762267.78835,20,1,5
1746762268.2196927,20,1,5
</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
1746192490,610.47265625,38.7
1746192490,608.30859375,38.1
1746192490,608.30859375,38.3
1746192490,608.30859375,40.4
1746192490,608.30859375,40.0
1746192490,608.30859375,39.3
1746192490,608.30859375,39.6
1746199479,712.484375,42.9
1746199479,712.484375,41.2
1746199479,712.484375,40.3
1746199479,712.484375,37.8
1746204672,733.95703125,39.0
1746204672,733.95703125,40.4
1746204672,733.95703125,40.6
1746204672,733.95703125,43.7
1746210353,756.45703125,33.0
1746210353,756.45703125,29.6
1746210353,756.45703125,29.2
1746210353,756.45703125,30.6
1746214671,724.79296875,24.0
1746214671,724.79296875,21.4
1746214671,724.79296875,21.7
1746214671,724.79296875,27.5
1746220516,742.375,18.3
1746220516,742.375,15.7
1746220516,742.375,15.5
1746220516,742.375,18.0
1746226277,754.18359375,14.9
1746226277,754.18359375,14.0
1746226277,754.18359375,13.2
1746226277,754.18359375,15.4
1746236073,759.37890625,15.8
1746236073,759.37890625,15.5
1746236074,759.37890625,15.3
1746236074,759.37890625,17.9
1746245191,870.578125,15.0
1746245191,870.578125,17.2
1746245191,870.578125,16.4
1746245191,870.578125,14.5
1746258346,809.375,16.0
1746258346,809.375,16.9
1746258346,809.375,16.4
1746258346,809.375,16.7
1746269374,834.8125,15.2
1746269374,834.8125,15.7
1746269374,834.8125,15.6
1746269374,834.8125,17.8
1746284608,856.6796875,16.4
1746284609,856.6796875,15.6
1746284609,856.6796875,15.9
1746284609,856.6796875,17.4
1746301382,856.37890625,15.6
1746301382,856.37890625,15.2
1746301382,856.37890625,14.6
1746301382,856.37890625,18.6
1746321304,888.94140625,15.7
1746321304,888.94140625,16.0
1746321304,888.94140625,15.0
1746321304,888.94140625,16.3
1746346358,864.35546875,15.7
1746346358,864.35546875,14.9
1746346358,864.35546875,15.1
1746346358,864.35546875,10.3
1746374834,948.2890625,18.5
1746374834,948.2890625,17.8
1746374834,948.2890625,17.2
1746374834,948.2890625,17.4
1746411276,882.234375,18.0
1746411276,882.234375,14.2
1746411276,882.234375,14.0
1746411276,882.234375,12.2
1746454346,903.0234375,15.8
1746454346,903.0234375,14.4
1746454346,903.0234375,14.1
1746454346,903.0234375,14.3
1746503456,906.79296875,16.0
1746503456,906.79296875,13.9
1746503456,906.79296875,13.5
1746503456,906.79296875,11.8
1746554475,931.94921875,15.9
1746554475,931.94921875,14.9
1746554475,931.94921875,15.5
1746554475,931.94921875,15.6
1746613597,946.296875,15.8
1746613597,946.296875,15.8
1746613597,946.296875,15.7
1746613597,946.296875,13.6
1746687812,957.00390625,22.0
1746687812,957.00390625,21.6
1746687812,957.00390625,21.2
1746687812,957.00390625,24.6
1746762277,999.28125,18.6
1746762277,999.28125,15.9
1746762277,999.28125,16.4
1746762277,999.28125,18.7
</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>
			<h1>&nbsp;Evolution</h1>
			<div class="invert_in_dark_mode" id="plotResultEvolution"></div>
			<h1>&nbsp;Exit-Codes</h1>
			<div class="invert_in_dark_mode" id="plotExitCodesPieChart"></div>
	</body>
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