start_time,end_time,run_time,program_string,recent_samples_size,n_reference_samples,recent_samples_proportion,threshold,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
1742404941,1742404954,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2064 n_reference_samples 152 recent_samples_proportion 0.5184078693389893 threshold 0.6554412364959716,2064,152,0.5184078693389893,0.6554412364959716,0.7363079398477629,2.183224678039551,0,None,i7119,2.183224678039551,525.50390625,525.15234375,-1,0,3299389
1742404974,1742404993,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1604 n_reference_samples 302 recent_samples_proportion 0.8769342464394867 threshold 0.6499908466823399,1604,302,0.8769342464394867,0.6499908466823399,0.7455288074757102,8.687381505966187,0,None,i7183,8.687381505966187,524.828125,524.4713541666666,-1,0,3299439
1742404974,1742404993,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 687 n_reference_samples 167 recent_samples_proportion 0.30379135590046646 threshold 0.7314148671925068,687,167,0.30379135590046646,0.7314148671925068,0.7437960269818676,9.968394041061401,0,None,i7018,9.968394041061401,525.37109375,525.0247395833334,-1,0,3299485
1742405005,1742405024,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3236 n_reference_samples 486 recent_samples_proportion 0.6134259903803467 threshold 0.5728207836858928,3236,486,0.6134259903803467,0.5728207836858928,0.7433009468407699,6.435246467590332,0,None,i7079,6.435246467590332,524.54296875,524.1861979166666,-1,0,3299519
1742405036,1742405049,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 477 n_reference_samples 423 recent_samples_proportion 0.41493000239133837 threshold 0.7954260398633779,477,423,0.41493000239133837,0.7954260398633779,0.7272727272727273,1.7258472442626953,0,None,i7025,1.7258472442626953,524.19140625,523.875,-1,0,3299597
1742405036,1742405067,31,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3931 n_reference_samples 221 recent_samples_proportion 0.9522322613745928 threshold 0.5085070656612516,3931,221,0.9522322613745928,0.5085070656612516,0.7392165356767126,22.193288564682007,0,None,i7121,22.193288564682007,526.54296875,523.69296875,-1,0,3299564
1742405098,1742405117,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2858 n_reference_samples 354 recent_samples_proportion 0.18218690669164062 threshold 0.7223872582428158,2858,354,0.18218690669164062,0.7223872582428158,0.7467046228108175,6.031735420227051,0,None,i7077,6.031735420227051,525.23828125,524.890625,-1,0,3299688
1742405067,1742405118,51,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1307 n_reference_samples 95 recent_samples_proportion 0.7631005900911987 threshold 0.5827617563307286,1307,95,0.7631005900911987,0.5827617563307286,0.7307382882604122,37.955897092819214,0,None,i7025,37.955897092819214,534.140625,526.5592447916666,-1,0,3299652
1742405099,1742405118,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2547 n_reference_samples 203 recent_samples_proportion 0.70756448013708 threshold 0.7699976408854128,2547,203,0.70756448013708,0.7699976408854128,0.7451574973698868,6.62424635887146,0,None,i7022,6.62424635887146,512.28125,511.9296875,-1,0,3299708
1742405126,1742405145,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1121 n_reference_samples 448 recent_samples_proportion 0.12521828254684805 threshold 0.5342740979976952,1121,448,0.12521828254684805,0.5342740979976952,0.7441673370876911,7.300962209701538,0,None,i7127,7.300962209701538,524.78515625,524.4205729166666,-1,0,3299737
1742405146,1742405159,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 173 n_reference_samples 134 recent_samples_proportion 0.8950439240783453 threshold 0.6965457499027252,173,134,0.8950439240783453,0.6965457499027252,0.7466427377931802,4.00784158706665,0,None,i7119,4.00784158706665,525.26171875,524.9114583333334,-1,0,3299776
1742405161,1742405187,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3750 n_reference_samples 323 recent_samples_proportion 0.3596136324107647 threshold 0.6088503899984061,3750,323,0.3596136324107647,0.6088503899984061,0.7444767621758772,13.332512140274048,0,None,i7040,13.332512140274048,524.015625,523.7578125,-1,0,3299803
1742405193,1742405212,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 992 n_reference_samples 376 recent_samples_proportion 0.5579988854005933 threshold 0.6861520287580789,992,376,0.5579988854005933,0.6861520287580789,0.7437341419642305,5.912884712219238,0,None,i7049,5.912884712219238,525.3515625,525.0143229166666,-1,0,3299856
1742405224,1742405237,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2375 n_reference_samples 391 recent_samples_proportion 0.819636904168874 threshold 0.7613485547713936,2375,391,0.819636904168874,0.7613485547713936,0.7343895043010087,1.3889381885528564,0,None,i7018,1.3889381885528564,524.80078125,524.4518229166666,-1,0,3299910
1742405192,1742405249,57,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3416 n_reference_samples 71 recent_samples_proportion 0.24671372678130865 threshold 0.6189599031582474,3416,71,0.24671372678130865,0.6189599031582474,0.7203416052973575,45.14087748527527,0,None,i7146,45.14087748527527,541.49609375,530.55078125,-1,0,3299830
1742405224,1742405257,33,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1790 n_reference_samples 255 recent_samples_proportion 0.4632005051709712 threshold 0.5426217764616013,1790,255,0.4632005051709712,0.5426217764616013,0.7397735008354477,22.39714789390564,0,None,i7151,22.39714789390564,525.6484375,524.28046875,-1,0,3299876
1742405255,1742405268,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1960 n_reference_samples 403 recent_samples_proportion 0.6726346949115396 threshold 0.7065900412388146,1960,403,0.6726346949115396,0.7065900412388146,0.7372362151123213,4.158936977386475,0,None,i7039,4.158936977386475,526.09375,525.7578125,-1,0,3299964
1742405255,1742405275,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2388 n_reference_samples 271 recent_samples_proportion 0.13203654419630767 threshold 0.5879678810015321,2388,271,0.13203654419630767,0.5879678810015321,0.7489324834457578,4.514317750930786,0,None,i7121,4.514317750930786,524.21875,523.8671875,-1,0,3299937
1742405287,1742405300,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3340 n_reference_samples 360 recent_samples_proportion 0.9299873885698616 threshold 0.7831164064817131,3340,360,0.9299873885698616,0.7831164064817131,0.7363079398477629,1.9707660675048828,0,None,i7015,1.9707660675048828,525.69140625,525.3763020833334,-1,0,3300033
1742405287,1742405331,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 761 n_reference_samples 59 recent_samples_proportion 0.352809050027281 threshold 0.5126574695110321,761,59,0.352809050027281,0.5126574695110321,0.729067392784207,32.8371148109436,0,None,i7121,32.8371148109436,534.6796875,528.390625,-1,0,3299993
1742405318,1742405332,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 93 n_reference_samples 310 recent_samples_proportion 0.23903009062632918 threshold 0.5605553743429482,93,310,0.23903009062632918,0.5605553743429482,0.7314190234544217,2.0448203086853027,0,None,i7015,2.0448203086853027,525.19921875,524.8658854166666,-1,0,3300088
1742405349,1742405362,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2721 n_reference_samples 464 recent_samples_proportion 0.47089792788028717 threshold 0.6341131064109504,2721,464,0.47089792788028717,0.6341131064109504,0.7482517482517482,4.048747539520264,0,None,i7025,4.048747539520264,524.98828125,524.6666666666666,-1,0,3300137
1742405348,1742405374,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1138 n_reference_samples 215 recent_samples_proportion 0.78382846750319 threshold 0.6607476562261582,1138,215,0.78382846750319,0.6607476562261582,0.7421870165232997,12.45731496810913,0,None,i7092,12.45731496810913,525.1171875,524.8671875,-1,0,3300114
1742405386,1742405399,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 277 n_reference_samples 233 recent_samples_proportion 0.649234467279166 threshold 0.6219315655529499,277,233,0.649234467279166,0.6219315655529499,0.7479423231635621,3.4459495544433594,0,None,i7130,3.4459495544433594,524.37109375,524.0169270833334,-1,0,3300194
1742405380,1742405399,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1446 n_reference_samples 342 recent_samples_proportion 0.5260915733873844 threshold 0.7467300792224706,1446,342,0.5260915733873844,0.7467300792224706,0.743610371928956,4.816474676132202,0,None,i7049,4.816474676132202,524.12890625,523.78515625,-1,0,3300180
1742405380,1742405418,38,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2903 n_reference_samples 79 recent_samples_proportion 0.8411120902746916 threshold 0.5490066425874829,2903,79,0.8411120902746916,0.5490066425874829,0.7310477133485983,25.862130165100098,0,None,i7099,25.862130165100098,532.90625,527.23203125,-1,0,3300165
1742405411,1742405424,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 576 n_reference_samples 498 recent_samples_proportion 0.9871620063669979 threshold 0.5954245497472584,576,498,0.9871620063669979,0.5954245497472584,0.7457144625286218,3.154695749282837,0,None,i7039,3.154695749282837,525.18359375,524.8411458333334,-1,0,3300231
1742405412,1742405431,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3823 n_reference_samples 439 recent_samples_proportion 0.2960939734242857 threshold 0.672663653921336,3823,439,0.2960939734242857,0.672663653921336,0.7471997029519153,10.086159706115723,0,None,i7133,10.086159706115723,524.16796875,523.8955078125,-1,0,3300205
1742405411,1742405437,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3032 n_reference_samples 183 recent_samples_proportion 0.40811170050874357 threshold 0.6994723724201322,3032,183,0.40811170050874357,0.6994723724201322,0.7410730862058296,13.642836093902588,0,None,i7088,13.642836093902588,524.875,524.6123046875,-1,0,3300218
1742405390,1742405531,141,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3515 n_reference_samples 118 recent_samples_proportion 0.5938211086206139 threshold 0.7355019206181169,3515,118,0.5938211086206139,0.7355019206181169,0.7330280339129897,73.84028887748718,0,None,i7089,73.84028887748718,533.15625,527.6875,-1,0,3300066
1742406586,1742406605,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2445 n_reference_samples 218 recent_samples_proportion 0.1 threshold 0.6674146268089677,2445,218,0.1,0.6674146268089677,0.7457144625286218,5.551334619522095,0,None,i7128,5.551334619522095,523.1484375,522.6940104166666,-1,0,3309521
1742406586,1742406605,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2605 n_reference_samples 239 recent_samples_proportion 0.1155065599954148 threshold 0.6446311272108849,2605,239,0.1155065599954148,0.6446311272108849,0.7468283928460919,7.96999454498291,0,None,i7140,7.96999454498291,526.1015625,525.7682291666666,-1,0,3309504
1742406589,1742406608,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2707 n_reference_samples 259 recent_samples_proportion 0.1 threshold 0.6331218991269842,2707,259,0.1,0.6331218991269842,0.7433628318584071,7.087778091430664,0,None,i7130,7.087778091430664,521.21875,520.8776041666666,-1,0,3309526
1742406591,1742406611,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2603 n_reference_samples 240 recent_samples_proportion 0.6810634012824138 threshold 0.6457457864287133,2603,240,0.6810634012824138,0.6457457864287133,0.7487468283928461,6.711926460266113,0,None,i7136,6.711926460266113,512.22265625,511.8802083333333,-1,0,3309513
1742406612,1742406625,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 10 n_reference_samples 315 recent_samples_proportion 0.14290196348232004 threshold 0.6983608002072669,10,315,0.14290196348232004,0.6983608002072669,0.720465375332632,1.2070462703704834,0,None,i7180,1.2070462703704834,525.2109375,524.828125,-1,0,3309532
1742406609,1742406628,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2715 n_reference_samples 257 recent_samples_proportion 1 threshold 0.63059383851544,2715,257,1,0.63059383851544,0.7456525775109846,5.931980609893799,0,None,i7145,5.931980609893799,525.6640625,525.3268229166666,-1,0,3309560
1742406609,1742406628,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2797 n_reference_samples 230 recent_samples_proportion 0.1 threshold 0.6094392028339851,2797,230,0.1,0.6094392028339851,0.7471378179342781,8.236652851104736,0,None,i7159,8.236652851104736,524.2578125,523.9283854166666,-1,0,3309541
1742406609,1742406628,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2511 n_reference_samples 256 recent_samples_proportion 0.1 threshold 0.683186750806578,2511,256,0.1,0.683186750806578,0.7483755182870228,5.543367385864258,0,None,i7117,5.543367385864258,525.43359375,525.0989583333334,-1,0,3309584
1742406616,1742406629,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 10 n_reference_samples 447 recent_samples_proportion 0.1 threshold 0.6181195591175385,10,447,0.1,0.6181195591175385,0.7228170060028467,0.9497056007385254,0,None,i7128,0.9497056007385254,517.55078125,517.2213541666666,-1,0,3309603
1742406629,1742406642,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 10 n_reference_samples 500 recent_samples_proportion 0.1 threshold 0.6605969228770929,10,500,0.1,0.6605969228770929,0.7146481836747324,1.0380525588989258,0,None,i7183,1.0380525588989258,525.62109375,525.26171875,-1,0,3309605
1742406656,1742406675,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 10 n_reference_samples 326 recent_samples_proportion 0.9207566628299415 threshold 0.7032847947608244,10,326,0.9207566628299415,0.7032847947608244,0.7348845844421066,1.090355396270752,0,None,i7133,1.090355396270752,526.6640625,525.9296875,-1,0,3309657
1742406659,1742406679,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1790 n_reference_samples 500 recent_samples_proportion 1 threshold 0.5892405492425556,1790,500,1,0.5892405492425556,0.7433628318584071,7.977913856506348,0,None,i7112,7.977913856506348,524.59765625,524.2526041666666,-1,0,3309677
1742406661,1742406681,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 10 n_reference_samples 284 recent_samples_proportion 0.6135400072378813 threshold 0.7308968820904225,10,284,0.6135400072378813,0.7308968820904225,0.7286960826783836,1.3051226139068604,0,None,i7094,1.3051226139068604,526.09375,525.7486979166666,-1,0,3309695
1742406656,1742406681,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1297 n_reference_samples 500 recent_samples_proportion 0.1832306602952891 threshold 0.6695265269368589,1297,500,0.1832306602952891,0.6695265269368589,0.7483136332693855,6.777904987335205,0,None,i7145,6.777904987335205,525.1328125,524.7825520833334,-1,0,3309637
1742406657,1742406683,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3207 n_reference_samples 500 recent_samples_proportion 1 threshold 0.8,3207,500,1,0.8,0.7338944241599109,1.5404186248779297,0,None,i7082,1.5404186248779297,524.859375,524.51953125,-1,0,3309712
1742406664,1742406684,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 10 n_reference_samples 205 recent_samples_proportion 1 threshold 0.7944923565112612,10,205,1,0.7944923565112612,0.721826845720651,1.2125580310821533,0,None,i7158,1.2125580310821533,525.71875,525.3046875,-1,0,3309622
1742406667,1742406686,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 10 n_reference_samples 492 recent_samples_proportion 0.1 threshold 0.5,10,492,0.1,0.5,0.7162571941333004,1.144540786743164,0,None,i7007,1.144540786743164,524.7109375,524.3502604166666,-1,0,3309799
1742406655,1742406693,38,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 10 n_reference_samples 431 recent_samples_proportion 1 threshold 0.5722955857677735,10,431,1,0.5722955857677735,0.7238071662850424,1.022796392440796,0,None,i7069,1.022796392440796,524.0078125,523.6640625,-1,0,3309729
1742406685,1742406698,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2198 n_reference_samples 221 recent_samples_proportion 0.1 threshold 0.7086487104850522,2198,221,0.1,0.7086487104850522,0.7451574973698868,2.942462205886841,0,None,i7021,2.942462205886841,523.7109375,523.3763020833334,-1,0,3309909
1742406685,1742406698,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 10 n_reference_samples 50 recent_samples_proportion 0.1 threshold 0.8,10,50,0.1,0.8,0.7292530478371186,3.6828131675720215,0,None,i7142,3.6828131675720215,525.98046875,525.6315104166666,-1,0,3309825
1742406685,1742406704,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2777 n_reference_samples 206 recent_samples_proportion 0.1 threshold 0.5897004226501164,2777,206,0.1,0.5897004226501164,0.7433628318584071,9.148422479629517,0,None,i7112,9.148422479629517,525.640625,519.8125,-1,0,3309839
1742406685,1742406704,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 10 n_reference_samples 424 recent_samples_proportion 1 threshold 0.5,10,424,1,0.5,0.7232502011263073,1.0180537700653076,0,None,i7068,1.0180537700653076,443.4140625,442.93359375,-1,0,3309871
1742406715,1742406728,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1742 n_reference_samples 500 recent_samples_proportion 1 threshold 0.8,1742,500,1,0.8,0.737978835323968,1.9358913898468018,0,None,i7144,1.9358913898468018,525.5703125,525.2096354166666,-1,0,3309961
1742406692,1742406731,39,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 10 n_reference_samples 323 recent_samples_proportion 0.1 threshold 0.8,10,323,0.1,0.8,0.715081378798193,1.5523357391357422,0,None,i7049,1.5523357391357422,379.9140625,379.0325520833333,-1,0,3309887
1742406686,1742406731,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2589 n_reference_samples 258 recent_samples_proportion 1 threshold 0.6787524210353338,2589,258,1,0.6787524210353338,0.7458382325638963,4.647129058837891,0,None,i7020,4.647129058837891,382.08984375,381.0065104166667,-1,0,3309785
1742406714,1742406734,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2200 n_reference_samples 272 recent_samples_proportion 0.1 threshold 0.6564630040132947,2200,272,0.1,0.6564630040132947,0.7466427377931802,3.4980239868164062,0,None,i7158,3.4980239868164062,526.0078125,525.6940104166666,-1,0,3309942
1742406718,1742406739,21,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2576 n_reference_samples 220 recent_samples_proportion 0.1 threshold 0.6424888818805148,2576,220,0.1,0.6424888818805148,0.7483136332693855,7.471195697784424,0,None,i7136,7.471195697784424,512.2578125,511.9049479166667,-1,0,3309978
1742406690,1742406743,53,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2717 n_reference_samples 256 recent_samples_proportion 0.4891126258632904 threshold 0.6323729175344419,2717,256,0.4891126258632904,0.6323729175344419,0.7433628318584071,7.715135097503662,0,None,i7090,7.715135097503662,509.984375,509.4544270833333,-1,0,3309862
1742406687,1742406796,109,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 10 n_reference_samples 254 recent_samples_proportion 1 threshold 0.8,10,254,1,0.8,0.7332136889659013,1.3041601181030273,0,None,i7059,1.3041601181030273,393.140625,392.5390625,-1,0,3309744
1742406743,1742406869,126,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 10 n_reference_samples 252 recent_samples_proportion 0.1 threshold 0.6328647670288212,10,252,0.1,0.6328647670288212,0.7269014171669039,3.337907314300537,0,None,i7044,3.337907314300537,507.16796875,506.8190104166667,-1,0,3309761
1742408140,1742408153,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2403 n_reference_samples 500 recent_samples_proportion 0.1 threshold 0.5136452879787561,2403,500,0.1,0.5136452879787561,0.7480042081811993,2.73844313621521,0,None,i7097,2.73844313621521,525.3828125,525.0247395833334,-1,0,3315299
1742408140,1742408153,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 304 n_reference_samples 480 recent_samples_proportion 1 threshold 0.621882268748546,304,480,1,0.621882268748546,0.7363698248654,1.976449728012085,0,None,i7138,1.976449728012085,524.125,523.7799479166666,-1,0,3315283
1742408140,1742408153,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 709 n_reference_samples 416 recent_samples_proportion 1 threshold 0.5849021487203575,709,416,1,0.5849021487203575,0.7462095426697196,3.3929426670074463,0,None,i7103,3.3929426670074463,524.5390625,524.1354166666666,-1,0,3315293
1742408140,1742408159,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2180 n_reference_samples 83 recent_samples_proportion 0.1 threshold 0.7232518107992914,2180,83,0.1,0.7232518107992914,0.7464570827402686,7.068891525268555,0,None,i7151,7.068891525268555,524.19921875,523.88671875,-1,0,3315267
1742408140,1742408159,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1633 n_reference_samples 417 recent_samples_proportion 0.32850244953174557 threshold 0.6978809956173884,1633,417,0.32850244953174557,0.6978809956173884,0.7455288074757102,8.818787813186646,0,None,i7147,8.818787813186646,523.9921875,523.63671875,-1,0,3315274
1742408140,1742408160,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2085 n_reference_samples 50 recent_samples_proportion 0.1 threshold 0.8,2085,50,0.1,0.8,0.7478804381459249,6.85554313659668,0,None,i7069,6.85554313659668,524.640625,524.4609375,-1,0,3315315
1742408141,1742408161,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 887 n_reference_samples 500 recent_samples_proportion 1 threshold 0.6094783825421928,887,500,1,0.6094783825421928,0.7452812674051612,4.1845176219940186,0,None,i7038,4.1845176219940186,524.2421875,523.8997395833334,-1,0,3315341
1742408142,1742408162,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 645 n_reference_samples 294 recent_samples_proportion 1 threshold 0.6388258095702621,645,294,1,0.6388258095702621,0.7333374590011759,4.783013820648193,0,None,i7169,4.783013820648193,525.70703125,525.3880208333334,-1,0,3315258
1742408152,1742408165,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 881 n_reference_samples 500 recent_samples_proportion 1 threshold 0.8,881,500,1,0.8,0.7308620582956866,1.2860996723175049,0,None,i7153,1.2860996723175049,524.515625,524.1705729166666,-1,0,3315347
1742408140,1742408165,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2953 n_reference_samples 500 recent_samples_proportion 0.1 threshold 0.6593516952200568,2953,500,0.1,0.6593516952200568,0.7446624172287889,5.252315282821655,0,None,i7043,5.252315282821655,510.890625,509.08203125,-1,0,3315336
1742408141,1742408167,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2162 n_reference_samples 50 recent_samples_proportion 0.1 threshold 0.5,2162,50,0.1,0.5,0.7434247168760443,12.912328958511353,0,None,i7081,12.912328958511353,524.1484375,523.900390625,-1,0,3315307
1742408140,1742408184,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3457 n_reference_samples 438 recent_samples_proportion 0.1 threshold 0.8,3457,438,0.1,0.8,0.7447243022464262,7.546589136123657,0,None,i7053,7.546589136123657,522.71484375,522.3411458333334,-1,0,3315321
1742408172,1742408185,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2218 n_reference_samples 500 recent_samples_proportion 0.1 threshold 0.5,2218,500,0.1,0.5,0.7350702394950183,1.9692952632904053,0,None,i7133,1.9692952632904053,524.7265625,524.3971354166666,-1,0,3315388
1742408172,1742408185,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 504 n_reference_samples 292 recent_samples_proportion 1 threshold 0.6369774996226137,504,292,1,0.6369774996226137,0.7354415496008416,2.943936824798584,0,None,i7151,2.943936824798584,524.24609375,523.91015625,-1,0,3315367
1742408172,1742408185,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2572 n_reference_samples 390 recent_samples_proportion 0.35536878031933694 threshold 0.5413601668949899,2572,390,0.35536878031933694,0.5413601668949899,0.7475710130577388,4.311360120773315,0,None,i7121,4.311360120773315,525.91796875,525.578125,-1,0,3315398
1742408173,1742408186,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 710 n_reference_samples 280 recent_samples_proportion 1 threshold 0.8,710,280,1,0.8,0.7290055077665697,1.3735289573669434,0,None,i7147,1.3735289573669434,524.08984375,523.7552083333334,-1,0,3315372
1742408171,1742408191,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2286 n_reference_samples 71 recent_samples_proportion 1 threshold 0.8,2286,71,1,0.8,0.7429296367349465,9.421009063720703,0,None,i7161,9.421009063720703,524.828125,524.4674479166666,-1,0,3315359
1742408172,1742408191,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2231 n_reference_samples 104 recent_samples_proportion 1 threshold 0.5,2231,104,1,0.5,0.7462714276873569,6.876530647277832,0,None,i7101,6.876530647277832,525.0546875,524.7057291666666,-1,0,3315406
1742408172,1742408191,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 624 n_reference_samples 355 recent_samples_proportion 1 threshold 0.5,624,355,1,0.5,0.7470759329166409,5.1409783363342285,0,None,i7182,5.1409783363342285,525.35546875,525.04296875,-1,0,3315354
1742408172,1742408191,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 443 n_reference_samples 203 recent_samples_proportion 1 threshold 0.6611353378621458,443,203,1,0.6611353378621458,0.7476328980753759,6.5818071365356445,0,None,i7140,6.5818071365356445,525.55859375,525.2122395833334,-1,0,3315380
1742408173,1742408192,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3148 n_reference_samples 418 recent_samples_proportion 0.1 threshold 0.8,3148,418,0.1,0.8,0.7457763475462591,6.6053853034973145,0,None,i7066,6.6053853034973145,512.14453125,511.80078125,-1,0,3315430
1742408173,1742408193,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3525 n_reference_samples 500 recent_samples_proportion 0.1 threshold 0.7061962515583957,3525,500,0.1,0.7061962515583957,0.7429915217525837,7.313158988952637,0,None,i7152,7.313158988952637,524.4140625,524.0651041666666,-1,0,3315464
1742408171,1742408197,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 4000 n_reference_samples 352 recent_samples_proportion 0.408337468376263 threshold 0.6052074950565773,4000,352,0.408337468376263,0.6052074950565773,0.7455288074757102,12.408201456069946,0,None,i7051,12.408201456069946,512.875,512.609375,-1,0,3315438
1742408171,1742408197,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2269 n_reference_samples 50 recent_samples_proportion 0.1 threshold 0.8,2269,50,0.1,0.8,0.738226375394517,13.17504620552063,0,None,i7097,13.17504620552063,525.36328125,525.1103515625,-1,0,3315412
1742408173,1742408198,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1546 n_reference_samples 428 recent_samples_proportion 1 threshold 0.6086983310063924,1546,428,1,0.6086983310063924,0.7426820966643976,5.720322132110596,0,None,i7026,5.720322132110596,512.2109375,511.8541666666667,-1,0,3315453
1742408173,1742408205,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1665 n_reference_samples 409 recent_samples_proportion 0.1 threshold 0.8,1665,409,0.1,0.8,0.7481279782164738,8.995258092880249,0,None,i7029,8.995258092880249,512.26953125,511.9075520833333,-1,0,3315446
1742408192,1742408218,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 281 n_reference_samples 50 recent_samples_proportion 1 threshold 0.6768266911252283,281,50,1,0.6768266911252283,0.7391546506590755,13.734014987945557,0,None,i7183,13.734014987945557,524.61328125,524.3564453125,-1,0,3315473
1742408202,1742408316,114,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1889 n_reference_samples 50 recent_samples_proportion 1 threshold 0.5986167994372307,1889,50,1,0.5986167994372307,0.7157002289745653,103.9233603477478,0,None,i7161,103.9233603477478,550.80859375,534.8885216346154,-1,0,3315481
1742408141,1742408493,352,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 766 n_reference_samples 276 recent_samples_proportion 1 threshold 0.5998289026744615,766,276,1,0.5998289026744615,0.7464570827402686,5.55061936378479,0,None,i7049,5.55061936378479,470.1875,469.5963541666667,-1,0,3315329
1742408274,1742408531,257,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2943 n_reference_samples 500 recent_samples_proportion 0.1 threshold 0.8,2943,500,0.1,0.8,0.7468283928460919,77.42754912376404,0,None,i7084,77.42754912376404,524.8359375,524.725390625,-1,0,3315421
1742410959,1742410978,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3891 n_reference_samples 414 recent_samples_proportion 0.3668792203308437 threshold 0.8,3891,414,0.3668792203308437,0.8,0.743610371928956,7.35576057434082,0,None,i7163,7.35576057434082,524.203125,523.8072916666666,-1,0,3322855
1742410971,1742410984,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 270 n_reference_samples 168 recent_samples_proportion 1 threshold 0.5425427188610771,270,168,1,0.5425427188610771,0.7477566681106504,4.856577396392822,0,None,i7146,4.856577396392822,523.9296875,523.5950520833334,-1,0,3322890
1742410971,1742410984,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2822 n_reference_samples 450 recent_samples_proportion 1 threshold 0.7429467399396703,2822,450,1,0.7429467399396703,0.7305526332075004,2.0292787551879883,0,None,i7122,2.0292787551879883,524.13671875,523.8151041666666,-1,0,3322926
1742410971,1742410984,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3694 n_reference_samples 500 recent_samples_proportion 1 threshold 0.6986514712338764,3694,500,1,0.6986514712338764,0.7449718423169751,3.315420627593994,0,None,i7139,3.315420627593994,524.08984375,523.7447916666666,-1,0,3322909
1742410971,1742410984,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 4000 n_reference_samples 500 recent_samples_proportion 1 threshold 0.7244938987299508,4000,500,1,0.7244938987299508,0.7377312952534192,3.1919524669647217,0,None,i7143,3.1919524669647217,525.01953125,524.67578125,-1,0,3322902
1742410976,1742410989,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3818 n_reference_samples 451 recent_samples_proportion 1 threshold 0.7928755418010242,3818,451,1,0.7928755418010242,0.7310477133485983,1.4783847332000732,0,None,i7158,1.4783847332000732,524.3515625,524.0091145833334,-1,0,3322867
1742410971,1742410990,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3921 n_reference_samples 500 recent_samples_proportion 0.1 threshold 0.6431345768661012,3921,500,0.1,0.6431345768661012,0.7481279782164738,9.15172791481018,0,None,i7152,9.15172791481018,524.87890625,524.53515625,-1,0,3322879
1742410971,1742410990,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2407 n_reference_samples 135 recent_samples_proportion 0.6863043452410827 threshold 0.5,2407,135,0.6863043452410827,0.5,0.7413206262763785,8.861977100372314,0,None,i7165,8.861977100372314,525.11328125,524.7786458333334,-1,0,3322861
1742410971,1742410990,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 4000 n_reference_samples 401 recent_samples_proportion 0.1 threshold 0.8,4000,401,0.1,0.8,0.7453431524227985,10.873683452606201,0,None,i7131,10.873683452606201,524.6640625,524.408203125,-1,0,3322920
1742410972,1742410992,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 776 n_reference_samples 464 recent_samples_proportion 1 threshold 0.5,776,464,1,0.5,0.7488705984281205,6.171407461166382,0,None,i7135,6.171407461166382,525.609375,525.25390625,-1,0,3322916
1742410977,1742411003,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 533 n_reference_samples 88 recent_samples_proportion 0.1 threshold 0.7160716080900635,533,88,0.1,0.7160716080900635,0.7367411349712235,13.916342973709106,0,None,i7118,13.916342973709106,526.0078125,525.3359375,-1,0,3322941
1742410971,1742411003,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 896 n_reference_samples 84 recent_samples_proportion 0.7511342864315839 threshold 0.8,896,84,0.7511342864315839,0.8,0.731790333560245,22.56560230255127,0,None,i7150,22.56560230255127,529.76171875,526.4140625,-1,0,3322886
1742410971,1742411009,38,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1040 n_reference_samples 87 recent_samples_proportion 0.19651555223341993 threshold 0.7745895039551999,1040,87,0.19651555223341993,0.7745895039551999,0.7306145182251377,27.411981105804443,0,None,i7154,27.411981105804443,531.26171875,525.94140625,-1,0,3322872
1742410997,1742411010,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 319 n_reference_samples 163 recent_samples_proportion 1 threshold 0.8,319,163,1,0.8,0.7441054520700539,5.074169397354126,0,None,i7171,5.074169397354126,525.0390625,524.7018229166666,-1,0,3322949
1742411001,1742411014,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3742 n_reference_samples 399 recent_samples_proportion 0.46582473435730165 threshold 0.8,3742,399,0.46582473435730165,0.8,0.7335849990717247,2.7727315425872803,0,None,i7153,2.7727315425872803,524.953125,524.6341145833334,-1,0,3322968
1742411001,1742411014,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 235 n_reference_samples 208 recent_samples_proportion 1 threshold 0.5,235,208,1,0.5,0.7473234729871898,3.638075828552246,0,None,i7161,3.638075828552246,525.36328125,525.0169270833334,-1,0,3322963
1742411001,1742411015,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3667 n_reference_samples 428 recent_samples_proportion 1 threshold 0.8,3667,428,1,0.8,0.7331518039482642,1.7635712623596191,0,None,i7167,1.7635712623596191,525.48828125,525.1666666666666,-1,0,3322955
1742410971,1742411015,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2416 n_reference_samples 152 recent_samples_proportion 1 threshold 0.5,2416,152,1,0.5,0.7460857726344452,8.040475130081177,0,None,i7121,8.040475130081177,389.828125,389.21875,-1,0,3322934
1742410971,1742411016,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1849 n_reference_samples 128 recent_samples_proportion 0.1 threshold 0.7737678112878124,1849,128,0.1,0.7737678112878124,0.7309239433133239,32.30349087715149,0,None,i7145,32.30349087715149,535.51953125,528.0071614583334,-1,0,3322896
1742411001,1742411021,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 425 n_reference_samples 127 recent_samples_proportion 0.1 threshold 0.6278460138614771,425,127,0.1,0.6278460138614771,0.7401448109412712,8.660166025161743,0,None,i7118,8.660166025161743,524.015625,523.6783854166666,-1,0,3323030
1742411001,1742411021,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3805 n_reference_samples 365 recent_samples_proportion 0.1 threshold 0.8,3805,365,0.1,0.8,0.7430534067702209,12.124515056610107,0,None,i7138,12.124515056610107,522.83203125,522.5751953125,-1,0,3323005
1742411001,1742411021,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 834 n_reference_samples 364 recent_samples_proportion 0.20460102591912038 threshold 0.5,834,364,0.20460102591912038,0.5,0.7457144625286218,7.488593578338623,0,None,i7122,7.488593578338623,525.5234375,525.1888020833334,-1,0,3323023
1742411001,1742411021,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 356 n_reference_samples 152 recent_samples_proportion 0.4180982028183986 threshold 0.5861505726851616,356,152,0.4180982028183986,0.5861505726851616,0.7471997029519153,6.987059593200684,0,None,i7150,6.987059593200684,524.12890625,523.7643229166666,-1,0,3322977
1742411001,1742411021,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2310 n_reference_samples 123 recent_samples_proportion 0.1 threshold 0.5,2310,123,0.1,0.5,0.7435484869113188,7.124074459075928,0,None,i7145,7.124074459075928,525.34375,525.0065104166666,-1,0,3322984
1742411002,1742411021,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 735 n_reference_samples 500 recent_samples_proportion 0.5744100430107577 threshold 0.5,735,500,0.5744100430107577,0.5,0.7482517482517482,4.647240877151489,0,None,i7115,4.647240877151489,512.28125,511.9518229166667,-1,0,3323038
1742411003,1742411023,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 173 n_reference_samples 250 recent_samples_proportion 1 threshold 0.5,173,250,1,0.5,0.7431771768054954,3.8080050945281982,0,None,i7140,3.8080050945281982,524.18359375,523.8333333333334,-1,0,3322998
1742411001,1742411027,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 591 n_reference_samples 65 recent_samples_proportion 1 threshold 0.8,591,65,1,0.8,0.7372981001299586,17.174033880233765,0,None,i7131,17.174033880233765,526.9375,525.3212890625,-1,0,3323016
1742411004,1742411030,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3854 n_reference_samples 432 recent_samples_proportion 0.1 threshold 0.5,3854,432,0.1,0.5,0.7477566681106504,12.204314947128296,0,None,i7135,12.204314947128296,524.97265625,524.7138671875,-1,0,3323011
1742411017,1742411031,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 4000 n_reference_samples 459 recent_samples_proportion 0.9337329245458182 threshold 0.8,4000,459,0.9337329245458182,0.8,0.733399344018813,1.892958164215088,0,None,i7175,1.892958164215088,525.16796875,524.8098958333334,-1,0,3323044
1742411001,1742411047,46,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1529 n_reference_samples 108 recent_samples_proportion 0.1 threshold 0.7873355302765959,1529,108,0.1,0.7873355302765959,0.7311714833838727,36.26256728172302,0,None,i7142,36.26256728172302,533.68359375,526.5188802083334,-1,0,3322992
1742414004,1742414017,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2444 n_reference_samples 332 recent_samples_proportion 0.1 threshold 0.5937601300244204,2444,332,0.1,0.5937601300244204,0.7471997029519153,3.821068286895752,0,None,i7145,3.821068286895752,525.16015625,524.8033854166666,-1,0,3328137
1742414017,1742414030,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1335 n_reference_samples 454 recent_samples_proportion 1 threshold 0.759340912913785,1335,454,1,0.759340912913785,0.7372981001299586,1.8266327381134033,0,None,i7151,1.8266327381134033,524.59765625,524.2721354166666,-1,0,3328141
1742414018,1742414031,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3238 n_reference_samples 395 recent_samples_proportion 0.5370605954577059 threshold 0.7964822763390199,3238,395,0.5370605954577059,0.7964822763390199,0.732594838789529,1.9495420455932617,0,None,i7183,1.9495420455932617,524.64453125,524.3072916666666,-1,0,3328139
1742414018,1742414031,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2569 n_reference_samples 447 recent_samples_proportion 0.1 threshold 0.5,2569,447,0.1,0.5,0.7486849433752089,3.771660804748535,0,None,i7144,3.771660804748535,524.8671875,524.54296875,-1,0,3328142
1742414018,1742414031,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2603 n_reference_samples 500 recent_samples_proportion 0.1 threshold 0.5954532471814694,2603,500,0.1,0.5954532471814694,0.7457144625286218,3.4370598793029785,0,None,i7142,3.4370598793029785,525.43359375,525.0481770833334,-1,0,3328144
1742414034,1742414047,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2663 n_reference_samples 418 recent_samples_proportion 0.1 threshold 0.617148910719189,2663,418,0.1,0.617148910719189,0.7458382325638963,4.295659065246582,0,None,i7146,4.295659065246582,524.41796875,524.0755208333334,-1,0,3328159
1742414034,1742414047,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2536 n_reference_samples 451 recent_samples_proportion 0.6936693159626116 threshold 0.5,2536,451,0.6936693159626116,0.5,0.7474472430224642,3.5673248767852783,0,None,i7152,3.5673248767852783,524.75390625,524.4231770833334,-1,0,3328152
1742414034,1742414047,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2485 n_reference_samples 327 recent_samples_proportion 0.1 threshold 0.5,2485,327,0.1,0.5,0.7481279782164738,4.132918119430542,0,None,i7150,4.132918119430542,524.296875,523.9453125,-1,0,3328157
1742414034,1742414047,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3758 n_reference_samples 500 recent_samples_proportion 1 threshold 0.8,3758,500,1,0.8,0.7379169503063309,1.6716043949127197,0,None,i7151,1.6716043949127197,525.640625,525.296875,-1,0,3328155
1742414034,1742414047,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2471 n_reference_samples 346 recent_samples_proportion 0.6823227759534095 threshold 0.6165982876627819,2471,346,0.6823227759534095,0.6165982876627819,0.7437341419642305,3.422290086746216,0,None,i7138,3.422290086746216,526.015625,525.6966145833334,-1,0,3328175
1742414035,1742414048,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2252 n_reference_samples 290 recent_samples_proportion 0.1 threshold 0.8,2252,290,0.1,0.8,0.7450337273346123,3.574683666229248,0,None,i7186,3.574683666229248,526.015625,525.6783854166666,-1,0,3328146
1742414039,1742414052,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1698 n_reference_samples 274 recent_samples_proportion 0.7475629481410955 threshold 0.8,1698,274,0.7475629481410955,0.8,0.7408255461352806,4.104442119598389,0,None,i7183,4.104442119598389,525.0546875,524.73046875,-1,0,3328181
1742414034,1742414054,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3463 n_reference_samples 384 recent_samples_proportion 1 threshold 0.5,3463,384,1,0.5,0.7463951977226313,9.798187732696533,0,None,i7144,9.798187732696533,525.07421875,524.7369791666666,-1,0,3328164
1742414034,1742414054,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1093 n_reference_samples 500 recent_samples_proportion 0.1 threshold 0.8,1093,500,0.1,0.8,0.7451574973698868,5.558305740356445,0,None,i7138,5.558305740356445,524.73828125,524.3880208333334,-1,0,3328171
1742414034,1742414054,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 925 n_reference_samples 269 recent_samples_proportion 0.1 threshold 0.775900393757729,925,269,0.1,0.775900393757729,0.7403304659941828,8.209368705749512,0,None,i7154,8.209368705749512,524.2421875,523.9140625,-1,0,3328150
1742414035,1742414054,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3041 n_reference_samples 306 recent_samples_proportion 0.1 threshold 0.5,3041,306,0.1,0.5,0.7447861872640633,10.294945001602173,0,None,i7165,10.294945001602173,524.16796875,523.9150390625,-1,0,3328148
1742414037,1742414057,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1734 n_reference_samples 375 recent_samples_proportion 1 threshold 0.5,1734,375,1,0.5,0.7433009468407699,10.489744663238525,0,None,i7143,10.489744663238525,524.6953125,524.4453125,-1,0,3328185
1742414041,1742414061,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3123 n_reference_samples 432 recent_samples_proportion 0.1 threshold 0.6133692133079055,3123,432,0.1,0.6133692133079055,0.7509128040101491,7.974772930145264,0,None,i7136,7.974772930145264,512.2890625,511.9270833333333,-1,0,3328179
1742414057,1742414070,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1336 n_reference_samples 415 recent_samples_proportion 1 threshold 0.8,1336,415,1,0.8,0.7346370443715576,1.2482612133026123,0,None,i7165,1.2482612133026123,525.4296875,525.1106770833334,-1,0,3328194
1742414057,1742414070,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 472 n_reference_samples 239 recent_samples_proportion 0.1 threshold 0.8,472,239,0.1,0.8,0.7476947830930132,5.346828460693359,0,None,i7183,5.346828460693359,524.328125,523.2135416666666,-1,0,3328190
1742414064,1742414077,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2547 n_reference_samples 352 recent_samples_proportion 1 threshold 0.6628839809164538,2547,352,1,0.6628839809164538,0.7338325391422736,1.811891794204712,0,None,i7158,1.811891794204712,524.4375,524.0859375,-1,0,3328197
1742414065,1742414078,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2366 n_reference_samples 181 recent_samples_proportion 1 threshold 0.6834037383150745,2366,181,1,0.6834037383150745,0.7468902778637292,4.822856664657593,0,None,i7150,4.822856664657593,522.96484375,522.6328125,-1,0,3328209
1742414065,1742414078,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2585 n_reference_samples 408 recent_samples_proportion 1 threshold 0.5,2585,408,1,0.5,0.7464570827402686,4.311033487319946,0,None,i7134,4.311033487319946,525.1953125,524.8776041666666,-1,0,3328236
1742414064,1742414084,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3673 n_reference_samples 500 recent_samples_proportion 1 threshold 0.5,3673,500,1,0.5,0.7440435670524166,8.164391279220581,0,None,i7151,8.164391279220581,524.01171875,523.69140625,-1,0,3328205
1742414064,1742414084,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 913 n_reference_samples 187 recent_samples_proportion 1 threshold 0.5,913,187,1,0.5,0.7433628318584071,11.415911197662354,0,None,i7152,11.415911197662354,525.51953125,525.2451171875,-1,0,3328202
1742414064,1742414084,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2781 n_reference_samples 252 recent_samples_proportion 0.1 threshold 0.8,2781,252,0.1,0.8,0.7463333127049941,8.618905782699585,0,None,i7144,8.618905782699585,524.41796875,524.0677083333334,-1,0,3328214
1742414066,1742414092,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3738 n_reference_samples 330 recent_samples_proportion 0.1 threshold 0.5,3738,330,0.1,0.5,0.7436722569465932,13.357019424438477,0,None,i7136,13.357019424438477,512.33984375,512.076171875,-1,0,3328231
1742414067,1742414093,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1520 n_reference_samples 277 recent_samples_proportion 0.1 threshold 0.8,1520,277,0.1,0.8,0.7440435670524166,15.854224443435669,0,None,i7137,15.854224443435669,512.3359375,512.072265625,-1,0,3328227
1742414064,1742414096,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1117 n_reference_samples 150 recent_samples_proportion 1 threshold 0.5,1117,150,1,0.5,0.7358747447243023,18.66506338119507,0,None,i7138,18.66506338119507,527.5078125,525.470703125,-1,0,3328222
1742414071,1742414097,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1781 n_reference_samples 352 recent_samples_proportion 0.1 threshold 0.5987471212185957,1781,352,0.1,0.5987471212185957,0.7428677517173092,14.871916055679321,0,None,i7141,14.871916055679321,524.90625,524.65234375,-1,0,3328218
1742418387,1742418400,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2263 n_reference_samples 308 recent_samples_proportion 0.6497028356165585 threshold 0.7515535342094458,2263,308,0.6497028356165585,0.7515535342094458,0.7295624729253047,1.6465258598327637,0,None,i7158,1.6465258598327637,524.55859375,524.2161458333334,-1,0,3334339
1742418400,1742418413,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2206 n_reference_samples 142 recent_samples_proportion 0.1 threshold 0.6493960251929328,2206,142,0.1,0.6493960251929328,0.7476947830930132,4.373811721801758,0,None,i7182,4.373811721801758,525.703125,525.3697916666666,-1,0,3334343
1742418400,1742418413,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1753 n_reference_samples 344 recent_samples_proportion 1 threshold 0.7906786888955483,1753,344,1,0.7906786888955483,0.7316665635249706,1.464430570602417,0,None,i7183,1.464430570602417,524.453125,524.1171875,-1,0,3334341
1742418400,1742418413,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 432 n_reference_samples 242 recent_samples_proportion 0.37141485125486196 threshold 0.5185397281111358,432,242,0.37141485125486196,0.5185397281111358,0.7470140478990036,5.053992986679077,0,None,i7172,5.053992986679077,525,524.64453125,-1,0,3334345
1742418417,1742418430,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 99 n_reference_samples 334 recent_samples_proportion 1 threshold 0.5787243624601819,99,334,1,0.5787243624601819,0.7323472987189802,1.4223978519439697,0,None,i7150,1.4223978519439697,525.80078125,525.4791666666666,-1,0,3334370
1742418417,1742418430,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 234 n_reference_samples 345 recent_samples_proportion 0.9557276223114232 threshold 0.8,234,345,0.9557276223114232,0.8,0.7330280339129897,1.0229053497314453,0,None,i7152,1.0229053497314453,525.66796875,525.33203125,-1,0,3334365
1742418417,1742418430,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 615 n_reference_samples 480 recent_samples_proportion 0.4085408407741587 threshold 0.5987304974787694,615,480,0.4085408407741587,0.5987304974787694,0.7450956123522495,4.238352298736572,0,None,i7169,4.238352298736572,524.54296875,524.1901041666666,-1,0,3334348
1742418417,1742418431,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 492 n_reference_samples 332 recent_samples_proportion 0.4453509884275539 threshold 0.77192741409198,492,332,0.4453509884275539,0.77192741409198,0.7413206262763785,3.5069334506988525,0,None,i7154,3.5069334506988525,522.828125,522.5052083333334,-1,0,3334358
1742418418,1742418431,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2471 n_reference_samples 285 recent_samples_proportion 1 threshold 0.8,2471,285,1,0.8,0.7314809084720589,1.300581455230713,0,None,i7153,1.300581455230713,525.34375,525.02734375,-1,0,3334361
1742418418,1742418431,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 558 n_reference_samples 426 recent_samples_proportion 0.46762503587946974 threshold 0.5,558,426,0.46762503587946974,0.5,0.7468902778637292,3.6853582859039307,0,None,i7163,3.6853582859039307,525.6015625,525.20703125,-1,0,3334355
1742418420,1742418433,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 308 n_reference_samples 411 recent_samples_proportion 0.17119766077111234 threshold 0.5,308,411,0.17119766077111234,0.5,0.7437341419642305,2.571712017059326,0,None,i7183,2.571712017059326,524.296875,523.96484375,-1,0,3334374
1742418417,1742418436,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3355 n_reference_samples 412 recent_samples_proportion 0.1 threshold 0.7320679510886899,3355,412,0.1,0.7320679510886899,0.7426202116467603,9.207936525344849,0,None,i7164,9.207936525344849,524.25390625,523.8828125,-1,0,3334353
1742418417,1742418436,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 867 n_reference_samples 291 recent_samples_proportion 1 threshold 0.5,867,291,1,0.5,0.7419394764527508,7.336583852767944,0,None,i7152,7.336583852767944,525.71875,525.3854166666666,-1,0,3334363
1742418417,1742418436,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 536 n_reference_samples 237 recent_samples_proportion 0.1 threshold 0.6894394769693292,536,237,0.1,0.6894394769693292,0.7469521628813665,6.17862868309021,0,None,i7151,6.17862868309021,524.1484375,523.8359375,-1,0,3334367
1742418419,1742418439,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 556 n_reference_samples 285 recent_samples_proportion 0.1 threshold 0.6556010984591966,556,285,0.1,0.6556010984591966,0.7449099572993378,6.328864574432373,0,None,i7168,6.328864574432373,525.72265625,525.38671875,-1,0,3334350
1742418439,1742418452,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 664 n_reference_samples 500 recent_samples_proportion 0.5731739052132515 threshold 0.711943687478496,664,500,0.5731739052132515,0.711943687478496,0.7343276192833715,1.8982419967651367,0,None,i7182,1.8982419967651367,524.546875,524.2239583333334,-1,0,3334377
1742418440,1742418453,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2086 n_reference_samples 328 recent_samples_proportion 1 threshold 0.8,2086,328,1,0.8,0.7327804938424407,1.0274231433868408,0,None,i7183,1.0274231433868408,524.8828125,524.5611979166666,-1,0,3334376
1742418440,1742418459,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 752 n_reference_samples 289 recent_samples_proportion 0.47079721175846423 threshold 0.5,752,289,0.47079721175846423,0.5,0.7463333127049941,7.437020301818848,0,None,i7169,7.437020301818848,525.5625,525.2018229166666,-1,0,3334380
1742418447,1742418460,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 805 n_reference_samples 500 recent_samples_proportion 0.1 threshold 0.5855584727364259,805,500,0.1,0.5855584727364259,0.7478804381459249,4.662485837936401,0,None,i7169,4.662485837936401,524.36328125,524.0364583333334,-1,0,3334383
1742418447,1742418460,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2578 n_reference_samples 315 recent_samples_proportion 1 threshold 0.5,2578,315,1,0.5,0.7464570827402686,4.9139158725738525,0,None,i7169,4.9139158725738525,525.703125,525.38671875,-1,0,3334388
1742418447,1742418460,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 301 n_reference_samples 412 recent_samples_proportion 1 threshold 0.705402243652485,301,412,1,0.705402243652485,0.7305526332075004,1.2607462406158447,0,None,i7153,1.2607462406158447,525.6796875,525.33984375,-1,0,3334404
1742418448,1742418461,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3490 n_reference_samples 264 recent_samples_proportion 1 threshold 0.7195404599674511,3490,264,1,0.7195404599674511,0.7369267900241352,3.9849941730499268,0,None,i7163,3.9849941730499268,524.94921875,524.5924479166666,-1,0,3334395
1742418448,1742418461,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2640 n_reference_samples 299 recent_samples_proportion 0.6728401664325135 threshold 0.7901327342473129,2640,299,0.6728401664325135,0.7901327342473129,0.7343276192833715,1.9953627586364746,0,None,i7164,1.9953627586364746,524.58984375,524.2369791666666,-1,0,3334392
1742418447,1742418466,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 538 n_reference_samples 277 recent_samples_proportion 0.1 threshold 0.5,538,277,0.1,0.5,0.7462095426697196,5.40580677986145,0,None,i7183,5.40580677986145,524.0859375,523.7747395833334,-1,0,3334382
1742418447,1742418467,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 457 n_reference_samples 369 recent_samples_proportion 0.1 threshold 0.5991495609202414,457,369,0.1,0.5991495609202414,0.7484374033046599,4.555063009262085,0,None,i7154,4.555063009262085,525.703125,525.3658854166666,-1,0,3334401
1742418448,1742418467,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 840 n_reference_samples 412 recent_samples_proportion 0.731196703116651 threshold 0.5,840,412,0.731196703116651,0.5,0.7441673370876911,5.904136657714844,0,None,i7150,5.904136657714844,524.30859375,523.9973958333334,-1,0,3334408
1742418449,1742418468,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 281 n_reference_samples 210 recent_samples_proportion 0.1 threshold 0.5,281,210,0.1,0.5,0.7488087134104833,5.0657408237457275,0,None,i7168,5.0657408237457275,526.01953125,525.7057291666666,-1,0,3334389
1742418450,1742418470,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 925 n_reference_samples 354 recent_samples_proportion 1 threshold 0.5654117570424089,925,354,1,0.5654117570424089,0.7459620025991708,5.9522669315338135,0,None,i7149,5.9522669315338135,525.00390625,524.6731770833334,-1,0,3334412
1742418459,1742418472,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 568 n_reference_samples 270 recent_samples_proportion 0.12543454574082646 threshold 0.572114654597392,568,270,0.12543454574082646,0.572114654597392,0.7445386471935145,5.7446043491363525,0,None,i7146,5.7446043491363525,524.890625,524.55078125,-1,0,3334416
1742418460,1742418473,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 4000 n_reference_samples 293 recent_samples_proportion 1 threshold 0.7428837207254272,4000,293,1,0.7428837207254272,0.7289436227489324,2.031710386276245,0,None,i7145,2.031710386276245,522.8359375,522.51953125,-1,0,3334420
1742423610,1742423623,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 30 n_reference_samples 249 recent_samples_proportion 1 threshold 0.5865744534054639,30,249,1,0.5865744534054639,0.7270251872021783,1.2887368202209473,0,None,i7150,1.2887368202209473,524.171875,523.83984375,-1,0,3343635
1742423610,1742423623,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 409 n_reference_samples 223 recent_samples_proportion 0.7280354382258002 threshold 0.7675723524365587,409,223,0.7280354382258002,0.7675723524365587,0.7389689956061638,3.0898656845092773,0,None,i7163,3.0898656845092773,524.30859375,523.9557291666666,-1,0,3343625
1742423610,1742423623,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 24 n_reference_samples 182 recent_samples_proportion 0.5891392680223151 threshold 0.7420711875903717,24,182,0.5891392680223151,0.7420711875903717,0.7257256018317966,1.4447476863861084,0,None,i7143,1.4447476863861084,526.05859375,525.7252604166666,-1,0,3343638
1742423610,1742423623,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 448 n_reference_samples 436 recent_samples_proportion 0.1 threshold 0.7072845683409272,448,436,0.1,0.7072845683409272,0.7468902778637292,3.565519094467163,0,None,i7154,3.565519094467163,525.5859375,525.1822916666666,-1,0,3343629
1742423611,1742423623,12,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3624 n_reference_samples 303 recent_samples_proportion 1 threshold 0.8,3624,303,1,0.8,0.7321616436660684,1.4267535209655762,0,None,i7132,1.4267535209655762,512.3203125,511.9661458333333,-1,0,3343648
1742423610,1742423630,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2367 n_reference_samples 177 recent_samples_proportion 0.4487388059882564 threshold 0.687116930713041,2367,177,0.4487388059882564,0.687116930713041,0.7475710130577388,6.085816383361816,0,None,i7151,6.085816383361816,525.078125,524.7291666666666,-1,0,3343632
1742423617,1742423630,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3529 n_reference_samples 334 recent_samples_proportion 1 threshold 0.6883815944329575,3529,334,1,0.6883815944329575,0.7368649050064979,2.397611141204834,0,None,i7141,2.397611141204834,525.50390625,525.1783854166666,-1,0,3343644
1742423612,1742423631,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2466 n_reference_samples 351 recent_samples_proportion 0.1 threshold 0.8,2466,351,0.1,0.8,0.7469521628813665,4.846801042556763,0,None,i7184,4.846801042556763,524.421875,524.02734375,-1,0,3343621
1742423622,1742423635,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2677 n_reference_samples 500 recent_samples_proportion 1 threshold 0.5,2677,500,1,0.5,0.7463333127049941,3.875694513320923,0,None,i7183,3.875694513320923,524.10546875,523.7643229166666,-1,0,3343651
1742423611,1742423648,37,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3273 n_reference_samples 500 recent_samples_proportion 0.1 threshold 0.6319773984714624,3273,500,0.1,0.6319773984714624,0.7467665078284548,6.893637657165527,0,None,i7142,6.893637657165527,511.89453125,511.46875,-1,0,3343641
1742423624,1742423650,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1531 n_reference_samples 500 recent_samples_proportion 0.4967859177451893 threshold 0.5,1531,500,0.4967859177451893,0.5,0.7430534067702209,10.767284631729126,0,None,i7156,10.767284631729126,525.3671875,525.123046875,-1,0,3343655
1742423641,1742423653,12,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2251 n_reference_samples 500 recent_samples_proportion 1 threshold 0.6959073525271748,2251,500,1,0.6959073525271748,0.723683396249768,1.1909146308898926,0,None,i7143,1.1909146308898926,524.68359375,524.3606770833334,-1,0,3343681
1742423641,1742423654,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1984 n_reference_samples 433 recent_samples_proportion 1 threshold 0.8,1984,433,1,0.8,0.732842378860078,1.5334970951080322,0,None,i7151,1.5334970951080322,524.76171875,524.41796875,-1,0,3343674
1742423641,1742423654,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 183 n_reference_samples 127 recent_samples_proportion 1 threshold 0.6184179841899,183,127,1,0.6184179841899,0.7485611733399344,4.198185205459595,0,None,i7150,4.198185205459595,525.30859375,524.9609375,-1,0,3343678
1742423642,1742423655,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 10 n_reference_samples 457 recent_samples_proportion 1 threshold 0.8,10,457,1,0.8,0.7338325391422736,0.9071462154388428,0,None,i7171,0.9071462154388428,524.65234375,524.3307291666666,-1,0,3343663
1742423641,1742423660,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3082 n_reference_samples 500 recent_samples_proportion 0.1 threshold 0.5,3082,500,0.1,0.5,0.7500464137632279,5.82453989982605,0,None,i7164,5.82453989982605,524.671875,524.2630208333334,-1,0,3343667
1742423641,1742423660,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2898 n_reference_samples 406 recent_samples_proportion 0.3912484269565077 threshold 0.5,2898,406,0.3912484269565077,0.5,0.7448480722817006,5.576772928237915,0,None,i7132,5.576772928237915,511.8515625,511.7669270833333,-1,0,3343694
1742423641,1742423660,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1837 n_reference_samples 466 recent_samples_proportion 0.1 threshold 0.5713916217651476,1837,466,0.1,0.5713916217651476,0.7485611733399344,9.189648389816284,0,None,i7142,9.189648389816284,512.234375,511.8515625,-1,0,3343684
1742423641,1742423660,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1569 n_reference_samples 500 recent_samples_proportion 0.1 threshold 0.558390753208333,1569,500,0.1,0.558390753208333,0.7399591558883595,7.9456727504730225,0,None,i7183,7.9456727504730225,524.9375,524.8268229166666,-1,0,3343659
1742423642,1742423661,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 930 n_reference_samples 220 recent_samples_proportion 1 threshold 0.8,930,220,1,0.8,0.7466427377931802,6.273688316345215,0,None,i7141,6.273688316345215,524.50390625,524.16015625,-1,0,3343687
1742423641,1742423673,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 4000 n_reference_samples 247 recent_samples_proportion 0.1 threshold 0.6878324561394636,4000,247,0.1,0.6878324561394636,0.7413825112940157,18.96773600578308,0,None,i7158,18.96773600578308,528.11328125,525.8515625,-1,0,3343671
1742423664,1742423677,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 10 n_reference_samples 146 recent_samples_proportion 0.29348778362619515 threshold 0.7720631067877758,10,146,0.29348778362619515,0.7720631067877758,0.7117395878457825,2.0566153526306152,0,None,i7176,2.0566153526306152,524.51953125,524.1822916666666,-1,0,3343700
1742423667,1742423680,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 616 n_reference_samples 491 recent_samples_proportion 0.1 threshold 0.5,616,491,0.1,0.5,0.7475091280401015,4.014353275299072,0,None,i7167,4.014353275299072,525.50390625,525.1653645833334,-1,0,3343703
1742423644,1742423682,38,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1338 n_reference_samples 160 recent_samples_proportion 0.1 threshold 0.6151797891341318,1338,160,0.1,0.6151797891341318,0.7372981001299586,25.139543294906616,0,None,i7185,25.139543294906616,515.4296875,512.6953125,-1,0,3343696
1742423671,1742423684,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3383 n_reference_samples 402 recent_samples_proportion 1 threshold 0.614139689138636,3383,402,1,0.614139689138636,0.7398972708707222,4.830780029296875,0,None,i7171,4.830780029296875,525.41015625,525.0533854166666,-1,0,3343710
1742423672,1742423686,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2251 n_reference_samples 345 recent_samples_proportion 0.1 threshold 0.7157995309013149,2251,345,0.1,0.7157995309013149,0.7436722569465932,3.0700266361236572,0,None,i7184,3.0700266361236572,524.3125,523.9739583333334,-1,0,3343707
1742423672,1742423691,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3043 n_reference_samples 338 recent_samples_proportion 1 threshold 0.583982619375754,3043,338,1,0.583982619375754,0.7451574973698868,6.903050422668457,0,None,i7144,6.903050422668457,524.8984375,524.56640625,-1,0,3343721
1742423673,1742423699,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1662 n_reference_samples 500 recent_samples_proportion 1 threshold 0.5,1662,500,1,0.5,0.7458382325638963,12.100521802902222,0,None,i7156,12.100521802902222,523.98828125,523.732421875,-1,0,3343714
1742423671,1742423703,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1511 n_reference_samples 191 recent_samples_proportion 0.1 threshold 0.646667075682614,1511,191,0.1,0.646667075682614,0.737978835323968,18.912549257278442,0,None,i7151,18.912549257278442,527.06640625,525.041015625,-1,0,3343717
1742423641,1742423755,114,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2529 n_reference_samples 417 recent_samples_proportion 1 threshold 0.6022413901497559,2529,417,1,0.6022413901497559,0.7410112011881923,2.9621784687042236,0,None,i7138,2.9621784687042236,386.51171875,385.9466145833333,-1,0,3343690
1742431884,1742431903,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 299 n_reference_samples 217 recent_samples_proportion 1 threshold 0.5614856198558127,299,217,1,0.5614856198558127,0.7467665078284548,5.282370090484619,0,None,i7161,5.282370090484619,525.0390625,524.6927083333334,-1,0,3350633
1742431901,1742431913,12,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 465 n_reference_samples 419 recent_samples_proportion 0.1 threshold 0.5602550596927598,465,419,0.1,0.5602550596927598,0.7447861872640633,3.3138303756713867,0,None,i7183,3.3138303756713867,524.1171875,523.77734375,-1,0,3350641
1742431901,1742431913,12,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 323 n_reference_samples 287 recent_samples_proportion 0.680094391563869 threshold 0.56724874972319,323,287,0.680094391563869,0.56724874972319,0.7463333127049941,3.6679177284240723,0,None,i7183,3.6679177284240723,524.3125,523.9739583333334,-1,0,3350637
1742431901,1742431914,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3546 n_reference_samples 489 recent_samples_proportion 1 threshold 0.7542590698740677,3546,489,1,0.7542590698740677,0.7376694102357819,1.4810283184051514,0,None,i7186,1.4810283184051514,524.52734375,524.1848958333334,-1,0,3350634
1742431902,1742431915,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 389 n_reference_samples 375 recent_samples_proportion 0.1 threshold 0.7125980985991547,389,375,0.1,0.7125980985991547,0.7467665078284548,3.7859456539154053,0,None,i7184,3.7859456539154053,524.76171875,524.4205729166666,-1,0,3350636
1742431904,1742431917,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1038 n_reference_samples 269 recent_samples_proportion 1 threshold 0.7417870433125158,1038,269,1,0.7417870433125158,0.7350702394950183,2.3116252422332764,0,None,i7186,2.3116252422332764,525.29296875,524.9557291666666,-1,0,3350644
1742431901,1742431920,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 4000 n_reference_samples 485 recent_samples_proportion 0.1 threshold 0.7172614786651952,4000,485,0.1,0.7172614786651952,0.7475710130577388,9.941710472106934,0,None,i7183,9.941710472106934,524.9375,524.58984375,-1,0,3350638
1742431901,1742431920,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3110 n_reference_samples 455 recent_samples_proportion 1 threshold 0.5,3110,455,1,0.5,0.7437960269818676,6.802497148513794,0,None,i7183,6.802497148513794,525.140625,524.78515625,-1,0,3350639
1742431901,1742431921,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2451 n_reference_samples 163 recent_samples_proportion 1 threshold 0.6065974416182855,2451,163,1,0.6065974416182855,0.7441054520700539,8.66434359550476,0,None,i7185,8.66434359550476,512.32421875,511.94921875,-1,0,3350635
1742431901,1742431932,31,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 4000 n_reference_samples 237 recent_samples_proportion 0.1 threshold 0.8,4000,237,0.1,0.8,0.7364317098830373,18.696664333343506,0,None,i7183,18.696664333343506,528.015625,526.068359375,-1,0,3350640
1742431923,1742431936,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 354 n_reference_samples 336 recent_samples_proportion 0.1 threshold 0.5,354,336,0.1,0.5,0.7471378179342781,3.3066155910491943,0,None,i7183,3.3066155910491943,524.18359375,523.8541666666666,-1,0,3350651
1742431923,1742431936,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 515 n_reference_samples 500 recent_samples_proportion 1 threshold 0.5,515,500,1,0.5,0.7463951977226313,3.4787962436676025,0,None,i7186,3.4787962436676025,525.58203125,525.2395833333334,-1,0,3350646
1742431924,1742431937,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2624 n_reference_samples 500 recent_samples_proportion 0.4748826962129866 threshold 0.5,2624,500,0.4748826962129866,0.5,0.7466427377931802,3.9785313606262207,0,None,i7184,3.9785313606262207,524.109375,523.7786458333334,-1,0,3350650
1742431924,1742431937,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1018 n_reference_samples 317 recent_samples_proportion 1 threshold 0.7401676263719191,1018,317,1,0.7401676263719191,0.7295624729253047,1.8026893138885498,0,None,i7185,1.8026893138885498,512.29296875,511.9713541666667,-1,0,3350648
1742431924,1742431937,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2784 n_reference_samples 500 recent_samples_proportion 1 threshold 0.6432463208422059,2784,500,1,0.6432463208422059,0.7408874311529179,3.4053690433502197,0,None,i7184,3.4053690433502197,524.21875,523.875,-1,0,3350649
1742431930,1742431943,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 369 n_reference_samples 382 recent_samples_proportion 0.5394349023777661 threshold 0.5456522145303193,369,382,0.5394349023777661,0.5456522145303193,0.7445386471935145,2.942617177963257,0,None,i7183,2.942617177963257,525.3125,524.9739583333334,-1,0,3350655
1742431930,1742431943,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 411 n_reference_samples 500 recent_samples_proportion 0.1 threshold 0.7777722511274027,411,500,0.1,0.7777722511274027,0.7436722569465932,2.731062412261963,0,None,i7183,2.731062412261963,524.85546875,524.5260416666666,-1,0,3350653
1742431930,1742431944,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1306 n_reference_samples 500 recent_samples_proportion 1 threshold 0.7073345185083949,1306,500,1,0.7073345185083949,0.7438579119995049,2.837200880050659,0,None,i7183,2.837200880050659,524.125,523.7643229166666,-1,0,3350654
1742431932,1742431945,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1605 n_reference_samples 500 recent_samples_proportion 1 threshold 0.7098619555338849,1605,500,1,0.7098619555338849,0.7426202116467603,2.7315661907196045,0,None,i7179,2.7315661907196045,524.19921875,523.8138020833334,-1,0,3350656
1742431932,1742431945,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1079 n_reference_samples 457 recent_samples_proportion 0.4396795783925307 threshold 0.8,1079,457,0.4396795783925307,0.8,0.7378550652886936,3.255117654800415,0,None,i7185,3.255117654800415,512.375,512.03515625,-1,0,3350652
1742431924,1742431956,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3978 n_reference_samples 214 recent_samples_proportion 0.1 threshold 0.6265037149276544,3978,214,0.1,0.6265037149276544,0.7366792499535862,23.650314331054688,0,None,i7186,23.650314331054688,529.3515625,526.0421875,-1,0,3350645
1742431944,1742431957,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 624 n_reference_samples 500 recent_samples_proportion 1 threshold 0.5,624,500,1,0.5,0.743610371928956,3.8557474613189697,0,None,i7186,3.8557474613189697,525.72265625,525.3815104166666,-1,0,3350658
1742431931,1742431957,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 935 n_reference_samples 146 recent_samples_proportion 1 threshold 0.6743353823590832,935,146,1,0.6743353823590832,0.7416919363822019,15.654021739959717,0,None,i7172,15.654021739959717,524.3203125,524.0537109375,-1,0,3350657
1742431943,1742431963,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 4000 n_reference_samples 500 recent_samples_proportion 0.1 threshold 0.5,4000,500,0.1,0.5,0.7515316541865215,9.969277381896973,0,None,i7183,9.969277381896973,526.02734375,525.7005208333334,-1,0,3350662
1742431945,1742431964,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2997 n_reference_samples 368 recent_samples_proportion 0.1 threshold 0.6194607105861288,2997,368,0.1,0.6194607105861288,0.7425583266291231,8.773682355880737,0,None,i7185,8.773682355880737,512.33984375,512,-1,0,3350659
1742431961,1742431974,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2640 n_reference_samples 500 recent_samples_proportion 0.727267823757965 threshold 0.6198534009539937,2640,500,0.727267823757965,0.6198534009539937,0.7456525775109846,3.0371310710906982,0,None,i7186,3.0371310710906982,524.5625,524.22265625,-1,0,3350665
1742431943,1742431988,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 4000 n_reference_samples 139 recent_samples_proportion 0.1 threshold 0.5,4000,139,0.1,0.5,0.731790333560245,33.814918756484985,0,None,i7172,33.814918756484985,536.3046875,528.431640625,-1,0,3350664
1742431901,1742432002,101,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 4000 n_reference_samples 50 recent_samples_proportion 0.1 threshold 0.5,4000,50,0.1,0.5,0.7160096540627514,93.111581325531,0,None,i7183,93.111581325531,553.71875,536.384765625,-1,0,3350642
1742431945,1742432016,71,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3740 n_reference_samples 95 recent_samples_proportion 1 threshold 0.5,3740,95,1,0.5,0.7220125007735627,56.38298511505127,0,None,i7184,56.38298511505127,537.24609375,527.767578125,-1,0,3350660
1742431924,1742432092,168,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 4000 n_reference_samples 50 recent_samples_proportion 0.6612681547839336 threshold 0.5,4000,50,0.6612681547839336,0.5,0.7144625286218207,152.56764817237854,0,None,i7185,152.56764817237854,540.16796875,523.1245659722222,-1,0,3350647
1742437153,1742437166,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2154 n_reference_samples 202 recent_samples_proportion 0.6436834862099038 threshold 0.6567230013075561,2154,202,0.6436834862099038,0.6567230013075561,0.7423107865585742,2.7658326625823975,0,None,i7185,2.7658326625823975,524.50390625,524.15234375,-1,0,3353778
1742437153,1742437172,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2923 n_reference_samples 500 recent_samples_proportion 0.1 threshold 0.5649319506557283,2923,500,0.1,0.5649319506557283,0.7463951977226313,5.5544469356536865,0,None,i7183,5.5544469356536865,524.26171875,523.9140625,-1,0,3353779
1742437164,1742437177,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2986 n_reference_samples 343 recent_samples_proportion 1 threshold 0.7959787138024973,2986,343,1,0.7959787138024973,0.734451389318646,1.2344050407409668,0,None,i7183,1.2344050407409668,525.14453125,524.8111979166666,-1,0,3353781
1742437164,1742437177,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3100 n_reference_samples 456 recent_samples_proportion 1 threshold 0.6802610612585359,3100,456,1,0.6802610612585359,0.7372362151123213,2.4730191230773926,0,None,i7172,2.4730191230773926,525.21875,524.8971354166666,-1,0,3353784
1742437165,1742437178,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2180 n_reference_samples 236 recent_samples_proportion 1 threshold 0.5027797443837826,2180,236,1,0.5027797443837826,0.7442292221053283,2.654918909072876,0,None,i7176,2.654918909072876,524.765625,524.4192708333334,-1,0,3353783
1742437165,1742437184,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3117 n_reference_samples 315 recent_samples_proportion 0.1 threshold 0.8,3117,315,0.1,0.8,0.7434247168760443,8.590234994888306,0,None,i7185,8.590234994888306,525.34375,524.9908854166666,-1,0,3353780
1742437164,1742437190,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3449 n_reference_samples 226 recent_samples_proportion 1 threshold 0.5,3449,226,1,0.5,0.7385976855003403,15.926228761672974,0,None,i7183,15.926228761672974,526.14453125,525.2099609375,-1,0,3353782
1742437164,1742437190,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 4000 n_reference_samples 265 recent_samples_proportion 0.1 threshold 0.5,4000,265,0.1,0.5,0.7394021907296243,17.50791907310486,0,None,i7172,17.50791907310486,525.1953125,523.2177734375,-1,0,3353785
1742437182,1742437195,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2185 n_reference_samples 222 recent_samples_proportion 0.7028905721173307 threshold 0.5,2185,222,0.7028905721173307,0.5,0.7444767621758772,3.326280355453491,0,None,i7183,3.326280355453491,524.640625,524.2890625,-1,0,3353789
1742437182,1742437195,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 33 n_reference_samples 50 recent_samples_proportion 0.5287991075309743 threshold 0.5,33,50,0.5287991075309743,0.5,0.7400210409059966,3.4165573120117188,0,None,i7180,3.4165573120117188,524.1796875,523.8294270833334,-1,0,3353791
1742437182,1742437195,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2091 n_reference_samples 193 recent_samples_proportion 0.8659695728089756 threshold 0.8,2091,193,0.8659695728089756,0.8,0.7311095983662356,1.7811949253082275,0,None,i7168,1.7811949253082275,524.21484375,523.87109375,-1,0,3353799
1742437184,1742437197,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2166 n_reference_samples 320 recent_samples_proportion 1 threshold 0.5,2166,320,1,0.5,0.7389689956061638,2.0328359603881836,0,None,i7176,2.0328359603881836,524.1328125,523.7799479166666,-1,0,3353801
1742437182,1742437202,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3048 n_reference_samples 500 recent_samples_proportion 0.1 threshold 0.5860273718152994,3048,500,0.1,0.5860273718152994,0.7448480722817006,6.36653208732605,0,None,i7183,6.36653208732605,525.35546875,525.0078125,-1,0,3353788
1742437182,1742437202,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1990 n_reference_samples 500 recent_samples_proportion 0.1 threshold 0.8,1990,500,0.1,0.8,0.7489324834457578,10.035173416137695,0,None,i7171,10.035173416137695,524.359375,524.0091145833334,-1,0,3353793
1742437182,1742437208,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3281 n_reference_samples 235 recent_samples_proportion 1 threshold 0.5,3281,235,1,0.5,0.7404542360294573,13.620818138122559,0,None,i7185,13.620818138122559,523.95703125,523.6533203125,-1,0,3353787
1742437183,1742437208,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3576 n_reference_samples 237 recent_samples_proportion 1 threshold 0.5,3576,237,1,0.5,0.7407636611176435,15.611873626708984,0,None,i7169,15.611873626708984,526.54296875,525.525390625,-1,0,3353797
1742437204,1742437217,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3021 n_reference_samples 276 recent_samples_proportion 1 threshold 0.8,3021,276,1,0.8,0.7334612290364503,1.3525128364562988,0,None,i7185,1.3525128364562988,525.7109375,525.359375,-1,0,3353803
1742437204,1742437217,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2965 n_reference_samples 500 recent_samples_proportion 0.3663563044820463 threshold 0.5730285944027455,2965,500,0.3663563044820463,0.5730285944027455,0.7475091280401015,5.133829355239868,0,None,i7176,5.133829355239868,525.4609375,525.1276041666666,-1,0,3353807
1742437204,1742437224,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3954 n_reference_samples 500 recent_samples_proportion 0.6548229038500488 threshold 0.5,3954,500,0.6548229038500488,0.5,0.7489324834457578,9.768106460571289,0,None,i7183,9.768106460571289,524.328125,523.9908854166666,-1,0,3353805
1742437212,1742437225,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2049 n_reference_samples 247 recent_samples_proportion 1 threshold 0.6638101563054024,2049,247,1,0.6638101563054024,0.7294387028900303,1.5599839687347412,0,None,i7168,1.5599839687347412,525.05859375,524.7213541666666,-1,0,3353819
1742437212,1742437225,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2133 n_reference_samples 235 recent_samples_proportion 1 threshold 0.5899736804993304,2133,235,1,0.5899736804993304,0.739835385853085,2.4430031776428223,0,None,i7172,2.4430031776428223,525.359375,525.0221354166666,-1,0,3353813
1742437212,1742437225,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2115 n_reference_samples 422 recent_samples_proportion 1 threshold 0.5,2115,422,1,0.5,0.732594838789529,1.69370698928833,0,None,i7167,1.69370698928833,525.35546875,525.0182291666666,-1,0,3353824
1742437212,1742437225,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2866 n_reference_samples 500 recent_samples_proportion 0.1 threshold 0.5457783613171763,2866,500,0.1,0.5457783613171763,0.7467665078284548,5.0325610637664795,0,None,i7168,5.0325610637664795,526.1171875,525.7708333333334,-1,0,3353817
1742437212,1742437225,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2170 n_reference_samples 500 recent_samples_proportion 0.1 threshold 0.8,2170,500,0.1,0.8,0.7305526332075004,1.9056038856506348,0,None,i7183,1.9056038856506348,525.6640625,525.3138020833334,-1,0,3353809
1742437213,1742437226,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2202 n_reference_samples 500 recent_samples_proportion 1 threshold 0.5,2202,500,1,0.5,0.7331518039482642,1.7680878639221191,0,None,i7163,1.7680878639221191,525.43359375,525.078125,-1,0,3353828
1742437212,1742437231,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1819 n_reference_samples 500 recent_samples_proportion 0.1 threshold 0.8,1819,500,0.1,0.8,0.7501701837985024,9.18901777267456,0,None,i7171,9.18901777267456,524.64453125,524.3098958333334,-1,0,3353815
1742437212,1742437232,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1402 n_reference_samples 327 recent_samples_proportion 0.1 threshold 0.5,1402,327,0.1,0.5,0.7450956123522495,10.43912148475647,0,None,i7176,10.43912148475647,525.45703125,525.22265625,-1,0,3353811
1742437212,1742437232,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 85 n_reference_samples 50 recent_samples_proportion 0.1 threshold 0.5,85,50,0.1,0.5,0.7468283928460919,6.220527410507202,0,None,i7167,6.220527410507202,526.1015625,525.7643229166666,-1,0,3353822
1742437225,1742437237,12,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 10 n_reference_samples 50 recent_samples_proportion 1 threshold 0.5,10,50,1,0.5,0.730985828330961,2.6107332706451416,0,None,i7185,2.6107332706451416,524.953125,524.6106770833334,-1,0,3353830
1742437213,1742437245,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3243 n_reference_samples 179 recent_samples_proportion 1 threshold 0.5,3243,179,1,0.5,0.7412587412587412,19.600237607955933,0,None,i7165,19.600237607955933,526.6484375,525.1240234375,-1,0,3353826
1742444834,1742444847,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1490 n_reference_samples 500 recent_samples_proportion 0.444660581211333 threshold 0.8,1490,500,0.444660581211333,0.8,0.7372981001299586,3.0256359577178955,0,None,i7168,3.0256359577178955,525.265625,524.9140625,-1,0,3358061
1742444835,1742444847,12,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2292 n_reference_samples 500 recent_samples_proportion 0.1 threshold 0.6621994001608074,2292,500,0.1,0.6621994001608074,0.7366792499535862,2.486107349395752,0,None,i7165,2.486107349395752,523.97265625,523.6328125,-1,0,3358084
1742444835,1742444847,12,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 10 n_reference_samples 149 recent_samples_proportion 0.6995594186955959 threshold 0.5,10,149,0.6995594186955959,0.5,0.7202797202797203,1.501877784729004,0,None,i7166,1.501877784729004,525.203125,524.8684895833334,-1,0,3358077
1742444835,1742444847,12,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 19 n_reference_samples 50 recent_samples_proportion 0.1 threshold 0.6406681700051938,19,50,0.1,0.6406681700051938,0.7323472987189802,3.4002556800842285,0,None,i7166,3.4002556800842285,524.9296875,524.5924479166666,-1,0,3358082
1742444835,1742444848,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1412 n_reference_samples 282 recent_samples_proportion 1 threshold 0.8,1412,282,1,0.8,0.7338325391422736,1.1721656322479248,0,None,i7167,1.1721656322479248,526.02734375,525.6901041666666,-1,0,3358070
1742444835,1742444854,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3190 n_reference_samples 275 recent_samples_proportion 1 threshold 0.683162059455073,3190,275,1,0.683162059455073,0.7457144625286218,5.31332540512085,0,None,i7167,5.31332540512085,525.61328125,525.2890625,-1,0,3358073
1742444835,1742444860,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3501 n_reference_samples 500 recent_samples_proportion 0.12163564013974972 threshold 0.5,3501,500,0.12163564013974972,0.5,0.7432390618231326,8.53948163986206,0,None,i7167,8.53948163986206,524.49609375,524.1432291666666,-1,0,3358066
1742444849,1742444862,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2231 n_reference_samples 376 recent_samples_proportion 0.1 threshold 0.5,2231,376,0.1,0.5,0.741196856241104,2.3896970748901367,0,None,i7176,2.3896970748901367,524.27734375,523.9361979166666,-1,0,3358087
1742444849,1742444868,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1308 n_reference_samples 391 recent_samples_proportion 1 threshold 0.5,1308,391,1,0.5,0.7407636611176435,9.321518898010254,0,None,i7169,9.321518898010254,525.546875,525.2096354166666,-1,0,3358089
1742444849,1742444869,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 748 n_reference_samples 500 recent_samples_proportion 0.1 threshold 0.8,748,500,0.1,0.8,0.7478185531282876,5.017153263092041,0,None,i7178,5.017153263092041,524.68359375,524.3203125,-1,0,3358085
1742444864,1742444877,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2110 n_reference_samples 163 recent_samples_proportion 0.1 threshold 0.5,2110,163,0.1,0.5,0.7396497308001733,2.885374069213867,0,None,i7163,2.885374069213867,525.04296875,524.7291666666666,-1,0,3358116
1742444865,1742444878,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 99 n_reference_samples 500 recent_samples_proportion 0.1 threshold 0.8,99,500,0.1,0.8,0.7260969119376199,2.2027978897094727,0,None,i7165,2.2027978897094727,524.59765625,524.2473958333334,-1,0,3358100
1742444865,1742444878,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 170 n_reference_samples 449 recent_samples_proportion 0.3343767853225843 threshold 0.8,170,449,0.3343767853225843,0.8,0.7273346122903646,1.6240901947021484,0,None,i7169,1.6240901947021484,525.26171875,524.9192708333334,-1,0,3358093
1742444865,1742444878,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 306 n_reference_samples 500 recent_samples_proportion 1 threshold 0.8,306,500,1,0.8,0.7227551209852094,1.446439504623413,0,None,i7164,1.446439504623413,524.97265625,524.6484375,-1,0,3358113
1742444869,1742444882,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 307 n_reference_samples 500 recent_samples_proportion 0.1 threshold 0.5994057104237525,307,500,0.1,0.5994057104237525,0.7398972708707222,2.384321689605713,0,None,i7184,2.384321689605713,525.5234375,525.1770833333334,-1,0,3358119
1742444864,1742444884,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2853 n_reference_samples 143 recent_samples_proportion 1 threshold 0.8,2853,143,1,0.8,0.7429296367349465,11.305749893188477,0,None,i7167,11.305749893188477,524.796875,524.5302734375,-1,0,3358097
1742444865,1742444884,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 782 n_reference_samples 418 recent_samples_proportion 0.1 threshold 0.8,782,418,0.1,0.8,0.7497988736926791,7.4311981201171875,0,None,i7164,7.4311981201171875,525.5859375,525.26171875,-1,0,3358108
1742444865,1742444884,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 191 n_reference_samples 129 recent_samples_proportion 0.607390144318669 threshold 0.5,191,129,0.607390144318669,0.5,0.7474472430224642,6.683629751205444,0,None,i7165,6.683629751205444,524.6875,524.33984375,-1,0,3358105
1742444869,1742444888,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 143 n_reference_samples 50 recent_samples_proportion 0.1 threshold 0.636355373423645,143,50,0.1,0.636355373423645,0.7391546506590755,8.757351636886597,0,None,i7169,8.757351636886597,524.9140625,524.5768229166666,-1,0,3358121
1742444865,1742444890,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3426 n_reference_samples 435 recent_samples_proportion 0.1 threshold 0.5,3426,435,0.1,0.5,0.7442292221053283,10.965194702148438,0,None,i7165,10.965194702148438,524.9921875,524.7353515625,-1,0,3358102
1742444865,1742444890,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1251 n_reference_samples 334 recent_samples_proportion 0.1 threshold 0.6331447729537386,1251,334,0.1,0.6331447729537386,0.7447243022464262,12.062621355056763,0,None,i7164,12.062621355056763,524.76953125,524.5146484375,-1,0,3358109
1742444866,1742444892,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1426 n_reference_samples 500 recent_samples_proportion 0.1 threshold 0.8,1426,500,0.1,0.8,0.7483136332693855,10.719771146774292,0,None,i7170,10.719771146774292,525.03125,524.76953125,-1,0,3358092
1742444894,1742444907,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 10 n_reference_samples 148 recent_samples_proportion 0.18116780556605616 threshold 0.5,10,148,0.18116780556605616,0.5,0.7205891453679064,1.543576955795288,0,None,i7166,1.543576955795288,524.69140625,524.3541666666666,-1,0,3358141
1742444889,1742444908,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 4000 n_reference_samples 398 recent_samples_proportion 1 threshold 0.5,4000,398,1,0.5,0.7402685809765456,12.310627222061157,0,None,i7176,12.310627222061157,525.16015625,524.908203125,-1,0,3358126
1742444889,1742444908,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2905 n_reference_samples 312 recent_samples_proportion 1 threshold 0.5,2905,312,1,0.5,0.7441054520700539,8.017669439315796,0,None,i7169,8.017669439315796,525.3671875,525.0299479166666,-1,0,3358130
1742444889,1742444909,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1337 n_reference_samples 438 recent_samples_proportion 0.1 threshold 0.8,1337,438,0.1,0.8,0.7470140478990036,7.284784555435181,0,None,i7184,7.284784555435181,525.7578125,525.41015625,-1,0,3358124
1742444894,1742444914,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1312 n_reference_samples 342 recent_samples_proportion 1 threshold 0.5,1312,342,1,0.5,0.7459001175815335,10.682255506515503,0,None,i7168,10.682255506515503,525.8671875,525.615234375,-1,0,3358133
1742444895,1742444914,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3441 n_reference_samples 500 recent_samples_proportion 0.4388450169850665 threshold 0.5,3441,500,0.4388450169850665,0.5,0.7442911071229655,8.775542736053467,0,None,i7167,8.775542736053467,525.04296875,524.7161458333334,-1,0,3358136
1742444895,1742444921,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1332 n_reference_samples 280 recent_samples_proportion 1 threshold 0.5,1332,280,1,0.5,0.7419394764527508,13.041456937789917,0,None,i7167,13.041456937789917,524.390625,524.1552734375,-1,0,3358138
1742444895,1742444939,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2802 n_reference_samples 52 recent_samples_proportion 1 threshold 0.8,2802,52,1,0.8,0.7268395321492667,35.528059244155884,0,None,i7165,35.528059244155884,531.671875,526.2115885416666,-1,0,3358143
1742457407,1742457420,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 207 n_reference_samples 262 recent_samples_proportion 1 threshold 0.7398105155847262,207,262,1,0.7398105155847262,0.7337706541246364,1.424285888671875,0,None,i7182,1.424285888671875,524.73046875,524.4153645833334,-1,0,3363341
1742457426,1742457439,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3292 n_reference_samples 445 recent_samples_proportion 1 threshold 0.8,3292,445,1,0.8,0.7293768178723931,1.2740685939788818,0,None,i7184,1.2740685939788818,525.10546875,524.7643229166666,-1,0,3363344
1742457426,1742457439,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2814 n_reference_samples 238 recent_samples_proportion 1 threshold 0.8,2814,238,1,0.8,0.7380407203416053,2.565800428390503,0,None,i7184,2.565800428390503,524.0078125,523.6692708333334,-1,0,3363345
1742457426,1742457439,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 974 n_reference_samples 500 recent_samples_proportion 0.37750641286870684 threshold 0.7007669882808267,974,500,0.37750641286870684,0.7007669882808267,0.742805866699672,3.7272140979766846,0,None,i7184,3.7272140979766846,524.14453125,523.8072916666666,-1,0,3363347
1742457426,1742457439,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 4000 n_reference_samples 381 recent_samples_proportion 1 threshold 0.7085434370199517,4000,381,1,0.7085434370199517,0.7390927656414382,2.453517198562622,0,None,i7184,2.453517198562622,526.07421875,525.73828125,-1,0,3363346
1742457426,1742457439,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1617 n_reference_samples 445 recent_samples_proportion 0.7870839059882001 threshold 0.8,1617,445,0.7870839059882001,0.8,0.7332755739835386,1.3012123107910156,0,None,i7185,1.3012123107910156,525.55859375,525.2395833333334,-1,0,3363343
1742457438,1742457450,12,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2211 n_reference_samples 156 recent_samples_proportion 0.6642069421224799 threshold 0.5,2211,156,0.6642069421224799,0.5,0.7482517482517482,4.066711664199829,0,None,i7182,4.066711664199829,524.890625,524.5598958333334,-1,0,3363351
1742457437,1742457450,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2382 n_reference_samples 354 recent_samples_proportion 0.609010501676018 threshold 0.5,2382,354,0.609010501676018,0.5,0.7481279782164738,3.3320746421813965,0,None,i7182,3.3320746421813965,524.6875,524.3723958333334,-1,0,3363353
1742457437,1742457450,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2156 n_reference_samples 367 recent_samples_proportion 1 threshold 0.6234554830268025,2156,367,1,0.6234554830268025,0.7333374590011759,1.3384244441986084,0,None,i7182,1.3384244441986084,524.69140625,524.3763020833334,-1,0,3363349
1742457437,1742457450,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 239 n_reference_samples 500 recent_samples_proportion 0.6744575113037857 threshold 0.5,239,500,0.6744575113037857,0.5,0.7375456402005075,1.9670743942260742,0,None,i7182,1.9670743942260742,525.36328125,525.02734375,-1,0,3363350
1742457438,1742457450,12,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 731 n_reference_samples 412 recent_samples_proportion 1 threshold 0.8,731,412,1,0.8,0.7338325391422736,0.9399309158325195,0,None,i7182,0.9399309158325195,525.28515625,524.9674479166666,-1,0,3363352
1742457426,1742457458,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3656 n_reference_samples 201 recent_samples_proportion 0.1 threshold 0.5,3656,201,0.1,0.5,0.7402685809765456,22.77449369430542,0,None,i7183,22.77449369430542,527.79296875,525.309375,-1,0,3363348
1742457446,1742457459,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2191 n_reference_samples 406 recent_samples_proportion 0.10440347018737073 threshold 0.8,2191,406,0.10440347018737073,0.8,0.7342657342657343,2.2698895931243896,0,None,i7185,2.2698895931243896,525.40234375,525.0755208333334,-1,0,3363354
1742457446,1742457459,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 10 n_reference_samples 72 recent_samples_proportion 1 threshold 0.8,10,72,1,0.8,0.7277678074138251,2.1574196815490723,0,None,i7184,2.1574196815490723,524.6640625,524.3372395833334,-1,0,3363356
1742457446,1742457459,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2358 n_reference_samples 500 recent_samples_proportion 1 threshold 0.8,2358,500,1,0.8,0.7269633021845411,1.1468470096588135,0,None,i7185,1.1468470096588135,525.44140625,525.0963541666666,-1,0,3363355
1742457446,1742457459,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 10 n_reference_samples 50 recent_samples_proportion 1 threshold 0.6596744467608918,10,50,1,0.6596744467608918,0.7281391175196484,2.6159634590148926,0,None,i7184,2.6159634590148926,524.05859375,523.7174479166666,-1,0,3363357
1742457466,1742457478,12,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1135 n_reference_samples 317 recent_samples_proportion 0.5366574348714481 threshold 0.8,1135,317,0.5366574348714481,0.8,0.7374837551828702,3.202265977859497,0,None,i7184,3.202265977859497,525.56640625,525.2395833333334,-1,0,3363363
1742457466,1742457478,12,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 4000 n_reference_samples 352 recent_samples_proportion 1 threshold 0.8,4000,352,1,0.8,0.7329042638777152,1.6074237823486328,0,None,i7184,1.6074237823486328,526.0625,525.7252604166666,-1,0,3363364
1742457466,1742457479,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 911 n_reference_samples 471 recent_samples_proportion 0.1 threshold 0.6915593748049232,911,471,0.1,0.6915593748049232,0.7468902778637292,5.530467510223389,0,None,i7185,5.530467510223389,525.41796875,525.0703125,-1,0,3363360
1742457466,1742457479,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2780 n_reference_samples 396 recent_samples_proportion 1 threshold 0.6971741991486287,2780,396,1,0.6971741991486287,0.7315427934896962,1.7532680034637451,0,None,i7184,1.7532680034637451,524.25,523.92578125,-1,0,3363361
1742457466,1742457479,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 325 n_reference_samples 256 recent_samples_proportion 0.1 threshold 0.6088444073282381,325,256,0.1,0.6088444073282381,0.7455288074757102,3.8525779247283936,0,None,i7186,3.8525779247283936,524.87890625,524.5455729166666,-1,0,3363358
1742457466,1742457485,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1192 n_reference_samples 500 recent_samples_proportion 1 threshold 0.5446405934722978,1192,500,1,0.5446405934722978,0.7465808527755431,6.220865964889526,0,None,i7184,6.220865964889526,524.58984375,524.2473958333334,-1,0,3363362
1742457467,1742457486,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 306 n_reference_samples 146 recent_samples_proportion 0.1 threshold 0.8,306,146,0.1,0.8,0.7451574973698868,6.580857992172241,0,None,i7185,6.580857992172241,525.4609375,525.1263020833334,-1,0,3363359
1742457468,1742457487,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2879 n_reference_samples 221 recent_samples_proportion 1 threshold 0.7359511230645495,2879,221,1,0.7359511230645495,0.7459001175815335,7.858701705932617,0,None,i7183,7.858701705932617,524.43359375,524.07421875,-1,0,3363365
1742457486,1742457499,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 752 n_reference_samples 434 recent_samples_proportion 1 threshold 0.7427155677558783,752,434,1,0.7427155677558783,0.7330899189306269,1.4799377918243408,0,None,i7182,1.4799377918243408,526.04296875,525.6861979166666,-1,0,3363372
1742457486,1742457499,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1407 n_reference_samples 500 recent_samples_proportion 1 threshold 0.8,1407,500,1,0.8,0.737174330094684,1.6657180786132812,0,None,i7184,1.6657180786132812,524.30078125,523.19140625,-1,0,3363368
1742457486,1742457499,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1320 n_reference_samples 346 recent_samples_proportion 1 threshold 0.6899723083150753,1320,346,1,0.6899723083150753,0.7377931802710563,2.5304737091064453,0,None,i7184,2.5304737091064453,524.09765625,523.76171875,-1,0,3363370
1742457486,1742457499,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2292 n_reference_samples 441 recent_samples_proportion 0.43393839683377466 threshold 0.5856931704143514,2292,441,0.43393839683377466,0.5856931704143514,0.7436722569465932,2.427412748336792,0,None,i7184,2.427412748336792,525.0234375,524.6861979166666,-1,0,3363369
1742457486,1742457499,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 755 n_reference_samples 419 recent_samples_proportion 0.1 threshold 0.6441477348935595,755,419,0.1,0.6441477348935595,0.7449099572993378,5.164891958236694,0,None,i7185,5.164891958236694,524.4609375,524.1393229166666,-1,0,3363367
1742457486,1742457512,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3438 n_reference_samples 220 recent_samples_proportion 0.1 threshold 0.5,3438,220,0.1,0.5,0.737978835323968,15.755581378936768,0,None,i7186,15.755581378936768,525.80078125,524.7275390625,-1,0,3363366
1742470804,1742470817,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3289 n_reference_samples 500 recent_samples_proportion 1 threshold 0.7074462212124952,3289,500,1,0.7074462212124952,0.7433009468407699,3.268395185470581,0,None,i7183,3.268395185470581,524.1171875,523.7721354166666,-1,0,3370176
1742470812,1742470825,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3572 n_reference_samples 500 recent_samples_proportion 0.677545013377922 threshold 0.8,3572,500,0.677545013377922,0.8,0.7289436227489324,1.2713017463684082,0,None,i7186,1.2713017463684082,525.31640625,524.9778645833334,-1,0,3370186
1742470832,1742470845,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 10 n_reference_samples 500 recent_samples_proportion 0.8290098308849699 threshold 0.7401628051038734,10,500,0.8290098308849699,0.7401628051038734,0.7213317655795531,0.9935789108276367,0,None,i7185,0.9935789108276367,525.30078125,524.9765625,-1,0,3370203
1742470832,1742470845,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2365 n_reference_samples 285 recent_samples_proportion 1 threshold 0.5703726548936957,2365,285,1,0.5703726548936957,0.7438579119995049,3.3795924186706543,0,None,i7180,3.3795924186706543,525.6328125,525.30078125,-1,0,3370213
1742470833,1742470846,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 281 n_reference_samples 500 recent_samples_proportion 0.5445949964918202 threshold 0.7101250573286485,281,500,0.5445949964918202,0.7101250573286485,0.7345751593539204,1.720879077911377,0,None,i7183,1.720879077911377,524.73828125,524.4192708333334,-1,0,3370209
1742470833,1742470846,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2446 n_reference_samples 500 recent_samples_proportion 1 threshold 0.5,2446,500,1,0.5,0.7446005322111516,3.1134254932403564,0,None,i7183,3.1134254932403564,525.7109375,525.3684895833334,-1,0,3370206
1742470833,1742470846,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 10 n_reference_samples 153 recent_samples_proportion 1 threshold 0.8,10,153,1,0.8,0.7187944798564267,1.401491641998291,0,None,i7179,1.401491641998291,524.28515625,523.9192708333334,-1,0,3370217
1742470833,1742470846,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2421 n_reference_samples 418 recent_samples_proportion 0.1 threshold 0.5,2421,418,0.1,0.5,0.7483136332693855,3.3168206214904785,0,None,i7179,3.3168206214904785,524.40234375,524.06640625,-1,0,3370219
1742470837,1742470850,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2265 n_reference_samples 165 recent_samples_proportion 1 threshold 0.8,2265,165,1,0.8,0.7405161210470945,3.7956128120422363,0,None,i7186,3.7956128120422363,524.54296875,524.1888020833334,-1,0,3370199
1742470812,1742470850,38,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2182 n_reference_samples 495 recent_samples_proportion 0.6019953554705748 threshold 0.8,2182,495,0.6019953554705748,0.8,0.7322235286837057,1.279465675354004,0,None,i7182,1.279465675354004,525.9921875,525.6536458333334,-1,0,3370189
1742470833,1742470852,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3424 n_reference_samples 500 recent_samples_proportion 1 threshold 0.6154084722582571,3424,500,1,0.6154084722582571,0.74039235101182,5.918169260025024,0,None,i7179,5.918169260025024,525.328125,524.9869791666666,-1,0,3370215
1742470810,1742470854,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 337 n_reference_samples 422 recent_samples_proportion 1 threshold 0.5,337,422,1,0.5,0.7441054520700539,3.4066786766052246,0,None,i7182,3.4066786766052246,525.54296875,525.20703125,-1,0,3370182
1742470812,1742470856,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2202 n_reference_samples 144 recent_samples_proportion 0.5901235123242045 threshold 0.7461221417864602,2202,144,0.5901235123242045,0.7461221417864602,0.7457763475462591,4.729415655136108,0,None,i7182,4.729415655136108,525.6640625,525.3307291666666,-1,0,3370195
1742470852,1742470865,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2277 n_reference_samples 277 recent_samples_proportion 0.1 threshold 0.5,2277,277,0.1,0.5,0.7462095426697196,3.5251898765563965,0,None,i7185,3.5251898765563965,524.796875,524.46484375,-1,0,3370221
1742470863,1742470876,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 1860 n_reference_samples 268 recent_samples_proportion 1 threshold 0.7537048691789631,1860,268,1,0.7537048691789631,0.7324710687542546,1.7884531021118164,0,None,i7186,1.7884531021118164,524.03125,523.6953125,-1,0,3370229
1742470863,1742470876,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3821 n_reference_samples 336 recent_samples_proportion 0.8255431934669873 threshold 0.7579835230741935,3821,336,0.8255431934669873,0.7579835230741935,0.7340181941951853,1.8204903602600098,0,None,i7179,1.8204903602600098,525.9921875,525.65625,-1,0,3370257
1742470863,1742470876,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3384 n_reference_samples 500 recent_samples_proportion 0.7309408926490552 threshold 0.7101756303889836,3384,500,0.7309408926490552,0.7101756303889836,0.7319141035955196,2.217083215713501,0,None,i7179,2.217083215713501,524.1953125,523.8541666666666,-1,0,3370261
1742470863,1742470876,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 224 n_reference_samples 265 recent_samples_proportion 0.4110837035385722 threshold 0.8,224,265,0.4110837035385722,0.8,0.7408874311529179,2.6604115962982178,0,None,i7184,2.6604115962982178,524.9375,524.5833333333334,-1,0,3370235
1742470863,1742470876,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2244 n_reference_samples 144 recent_samples_proportion 0.5302987771880566 threshold 0.8,2244,144,0.5302987771880566,0.8,0.7481279782164738,4.535629987716675,0,None,i7182,4.535629987716675,524.765625,524.4140625,-1,0,3370253
1742470863,1742470876,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 260 n_reference_samples 312 recent_samples_proportion 0.1 threshold 0.8,260,312,0.1,0.8,0.7460238876168079,2.8544178009033203,0,None,i7184,2.8544178009033203,525.01171875,524.6953125,-1,0,3370240
1742470863,1742470876,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2589 n_reference_samples 379 recent_samples_proportion 1 threshold 0.8,2589,379,1,0.8,0.7329042638777152,1.1667392253875732,0,None,i7182,1.1667392253875732,524.87109375,524.5559895833334,-1,0,3370248
1742470863,1742470876,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2461 n_reference_samples 500 recent_samples_proportion 0.5313717402790264 threshold 0.5,2461,500,0.5313717402790264,0.5,0.7464570827402686,2.9382033348083496,0,None,i7183,2.9382033348083496,525.0078125,524.6731770833334,-1,0,3370244
1742470852,1742470884,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2439 n_reference_samples 50 recent_samples_proportion 1 threshold 0.5,2439,50,1,0.5,0.7298100129958537,21.65936851501465,0,None,i7185,21.65936851501465,528.48046875,525.7875,-1,0,3370224
1742470872,1742470885,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2439 n_reference_samples 275 recent_samples_proportion 0.1 threshold 0.8,2439,275,0.1,0.8,0.7497988736926791,4.91323447227478,0,None,i7185,4.91323447227478,524.12890625,523.8151041666666,-1,0,3370265
1742470872,1742470885,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 350 n_reference_samples 500 recent_samples_proportion 0.1 threshold 0.5,350,500,0.1,0.5,0.7458382325638963,2.324838638305664,0,None,i7180,2.324838638305664,525.06640625,524.7265625,-1,0,3370271
1742470893,1742470906,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 10 n_reference_samples 500 recent_samples_proportion 1 threshold 0.6911961193801289,10,500,1,0.6911961193801289,0.7299956680487654,0.916050910949707,0,None,i7184,0.916050910949707,524.49609375,524.15234375,-1,0,3370289
1742470893,1742470906,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 625 n_reference_samples 500 recent_samples_proportion 1 threshold 0.8,625,500,1,0.8,0.7324091837366173,1.211205244064331,0,None,i7184,1.211205244064331,524.78515625,524.44140625,-1,0,3370284
1742470893,1742470906,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 3800 n_reference_samples 308 recent_samples_proportion 1 threshold 0.69578525960162,3800,308,1,0.69578525960162,0.7356890896713906,4.335514068603516,0,None,i7183,4.335514068603516,524.8671875,524.5299479166666,-1,0,3370295
1742470894,1742470906,12,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 10 n_reference_samples 110 recent_samples_proportion 0.62875888802279 threshold 0.5980681657803751,10,110,0.62875888802279,0.5980681657803751,0.7204034903149947,1.592994213104248,0,None,i7185,1.592994213104248,526.03515625,525.6875,-1,0,3370279
1742470892,1742470918,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py NOAAWeather 2000 HoeffdingTreeClassifier D3 recent_samples_size 2847 n_reference_samples 147 recent_samples_proportion 0.1 threshold 0.8,2847,147,0.1,0.8,0.7437341419642305,13.55148196220398,0,None,i7186,13.55148196220398,524.234375,523.9990234375,-1,0,3370275
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1742470821.202698,30,10,33
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1742470823.3508117,30,11,37
1742470823.826131,30,11,37
1742470826.0454993,30,12,40
1742470826.1014616,30,12,40
1742470826.6288612,30,12,40
1742470828.7283628,30,13,43
1742470828.8096023,30,13,43
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1742470831.7130022,30,14,47
1742470832.1095145,30,14,47
1742470834.6468556,30,15,50
1742470834.7593997,30,15,50
1742470835.2206147,30,15,50
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1742470854.791268,30,21,70
1742470857.1302736,30,22,73
1742470857.1814187,30,22,73
1742470857.651736,30,22,73
1742470859.5343344,30,23,77
1742470859.6914186,30,23,77
1742470860.1596763,30,23,77
1742470862.4873793,30,24,80
1742470862.5483875,30,24,80
1742470863.0436552,30,24,80
1742470865.293317,30,25,83
1742470865.3426383,30,25,83
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1742470867.5358937,30,26,87
1742470867.6491947,30,26,87
1742470868.079199,30,26,87
1742470870.1526818,30,27,90
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1742470872.6505525,30,28,93
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1742470880.1059806,30,30,100
1742470881.5893273,30,29,97
1742470881.846873,30,29,97
1742470883.233581,30,28,93
1742470884.6656659,30,28,93
1742470886.0074306,30,27,90
1742470886.3005338,30,27,90
1742470888.1247885,30,26,87
1742470888.4431608,30,26,87
1742470889.911202,30,25,83
1742470890.189952,30,25,83
1742470891.6798377,30,24,80
1742470892.0283551,30,24,80
1742470893.5083325,30,23,77
1742470893.9568808,30,23,77
1742470895.4905293,30,22,73
1742470895.7257876,30,22,73
1742470897.1382012,30,21,70
1742470897.4332535,30,21,70
1742470898.8007615,30,20,67
1742470899.0918303,30,20,67
1742470900.9347126,30,19,63
1742470901.1448727,30,19,63
1742470902.8624277,30,18,60
1742470903.0948303,30,18,60
1742470904.5118074,30,17,57
1742470904.7824035,30,17,57
1742470906.3095794,30,16,53
1742470906.5948157,30,16,53
1742470908.2405667,30,15,50
1742470908.5975082,30,15,50
1742470909.959956,30,14,47
1742470910.1687849,30,14,47
1742470911.4606984,30,13,43
1742470911.6408806,30,13,43
1742470913.401957,30,12,40
1742470913.6995592,30,12,40
1742470915.131399,30,11,37
1742470915.375563,30,11,37
1742470916.6251729,30,10,33
1742470916.8132699,30,10,33
1742470918.1302354,30,9,30
1742470918.3204467,30,9,30
1742470919.6687727,30,8,27
1742470919.9046845,30,8,27
1742470921.2927961,30,7,23
1742470921.5772736,30,7,23
1742470922.839834,30,6,20
1742470923.0511706,30,6,20
1742470924.773511,30,5,17
1742470925.0368485,30,5,17
1742470926.4492972,30,4,13
1742470926.665474,30,4,13
1742470927.9164739,30,3,10
1742470928.1871128,30,3,10
1742470929.5352292,30,2,7
1742470929.780916,30,2,7
1742470931.1170034,30,1,3
1742470931.3473086,30,1,3
1742470934.313807,30,0,0
1742470934.4837058,30,0,0
Skipped tabs:
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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 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}
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width: 17px;
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}
: :-webkit-scrollbar-button: horizontal: end{
width: 17px;
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}
.window{
box-shadow: inset -1px -1px #00138c,inset 1px 1px #0831d9,inset -2px -2px #001ea0,inset 2px 2px #166aee,inset -3px -3px #003bda,inset 3px 3px #0855dd;
border-top-left-radius: 8px;
border-top-right-radius: 8px;
padding: 0 0 3px;
-webkit-font-smoothing: antialiased
}
.title-bar{
background: linear-gradient(180deg,#0997ff,#0053ee 8%,#0050ee 40%,#06f 88%,#06f 93%,#005bff 95%,#003dd7 96%,#003dd7);
padding: 3px 5px 3px 3px;
border-top: 1px solid #0831d9;
border-left: 1px solid #0831d9;
border-right: 1px solid #001ea0;
border-top-left-radius: 8px;
border-top-right-radius: 7px;
font-size: 13px;
text-shadow: 1px 1px #0f1089;
height: 21px
}
.title-bar-text{
padding-left: 3px
}
.title-bar-controls{
display: flex
}
.title-bar-controls button{
min-width: 21px;
min-height: 21px;
margin-left: 2px;
background-repeat: no-repeat;
background-position: 50%;
box-shadow: none;
background-color: #0050ee;
transition: background .1s;
border: none
}
.title-bar-controls button: active,.title-bar-controls button: focus,.title-bar-controls button: hover{
box-shadow: none!important
}
.title-bar-controls button[aria-label=Minimize]{
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stroke='%239e3217' d='M2 10h1'/%3E%3Cpath stroke='%23b4381a' d='M3 10h1'/%3E%3Cpath stroke='%23df9a87' d='M10 10h1m-2 1h1m-2 2h1'/%3E%3Cpath stroke='%23c6441f' d='M13 10h1m3 0h1m-8 3h1m-1 3h1'/%3E%3Cpath stroke='%23c74520' d='M14 10h2m-6 4h1m-1 1h1m7 2h1m-7 1h1m4 0h1'/%3E%3Cpath stroke='%23c7451f' d='M16 10h1m1 2h1'/%3E%3Cpath stroke='%237b2711' d='M1 11h1'/%3E%3Cpath stroke='%23a13217' d='M2 11h1'/%3E%3Cpath stroke='%23b7391a' d='M3 11h1'/%3E%3Cpath stroke='%23e09b88' d='M11 11h1'/%3E%3Cpath stroke='%23e29d89' d='M12 11h1'/%3E%3Cpath stroke='%23c94621' d='M13 11h1m-3 2h1'/%3E%3Cpath stroke='%23ca4721' d='M14 11h1m2 1h1m-7 2h1m-1 1h1m0 2h1m2 1h1'/%3E%3Cpath stroke='%23ca4821' d='M15 11h1m1 6h1'/%3E%3Cpath stroke='%23c94620' d='M16 11h1m1 3h1m-8 2h1m6 0h1'/%3E%3Cpath stroke='%23c84620' d='M17 11h1m0 2h1'/%3E%3Cpath stroke='%23a53418' d='M2 12h1'/%3E%3Cpath stroke='%23b83a1b' d='M3 12h1'/%3E%3Cpath stroke='%23e19d89' d='M11 12h1'/%3E%3Cpath stroke='%23e39e89' d='M12 12h1'/%3E%3Cpath stroke='%23e0947c' d='M13 12h1'/%3E%3Cpath stroke='%23cc4a22' d='M14 12h1m-3 2h1m4 0h1m-6 1h1'/%3E%3Cpath stroke='%23cd4a22' d='M15 12h1m0 1h1m0 2h1m-5 1h1m1 1h1'/%3E%3Cpath stroke='%23cb4922' d='M16 12h1m0 1h1m-5 4h1'/%3E%3Cpath stroke='%23c3411e' d='M19 12h1m-1 1h1m-1 4h1m-8 2h2m3 0h1'/%3E%3Cpath stroke='%23a93618' d='M2 13h1'/%3E%3Cpath stroke='%23dd9987' d='M7 13h1m-2 2h1'/%3E%3Cpath stroke='%23e39f8a' d='M12 13h1'/%3E%3Cpath stroke='%23e59f8b' d='M13 13h1'/%3E%3Cpath stroke='%23e5a08b' d='M14 13h1m-2 1h1'/%3E%3Cpath stroke='%23ce4c23' d='M15 13h1m0 3h1'/%3E%3Cpath stroke='%23882b13' d='M1 14h1'/%3E%3Cpath stroke='%23e6a08b' d='M14 14h1'/%3E%3Cpath stroke='%23e6a18b' d='M15 14h1m-2 1h1'/%3E%3Cpath stroke='%23ce4b23' d='M16 14h1m-4 1h1'/%3E%3Cpath stroke='%238b2c14' d='M1 15h1m-1 1h1'/%3E%3Cpath stroke='%23ac3619' d='M2 15h1'/%3E%3Cpath stroke='%23d76b48' d='M15 15h1'/%3E%3Cpath stroke='%23cf4c23' d='M16 15h1m-2 1h1'/%3E%3Cpath stroke='%23c94721' d='M18 15h1m-3 3h1'/%3E%3Cpath stroke='%23bb3c1b' d='M3 16h1'/%3E%3Cpath stroke='%23bf3e1d' d='M6 16h1'/%3E%3Cpath stroke='%23cb4821' d='M12 16h1'/%3E%3Cpath stroke='%23cd4b23' d='M14 16h1'/%3E%3Cpath stroke='%23cc4922' d='M17 16h1m-4 1h1m1 0h1'/%3E%3Cpath stroke='%238d2d14' d='M1 17h1'/%3E%3Cpath stroke='%23bc3c1b' d='M3 17h1m-1 1h1'/%3E%3Cpath stroke='%23c84520' d='M11 17h1m1 1h1'/%3E%3Cpath stroke='%23ae3719' d='M2 18h1'/%3E%3Cpath stroke='%23c94720' d='M14 18h1'/%3E%3Cpath stroke='%23c95839' d='M19 18h1'/%3E%3Cpath stroke='%23a7bdf0' d='M0 19h1m0 1h1'/%3E%3Cpath stroke='%23ead7d3' d='M1 19h1'/%3E%3Cpath stroke='%23b34e35' d='M2 19h1'/%3E%3Cpath stroke='%23c03e1c' d='M8 19h1'/%3E%3Cpath stroke='%23c9583a' d='M18 19h1'/%3E%3Cpath stroke='%23f3dbd4' d='M19 19h1'/%3E%3Cpath stroke='%23a7bcef' d='M20 19h1m-2 1h1'/%3E%3C/svg%3E")
}
.status-bar{
margin: 0 3px;
box-shadow: inset 0 1px 2px grey;
padding: 2px 1px;
gap: 0
}
.status-bar-field{
-webkit-font-smoothing: antialiased;
box-shadow: none;
padding: 1px 2px;
border-right: 1px solid rgba(208,206,191,.75);
border-left: 1px solid hsla(0,0%,100%,.75)
}
.status-bar-field: first-of-type{
border-left: none
}
.status-bar-field: last-of-type{
border-right: none
}
button{
-webkit-font-smoothing: antialiased;
box-sizing: border-box;
border: 1px solid #003c74;
background: linear-gradient(180deg,#fff,#ecebe5 86%,#d8d0c4);
box-shadow: none;
border-radius: 3px
}
button: not(: disabled).active,button: not(: disabled): active{
box-shadow: none;
background: linear-gradient(180deg,#cdcac3,#e3e3db 8%,#e5e5de 94%,#f2f2f1)
}
button: not(: disabled): hover{
box-shadow: inset -1px 1px #fff0cf,inset 1px 2px #fdd889,inset -2px 2px #fbc761,inset 2px -2px #e5a01a
}
button.focused,button: focus{
box-shadow: inset -1px 1px #cee7ff,inset 1px 2px #98b8ea,inset -2px 2px #bcd4f6,inset 1px -1px #89ade4,inset 2px -2px #89ade4
}
button: :-moz-focus-inner{
border: 0
}
input,label,option,select,textarea{
-webkit-font-smoothing: antialiased
}
input[type=radio]{
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
margin: 0;
background: 0;
position: fixed;
opacity: 0;
border: none
}
input[type=radio]+label{
line-height: 16px
}
input[type=radio]+label: before{
background: linear-gradient(135deg,#dcdcd7,#fff);
border-radius: 50%;
border: 1px solid #1d5281
}
input[type=radio]: not([disabled]): not(: active)+label: hover: before{
box-shadow: inset -2px -2px #f8b636,inset 2px 2px #fedf9c
}
input[type=radio]: active+label: before{
background: linear-gradient(135deg,#b0b0a7,#e3e1d2)
}
input[type=radio]: checked+label: after{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 5 5' shape-rendering='crispEdges'%3E%3Cpath stroke='%23a9dca6' d='M1 0h1M0 1h1'/%3E%3Cpath stroke='%234dbf4a' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23a0d29e' d='M3 0h1M0 3h1'/%3E%3Cpath stroke='%2355d551' d='M1 1h1'/%3E%3Cpath stroke='%2343c33f' d='M2 1h1'/%3E%3Cpath stroke='%2329a826' d='M3 1h1'/%3E%3Cpath stroke='%239acc98' d='M4 1h1M1 4h1'/%3E%3Cpath stroke='%2342c33f' d='M1 2h1'/%3E%3Cpath stroke='%2338b935' d='M2 2h1'/%3E%3Cpath stroke='%2321a121' d='M3 2h1'/%3E%3Cpath stroke='%23269623' d='M4 2h1'/%3E%3Cpath stroke='%232aa827' d='M1 3h1'/%3E%3Cpath stroke='%2322a220' d='M2 3h1'/%3E%3Cpath stroke='%23139210' d='M3 3h1'/%3E%3Cpath stroke='%2398c897' d='M4 3h1'/%3E%3Cpath stroke='%23249624' d='M2 4h1'/%3E%3Cpath stroke='%2398c997' d='M3 4h1'/%3E%3C/svg%3E")
}
input[type=radio]: focus+label{
outline: 1px dotted #000
}
input[type=radio][disabled]+label: before{
border: 1px solid #cac8bb;
background: #fff
}
input[type=radio][disabled]: checked+label: after{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 5 5' shape-rendering='crispEdges'%3E%3Cpath stroke='%23e8e6da' d='M1 0h1M0 1h1'/%3E%3Cpath stroke='%23d2ceb5' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23e5e3d4' d='M3 0h1M0 3h1'/%3E%3Cpath stroke='%23d7d3bd' d='M1 1h1'/%3E%3Cpath stroke='%23d0ccb2' d='M2 1h1M1 2h1'/%3E%3Cpath stroke='%23c7c2a2' d='M3 1h1M1 3h1'/%3E%3Cpath stroke='%23e2dfd0' d='M4 1h1M1 4h1'/%3E%3Cpath stroke='%23cdc8ac' d='M2 2h1'/%3E%3Cpath stroke='%23c5bf9f' d='M3 2h1M2 3h1'/%3E%3Cpath stroke='%23c3bd9c' d='M4 2h1'/%3E%3Cpath stroke='%23bfb995' d='M3 3h1'/%3E%3Cpath stroke='%23e2dfcf' d='M4 3h1M3 4h1'/%3E%3Cpath stroke='%23c4be9d' d='M2 4h1'/%3E%3C/svg%3E")
}
input[type=email],input[type=password],textarea: :selection{
background: #2267cb;
color: #fff
}
input[type=range]: :-webkit-slider-thumb{
height: 21px;
width: 11px;
background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 11 21' shape-rendering='crispEdges'%3E%3Cpath stroke='%23becbd3' d='M1 0h1M0 1h1'/%3E%3Cpath stroke='%23b6c5cd' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23b5c4cd' d='M3 0h5M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23afbfc8' d='M8 0h1M0 14h1'/%3E%3Cpath stroke='%239fb2be' d='M9 0h1M0 15h1'/%3E%3Cpath stroke='%23a6d1b1' d='M1 1h1'/%3E%3Cpath stroke='%236fd16e' d='M2 1h1M1 2h1'/%3E%3Cpath stroke='%2367ce65' d='M3 1h1M1 3h1'/%3E%3Cpath stroke='%2366ce64' d='M4 1h3'/%3E%3Cpath stroke='%2362cd61' d='M7 1h1'/%3E%3Cpath stroke='%2345c343' d='M8 1h1M7 2h1'/%3E%3Cpath stroke='%2363ac76' d='M9 1h1M2 16h1m0 1h1m0 1h1'/%3E%3Cpath stroke='%23879aa6' d='M10 1h1'/%3E%3Cpath stroke='%2363cd62' d='M2 2h1'/%3E%3Cpath stroke='%2349c547' d='M3 2h1M2 3h1'/%3E%3Cpath stroke='%2347c446' d='M4 2h3'/%3E%3Cpath stroke='%2321b71f' d='M8 2h1'/%3E%3Cpath stroke='%231da41c' d='M9 2h1'/%3E%3Cpath stroke='%237d8e99' d='M10 2h1'/%3E%3Cpath stroke='%2325b923' d='M3 3h1'/%3E%3Cpath stroke='%2321b81f' d='M4 3h4M2 15h1'/%3E%3Cpath stroke='%231ea71c' d='M8 3h1'/%3E%3Cpath stroke='%231b9619' d='M9 3h1'/%3E%3Cpath stroke='%23778892' d='M10 3h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f7f7f4' d='M1 4h1M1 5h1M1 6h1M1 7h1M1 8h1M1 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f5f5f2' d='M2 4h1M2 5h1M2 6h1M2 7h1M2 8h1M2 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f3f3ef' d='M3 4h5M3 5h5M3 6h5M3 7h5M3 8h5M3 9h5m-5 1h5m-5 1h5m-5 1h5m-5 1h4m-4 1h3m-2 1h1'/%3E%3Cpath stroke='%23dcdcd9' d='M8 4h1M8 5h1M8 6h1M8 7h1M8 8h1M8 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c3c3c0' d='M9 4h1M9 5h1M9 6h1M9 7h1M9 8h1M9 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f1f1ed' d='M7 13h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%23dbdbd8' d='M8 13h1'/%3E%3Cpath stroke='%23c4c4c1' d='M9 13h1'/%3E%3Cpath stroke='%234bc549' d='M1 14h1'/%3E%3Cpath stroke='%23f4f4f1' d='M2 14h1'/%3E%3Cpath stroke='%23e6e6e2' d='M7 14h1m-2 1h1'/%3E%3Cpath stroke='%23cececa' d='M8 14h1'/%3E%3Cpath stroke='%231a9319' d='M9 14h1'/%3E%3Cpath stroke='%23788993' d='M10 14h1'/%3E%3Cpath stroke='%2369b17b' d='M1 15h1'/%3E%3Cpath stroke='%23f2f2ee' d='M3 15h1m0 1h1'/%3E%3Cpath stroke='%23d0d0cc' d='M7 15h1m-2 1h1'/%3E%3Cpath stroke='%231a9118' d='M8 15h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%234c845a' d='M9 15h1'/%3E%3Cpath stroke='%2372838d' d='M10 15h1'/%3E%3Cpath stroke='%2391a6b2' d='M1 16h1m0 1h1m0 1h1m0 1h1'/%3E%3Cpath stroke='%2321b61f' d='M3 16h1m0 1h1'/%3E%3Cpath stroke='%23e7e7e3' d='M5 16h1'/%3E%3Cpath stroke='%234b8259' d='M8 16h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%236e7e88' d='M9 16h1m-2 1h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%23d7d7d4' d='M5 17h1'/%3E%3Cpath stroke='%231da21b' d='M5 18h1'/%3E%3Cpath stroke='%23589868' d='M5 19h1'/%3E%3Cpath stroke='%2380929e' d='M5 20h1'/%3E%3C/svg%3E");
transform: translateY(-8px)
}
input[type=range]: :-moz-range-thumb{
height: 21px;
width: 11px;
border: 0;
border-radius: 0;
background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 11 21' shape-rendering='crispEdges'%3E%3Cpath stroke='%23becbd3' d='M1 0h1M0 1h1'/%3E%3Cpath stroke='%23b6c5cd' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23b5c4cd' d='M3 0h5M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23afbfc8' d='M8 0h1M0 14h1'/%3E%3Cpath stroke='%239fb2be' d='M9 0h1M0 15h1'/%3E%3Cpath stroke='%23a6d1b1' d='M1 1h1'/%3E%3Cpath stroke='%236fd16e' d='M2 1h1M1 2h1'/%3E%3Cpath stroke='%2367ce65' d='M3 1h1M1 3h1'/%3E%3Cpath stroke='%2366ce64' d='M4 1h3'/%3E%3Cpath stroke='%2362cd61' d='M7 1h1'/%3E%3Cpath stroke='%2345c343' d='M8 1h1M7 2h1'/%3E%3Cpath stroke='%2363ac76' d='M9 1h1M2 16h1m0 1h1m0 1h1'/%3E%3Cpath stroke='%23879aa6' d='M10 1h1'/%3E%3Cpath stroke='%2363cd62' d='M2 2h1'/%3E%3Cpath stroke='%2349c547' d='M3 2h1M2 3h1'/%3E%3Cpath stroke='%2347c446' d='M4 2h3'/%3E%3Cpath stroke='%2321b71f' d='M8 2h1'/%3E%3Cpath stroke='%231da41c' d='M9 2h1'/%3E%3Cpath stroke='%237d8e99' d='M10 2h1'/%3E%3Cpath stroke='%2325b923' d='M3 3h1'/%3E%3Cpath stroke='%2321b81f' d='M4 3h4M2 15h1'/%3E%3Cpath stroke='%231ea71c' d='M8 3h1'/%3E%3Cpath stroke='%231b9619' d='M9 3h1'/%3E%3Cpath stroke='%23778892' d='M10 3h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f7f7f4' d='M1 4h1M1 5h1M1 6h1M1 7h1M1 8h1M1 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f5f5f2' d='M2 4h1M2 5h1M2 6h1M2 7h1M2 8h1M2 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f3f3ef' d='M3 4h5M3 5h5M3 6h5M3 7h5M3 8h5M3 9h5m-5 1h5m-5 1h5m-5 1h5m-5 1h4m-4 1h3m-2 1h1'/%3E%3Cpath stroke='%23dcdcd9' d='M8 4h1M8 5h1M8 6h1M8 7h1M8 8h1M8 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c3c3c0' d='M9 4h1M9 5h1M9 6h1M9 7h1M9 8h1M9 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f1f1ed' d='M7 13h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%23dbdbd8' d='M8 13h1'/%3E%3Cpath stroke='%23c4c4c1' d='M9 13h1'/%3E%3Cpath stroke='%234bc549' d='M1 14h1'/%3E%3Cpath stroke='%23f4f4f1' d='M2 14h1'/%3E%3Cpath stroke='%23e6e6e2' d='M7 14h1m-2 1h1'/%3E%3Cpath stroke='%23cececa' d='M8 14h1'/%3E%3Cpath stroke='%231a9319' d='M9 14h1'/%3E%3Cpath stroke='%23788993' d='M10 14h1'/%3E%3Cpath stroke='%2369b17b' d='M1 15h1'/%3E%3Cpath stroke='%23f2f2ee' d='M3 15h1m0 1h1'/%3E%3Cpath stroke='%23d0d0cc' d='M7 15h1m-2 1h1'/%3E%3Cpath stroke='%231a9118' d='M8 15h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%234c845a' d='M9 15h1'/%3E%3Cpath stroke='%2372838d' d='M10 15h1'/%3E%3Cpath stroke='%2391a6b2' d='M1 16h1m0 1h1m0 1h1m0 1h1'/%3E%3Cpath stroke='%2321b61f' d='M3 16h1m0 1h1'/%3E%3Cpath stroke='%23e7e7e3' d='M5 16h1'/%3E%3Cpath stroke='%234b8259' d='M8 16h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%236e7e88' d='M9 16h1m-2 1h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%23d7d7d4' d='M5 17h1'/%3E%3Cpath stroke='%231da21b' d='M5 18h1'/%3E%3Cpath stroke='%23589868' d='M5 19h1'/%3E%3Cpath stroke='%2380929e' d='M5 20h1'/%3E%3C/svg%3E");
transform: translateY(2px)
}
input[type=range]: :-webkit-slider-runnable-track{
width: 100%;
height: 2px;
box-sizing: border-box;
background: #ecebe4;
border-right: 1px solid #f3f2ea;
border-bottom: 1px solid #f3f2ea;
border-radius: 2px;
box-shadow: 1px 0 0 #fff,1px 1px 0 #fff,0 1px 0 #fff,-1px 0 0 #9d9c99,-1px -1px 0 #9d9c99,0 -1px 0 #9d9c99,-1px 1px 0 #fff,1px -1px #9d9c99
}
input[type=range]: :-moz-range-track{
width: 100%;
height: 2px;
box-sizing: border-box;
background: #ecebe4;
border-right: 1px solid #f3f2ea;
border-bottom: 1px solid #f3f2ea;
border-radius: 2px;
box-shadow: 1px 0 0 #fff,1px 1px 0 #fff,0 1px 0 #fff,-1px 0 0 #9d9c99,-1px -1px 0 #9d9c99,0 -1px 0 #9d9c99,-1px 1px 0 #fff,1px -1px #9d9c99
}
input[type=range].has-box-indicator: :-webkit-slider-thumb{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 11 22' shape-rendering='crispEdges'%3E%3Cpath stroke='%23f2f1e7' d='M0 0h1m9 0h1M0 21h1m9 0h1'/%3E%3Cpath stroke='%23879aa6' d='M1 0h1m8 20h1'/%3E%3Cpath stroke='%237d8e99' d='M2 0h1m7 19h1'/%3E%3Cpath stroke='%23778892' d='M3 0h5m2 3h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23788993' d='M8 0h1m1 2h1'/%3E%3Cpath stroke='%2372838d' d='M9 0h1m0 1h1'/%3E%3Cpath stroke='%239fb2be' d='M0 1h1m8 20h1'/%3E%3Cpath stroke='%2363af76' d='M1 1h1m7 19h1'/%3E%3Cpath stroke='%231eab1c' d='M2 1h1m6 18h1'/%3E%3Cpath stroke='%231c9d1a' d='M3 1h1'/%3E%3Cpath stroke='%231b9a1a' d='M4 1h3m1 0h1m0 1h1'/%3E%3Cpath stroke='%231b9b1a' d='M7 1h1'/%3E%3Cpath stroke='%234d875b' d='M9 1h1'/%3E%3Cpath stroke='%23afbfc8' d='M0 2h1m7 19h1'/%3E%3Cpath stroke='%2346ca44' d='M1 2h1m5 17h1m0 1h1'/%3E%3Cpath stroke='%2322be20' d='M2 2h1m5 17h1'/%3E%3Cpath stroke='%231faf1d' d='M3 2h1'/%3E%3Cpath stroke='%231fae1d' d='M4 2h3'/%3E%3Cpath stroke='%231fad1d' d='M7 2h1'/%3E%3Cpath stroke='%231da11b' d='M8 2h1'/%3E%3Cpath stroke='%23b5c4cd' d='M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m2 3h5'/%3E%3Cpath stroke='%23f7f7f4' d='M1 3h1M1 4h1M1 5h1M1 6h1M1 7h1M1 8h1M1 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f5f5f2' d='M2 3h1M2 4h1M2 5h1M2 6h1M2 7h1M2 8h1M2 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f3f3ef' d='M3 3h4M3 4h5M3 5h5M3 6h5M3 7h5M3 8h5M3 9h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5'/%3E%3Cpath stroke='%23f1f1ed' d='M7 3h1'/%3E%3Cpath stroke='%23dbdbd8' d='M8 3h1'/%3E%3Cpath stroke='%23c4c4c1' d='M9 3h1'/%3E%3Cpath stroke='%23ddddd9' d='M8 4h1M8 18h1'/%3E%3Cpath stroke='%23c6c6c3' d='M9 4h1M9 18h1'/%3E%3Cpath stroke='%23dcdcd9' d='M8 5h1M8 6h1M8 7h1M8 8h1M8 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c3c3c0' d='M9 5h1M9 6h1M9 7h1M9 8h1M9 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b6c5cd' d='M0 19h1m1 2h1'/%3E%3Cpath stroke='%2370d66f' d='M1 19h1m0 1h1'/%3E%3Cpath stroke='%2364d362' d='M2 19h1'/%3E%3Cpath stroke='%234acb48' d='M3 19h1'/%3E%3Cpath stroke='%2348cb46' d='M4 19h3'/%3E%3Cpath stroke='%23becbd3' d='M0 20h1m0 1h1'/%3E%3Cpath stroke='%23a6d2b1' d='M1 20h1'/%3E%3Cpath stroke='%2367d466' d='M3 20h1'/%3E%3Cpath stroke='%2366d465' d='M4 20h3'/%3E%3Cpath stroke='%2363d362' d='M7 20h1'/%3E%3C/svg%3E");transform: translateY(-10px)
}
input[type=range].has-box-indicator: :-moz-range-thumb{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 11 22' shape-rendering='crispEdges'%3E%3Cpath stroke='%23f2f1e7' d='M0 0h1m9 0h1M0 21h1m9 0h1'/%3E%3Cpath stroke='%23879aa6' d='M1 0h1m8 20h1'/%3E%3Cpath stroke='%237d8e99' d='M2 0h1m7 19h1'/%3E%3Cpath stroke='%23778892' d='M3 0h5m2 3h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23788993' d='M8 0h1m1 2h1'/%3E%3Cpath stroke='%2372838d' d='M9 0h1m0 1h1'/%3E%3Cpath stroke='%239fb2be' d='M0 1h1m8 20h1'/%3E%3Cpath stroke='%2363af76' d='M1 1h1m7 19h1'/%3E%3Cpath stroke='%231eab1c' d='M2 1h1m6 18h1'/%3E%3Cpath stroke='%231c9d1a' d='M3 1h1'/%3E%3Cpath stroke='%231b9a1a' d='M4 1h3m1 0h1m0 1h1'/%3E%3Cpath stroke='%231b9b1a' d='M7 1h1'/%3E%3Cpath stroke='%234d875b' d='M9 1h1'/%3E%3Cpath stroke='%23afbfc8' d='M0 2h1m7 19h1'/%3E%3Cpath stroke='%2346ca44' d='M1 2h1m5 17h1m0 1h1'/%3E%3Cpath stroke='%2322be20' d='M2 2h1m5 17h1'/%3E%3Cpath stroke='%231faf1d' d='M3 2h1'/%3E%3Cpath stroke='%231fae1d' d='M4 2h3'/%3E%3Cpath stroke='%231fad1d' d='M7 2h1'/%3E%3Cpath stroke='%231da11b' d='M8 2h1'/%3E%3Cpath stroke='%23b5c4cd' d='M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m2 3h5'/%3E%3Cpath stroke='%23f7f7f4' d='M1 3h1M1 4h1M1 5h1M1 6h1M1 7h1M1 8h1M1 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f5f5f2' d='M2 3h1M2 4h1M2 5h1M2 6h1M2 7h1M2 8h1M2 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f3f3ef' d='M3 3h4M3 4h5M3 5h5M3 6h5M3 7h5M3 8h5M3 9h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5'/%3E%3Cpath stroke='%23f1f1ed' d='M7 3h1'/%3E%3Cpath stroke='%23dbdbd8' d='M8 3h1'/%3E%3Cpath stroke='%23c4c4c1' d='M9 3h1'/%3E%3Cpath stroke='%23ddddd9' d='M8 4h1M8 18h1'/%3E%3Cpath stroke='%23c6c6c3' d='M9 4h1M9 18h1'/%3E%3Cpath stroke='%23dcdcd9' d='M8 5h1M8 6h1M8 7h1M8 8h1M8 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c3c3c0' d='M9 5h1M9 6h1M9 7h1M9 8h1M9 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b6c5cd' d='M0 19h1m1 2h1'/%3E%3Cpath stroke='%2370d66f' d='M1 19h1m0 1h1'/%3E%3Cpath stroke='%2364d362' d='M2 19h1'/%3E%3Cpath stroke='%234acb48' d='M3 19h1'/%3E%3Cpath stroke='%2348cb46' d='M4 19h3'/%3E%3Cpath stroke='%23becbd3' d='M0 20h1m0 1h1'/%3E%3Cpath stroke='%23a6d2b1' d='M1 20h1'/%3E%3Cpath stroke='%2367d466' d='M3 20h1'/%3E%3Cpath stroke='%2366d465' d='M4 20h3'/%3E%3Cpath stroke='%2363d362' d='M7 20h1'/%3E%3C/svg%3E");transform: translateY(0)
}
.is-vertical>input[type=range]: :-webkit-slider-runnable-track{
border-left: 1px solid #f3f2ea;
border-right: 0;
border-bottom: 1px solid #f3f2ea;
box-shadow: -1px 0 0 #fff,-1px 1px 0 #fff,0 1px 0 #fff,1px 0 0 #9d9c99,1px -1px 0 #9d9c99,0 -1px 0 #9d9c99,1px 1px 0 #fff,-1px -1px #9d9c99
}
.is-vertical>input[type=range]: :-moz-range-track{
border-left: 1px solid #f3f2ea;
border-right: 0;
border-bottom: 1px solid #f3f2ea;
box-shadow: -1px 0 0 #fff,-1px 1px 0 #fff,0 1px 0 #fff,1px 0 0 #9d9c99,1px -1px 0 #9d9c99,0 -1px 0 #9d9c99,1px 1px 0 #fff,-1px -1px #9d9c99
}
fieldset{
box-shadow: none;
background: #fff;
border: 1px solid #d0d0bf;
border-radius: 4px;
padding-top: 10px
}
legend{
background: transparent;
color: #0046d5
}
.field-row{
display: flex;
align-items: center
}
.field-row>*+*{
margin-left: 6px
}
[class^=field-row]+[class^=field-row]{
margin-top: 6px
}
.field-row-stacked{
display: flex;
flex-direction: column
}
.field-row-stacked *+*{
margin-top: 6px
}
menu[role=tablist] button{
background: linear-gradient(180deg,#fff,#fafaf9 26%,#f0f0ea 95%,#ecebe5);
margin-left: -1px;
margin-right: 2px;
border-radius: 0;
border-color: #91a7b4;
border-top-right-radius: 3px;
border-top-left-radius: 3px;
padding: 0 12px 3px
}
menu[role=tablist] button: hover{
box-shadow: unset;
border-top: 1px solid #e68b2c;
box-shadow: inset 0 2px #ffc73c
}
menu[role=tablist] button[aria-selected=true]{
border-color: #919b9c;
margin-right: -1px;
border-bottom: 1px solid transparent;
border-top: 1px solid #e68b2c;
box-shadow: inset 0 2px #ffc73c
}
menu[role=tablist] button[aria-selected=true]: first-of-type: before{
content: "";
display: block;
position: absolute;
z-index: -1;
top: 100%;
left: -1px;
height: 2px;
width: 0;
border-left: 1px solid #919b9c
}
[role=tabpanel]{
box-shadow: inset 1px 1px #fcfcfe,inset -1px -1px #fcfcfe,1px 2px 2px 0 rgba(208,206,191,.75)
}
ul.tree-view{
-webkit-font-smoothing: auto;
border: 1px solid #7f9db9;
padding: 2px 5px
}
@keyframes sliding{
0%{
transform: translateX(-30px)
}
to{
transform: translateX(100%)
}
}
progress{
box-sizing: border-box;
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
height: 14px;
border: 1px solid #686868;
border-radius: 4px;
padding: 1px 2px 1px 0;
overflow: hidden;
background-color: #fff;
-webkit-box-shadow: inset 0 0 1px 0 #686868;
-moz-box-shadow: inset 0 0 1px 0 #686868
}
progress,progress: not([value]){
box-shadow: inset 0 0 1px 0 #686868
}
progress: not([value]){
-moz-box-shadow: inset 0 0 1px 0 #686868;
-webkit-box-shadow: inset 0 0 1px 0 #686868;
height: 14px
}
progress[value]: :-webkit-progress-bar{
background-color: transparent
}
progress[value]: :-webkit-progress-value{
border-radius: 2px;
background: repeating-linear-gradient(90deg,#fff 0,#fff 2px,transparent 0,transparent 10px),linear-gradient(180deg,#acedad 0,#7be47d 14%,#4cda50 28%,#2ed330 42%,#42d845 57%,#76e275 71%,#8fe791 85%,#fff)
}
progress[value]: :-moz-progress-bar{
border-radius: 2px;
background: repeating-linear-gradient(90deg,#fff 0,#fff 2px,transparent 0,transparent 10px),linear-gradient(180deg,#acedad 0,#7be47d 14%,#4cda50 28%,#2ed330 42%,#42d845 57%,#76e275 71%,#8fe791 85%,#fff)
}
progress: not([value]): :-webkit-progress-bar{
width: 100%;
background: repeating-linear-gradient(90deg,transparent 0,transparent 8px,#fff 0,#fff 10px,transparent 0,transparent 18px,#fff 0,#fff 20px,transparent 0,transparent 28px,#fff 0,#fff),linear-gradient(180deg,#acedad 0,#7be47d 14%,#4cda50 28%,#2ed330 42%,#42d845 57%,#76e275 71%,#8fe791 85%,#fff);
animation: sliding 2s linear 0s infinite
}
progress: not([value]): :-webkit-progress-bar: not([value]){
animation: sliding 2s linear 0s infinite;
background: repeating-linear-gradient(90deg,transparent 0,transparent 8px,#fff 0,#fff 10px,transparent 0,transparent 18px,#fff 0,#fff 20px,transparent 0,transparent 28px,#fff 0,#fff),linear-gradient(180deg,#acedad 0,#7be47d 14%,#4cda50 28%,#2ed330 42%,#42d845 57%,#76e275 71%,#8fe791 85%,#fff)
}
progress: not([value]){
position: relative
}
progress: not([value]): before{
box-sizing: border-box;
content: "";
position: absolute;
top: 0;
left: 0;
width: 100%;
height: 100%;
background-color: #fff;
-webkit-box-shadow: inset 0 0 1px 0 #686868;
-moz-box-shadow: inset 0 0 1px 0 #686868
}
progress: not([value]): before,progress: not([value]): before: not([value]){
box-shadow: inset 0 0 1px 0 #686868
}
progress: not([value]): before: not([value]){
-moz-box-shadow: inset 0 0 1px 0 #686868;
-webkit-box-shadow: inset 0 0 1px 0 #686868
}
progress: not([value]): after{
box-sizing: border-box;
content: "";
position: absolute;
top: 1px;
left: 2px;
width: 100%;
height: calc(100% - 2px);
padding: 1px 2px;
border-radius: 2px;
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]): after,progress: not([value]): after: not([value]){
animation: sliding 2s linear 0s infinite
}
progress: not([value]): after: not([value]){
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]): :-moz-progress-bar{
width: 100%;
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[
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673.56640625,
2.7
],
[
1742406667,
673.56640625,
4.6
],
[
1742406667,
673.56640625,
5.4
],
[
1742408181,
675.43359375,
5.5
],
[
1742408181,
675.43359375,
2.5
],
[
1742408181,
675.43359375,
5.8
],
[
1742408181,
675.43359375,
5.9
],
[
1742411011,
689.11328125,
6.3
],
[
1742411011,
689.11328125,
7.7
],
[
1742411011,
689.11328125,
6.2
],
[
1742411011,
689.11328125,
7.4
],
[
1742414076,
703.265625,
6.4
],
[
1742414076,
703.265625,
5.3
],
[
1742414076,
703.265625,
5.3
],
[
1742414076,
703.265625,
5.4
],
[
1742418479,
699.10546875,
6.6
],
[
1742418479,
699.10546875,
6.2
],
[
1742418479,
699.10546875,
6.8
],
[
1742418479,
699.10546875,
6.6
],
[
1742423689,
740.2734375,
7
],
[
1742423689,
740.2734375,
7.8
],
[
1742423689,
740.2734375,
7.6
],
[
1742423689,
740.2734375,
11.6
],
[
1742431972,
767.03125,
7.3
],
[
1742431972,
767.03125,
6.5
],
[
1742431972,
767.28125,
6.5
],
[
1742431972,
767.28125,
9.3
],
[
1742437250,
812.609375,
7.5
],
[
1742437250,
812.609375,
6.8
],
[
1742437250,
812.609375,
7
],
[
1742437250,
812.609375,
7
],
[
1742444930,
796.546875,
5.6
],
[
1742444930,
796.546875,
6.5
],
[
1742444930,
796.546875,
6.6
],
[
1742444930,
796.546875,
7
],
[
1742457527,
784.20703125,
4.9
],
[
1742457527,
784.20703125,
3.1
],
[
1742457527,
784.20703125,
3.4
],
[
1742457527,
784.20703125,
5.1
],
[
1742470937,
778.75,
4.7
],
[
1742470937,
778.75,
3.9
],
[
1742470937,
778.75,
3.9
],
[
1742470937,
778.75,
2.6
]
];
var tab_main_worker_cpu_ram_headers_json = [
"timestamp",
"ram_usage_mb",
"cpu_usage_percent"
];
"use strict";
function add_default_layout_data (layout, no_height = 0) {
layout["width"] = get_graph_width();
if (!no_height) {
layout["height"] = get_graph_height();
}
layout["paper_bgcolor"] = 'rgba(0,0,0,0)';
layout["plot_bgcolor"] = 'rgba(0,0,0,0)';
return layout;
}
function get_marker_size() {
return 12;
}
function get_text_color() {
return theme == "dark" ? "white" : "black";
}
function get_font_size() {
return 14;
}
function get_graph_height() {
return 800;
}
function get_font_data() {
return {
size: get_font_size(),
color: get_text_color()
}
}
function get_axis_title_data(name, axis_type = "") {
if(axis_type) {
return {
text: name,
type: axis_type,
font: get_font_data()
};
}
return {
text: name,
font: get_font_data()
};
}
function get_graph_width() {
var width = document.body.clientWidth || window.innerWidth || document.documentElement.clientWidth;
return Math.max(800, Math.floor(width * 0.9));
}
function createTable(data, headers, table_name) {
if (!$("#" + table_name).length) {
console.error("#" + table_name + " not found");
return;
}
new gridjs.Grid({
columns: headers,
data: data,
search: true,
sort: true,
ellipsis: false
}).render(document.getElementById(table_name));
if (typeof apply_theme_based_on_system_preferences === 'function') {
apply_theme_based_on_system_preferences();
}
colorize_table_entries();
add_colorize_to_gridjs_table();
}
function download_as_file(id, filename) {
var text = $("#" + id).text();
var blob = new Blob([text], {
type: "text/plain"
});
var link = document.createElement("a");
link.href = URL.createObjectURL(blob);
link.download = filename;
document.body.appendChild(link);
link.click();
document.body.removeChild(link);
}
function copy_to_clipboard_from_id (id) {
var text = $("#" + id).text();
copy_to_clipboard(text);
}
function copy_to_clipboard(text) {
if (!navigator.clipboard) {
let textarea = document.createElement("textarea");
textarea.value = text;
document.body.appendChild(textarea);
textarea.select();
try {
document.execCommand("copy");
} catch (err) {
console.error("Copy failed:", err);
}
document.body.removeChild(textarea);
return;
}
navigator.clipboard.writeText(text).then(() => {
console.log("Text copied to clipboard");
}).catch(err => {
console.error("Failed to copy text:", err);
});
}
function filterNonEmptyRows(data) {
var new_data = [];
for (var row_idx = 0; row_idx < data.length; row_idx++) {
var line = data[row_idx];
var line_has_empty_data = false;
for (var col_idx = 0; col_idx < line.length; col_idx++) {
var col_header_name = tab_results_headers_json[col_idx];
var single_data_point = line[col_idx];
if(single_data_point === "" && !special_col_names.includes(col_header_name)) {
line_has_empty_data = true;
continue;
}
}
if(!line_has_empty_data) {
new_data.push(line);
}
}
return new_data;
}
function make_text_in_parallel_plot_nicer() {
$(".parcoords g > g > text").each(function() {
if (theme == "dark") {
$(this)
.css("text-shadow", "unset")
.css("font-size", "0.9em")
.css("fill", "white")
.css("stroke", "black")
.css("stroke-width", "2px")
.css("paint-order", "stroke fill");
} else {
$(this)
.css("text-shadow", "unset")
.css("font-size", "0.9em")
.css("fill", "black")
.css("stroke", "unset")
.css("stroke-width", "unset")
.css("paint-order", "stroke fill");
}
});
}
function createParallelPlot(dataArray, headers, resultNames, ignoreColumns = []) {
if ($("#parallel-plot").data("loaded") == "true") {
return;
}
dataArray = filterNonEmptyRows(dataArray);
const ignoreSet = new Set(ignoreColumns);
const numericalCols = [];
const categoricalCols = [];
const categoryMappings = {};
headers.forEach((header, colIndex) => {
if (ignoreSet.has(header)) return;
const values = dataArray.map(row => row[colIndex]);
if (values.every(val => !isNaN(parseFloat(val)))) {
numericalCols.push({ name: header, index: colIndex });
} else {
categoricalCols.push({ name: header, index: colIndex });
const uniqueValues = [...new Set(values)];
categoryMappings[header] = Object.fromEntries(uniqueValues.map((val, i) => [val, i]));
}
});
const dimensions = [];
numericalCols.forEach(col => {
dimensions.push({
label: col.name,
values: dataArray.map(row => parseFloat(row[col.index])),
range: [
Math.min(...dataArray.map(row => parseFloat(row[col.index]))),
Math.max(...dataArray.map(row => parseFloat(row[col.index])))
]
});
});
categoricalCols.forEach(col => {
dimensions.push({
label: col.name,
values: dataArray.map(row => categoryMappings[col.name][row[col.index]]),
tickvals: Object.values(categoryMappings[col.name]),
ticktext: Object.keys(categoryMappings[col.name])
});
});
let colorScale = null;
let colorValues = null;
if (resultNames.length > 1) {
let selectBox = '<select id="result-select" style="margin-bottom: 10px;">';
selectBox += '<option value="none">No color</option>';
var k = 0;
resultNames.forEach(resultName => {
var minMax = result_min_max[k];
if(minMax === undefined) {
minMax = "min [automatically chosen]"
}
selectBox += `<option value="${resultName}">${resultName} (${minMax})</option>`;
k = k + 1;
});
selectBox += '</select>';
$("#parallel-plot").before(selectBox);
$("#result-select").change(function() {
const selectedResult = $(this).val();
if (selectedResult === "none") {
colorValues = null;
colorScale = null;
} else {
const resultCol = numericalCols.find(col => col.name.toLowerCase() === selectedResult.toLowerCase());
colorValues = dataArray.map(row => parseFloat(row[resultCol.index]));
let minResult = Math.min(...colorValues);
let maxResult = Math.max(...colorValues);
var _result_min_max_idx = result_names.indexOf(selectedResult);
let invertColor = false;
if (result_min_max.length > _result_min_max_idx) {
invertColor = result_min_max[_result_min_max_idx] === "max";
}
colorScale = invertColor
? [[0, 'red'], [1, 'green']]
: [[0, 'green'], [1, 'red']];
}
updatePlot();
});
} else {
let invertColor = false;
if (Object.keys(result_min_max).length == 1) {
invertColor = result_min_max[0] === "max";
}
colorScale = invertColor
? [[0, 'red'], [1, 'green']]
: [[0, 'green'], [1, 'red']];
const resultCol = numericalCols.find(col => col.name.toLowerCase() === resultNames[0].toLowerCase());
colorValues = dataArray.map(row => parseFloat(row[resultCol.index]));
}
function updatePlot() {
const trace = {
type: 'parcoords',
dimensions: dimensions,
line: colorValues ? { color: colorValues, colorscale: colorScale } : {},
unselected: {
line: {
color: get_text_color(),
opacity: 0
}
},
};
dimensions.forEach(dim => {
if (!dim.line) {
dim.line = {};
}
if (!dim.line.color) {
dim.line.color = 'rgba(169,169,169, 0.01)';
}
});
Plotly.newPlot('parallel-plot', [trace], add_default_layout_data({}));
make_text_in_parallel_plot_nicer();
}
updatePlot();
$("#parallel-plot").data("loaded", "true");
make_text_in_parallel_plot_nicer();
}
function plotWorkerUsage() {
if($("#workerUsagePlot").data("loaded") == "true") {
return;
}
var data = tab_worker_usage_csv_json;
if (!Array.isArray(data) || data.length === 0) {
console.error("Invalid or empty data provided.");
return;
}
let timestamps = [];
let desiredWorkers = [];
let realWorkers = [];
for (let i = 0; i < data.length; i++) {
let entry = data[i];
if (!Array.isArray(entry) || entry.length < 3) {
console.warn("Skipping invalid entry:", entry);
continue;
}
let unixTime = parseFloat(entry[0]);
let desired = parseInt(entry[1], 10);
let real = parseInt(entry[2], 10);
if (isNaN(unixTime) || isNaN(desired) || isNaN(real)) {
console.warn("Skipping invalid numerical values:", entry);
continue;
}
timestamps.push(new Date(unixTime * 1000).toISOString());
desiredWorkers.push(desired);
realWorkers.push(real);
}
let trace1 = {
x: timestamps,
y: desiredWorkers,
mode: 'lines+markers',
name: 'Desired Workers',
line: {
color: 'blue'
}
};
let trace2 = {
x: timestamps,
y: realWorkers,
mode: 'lines+markers',
name: 'Real Workers',
line: {
color: 'red'
}
};
let layout = {
title: "Worker Usage Over Time",
xaxis: {
title: get_axis_title_data("Time", "date")
},
yaxis: {
title: get_axis_title_data("Number of Workers")
},
legend: {
x: 0,
y: 1
}
};
Plotly.newPlot('workerUsagePlot', [trace1, trace2], add_default_layout_data(layout));
$("#workerUsagePlot").data("loaded", "true");
}
function plotCPUAndRAMUsage() {
if($("#mainWorkerCPURAM").data("loaded") == "true") {
return;
}
var timestamps = tab_main_worker_cpu_ram_csv_json.map(row => new Date(row[0] * 1000));
var ramUsage = tab_main_worker_cpu_ram_csv_json.map(row => row[1]);
var cpuUsage = tab_main_worker_cpu_ram_csv_json.map(row => row[2]);
var trace1 = {
x: timestamps,
y: cpuUsage,
mode: 'lines+markers',
marker: {
size: get_marker_size(),
},
name: 'CPU Usage (%)',
type: 'scatter',
yaxis: 'y1'
};
var trace2 = {
x: timestamps,
y: ramUsage,
mode: 'lines+markers',
marker: {
size: get_marker_size(),
},
name: 'RAM Usage (MB)',
type: 'scatter',
yaxis: 'y2'
};
var layout = {
title: 'CPU and RAM Usage Over Time',
xaxis: {
title: get_axis_title_data("Timestamp", "date"),
tickmode: 'array',
tickvals: timestamps.filter((_, index) => index % Math.max(Math.floor(timestamps.length / 10), 1) === 0),
ticktext: timestamps.filter((_, index) => index % Math.max(Math.floor(timestamps.length / 10), 1) === 0).map(t => t.toLocaleString()),
tickangle: -45
},
yaxis: {
title: get_axis_title_data("CPU Usage (%)"),
rangemode: 'tozero'
},
yaxis2: {
title: get_axis_title_data("RAM Usage (MB)"),
overlaying: 'y',
side: 'right',
rangemode: 'tozero'
},
legend: {
x: 0.1,
y: 0.9
}
};
var data = [trace1, trace2];
Plotly.newPlot('mainWorkerCPURAM', data, add_default_layout_data(layout));
$("#mainWorkerCPURAM").data("loaded", "true");
}
function plotScatter2d() {
if ($("#plotScatter2d").data("loaded") == "true") {
return;
}
var plotDiv = document.getElementById("plotScatter2d");
var minInput = document.getElementById("minValue");
var maxInput = document.getElementById("maxValue");
if (!minInput || !maxInput) {
minInput = document.createElement("input");
minInput.id = "minValue";
minInput.type = "number";
minInput.placeholder = "Min Value";
minInput.step = "any";
maxInput = document.createElement("input");
maxInput.id = "maxValue";
maxInput.type = "number";
maxInput.placeholder = "Max Value";
maxInput.step = "any";
var inputContainer = document.createElement("div");
inputContainer.style.marginBottom = "10px";
inputContainer.appendChild(minInput);
inputContainer.appendChild(maxInput);
plotDiv.appendChild(inputContainer);
}
var resultSelect = document.getElementById("resultSelect");
if (result_names.length > 1 && !resultSelect) {
resultSelect = document.createElement("select");
resultSelect.id = "resultSelect";
resultSelect.style.marginBottom = "10px";
var sortedResults = [...result_names].sort();
sortedResults.forEach(result => {
var option = document.createElement("option");
option.value = result;
option.textContent = result;
resultSelect.appendChild(option);
});
var selectContainer = document.createElement("div");
selectContainer.style.marginBottom = "10px";
selectContainer.appendChild(resultSelect);
plotDiv.appendChild(selectContainer);
}
minInput.addEventListener("input", updatePlots);
maxInput.addEventListener("input", updatePlots);
if (resultSelect) {
resultSelect.addEventListener("change", updatePlots);
}
updatePlots();
async function updatePlots() {
var minValue = parseFloat(minInput.value);
var maxValue = parseFloat(maxInput.value);
if (isNaN(minValue)) minValue = -Infinity;
if (isNaN(maxValue)) maxValue = Infinity;
while (plotDiv.children.length > 2) {
plotDiv.removeChild(plotDiv.lastChild);
}
var selectedResult = resultSelect ? resultSelect.value : result_names[0];
var resultIndex = tab_results_headers_json.findIndex(header =>
header.toLowerCase() === selectedResult.toLowerCase()
);
var resultValues = tab_results_csv_json.map(row => row[resultIndex]);
var minResult = Math.min(...resultValues.filter(value => value !== null && value !== ""));
var maxResult = Math.max(...resultValues.filter(value => value !== null && value !== ""));
if (minValue !== -Infinity) minResult = Math.max(minResult, minValue);
if (maxValue !== Infinity) maxResult = Math.min(maxResult, maxValue);
var invertColor = result_min_max[result_names.indexOf(selectedResult)] === "max";
var numericColumns = tab_results_headers_json.filter(col =>
!special_col_names.includes(col) && !result_names.includes(col) &&
!col.startsWith("OO_Info") &&
tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
);
if (numericColumns.length < 2) {
console.error("Not enough columns for Scatter-Plots");
return;
}
for (let i = 0; i < numericColumns.length; i++) {
for (let j = i + 1; j < numericColumns.length; j++) {
let xCol = numericColumns[i];
let yCol = numericColumns[j];
let xIndex = tab_results_headers_json.indexOf(xCol);
let yIndex = tab_results_headers_json.indexOf(yCol);
let data = tab_results_csv_json.map(row => ({
x: parseFloat(row[xIndex]),
y: parseFloat(row[yIndex]),
result: row[resultIndex] !== "" ? parseFloat(row[resultIndex]) : null
}));
data = data.filter(d => d.result >= minResult && d.result <= maxResult);
let layoutTitle = `${xCol} (x) vs ${yCol} (y), result: ${selectedResult}`;
let layout = {
title: layoutTitle,
xaxis: {
title: get_axis_title_data(xCol)
},
yaxis: {
title: get_axis_title_data(yCol)
},
showlegend: false
};
let subDiv = document.createElement("div");
let spinnerContainer = document.createElement("div");
spinnerContainer.style.display = "flex";
spinnerContainer.style.alignItems = "center";
spinnerContainer.style.justifyContent = "center";
spinnerContainer.style.width = layout.width + "px";
spinnerContainer.style.height = layout.height + "px";
spinnerContainer.style.position = "relative";
let spinner = document.createElement("div");
spinner.className = "spinner";
spinner.style.width = "40px";
spinner.style.height = "40px";
let loadingText = document.createElement("span");
loadingText.innerText = `Loading ${layoutTitle}`;
loadingText.style.marginLeft = "10px";
spinnerContainer.appendChild(spinner);
spinnerContainer.appendChild(loadingText);
plotDiv.appendChild(spinnerContainer);
await new Promise(resolve => setTimeout(resolve, 50));
let colors = data.map(d => {
if (d.result === null) {
return 'rgb(0, 0, 0)';
} else {
let norm = (d.result - minResult) / (maxResult - minResult);
if (invertColor) {
norm = 1 - norm;
}
return `rgb(${Math.round(255 * norm)}, ${Math.round(255 * (1 - norm))}, 0)`;
}
});
let trace = {
x: data.map(d => d.x),
y: data.map(d => d.y),
mode: 'markers',
marker: {
size: get_marker_size(),
color: data.map(d => d.result !== null ? d.result : null),
colorscale: invertColor ? [
[0, 'red'],
[1, 'green']
] : [
[0, 'green'],
[1, 'red']
],
colorbar: {
title: 'Result',
tickvals: [minResult, maxResult],
ticktext: [`${minResult}`, `${maxResult}`]
},
symbol: data.map(d => d.result === null ? 'x' : 'circle'),
},
text: data.map(d => d.result !== null ? `Result: ${d.result}` : 'No result'),
type: 'scatter',
showlegend: false
};
try {
plotDiv.replaceChild(subDiv, spinnerContainer);
} catch (err) {
//
}
Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
}
}
}
$("#plotScatter2d").data("loaded", "true");
}
function plotScatter3d() {
if ($("#plotScatter3d").data("loaded") == "true") {
return;
}
var plotDiv = document.getElementById("plotScatter3d");
if (!plotDiv) {
console.error("Div element with id 'plotScatter3d' not found");
return;
}
plotDiv.innerHTML = "";
var minInput3d = document.getElementById("minValue3d");
var maxInput3d = document.getElementById("maxValue3d");
if (!minInput3d || !maxInput3d) {
minInput3d = document.createElement("input");
minInput3d.id = "minValue3d";
minInput3d.type = "number";
minInput3d.placeholder = "Min Value";
minInput3d.step = "any";
maxInput3d = document.createElement("input");
maxInput3d.id = "maxValue3d";
maxInput3d.type = "number";
maxInput3d.placeholder = "Max Value";
maxInput3d.step = "any";
var inputContainer3d = document.createElement("div");
inputContainer3d.style.marginBottom = "10px";
inputContainer3d.appendChild(minInput3d);
inputContainer3d.appendChild(maxInput3d);
plotDiv.appendChild(inputContainer3d);
}
var select3d = document.getElementById("select3dScatter");
if (result_names.length > 1 && !select3d) {
if (!select3d) {
select3d = document.createElement("select");
select3d.id = "select3dScatter";
select3d.style.marginBottom = "10px";
select3d.innerHTML = result_names.map(name => `<option value="${name}">${name}</option>`).join("");
select3d.addEventListener("change", updatePlots3d);
plotDiv.appendChild(select3d);
}
}
minInput3d.addEventListener("input", updatePlots3d);
maxInput3d.addEventListener("input", updatePlots3d);
updatePlots3d();
async function updatePlots3d() {
var selectedResult = select3d ? select3d.value : result_names[0];
var minValue3d = parseFloat(minInput3d.value);
var maxValue3d = parseFloat(maxInput3d.value);
if (isNaN(minValue3d)) minValue3d = -Infinity;
if (isNaN(maxValue3d)) maxValue3d = Infinity;
while (plotDiv.children.length > 2) {
plotDiv.removeChild(plotDiv.lastChild);
}
var resultIndex = tab_results_headers_json.findIndex(header =>
header.toLowerCase() === selectedResult.toLowerCase()
);
var resultValues = tab_results_csv_json.map(row => row[resultIndex]);
var minResult = Math.min(...resultValues.filter(value => value !== null && value !== ""));
var maxResult = Math.max(...resultValues.filter(value => value !== null && value !== ""));
if (minValue3d !== -Infinity) minResult = Math.max(minResult, minValue3d);
if (maxValue3d !== Infinity) maxResult = Math.min(maxResult, maxValue3d);
var invertColor = result_min_max[result_names.indexOf(selectedResult)] === "max";
var numericColumns = tab_results_headers_json.filter(col =>
!special_col_names.includes(col) && !result_names.includes(col) &&
!col.startsWith("OO_Info") &&
tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
);
if (numericColumns.length < 3) {
console.error("Not enough columns for 3D scatter plots");
return;
}
for (let i = 0; i < numericColumns.length; i++) {
for (let j = i + 1; j < numericColumns.length; j++) {
for (let k = j + 1; k < numericColumns.length; k++) {
let xCol = numericColumns[i];
let yCol = numericColumns[j];
let zCol = numericColumns[k];
let xIndex = tab_results_headers_json.indexOf(xCol);
let yIndex = tab_results_headers_json.indexOf(yCol);
let zIndex = tab_results_headers_json.indexOf(zCol);
let data = tab_results_csv_json.map(row => ({
x: parseFloat(row[xIndex]),
y: parseFloat(row[yIndex]),
z: parseFloat(row[zIndex]),
result: row[resultIndex] !== "" ? parseFloat(row[resultIndex]) : null
}));
data = data.filter(d => d.result >= minResult && d.result <= maxResult);
let layoutTitle = `${xCol} (x) vs ${yCol} (y) vs ${zCol} (z), result: ${selectedResult}`;
let layout = {
title: layoutTitle,
scene: {
xaxis: {
title: get_axis_title_data(xCol)
},
yaxis: {
title: get_axis_title_data(yCol)
},
zaxis: {
title: get_axis_title_data(zCol)
}
},
showlegend: false
};
let spinnerContainer = document.createElement("div");
spinnerContainer.style.display = "flex";
spinnerContainer.style.alignItems = "center";
spinnerContainer.style.justifyContent = "center";
spinnerContainer.style.width = layout.width + "px";
spinnerContainer.style.height = layout.height + "px";
spinnerContainer.style.position = "relative";
let spinner = document.createElement("div");
spinner.className = "spinner";
spinner.style.width = "40px";
spinner.style.height = "40px";
let loadingText = document.createElement("span");
loadingText.innerText = `Loading ${layoutTitle}`;
loadingText.style.marginLeft = "10px";
spinnerContainer.appendChild(spinner);
spinnerContainer.appendChild(loadingText);
plotDiv.appendChild(spinnerContainer);
await new Promise(resolve => setTimeout(resolve, 50));
let colors = data.map(d => {
if (d.result === null) {
return 'rgb(0, 0, 0)';
} else {
let norm = (d.result - minResult) / (maxResult - minResult);
if (invertColor) {
norm = 1 - norm;
}
return `rgb(${Math.round(255 * norm)}, ${Math.round(255 * (1 - norm))}, 0)`;
}
});
let trace = {
x: data.map(d => d.x),
y: data.map(d => d.y),
z: data.map(d => d.z),
mode: 'markers',
marker: {
size: get_marker_size(),
color: data.map(d => d.result !== null ? d.result : null),
colorscale: invertColor ? [
[0, 'red'],
[1, 'green']
] : [
[0, 'green'],
[1, 'red']
],
colorbar: {
title: 'Result',
tickvals: [minResult, maxResult],
ticktext: [`${minResult}`, `${maxResult}`]
},
},
text: data.map(d => d.result !== null ? `Result: ${d.result}` : 'No result'),
type: 'scatter3d',
showlegend: false
};
let subDiv = document.createElement("div");
try {
plotDiv.replaceChild(subDiv, spinnerContainer);
} catch (err) {
//
}
Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
}
}
}
}
$("#plotScatter3d").data("loaded", "true");
}
async function plot_worker_cpu_ram() {
if($("#worker_cpu_ram_pre").data("loaded") == "true") {
return;
}
const logData = $("#worker_cpu_ram_pre").text();
const regex = /^Unix-Timestamp: (\d+), Hostname: ([\w-]+), CPU: ([\d.]+)%, RAM: ([\d.]+) MB \/ ([\d.]+) MB$/;
const hostData = {};
logData.split("\n").forEach(line => {
line = line.trim();
const match = line.match(regex);
if (match) {
const timestamp = new Date(parseInt(match[1]) * 1000);
const hostname = match[2];
const cpu = parseFloat(match[3]);
const ram = parseFloat(match[4]);
if (!hostData[hostname]) {
hostData[hostname] = { timestamps: [], cpuUsage: [], ramUsage: [] };
}
hostData[hostname].timestamps.push(timestamp);
hostData[hostname].cpuUsage.push(cpu);
hostData[hostname].ramUsage.push(ram);
}
});
if (!Object.keys(hostData).length) {
console.log("No valid data found");
return;
}
const container = document.getElementById("cpuRamWorkerChartContainer");
container.innerHTML = "";
var i = 1;
Object.entries(hostData).forEach(([hostname, { timestamps, cpuUsage, ramUsage }], index) => {
const chartId = `workerChart_${index}`;
const chartDiv = document.createElement("div");
chartDiv.id = chartId;
chartDiv.style.marginBottom = "40px";
container.appendChild(chartDiv);
const cpuTrace = {
x: timestamps,
y: cpuUsage,
mode: "lines+markers",
name: "CPU Usage (%)",
yaxis: "y1",
line: {
color: "red"
}
};
const ramTrace = {
x: timestamps,
y: ramUsage,
mode: "lines+markers",
name: "RAM Usage (MB)",
yaxis: "y2",
line: {
color: "blue"
}
};
const layout = {
title: `Worker CPU and RAM Usage - ${hostname}`,
xaxis: {
title: get_axis_title_data("Timestamp", "date")
},
yaxis: {
title: get_axis_title_data("CPU Usage (%)"),
side: "left",
color: "red"
},
yaxis2: {
title: get_axis_title_data("RAM Usage (MB)"),
side: "right",
overlaying: "y",
color: "blue"
},
showlegend: true
};
Plotly.newPlot(chartId, [cpuTrace, ramTrace], add_default_layout_data(layout));
i++;
});
$("#plot_worker_cpu_ram_button").remove();
$("#worker_cpu_ram_pre").data("loaded", "true");
}
function load_log_file(log_nr, filename) {
var pre_id = `single_run_${log_nr}_pre`;
if (!$("#" + pre_id).data("loaded")) {
const params = new URLSearchParams(window.location.search);
const user_id = params.get('user_id');
const experiment_name = params.get('experiment_name');
const run_nr = params.get('run_nr');
var url = `get_log?user_id=${user_id}&experiment_name=${experiment_name}&run_nr=${run_nr}&filename=${filename}`;
fetch(url)
.then(response => response.json())
.then(data => {
if (data.data) {
$("#" + pre_id).html(data.data);
$("#" + pre_id).data("loaded", true);
} else {
log(`No 'data' key found in response.`);
}
$("#spinner_log_" + log_nr).remove();
})
.catch(error => {
log(`Error loading log: ${error}`);
$("#spinner_log_" + log_nr).remove();
});
}
}
function load_debug_log () {
var pre_id = `here_debuglogs_go`;
if (!$("#" + pre_id).data("loaded")) {
const params = new URLSearchParams(window.location.search);
const user_id = params.get('user_id');
const experiment_name = params.get('experiment_name');
const run_nr = params.get('run_nr');
var url = `get_debug_log?user_id=${user_id}&experiment_name=${experiment_name}&run_nr=${run_nr}`;
fetch(url)
.then(response => response.json())
.then(data => {
$("#debug_log_spinner").remove();
if (data.data) {
try {
$("#" + pre_id).html(data.data);
} catch (err) {
$("#" + pre_id).text(`Error loading data: ${err}`);
}
$("#" + pre_id).data("loaded", true);
if (typeof apply_theme_based_on_system_preferences === 'function') {
apply_theme_based_on_system_preferences();
}
} else {
log(`No 'data' key found in response.`);
}
})
.catch(error => {
log(`Error loading log: ${error}`);
$("#debug_log_spinner").remove();
});
}
}
function plotBoxplot() {
if ($("#plotBoxplot").data("loaded") == "true") {
return;
}
var numericColumns = tab_results_headers_json.filter(col =>
!special_col_names.includes(col) && !result_names.includes(col) &&
!col.startsWith("OO_Info") &&
tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
);
if (numericColumns.length < 1) {
console.error("Not enough numeric columns for Boxplot");
return;
}
var resultIndex = tab_results_headers_json.findIndex(function(header) {
return result_names.includes(header.toLowerCase());
});
var resultValues = tab_results_csv_json.map(row => row[resultIndex]);
var minResult = Math.min(...resultValues.filter(value => value !== null && value !== ""));
var maxResult = Math.max(...resultValues.filter(value => value !== null && value !== ""));
var plotDiv = document.getElementById("plotBoxplot");
plotDiv.innerHTML = "";
let traces = numericColumns.map(col => {
let index = tab_results_headers_json.indexOf(col);
let data = tab_results_csv_json.map(row => parseFloat(row[index]));
return {
y: data,
type: 'box',
name: col,
boxmean: 'sd',
marker: {
color: 'rgb(0, 255, 0)'
},
};
});
let layout = {
title: 'Boxplot of Numerical Columns',
xaxis: {
title: get_axis_title_data("Columns")
},
yaxis: {
title: get_axis_title_data("Value")
},
showlegend: false
};
Plotly.newPlot(plotDiv, traces, add_default_layout_data(layout));
$("#plotBoxplot").data("loaded", "true");
}
function plotHeatmap() {
if ($("#plotHeatmap").data("loaded") === "true") {
return;
}
var numericColumns = tab_results_headers_json.filter(col => {
if (special_col_names.includes(col) || result_names.includes(col)) {
return false;
}
if (!col.startsWith("OO_Info")) {
return;
}
let index = tab_results_headers_json.indexOf(col);
return tab_results_csv_json.every(row => {
let value = parseFloat(row[index]);
return !isNaN(value) && isFinite(value);
});
});
if (numericColumns.length < 2) {
console.error("Not enough valid numeric columns for Heatmap");
return;
}
var columnData = numericColumns.map(col => {
let index = tab_results_headers_json.indexOf(col);
return tab_results_csv_json.map(row => parseFloat(row[index]));
});
var dataMatrix = numericColumns.map((_, i) =>
numericColumns.map((_, j) => {
let values = columnData[i].map((val, index) => (val + columnData[j][index]) / 2);
return values.reduce((a, b) => a + b, 0) / values.length;
})
);
var trace = {
z: dataMatrix,
x: numericColumns,
y: numericColumns,
colorscale: 'Viridis',
type: 'heatmap'
};
var layout = {
xaxis: {
title: get_axis_title_data("Columns")
},
yaxis: {
title: get_axis_title_data("Columns")
},
showlegend: false
};
var plotDiv = document.getElementById("plotHeatmap");
plotDiv.innerHTML = "";
Plotly.newPlot(plotDiv, [trace], add_default_layout_data(layout));
$("#plotHeatmap").data("loaded", "true");
}
function plotHistogram() {
if ($("#plotHistogram").data("loaded") == "true") {
return;
}
var numericColumns = tab_results_headers_json.filter(col =>
!special_col_names.includes(col) && !result_names.includes(col) &&
!col.startsWith("OO_Info") &&
tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
);
if (numericColumns.length < 1) {
console.error("Not enough columns for Histogram");
return;
}
var plotDiv = document.getElementById("plotHistogram");
plotDiv.innerHTML = "";
const colorPalette = ['#ff9999', '#66b3ff', '#99ff99', '#ffcc99', '#c2c2f0', '#ffb3e6'];
let traces = numericColumns.map((col, index) => {
let data = tab_results_csv_json.map(row => parseFloat(row[tab_results_headers_json.indexOf(col)]));
return {
x: data,
type: 'histogram',
name: col,
opacity: 0.7,
marker: {
color: colorPalette[index % colorPalette.length]
},
autobinx: true
};
});
let layout = {
title: 'Histogram of Numerical Columns',
xaxis: {
title: get_axis_title_data("Value")
},
yaxis: {
title: get_axis_title_data("Frequency")
},
showlegend: true,
barmode: 'overlay'
};
Plotly.newPlot(plotDiv, traces, add_default_layout_data(layout));
$("#plotHistogram").data("loaded", "true");
}
function plotViolin() {
if ($("#plotViolin").data("loaded") == "true") {
return;
}
var numericColumns = tab_results_headers_json.filter(col =>
!special_col_names.includes(col) && !result_names.includes(col) &&
!col.startsWith("OO_Info") &&
tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
);
if (numericColumns.length < 1) {
console.error("Not enough columns for Violin Plot");
return;
}
var plotDiv = document.getElementById("plotViolin");
plotDiv.innerHTML = "";
let traces = numericColumns.map(col => {
let index = tab_results_headers_json.indexOf(col);
let data = tab_results_csv_json.map(row => parseFloat(row[index]));
return {
y: data,
type: 'violin',
name: col,
box: {
visible: true
},
line: {
color: 'rgb(0, 255, 0)'
},
marker: {
color: 'rgb(0, 255, 0)'
},
meanline: {
visible: true
},
};
});
let layout = {
title: 'Violin Plot of Numerical Columns',
yaxis: {
title: get_axis_title_data("Value")
},
xaxis: {
title: get_axis_title_data("Columns")
},
showlegend: false
};
Plotly.newPlot(plotDiv, traces, add_default_layout_data(layout));
$("#plotViolin").data("loaded", "true");
}
function plotExitCodesPieChart() {
if ($("#plotExitCodesPieChart").data("loaded") == "true") {
return;
}
var exitCodes = tab_job_infos_csv_json.map(row => row[tab_job_infos_headers_json.indexOf("exit_code")]);
var exitCodeCounts = exitCodes.reduce(function(counts, exitCode) {
counts[exitCode] = (counts[exitCode] || 0) + 1;
return counts;
}, {});
var labels = Object.keys(exitCodeCounts);
var values = Object.values(exitCodeCounts);
var plotDiv = document.getElementById("plotExitCodesPieChart");
plotDiv.innerHTML = "";
var trace = {
labels: labels,
values: values,
type: 'pie',
hoverinfo: 'label+percent',
textinfo: 'label+value',
marker: {
colors: ['#ff9999','#66b3ff','#99ff99','#ffcc99','#c2c2f0']
}
};
var layout = {
title: 'Exit Code Distribution',
showlegend: true
};
Plotly.newPlot(plotDiv, [trace], add_default_layout_data(layout));
$("#plotExitCodesPieChart").data("loaded", "true");
}
function plotResultEvolution() {
if ($("#plotResultEvolution").data("loaded") == "true") {
return;
}
result_names.forEach(resultName => {
var relevantColumns = tab_results_headers_json.filter(col =>
!special_col_names.includes(col) && !col.startsWith("OO_Info") && col.toLowerCase() !== resultName.toLowerCase()
);
var xColumnIndex = tab_results_headers_json.indexOf("trial_index");
var resultIndex = tab_results_headers_json.indexOf(resultName);
let data = tab_results_csv_json.map(row => ({
x: row[xColumnIndex],
y: parseFloat(row[resultIndex])
}));
data.sort((a, b) => a.x - b.x);
let xData = data.map(item => item.x);
let yData = data.map(item => item.y);
let trace = {
x: xData,
y: yData,
mode: 'lines+markers',
name: resultName,
line: {
shape: 'linear'
},
marker: {
size: get_marker_size()
}
};
let layout = {
title: `Evolution of ${resultName} over time`,
xaxis: {
title: get_axis_title_data("Trial-Index")
},
yaxis: {
title: get_axis_title_data(resultName)
},
showlegend: true
};
let subDiv = document.createElement("div");
document.getElementById("plotResultEvolution").appendChild(subDiv);
Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
});
$("#plotResultEvolution").data("loaded", "true");
}
function plotResultPairs() {
if ($("#plotResultPairs").data("loaded") == "true") {
return;
}
var plotDiv = document.getElementById("plotResultPairs");
plotDiv.innerHTML = "";
for (let i = 0; i < result_names.length; i++) {
for (let j = i + 1; j < result_names.length; j++) {
let xName = result_names[i];
let yName = result_names[j];
let xIndex = tab_results_headers_json.indexOf(xName);
let yIndex = tab_results_headers_json.indexOf(yName);
let data = tab_results_csv_json
.filter(row => row[xIndex] !== "" && row[yIndex] !== "")
.map(row => ({
x: parseFloat(row[xIndex]),
y: parseFloat(row[yIndex]),
status: row[tab_results_headers_json.indexOf("trial_status")]
}));
let colors = data.map(d => d.status === "COMPLETED" ? 'green' : (d.status === "FAILED" ? 'red' : 'gray'));
let trace = {
x: data.map(d => d.x),
y: data.map(d => d.y),
mode: 'markers',
marker: {
size: get_marker_size(),
color: colors
},
text: data.map(d => `Status: ${d.status}`),
type: 'scatter',
showlegend: false
};
let layout = {
xaxis: {
title: get_axis_title_data(xName)
},
yaxis: {
title: get_axis_title_data(yName)
},
showlegend: false
};
let subDiv = document.createElement("div");
plotDiv.appendChild(subDiv);
Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
}
}
$("#plotResultPairs").data("loaded", "true");
}
function add_up_down_arrows_for_scrolling () {
const upArrow = document.createElement('div');
const downArrow = document.createElement('div');
const style = document.createElement('style');
style.innerHTML = `
.scroll-arrow {
position: fixed;
right: 10px;
z-index: 100;
cursor: pointer;
font-size: 25px;
display: none;
background-color: green;
color: white;
padding: 5px;
outline: 2px solid white;
box-shadow: 0 0 10px rgba(0, 0, 0, 0.5);
transition: background-color 0.3s, transform 0.3s;
}
.scroll-arrow:hover {
background-color: darkgreen;
transform: scale(1.1);
}
#up-arrow {
top: 10px;
}
#down-arrow {
bottom: 10px;
}
`;
document.head.appendChild(style);
upArrow.id = "up-arrow";
upArrow.classList.add("scroll-arrow");
upArrow.classList.add("invert_in_dark_mode");
upArrow.innerHTML = "↑";
downArrow.id = "down-arrow";
downArrow.classList.add("scroll-arrow");
downArrow.classList.add("invert_in_dark_mode");
downArrow.innerHTML = "↓";
document.body.appendChild(upArrow);
document.body.appendChild(downArrow);
function checkScrollPosition() {
const scrollPosition = window.scrollY;
const pageHeight = document.documentElement.scrollHeight;
const windowHeight = window.innerHeight;
if (scrollPosition > 0) {
upArrow.style.display = "block";
} else {
upArrow.style.display = "none";
}
if (scrollPosition + windowHeight < pageHeight) {
downArrow.style.display = "block";
} else {
downArrow.style.display = "none";
}
}
window.addEventListener("scroll", checkScrollPosition);
upArrow.addEventListener("click", function () {
window.scrollTo({ top: 0, behavior: 'smooth' });
});
downArrow.addEventListener("click", function () {
window.scrollTo({ top: document.documentElement.scrollHeight, behavior: 'smooth' });
});
checkScrollPosition();
if (typeof apply_theme_based_on_system_preferences === 'function') {
apply_theme_based_on_system_preferences();
}
}
function plotGPUUsage() {
if ($("#tab_gpu_usage").data("loaded") === "true") {
return;
}
Object.keys(gpu_usage).forEach(node => {
const nodeData = gpu_usage[node];
var timestamps = [];
var gpuUtilizations = [];
var temperatures = [];
nodeData.forEach(entry => {
try {
var timestamp = new Date(entry[0]* 1000);
var utilization = parseFloat(entry[1]);
var temperature = parseFloat(entry[2]);
if (!isNaN(timestamp) && !isNaN(utilization) && !isNaN(temperature)) {
timestamps.push(timestamp);
gpuUtilizations.push(utilization);
temperatures.push(temperature);
} else {
console.warn("Invalid data point:", entry);
}
} catch (error) {
console.error("Error processing GPU data entry:", error, entry);
}
});
var trace1 = {
x: timestamps,
y: gpuUtilizations,
mode: 'lines+markers',
marker: {
size: get_marker_size(),
},
name: 'GPU Utilization (%)',
type: 'scatter',
yaxis: 'y1'
};
var trace2 = {
x: timestamps,
y: temperatures,
mode: 'lines+markers',
marker: {
size: get_marker_size(),
},
name: 'GPU Temperature (°C)',
type: 'scatter',
yaxis: 'y2'
};
var layout = {
title: 'GPU Usage Over Time - ' + node,
xaxis: {
title: get_axis_title_data("Timestamp", "date"),
tickmode: 'array',
tickvals: timestamps.filter((_, index) => index % Math.max(Math.floor(timestamps.length / 10), 1) === 0),
ticktext: timestamps.filter((_, index) => index % Math.max(Math.floor(timestamps.length / 10), 1) === 0).map(t => t.toLocaleString()),
tickangle: -45
},
yaxis: {
title: get_axis_title_data("GPU Utilization (%)"),
overlaying: 'y',
rangemode: 'tozero'
},
yaxis2: {
title: get_axis_title_data("GPU Temperature (°C)"),
overlaying: 'y',
side: 'right',
position: 0.85,
rangemode: 'tozero'
},
legend: {
x: 0.1,
y: 0.9
}
};
var divId = 'gpu_usage_plot_' + node;
if (!document.getElementById(divId)) {
var div = document.createElement('div');
div.id = divId;
div.className = 'gpu-usage-plot';
document.getElementById('tab_gpu_usage').appendChild(div);
}
var plotData = [trace1, trace2];
Plotly.newPlot(divId, plotData, add_default_layout_data(layout));
});
$("#tab_gpu_usage").data("loaded", "true");
}
function plotResultsDistributionByGenerationMethod() {
if ("true" === $("#plotResultsDistributionByGenerationMethod").data("loaded")) {
return;
}
var res_col = result_names[0];
var gen_method_col = "generation_node";
var data = {};
tab_results_csv_json.forEach(row => {
var gen_method = row[tab_results_headers_json.indexOf(gen_method_col)];
var result = row[tab_results_headers_json.indexOf(res_col)];
if (!data[gen_method]) {
data[gen_method] = [];
}
data[gen_method].push(result);
});
var traces = Object.keys(data).map(method => {
return {
y: data[method],
type: 'box',
name: method,
boxpoints: 'outliers',
jitter: 0.5,
pointpos: 0
};
});
var layout = {
title: 'Distribution of Results by Generation Method',
yaxis: {
title: get_axis_title_data(res_col)
},
xaxis: {
title: get_axis_title_data("Generation Method")
},
boxmode: 'group'
};
Plotly.newPlot("plotResultsDistributionByGenerationMethod", traces, add_default_layout_data(layout));
$("#plotResultsDistributionByGenerationMethod").data("loaded", "true");
}
function plotJobStatusDistribution() {
if ($("#plotJobStatusDistribution").data("loaded") === "true") {
return;
}
var status_col = "trial_status";
var status_counts = {};
tab_results_csv_json.forEach(row => {
var status = row[tab_results_headers_json.indexOf(status_col)];
if (status) {
status_counts[status] = (status_counts[status] || 0) + 1;
}
});
var statuses = Object.keys(status_counts);
var counts = Object.values(status_counts);
var colors = statuses.map((status, i) =>
status === "FAILED" ? "#FF0000" : `hsl(${30 + ((i * 137) % 330)}, 70%, 50%)`
);
var trace = {
x: statuses,
y: counts,
type: 'bar',
marker: { color: colors }
};
var layout = {
title: 'Distribution of Job Status',
xaxis: { title: 'Trial Status' },
yaxis: { title: 'Nr. of jobs' }
};
Plotly.newPlot("plotJobStatusDistribution", [trace], add_default_layout_data(layout));
$("#plotJobStatusDistribution").data("loaded", "true");
}
function _colorize_table_entries_by_generation_method () {
document.querySelectorAll('[data-column-id="generation_node"]').forEach(el => {
let text = el.textContent.toLowerCase();
let color = text.includes("manual") ? "green" :
text.includes("sobol") ? "orange" :
text.includes("saasbo") ? "pink" :
text.includes("uniform") ? "lightblue" :
text.includes("legacy_gpei") ? "sienna" :
text.includes("bo_mixed") ? "aqua" :
text.includes("randomforest") ? "darkseagreen" :
text.includes("external_generator") ? "purple" :
text.includes("botorch") ? "yellow" : "";
if (color !== "") {
el.style.backgroundColor = color;
}
el.classList.add("invert_in_dark_mode");
});
}
function _colorize_table_entries_by_trial_status () {
document.querySelectorAll('[data-column-id="trial_status"]').forEach(el => {
let color = el.textContent.includes("COMPLETED") ? "lightgreen" :
el.textContent.includes("RUNNING") ? "orange" :
el.textContent.includes("FAILED") ? "red" :
el.textContent.includes("ABANDONED") ? "yellow" : "";
if (color) el.style.backgroundColor = color;
el.classList.add("invert_in_dark_mode");
});
}
function _colorize_table_entries_by_run_time() {
let cells = [...document.querySelectorAll('[data-column-id="run_time"]')];
if (cells.length === 0) return;
let values = cells.map(el => parseFloat(el.textContent)).filter(v => !isNaN(v));
if (values.length === 0) return;
let min = Math.min(...values);
let max = Math.max(...values);
let range = max - min || 1;
cells.forEach(el => {
let value = parseFloat(el.textContent);
if (isNaN(value)) return;
let ratio = (value - min) / range;
let red = Math.round(255 * ratio);
let green = Math.round(255 * (1 - ratio));
el.style.backgroundColor = `rgb(${red}, ${green}, 0)`;
el.classList.add("invert_in_dark_mode");
});
}
function _colorize_table_entries_by_results() {
result_names.forEach((name, index) => {
let minMax = result_min_max[index];
let selector_query = `[data-column-id="${name}"]`;
let cells = [...document.querySelectorAll(selector_query)];
if (cells.length === 0) return;
let values = cells.map(el => parseFloat(el.textContent)).filter(v => v > 0 && !isNaN(v));
if (values.length === 0) return;
let logValues = values.map(v => Math.log(v));
let logMin = Math.min(...logValues);
let logMax = Math.max(...logValues);
let logRange = logMax - logMin || 1;
cells.forEach(el => {
let value = parseFloat(el.textContent);
if (isNaN(value) || value <= 0) return;
let logValue = Math.log(value);
let ratio = (logValue - logMin) / logRange;
if (minMax === "max") ratio = 1 - ratio;
let red = Math.round(255 * ratio);
let green = Math.round(255 * (1 - ratio));
el.style.backgroundColor = `rgb(${red}, ${green}, 0)`;
el.classList.add("invert_in_dark_mode");
});
});
}
function _colorize_table_entries_by_generation_node_or_hostname() {
["hostname", "generation_node"].forEach(element => {
let selector_query = '[data-column-id="' + element + '"]:not(.gridjs-th)';
let cells = [...document.querySelectorAll(selector_query)];
if (cells.length === 0) return;
let uniqueValues = [...new Set(cells.map(el => el.textContent.trim()))];
let colorMap = {};
uniqueValues.forEach((value, index) => {
let hue = Math.round((360 / uniqueValues.length) * index);
colorMap[value] = `hsl(${hue}, 70%, 60%)`;
});
cells.forEach(el => {
let value = el.textContent.trim();
if (colorMap[value]) {
el.style.backgroundColor = colorMap[value];
el.classList.add("invert_in_dark_mode");
}
});
});
}
function colorize_table_entries () {
setTimeout(() => {
if (typeof result_names !== "undefined" && Array.isArray(result_names) && result_names.length > 0) {
_colorize_table_entries_by_trial_status();
_colorize_table_entries_by_results();
_colorize_table_entries_by_run_time();
_colorize_table_entries_by_generation_method();
_colorize_table_entries_by_generation_node_or_hostname();
if (typeof apply_theme_based_on_system_preferences === 'function') {
apply_theme_based_on_system_preferences();
}
}
}, 300);
}
function add_colorize_to_gridjs_table () {
let searchInput = document.querySelector(".gridjs-search-input");
if (searchInput) {
searchInput.addEventListener("input", colorize_table_entries);
}
}
function updatePreWidths() {
var width = window.innerWidth * 0.95;
var pres = document.getElementsByTagName('pre');
for (var i = 0; i < pres.length; i++) {
pres[i].style.width = width + 'px';
}
}
function demo_mode(nr_sec = 3) {
let i = 0;
let tabs = $('menu[role="tablist"] > button');
setInterval(() => {
tabs.attr('aria-selected', 'false').removeClass('active');
let tab = tabs.eq(i % tabs.length);
tab.attr('aria-selected', 'true').addClass('active');
tab.trigger('click');
i++;
}, nr_sec * 1000);
}
function resizePlotlyCharts() {
const plotlyElements = document.querySelectorAll('.js-plotly-plot');
if (plotlyElements.length) {
const windowWidth = window.innerWidth;
const windowHeight = window.innerHeight;
const newWidth = windowWidth * 0.9;
const newHeight = windowHeight * 0.9;
plotlyElements.forEach(function(element, index) {
const layout = {
width: newWidth,
height: newHeight,
plot_bgcolor: 'rgba(0, 0, 0, 0)',
paper_bgcolor: 'rgba(0, 0, 0, 0)',
};
Plotly.relayout(element, layout)
});
}
make_text_in_parallel_plot_nicer();
apply_theme_based_on_system_preferences();
}
function plotTimelineFromGlobals() {
if (
typeof tab_results_headers_json === "undefined" ||
typeof tab_results_csv_json === "undefined" ||
!Array.isArray(tab_results_headers_json) ||
!Array.isArray(tab_results_csv_json)
) {
console.warn("Global variables 'tab_results_headers_json' or 'tab_results_csv_json' missing or invalid.");
return null;
}
const headers = tab_results_headers_json;
const data = tab_results_csv_json;
const col = name => headers.indexOf(name);
const ix_trial_index = col("trial_index");
const ix_start_time = col("start_time");
const ix_end_time = col("end_time");
const ix_status = col("trial_status");
if ([ix_trial_index, ix_start_time, ix_end_time, ix_status].some(ix => ix === -1)) {
console.warn("One or more needed columns missing");
return null;
}
const traces = [];
// Add dummy traces for legend
traces.push({
type: "scatter",
mode: "lines",
x: [null, null],
y: [null, null],
line: { color: "green", width: 4 },
name: "COMPLETED",
showlegend: true,
hoverinfo: "none"
});
traces.push({
type: "scatter",
mode: "lines",
x: [null, null],
y: [null, null],
line: { color: "yellow", width: 4 },
name: "RUNNING",
showlegend: true,
hoverinfo: "none"
});
traces.push({
type: "scatter",
mode: "lines",
x: [null, null],
y: [null, null],
line: { color: "red", width: 4 },
name: "FAILED/OTHER",
showlegend: true,
hoverinfo: "none"
});
for (const row of data) {
const trial_index = row[ix_trial_index];
const start = row[ix_start_time];
const end = row[ix_end_time];
const status = row[ix_status];
if (
trial_index === "" || start === "" || end === "" ||
isNaN(start) || isNaN(end)
) continue;
let color = "red"; // default
if (status === "COMPLETED") color = "green";
else if (status === "RUNNING") color = "yellow";
traces.push({
type: "scatter",
mode: "lines",
x: [new Date(start * 1000), new Date(end * 1000)],
y: [trial_index, trial_index],
line: { color: color, width: 4 },
name: `Trial ${trial_index} (${status})`,
showlegend: false,
hoverinfo: "x+y+name"
});
}
if (traces.length <= 3) { // only dummy traces added
console.warn("No valid data for plotting found.");
return null;
}
const layout = {
title: "Trial Timeline",
xaxis: {
title: "Time",
type: "date"
},
yaxis: {
title: "Trial Index",
autorange: "reversed"
},
margin: { t: 50 }
};
Plotly.newPlot('plot_timeline', traces, add_default_layout_data(layout));
return true;
}
window.addEventListener('load', updatePreWidths);
window.addEventListener('resize', updatePreWidths);
$(document).ready(function() {
colorize_table_entries();
add_up_down_arrows_for_scrolling();
add_colorize_to_gridjs_table();
});
window.addEventListener('resize', function() {
resizePlotlyCharts();
});
"use strict";
function get_row_by_index(idx) {
if (!Object.keys(window).includes("tab_results_csv_json")) {
error("tab_results_csv_json is not defined");
return;
}
if (!Object.keys(window).includes("tab_results_headers_json")) {
error("tab_results_headers_json is not defined");
return;
}
var trial_index_col_idx = tab_results_headers_json.indexOf("trial_index");
if(trial_index_col_idx == -1) {
error(`"trial_index" could not be found in tab_results_headers_json. Cannot continue`);
return null;
}
for (var i = 0; i < tab_results_csv_json.length; i++) {
var row = tab_results_csv_json[i];
var trial_index = row[trial_index_col_idx];
if (trial_index == idx) {
return row;
}
}
return null;
}
function load_pareto_graph_from_idxs () {
if (!Object.keys(window).includes("pareto_idxs")) {
error("pareto_idxs is not defined");
return;
}
if (!Object.keys(window).includes("tab_results_csv_json")) {
error("tab_results_csv_json is not defined");
return;
}
if (!Object.keys(window).includes("tab_results_headers_json")) {
error("tab_results_headers_json is not defined");
return;
}
if(pareto_idxs === null) {
var err_msg = "pareto_idxs is null. Cannot plot or create tables from empty data. This can be caused by a defective <tt>pareto_idxs.json</tt> file. Please try reloading, or re-calculating the pareto-front and re-submitting if this problem persists.";
$("#pareto_from_idxs_table").html(`<div class="caveat alarm">${err_msg}</div>`);
return;
}
var table = get_pareto_table_data_from_idx();
var html_tables = createParetoTablesFromData(table);
$("#pareto_from_idxs_table").html(html_tables);
renderParetoFrontPlots(table);
apply_theme_based_on_system_preferences();
}
function renderParetoFrontPlots(data) {
try {
let container = document.getElementById("pareto_front_idxs_plot_container");
if (!container) {
console.error("DIV with id 'pareto_front_idxs_plot_container' not found.");
return;
}
container.innerHTML = "";
if(data === undefined || data === null) {
var err_msg = "There was an error getting the data for Pareto-Fronts. See the developer's console to see further details.";
$("#pareto_from_idxs_table").html(`<div class="caveat alarm">${err_msg}</div>`);
return;
}
Object.keys(data).forEach((key, idx) => {
if (!key.startsWith("Pareto front for ")) return;
let label = key.replace("Pareto front for ", "");
let [xKey, yKey] = label.split("/");
if (!xKey || !yKey) {
console.warn("Could not extract two objectives from key:", key);
return;
}
let entries = data[key];
let x = [];
let y = [];
let hoverTexts = [];
entries.forEach((entry) => {
let results = entry.results || {};
let values = entry.values || {};
let xVal = (results[xKey] || [])[0];
let yVal = (results[yKey] || [])[0];
if (xVal === undefined || yVal === undefined) {
console.warn("Missing values for", xKey, yKey, "in", entry);
return;
}
x.push(xVal);
y.push(yVal);
let hoverInfo = [];
if ("trial_index" in values) {
hoverInfo.push(`<b>Trial Index:</b> ${values.trial_index[0]}`);
}
Object.keys(values)
.filter(k => k !== "trial_index")
.sort()
.forEach(k => {
hoverInfo.push(`<b>${k}:</b> ${values[k][0]}`);
});
Object.keys(results)
.sort()
.forEach(k => {
hoverInfo.push(`<b>${k}:</b> ${results[k][0]}`);
});
hoverTexts.push(hoverInfo.join("<br>"));
});
let wrapper = document.createElement("div");
wrapper.style.marginBottom = "30px";
let titleEl = document.createElement("h3");
titleEl.textContent = `Pareto Front: ${xKey} (${getMinMaxByResultName(xKey)}) vs ${yKey} (${getMinMaxByResultName(yKey)})`;
wrapper.appendChild(titleEl);
let divId = `pareto_plot_${idx}`;
let plotDiv = document.createElement("div");
plotDiv.id = divId;
plotDiv.style.width = "100%";
plotDiv.style.height = "400px";
wrapper.appendChild(plotDiv);
container.appendChild(wrapper);
let trace = {
x: x,
y: y,
text: hoverTexts,
hoverinfo: "text",
mode: "markers",
type: "scatter",
marker: {
size: 8,
color: 'rgb(31, 119, 180)',
line: {
width: 1,
color: 'black'
}
},
name: label
};
let layout = {
xaxis: { title: { text: xKey } },
yaxis: { title: { text: yKey } },
margin: { t: 10, l: 60, r: 20, b: 50 },
hovermode: "closest",
showlegend: false
};
Plotly.newPlot(divId, [trace], add_default_layout_data(layout, 1));
});
} catch (e) {
console.error("Error while rendering Pareto front plots:", e);
}
}
function createParetoTablesFromData(data) {
try {
var container = document.createElement("div");
var parsedData;
try {
parsedData = typeof data === "string" ? JSON.parse(data) : data;
} catch (e) {
console.error("JSON parsing failed:", e);
return container;
}
for (var sectionTitle in parsedData) {
if (!parsedData.hasOwnProperty(sectionTitle)) {
continue;
}
var sectionData = parsedData[sectionTitle];
var heading = document.createElement("h2");
heading.textContent = sectionTitle;
container.appendChild(heading);
var table = document.createElement("table");
table.style.borderCollapse = "collapse";
table.style.marginBottom = "2em";
table.style.width = "100%";
var thead = document.createElement("thead");
var headerRow = document.createElement("tr");
var allValueKeys = new Set();
var allResultKeys = new Set();
sectionData.forEach(entry => {
var values = entry.values || {};
var results = entry.results || {};
Object.keys(values).forEach(key => {
allValueKeys.add(key);
});
Object.keys(results).forEach(key => {
allResultKeys.add(key);
});
});
var sortedValueKeys = Array.from(allValueKeys).sort();
var sortedResultKeys = Array.from(allResultKeys).sort();
if (sortedValueKeys.includes("trial_index")) {
sortedValueKeys = sortedValueKeys.filter(k => k !== "trial_index");
sortedValueKeys.unshift("trial_index");
}
var allColumns = [...sortedValueKeys, ...sortedResultKeys];
allColumns.forEach(col => {
var th = document.createElement("th");
th.textContent = col;
th.style.border = "1px solid black";
th.style.padding = "4px";
headerRow.appendChild(th);
});
thead.appendChild(headerRow);
table.appendChild(thead);
var tbody = document.createElement("tbody");
sectionData.forEach(entry => {
var tr = document.createElement("tr");
allColumns.forEach(col => {
var td = document.createElement("td");
td.style.border = "1px solid black";
td.style.padding = "4px";
var value = null;
if (col in entry.values) {
value = entry.values[col];
} else if (col in entry.results) {
value = entry.results[col];
}
if (Array.isArray(value)) {
td.textContent = value.join(", ");
} else {
td.textContent = value !== null && value !== undefined ? value : "";
}
tr.appendChild(td);
});
tbody.appendChild(tr);
});
table.appendChild(tbody);
container.appendChild(table);
}
return container;
} catch (err) {
console.error("Unexpected error:", err);
var errorDiv = document.createElement("div");
errorDiv.textContent = "Error generating tables.";
return errorDiv;
}
}
function get_pareto_table_data_from_idx () {
if (!Object.keys(window).includes("pareto_idxs")) {
error("pareto_idxs is not defined");
return;
}
if (!Object.keys(window).includes("tab_results_csv_json")) {
error("tab_results_csv_json is not defined");
return;
}
if (!Object.keys(window).includes("tab_results_headers_json")) {
error("tab_results_headers_json is not defined");
return;
}
var x_keys = Object.keys(pareto_idxs);
var tables = {};
for (var i = 0; i < x_keys.length; i++) {
var x_key = x_keys[i];
var y_keys = Object.keys(pareto_idxs[x_key]);
for (var j = 0; j < y_keys.length; j++) {
var y_key = y_keys[j];
var indices = pareto_idxs[x_key][y_key];
for (var k = 0; k < indices.length; k++) {
var idx = indices[k];
var row = get_row_by_index(idx);
if(row === null) {
error(`Error getting the row for index ${idx}`);
return;
}
var row_dict = {
"results": {},
"values": {},
};
for (var l = 0; l < tab_results_headers_json.length; l++) {
var header = tab_results_headers_json[l];
if (!special_col_names.includes(header) || header == "trial_index") {
var val = row[l];
if (result_names.includes(header)) {
if (!Object.keys(row_dict["results"]).includes(header)) {
row_dict["results"][header] = [];
}
row_dict["results"][header].push(val);
} else {
if (!Object.keys(row_dict["values"]).includes(header)) {
row_dict["values"][header] = [];
}
row_dict["values"][header].push(val);
}
}
}
var table_key = `Pareto front for ${x_key}/${y_key}`;
if(!Object.keys(tables).includes(table_key)) {
tables[table_key] = [];
}
tables[table_key].push(row_dict);
}
}
}
return tables;
}
function getMinMaxByResultName(resultName) {
try {
if (typeof resultName !== "string") {
error("Parameter resultName must be a string");
return;
}
if (!Array.isArray(result_names)) {
error("Global variable result_names is not an array or undefined");
return;
}
if (!Array.isArray(result_min_max)) {
error("Global variable result_min_max is not an array or undefined");
return;
}
if (result_names.length !== result_min_max.length) {
error("Global arrays result_names and result_min_max must have the same length");
return;
}
var index = result_names.indexOf(resultName);
if (index === -1) {
error("Result name '" + resultName + "' not found in result_names");
return;
}
var minMaxValue = result_min_max[index];
if (minMaxValue !== "min" && minMaxValue !== "max") {
error("Value for result name '" + resultName + "' is invalid: expected 'min' or 'max'");
return;
}
return minMaxValue;
} catch (e) {
error("Unexpected error: " + e.message);
}
}
$(document).ready(function() {
colorize_table_entries();;
plotWorkerUsage();;
plotCPUAndRAMUsage();;
createParallelPlot(tab_results_csv_json, tab_results_headers_json, result_names, special_col_names);;
plotScatter2d();;
plotScatter3d();
plotJobStatusDistribution();;
plotBoxplot();;
plotViolin();;
plotHistogram();;
plotHeatmap();;
plotResultPairs();
colorize_table_entries();
});
</script>
<h1> Overview</h1>
<h2>Experiment overview: </h2><table cellspacing="0" cellpadding="5"><thead><tr><th> Setting</th><th>Value </th></tr></thead><tbody><tr><td> Model for non-random steps</td><td>BOTORCH_MODULAR </td></tr><tr><td> Max. nr. evaluations</td><td>500 </td></tr><tr><td> Number random steps</td><td>20 </td></tr><tr><td> Nr. of workers (parameter)</td><td>30 </td></tr><tr><td> Main process memory (GB)</td><td>8 </td></tr><tr><td> Worker memory (GB)</td><td>32 </td></tr></tbody></table><h2>Experiment parameters: </h2><table cellspacing="0" cellpadding="5"><thead><tr><th> Name</th><th>Type</th><th>Lower bound</th><th>Upper bound</th><th>Type</th><th>Log Scale? </th></tr></thead><tbody><tr><td> recent_samples_size</td><td>range</td><td>10</td><td>4000</td><td>int</td><td>No </td></tr><tr><td> n_reference_samples</td><td>range</td><td>50</td><td>500</td><td>int</td><td>No </td></tr><tr><td> recent_samples_proportion</td><td>range</td><td>0.1</td><td>1</td><td>float</td><td>No </td></tr><tr><td> threshold</td><td>range</td><td>0.5</td><td>0.8</td><td>float</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>0</td>
<td>356</td>
<td>4</td>
<td>360</td>
</tr>
</tbody>
</table>
<h2>Result names and types</h2>
<table>
<tr><th>name</th><th>min/max</th></tr>
<tr>
<td>ACCURACY</td>
<td>max</td>
</tr>
<tr>
<td>RUNTIME</td>
<td>min</td>
</tr>
</table>
<h1> Results</h1>
<div id='tab_results_csv_table'></div>
<button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("tab_results_csv_table_pre")'> Copy raw data to clipboard</button>
<button onclick='download_as_file("tab_results_csv_table_pre", "results.csv")'> Download »results.csv« as file</button>
<pre id='tab_results_csv_table_pre'>trial_index,arm_name,trial_status,generation_method,generation_node,ACCURACY,RUNTIME,recent_samples_size,n_reference_samples,recent_samples_proportion,threshold
0,0_0,COMPLETED,Sobol,GenerationStep_0,0.736307939847762882301651643502,2.183224678039550781250000000000,2064,152,0.518407869338989302221420985006,0.655441236495971635278579014994
1,1_0,COMPLETED,Sobol,GenerationStep_0,0.745528807475710153518377865112,8.687381505966186523437500000000,1604,302,0.876934246439486697610732335306,0.649990846682339862283583897806
2,2_0,COMPLETED,Sobol,GenerationStep_0,0.743796026981867641758583431510,9.968394041061401367187500000000,687,167,0.303791355900466464312614789378,0.731414867192506812365593305003
3,3_0,COMPLETED,Sobol,GenerationStep_0,0.743300946840769860557429637993,6.435246467590332031250000000000,3236,486,0.613425990380346730646010655619,0.572820783685892842562736859691
4,4_0,COMPLETED,Sobol,GenerationStep_0,0.739216535676712638291974144522,22.193288564682006835937500000000,3931,221,0.952232261374592825475815516256,0.508507065661251589361313563131
5,5_0,COMPLETED,Sobol,GenerationStep_0,0.727272727272727292913145902276,1.725847244262695312500000000000,477,423,0.414930002391338370593132367503,0.795426039863377898342378102825
6,6_0,COMPLETED,Sobol,GenerationStep_0,0.730738288260412205410432306962,37.955897092819213867187500000000,1307,95,0.763100590091198682785034179688,0.582761756330728575292710047506
7,7_0,COMPLETED,Sobol,GenerationStep_0,0.746704622810817508771208395046,6.031735420227050781250000000000,2858,354,0.182186906691640615463256835938,0.722387258242815799569314094697
8,8_0,COMPLETED,Sobol,GenerationStep_0,0.745157497369886789861936904344,6.624246358871459960937500000000,2547,203,0.707564480137079954147338867188,0.769997640885412781841523610638
9,9_0,COMPLETED,Sobol,GenerationStep_0,0.744167337087691116437326854793,7.300962209701538085937500000000,1121,448,0.125218282546848053149446400312,0.534274097997695207595825195312
10,10_0,COMPLETED,Sobol,GenerationStep_0,0.746642737793180244487700747413,4.007841587066650390625000000000,173,134,0.895043924078345320971550336253,0.696545749902725219726562500000
11,11_0,COMPLETED,Sobol,GenerationStep_0,0.744476762175877215810260167927,13.332512140274047851562500000000,3750,323,0.359613632410764716418327680003,0.608850389998406127389785069681
12,12_0,COMPLETED,Sobol,GenerationStep_0,0.720341605297357467918573092902,45.140877485275268554687500000000,3416,71,0.246713726781308650970458984375,0.618959903158247448651252398122
13,13_0,COMPLETED,Sobol,GenerationStep_0,0.743734141964230488497378246393,5.912884712219238281250000000000,992,376,0.557998885400593280792236328125,0.686152028758078902370698415325
14,14_0,COMPLETED,Sobol,GenerationStep_0,0.739773500835447683776635585673,22.397147893905639648437500000000,1790,255,0.463200505170971221780007454072,0.542621776461601257324218750000
15,15_0,COMPLETED,Sobol,GenerationStep_0,0.734389504301008688713636729517,1.388938188552856445312500000000,2375,391,0.819636904168874025344848632812,0.761348554771393626339204274700
16,16_0,COMPLETED,Sobol,GenerationStep_0,0.748932483445757801732156622165,4.514317750930786132812500000000,2388,271,0.132036544196307670251400168127,0.587967881001532077789306640625
17,17_0,COMPLETED,Sobol,GenerationStep_0,0.737236215112321291442754045420,4.158936977386474609375000000000,1960,403,0.672634694911539599004868250631,0.706590041238814636770371180319
18,18_0,COMPLETED,Sobol,GenerationStep_0,0.729067392784206957934145520994,32.837114810943603515625000000000,761,59,0.352809050027281023709235796559,0.512657469511032082287727007497
19,19_0,COMPLETED,Sobol,GenerationStep_0,0.736307939847762882301651643502,1.970766067504882812500000000000,3340,360,0.929987388569861628262458452809,0.783116406481713100973252039694
20,20_0,COMPLETED,Sobol,GenerationStep_0,0.733028033912989651632585719199,73.840288877487182617187500000000,3515,118,0.593821108620613880013650032197,0.735501920618116922234719368134
21,21_0,COMPLETED,Sobol,GenerationStep_0,0.731419023454421668439806580864,2.044820308685302734375000000000,93,310,0.239030090626329183578491210938,0.560555374342948220522941937816
22,22_0,COMPLETED,Sobol,GenerationStep_0,0.742187016523299658565804293175,12.457314968109130859375000000000,1138,215,0.783828467503190018383918413747,0.660747656226158164294304242503
23,23_0,COMPLETED,Sobol,GenerationStep_0,0.748251748251748227680479885748,4.048747539520263671875000000000,2721,464,0.470897927880287170410156250000,0.634113106410950422286987304688
24,24_0,COMPLETED,Sobol,GenerationStep_0,0.731047713348598304783365620096,25.862130165100097656250000000000,2903,79,0.841112090274691581726074218750,0.549006642587482884820815343119
25,25_0,COMPLETED,Sobol,GenerationStep_0,0.743610371928955959930362951127,4.816474676132202148437500000000,1446,342,0.526091573387384436877312055003,0.746730079222470588540261360322
26,26_0,COMPLETED,Sobol,GenerationStep_0,0.747942323163562128307546572614,3.445949554443359375000000000000,277,233,0.649234467279166005404533734691,0.621931565552949927599968305003
27,27_0,COMPLETED,Sobol,GenerationStep_0,0.747199702951915289972362188564,10.086159706115722656250000000000,3823,439,0.296093973424285672457756390941,0.672663653921335980001572352194
28,28_0,COMPLETED,Sobol,GenerationStep_0,0.741073086205829567596481410874,13.642836093902587890625000000000,3032,183,0.408111700508743568960312586569,0.699472372420132160186767578125
29,29_0,COMPLETED,Sobol,GenerationStep_0,0.745714462528621835346598345495,3.154695749282836914062500000000,576,498,0.987162006366997912820693272806,0.595424549747258446963371625316
30,30_0,COMPLETED,BoTorch,GenerationStep_1,0.746828392846091926315921227797,7.969994544982910156250000000000,2605,239,0.115506559995414800900981333598,0.644631127210884891098885418614
31,31_0,COMPLETED,BoTorch,GenerationStep_1,0.748746828392846119903936141782,6.711926460266113281250000000000,2603,240,0.681063401282413827253492399905,0.645745786428713275384438929905
32,32_0,COMPLETED,BoTorch,GenerationStep_1,0.745714462528621835346598345495,5.551334619522094726562500000000,2445,218,0.100000000000000005551115123126,0.667414626808967681448336861649
33,33_0,COMPLETED,BoTorch,GenerationStep_1,0.743362831858407124840937285626,7.087778091430664062500000000000,2707,259,0.100000000000000005551115123126,0.633121899126984244432492232590
34,34_0,COMPLETED,BoTorch,GenerationStep_1,0.720465375332631996485588388168,1.207046270370483398437500000000,10,315,0.142901963482320037979178550813,0.698360800207266874117806310096
35,35_0,COMPLETED,BoTorch,GenerationStep_1,0.747137817934278136711157003447,8.236652851104736328125000000000,2797,230,0.100000000000000005551115123126,0.609439202833985116392057079793
36,36_0,COMPLETED,BoTorch,GenerationStep_1,0.745652577510984571063090697862,5.931980609893798828125000000000,2715,257,1.000000000000000000000000000000,0.630593838515440041625481626397
37,37_0,COMPLETED,BoTorch,GenerationStep_1,0.748375518287022756247495181015,5.543367385864257812500000000000,2511,256,0.100000000000000005551115123126,0.683186750806577980377198855422
38,38_0,COMPLETED,BoTorch,GenerationStep_1,0.722817006002846706991249448038,0.949705600738525390625000000000,10,447,0.100000000000000005551115123126,0.618119559117538464043661861069
39,39_0,COMPLETED,BoTorch,GenerationStep_1,0.714648183674732373482640923612,1.038052558898925781250000000000,10,500,0.100000000000000005551115123126,0.660596922877092929127229581354
40,40_0,RUNNING,BoTorch,GenerationStep_1,,,10,205,1.000000000000000000000000000000,0.794492356511261155205261275114
41,41_0,COMPLETED,BoTorch,GenerationStep_1,0.748313633269385491963987533381,6.777904987335205078125000000000,1297,500,0.183230660295289088379533382067,0.669526526936858878968905628426
42,42_0,COMPLETED,BoTorch,GenerationStep_1,0.734884584442106580937092985550,1.090355396270751953125000000000,10,326,0.920756662829941507908415587735,0.703284794760824394366238720977
43,43_0,COMPLETED,BoTorch,GenerationStep_1,0.743362831858407124840937285626,7.977913856506347656250000000000,1790,500,1.000000000000000000000000000000,0.589240549242555644582353124861
44,44_0,COMPLETED,BoTorch,GenerationStep_1,0.728696082678383594277704560227,1.305122613906860351562500000000,10,284,0.613540007237881268586932037579,0.730896882090422472799673414556
45,45_0,COMPLETED,BoTorch,GenerationStep_1,0.733894424159910907512482935999,1.540418624877929687500000000000,3207,500,1.000000000000000000000000000000,0.800000000000000044408920985006
46,46_0,COMPLETED,BoTorch,GenerationStep_1,0.723807166285042380415859497589,1.022796392440795898437500000000,10,431,1.000000000000000000000000000000,0.572295585767773506979949615925
47,47_0,COMPLETED,BoTorch,GenerationStep_1,0.733213688965901333460806199582,1.304160118103027343750000000000,10,254,1.000000000000000000000000000000,0.800000000000000044408920985006
48,48_0,COMPLETED,BoTorch,GenerationStep_1,0.726901417166903929256704941508,3.337907314300537109375000000000,10,252,0.100000000000000005551115123126,0.632864767028821217920153685554
49,49_0,COMPLETED,BoTorch,GenerationStep_1,0.745838232563896252891311178246,4.647129058837890625000000000000,2589,258,1.000000000000000000000000000000,0.678752421035333841636827401089
50,50_0,COMPLETED,BoTorch,GenerationStep_1,0.716257194133300356675420061947,1.144540786743164062500000000000,10,492,0.100000000000000005551115123126,0.500000000000000000000000000000
51,51_0,COMPLETED,BoTorch,GenerationStep_1,0.729253047837118639762366001378,3.682813167572021484375000000000,10,50,0.100000000000000005551115123126,0.800000000000000044408920985006
52,52_0,COMPLETED,BoTorch,GenerationStep_1,0.743362831858407124840937285626,9.148422479629516601562500000000,2777,206,0.100000000000000005551115123126,0.589700422650116351519500312861
53,53_0,COMPLETED,BoTorch,GenerationStep_1,0.743362831858407124840937285626,7.715135097503662109375000000000,2717,256,0.489112625863290406691419320850,0.632372917534441914000353790470
54,54_0,COMPLETED,BoTorch,GenerationStep_1,0.723250201126307334931198056438,1.018053770065307617187500000000,10,424,1.000000000000000000000000000000,0.500000000000000000000000000000
55,55_0,COMPLETED,BoTorch,GenerationStep_1,0.715081378798193001422589532012,1.552335739135742187500000000000,10,323,0.100000000000000005551115123126,0.800000000000000044408920985006
56,56_0,COMPLETED,BoTorch,GenerationStep_1,0.745157497369886789861936904344,2.942462205886840820312500000000,2198,221,0.100000000000000005551115123126,0.708648710485052180096943175158
57,57_0,COMPLETED,BoTorch,GenerationStep_1,0.746642737793180244487700747413,3.498023986816406250000000000000,2200,272,0.100000000000000005551115123126,0.656463004013294715299764447991
58,58_0,COMPLETED,BoTorch,GenerationStep_1,0.737978835323968018755635966954,1.935891389846801757812500000000,1742,500,1.000000000000000000000000000000,0.800000000000000044408920985006
59,59_0,COMPLETED,BoTorch,GenerationStep_1,0.748313633269385491963987533381,7.471195697784423828125000000000,2576,220,0.100000000000000005551115123126,0.642488881880514783873081796628
60,60_0,COMPLETED,BoTorch,GenerationStep_1,0.733337459001175862027821494848,4.783013820648193359375000000000,645,294,1.000000000000000000000000000000,0.638825809570262137526697188150
61,61_0,COMPLETED,BoTorch,GenerationStep_1,0.746457082740268562659480267030,7.068891525268554687500000000000,2180,83,0.100000000000000005551115123126,0.723251810799291350306816639204
62,62_0,COMPLETED,BoTorch,GenerationStep_1,0.745528807475710153518377865112,8.818787813186645507812500000000,1633,417,0.328502449531745566169149697089,0.697880995617388366625277740241
63,63_0,COMPLETED,BoTorch,GenerationStep_1,0.736369824865400035562856828619,1.976449728012084960937500000000,304,480,1.000000000000000000000000000000,0.621882268748546018777290100843
64,64_0,COMPLETED,BoTorch,GenerationStep_1,0.746209542669719616547752139013,3.392942667007446289062500000000,709,416,1.000000000000000000000000000000,0.584902148720357506483935594588
65,65_0,COMPLETED,BoTorch,GenerationStep_1,0.748004208181199281568751757732,2.738443136215209960937500000000,2403,500,0.100000000000000005551115123126,0.513645287978756082125642024039
66,66_0,COMPLETED,BoTorch,GenerationStep_1,0.743424716876044278102142470743,12.912328958511352539062500000000,2162,50,0.100000000000000005551115123126,0.500000000000000000000000000000
67,67_0,COMPLETED,BoTorch,GenerationStep_1,0.747880438145924864024038924981,6.855543136596679687500000000000,2085,50,0.100000000000000005551115123126,0.800000000000000044408920985006
68,68_0,COMPLETED,BoTorch,GenerationStep_1,0.744724302246426161921988295944,7.546589136123657226562500000000,3457,438,0.100000000000000005551115123126,0.800000000000000044408920985006
69,69_0,COMPLETED,BoTorch,GenerationStep_1,0.746457082740268562659480267030,5.550619363784790039062500000000,766,276,1.000000000000000000000000000000,0.599828902674461539312744662311
70,70_0,COMPLETED,BoTorch,GenerationStep_1,0.744662417228788897638480648311,5.252315282821655273437500000000,2953,500,0.100000000000000005551115123126,0.659351695220056766011396121030
71,71_0,COMPLETED,BoTorch,GenerationStep_1,0.745281267405161207406649737095,4.184517621994018554687500000000,887,500,1.000000000000000000000000000000,0.609478382542192775872536003590
72,72_0,COMPLETED,BoTorch,GenerationStep_1,0.730862058295686622955145139713,1.286099672317504882812500000000,881,500,1.000000000000000000000000000000,0.800000000000000044408920985006
73,73_0,COMPLETED,BoTorch,GenerationStep_1,0.747075932916640872427649355814,5.140978336334228515625000000000,624,355,1.000000000000000000000000000000,0.500000000000000000000000000000
74,74_0,COMPLETED,BoTorch,GenerationStep_1,0.742929636734946496900988677226,9.421009063720703125000000000000,2286,71,1.000000000000000000000000000000,0.800000000000000044408920985006
75,75_0,COMPLETED,BoTorch,GenerationStep_1,0.735441549600841626421754426701,2.943936824798583984375000000000,504,292,1.000000000000000000000000000000,0.636977499622613740903886991873
76,76_0,COMPLETED,BoTorch,GenerationStep_1,0.729005507766569693650637873361,1.373528957366943359375000000000,710,280,1.000000000000000000000000000000,0.800000000000000044408920985006
77,77_0,COMPLETED,BoTorch,GenerationStep_1,0.747632898075375917912310796964,6.581807136535644531250000000000,443,203,1.000000000000000000000000000000,0.661135337862145844312067310966
78,78_0,COMPLETED,BoTorch,GenerationStep_1,0.735070239495018262765313465934,1.969295263290405273437500000000,2218,500,0.100000000000000005551115123126,0.500000000000000000000000000000
79,79_0,COMPLETED,BoTorch,GenerationStep_1,0.747571013057738764651105611847,4.311360120773315429687500000000,2572,390,0.355368780319336940998198315356,0.541360166894989891517298019608
80,80_0,COMPLETED,BoTorch,GenerationStep_1,0.746271427687356880831259786646,6.876530647277832031250000000000,2231,104,1.000000000000000000000000000000,0.500000000000000000000000000000
81,81_0,COMPLETED,BoTorch,GenerationStep_1,0.738226375394516964867364094971,13.175046205520629882812500000000,2269,50,0.100000000000000005551115123126,0.800000000000000044408920985006
82,82_0,COMPLETED,BoTorch,GenerationStep_1,0.746828392846091926315921227797,77.427549123764038085937500000000,2943,500,0.100000000000000005551115123126,0.800000000000000044408920985006
83,83_0,COMPLETED,BoTorch,GenerationStep_1,0.745776347546259099630105993128,6.605385303497314453125000000000,3148,418,0.100000000000000005551115123126,0.800000000000000044408920985006
84,84_0,COMPLETED,BoTorch,GenerationStep_1,0.745528807475710153518377865112,12.408201456069946289062500000000,4000,352,0.408337468376263001967885202248,0.605207495056577338132797194703
85,85_0,COMPLETED,BoTorch,GenerationStep_1,0.748127978216473810135767052998,8.995258092880249023437500000000,1665,409,0.100000000000000005551115123126,0.800000000000000044408920985006
86,86_0,COMPLETED,BoTorch,GenerationStep_1,0.742682096664397550789260549209,5.720322132110595703125000000000,1546,428,1.000000000000000000000000000000,0.608698331006392368003332649096
87,87_0,COMPLETED,BoTorch,GenerationStep_1,0.742991521752583650162193862343,7.313158988952636718750000000000,3525,500,0.100000000000000005551115123126,0.706196251558395715619553811848
88,88_0,COMPLETED,BoTorch,GenerationStep_1,0.739154650659075485030768959405,13.734014987945556640625000000000,281,50,1.000000000000000000000000000000,0.676826691125228308010264299810
89,89_0,COMPLETED,BoTorch,GenerationStep_1,0.715700228974565311190758620796,103.923360347747802734375000000000,1889,50,1.000000000000000000000000000000,0.598616799437230673319731977244
90,90_0,COMPLETED,BoTorch,GenerationStep_1,0.743610371928955959930362951127,7.355760574340820312500000000000,3891,414,0.366879220330843691666444783550,0.800000000000000044408920985006
91,91_0,COMPLETED,BoTorch,GenerationStep_1,0.741320626276378513708209538891,8.861977100372314453125000000000,2407,135,0.686304345241082747186567303288,0.500000000000000000000000000000
92,92_0,COMPLETED,BoTorch,GenerationStep_1,0.731047713348598304783365620096,1.478384733200073242187500000000,3818,451,1.000000000000000000000000000000,0.792875541801024152910315478948
93,93_0,COMPLETED,BoTorch,GenerationStep_1,0.730614518225137676843417011696,27.411981105804443359375000000000,1040,87,0.196515552233419932282032505100,0.774589503955199876195081287733
94,94_0,COMPLETED,BoTorch,GenerationStep_1,0.748127978216473810135767052998,9.151727914810180664062500000000,3921,500,0.100000000000000005551115123126,0.643134576866101204117853740172
95,95_0,RUNNING,BoTorch,GenerationStep_1,,,896,84,0.751134286431583864107608405902,0.800000000000000044408920985006
96,96_0,COMPLETED,BoTorch,GenerationStep_1,0.747756668110650446479326092231,4.856577396392822265625000000000,270,168,1.000000000000000000000000000000,0.542542718861077077896482023789
97,97_0,COMPLETED,BoTorch,GenerationStep_1,0.730923943313323887238652787346,32.303490877151489257812500000000,1849,128,0.100000000000000005551115123126,0.773767811287812357079474168131
98,98_0,COMPLETED,BoTorch,GenerationStep_1,0.737731295253419183666210301453,3.191952466964721679687500000000,4000,500,1.000000000000000000000000000000,0.724493898729950847048542073026
99,99_0,COMPLETED,BoTorch,GenerationStep_1,0.744971842316975108033716423961,3.315420627593994140625000000000,3694,500,1.000000000000000000000000000000,0.698651471233876386612848818913
100,100_0,COMPLETED,BoTorch,GenerationStep_1,0.748870598428120537448648974532,6.171407461166381835937500000000,776,464,1.000000000000000000000000000000,0.500000000000000000000000000000
101,101_0,COMPLETED,BoTorch,GenerationStep_1,0.745343152422798471690157384728,10.873683452606201171875000000000,4000,401,0.100000000000000005551115123126,0.800000000000000044408920985006
102,102_0,COMPLETED,BoTorch,GenerationStep_1,0.730552633207500412559909364063,2.029278755187988281250000000000,2822,450,1.000000000000000000000000000000,0.742946739939670308672248211224
103,103_0,COMPLETED,BoTorch,GenerationStep_1,0.746085772634445199003039306263,8.040475130081176757812500000000,2416,152,1.000000000000000000000000000000,0.500000000000000000000000000000
104,104_0,COMPLETED,BoTorch,GenerationStep_1,0.736741134971223510241600251902,13.916342973709106445312500000000,533,88,0.100000000000000005551115123126,0.716071608090063538298863932141
105,105_0,COMPLETED,BoTorch,GenerationStep_1,0.744105452070053852153819207160,5.074169397354125976562500000000,319,163,1.000000000000000000000000000000,0.800000000000000044408920985006
106,106_0,COMPLETED,BoTorch,GenerationStep_1,0.733151803948264180199601014465,1.763571262359619140625000000000,3667,428,1.000000000000000000000000000000,0.800000000000000044408920985006
107,107_0,COMPLETED,BoTorch,GenerationStep_1,0.747323472987189818539377483830,3.638075828552246093750000000000,235,208,1.000000000000000000000000000000,0.500000000000000000000000000000
108,108_0,COMPLETED,BoTorch,GenerationStep_1,0.733584999071724697117247160350,2.772731542587280273437500000000,3742,399,0.465824734357301650788940605707,0.800000000000000044408920985006
109,109_0,COMPLETED,BoTorch,GenerationStep_1,0.747199702951915289972362188564,6.987059593200683593750000000000,356,152,0.418098202818398601010585480253,0.586150572685161574959522567951
110,110_0,COMPLETED,BoTorch,GenerationStep_1,0.743548486911318806669157766009,7.124074459075927734375000000000,2310,123,0.100000000000000005551115123126,0.500000000000000000000000000000
111,111_0,COMPLETED,BoTorch,GenerationStep_1,0.731171483383872722328078452847,36.262567281723022460937500000000,1529,108,0.100000000000000005551115123126,0.787335530276595862986255269789
112,112_0,COMPLETED,BoTorch,GenerationStep_1,0.743177176805495443012716805242,3.808005094528198242187500000000,173,250,1.000000000000000000000000000000,0.500000000000000000000000000000
113,113_0,COMPLETED,BoTorch,GenerationStep_1,0.743053406770220914445701509976,12.124515056610107421875000000000,3805,365,0.100000000000000005551115123126,0.800000000000000044408920985006
114,114_0,COMPLETED,BoTorch,GenerationStep_1,0.747756668110650446479326092231,12.204314947128295898437500000000,3854,432,0.100000000000000005551115123126,0.500000000000000000000000000000
115,115_0,COMPLETED,BoTorch,GenerationStep_1,0.737298100129958555726261693053,17.174033880233764648437500000000,591,65,1.000000000000000000000000000000,0.800000000000000044408920985006
116,116_0,COMPLETED,BoTorch,GenerationStep_1,0.745714462528621835346598345495,7.488593578338623046875000000000,834,364,0.204601025919120382834393012672,0.500000000000000000000000000000
117,117_0,COMPLETED,BoTorch,GenerationStep_1,0.740144810941271158455379008956,8.660166025161743164062500000000,425,127,0.100000000000000005551115123126,0.627846013861477092454776993691
118,118_0,COMPLETED,BoTorch,GenerationStep_1,0.748251748251748227680479885748,4.647240877151489257812500000000,735,500,0.574410043010757709325275754964,0.500000000000000000000000000000
119,119_0,COMPLETED,BoTorch,GenerationStep_1,0.733399344018813015289026679966,1.892958164215087890625000000000,4000,459,0.933732924545818243622363752365,0.800000000000000044408920985006
120,120_0,COMPLETED,BoTorch,GenerationStep_1,0.747199702951915289972362188564,3.821068286895751953125000000000,2444,332,0.100000000000000005551115123126,0.593760130024420407224283735559
121,121_0,COMPLETED,BoTorch,GenerationStep_1,0.732594838789529023692637110798,1.949542045593261718750000000000,3238,395,0.537060595457705902688871901773,0.796482276339019912292371827789
122,122_0,COMPLETED,BoTorch,GenerationStep_1,0.737298100129958555726261693053,1.826632738113403320312500000000,1335,454,1.000000000000000000000000000000,0.759340912913785026638890940376
123,123_0,COMPLETED,BoTorch,GenerationStep_1,0.748684943375208855620428494149,3.771660804748535156250000000000,2569,447,0.100000000000000005551115123126,0.500000000000000000000000000000
124,124_0,COMPLETED,BoTorch,GenerationStep_1,0.745714462528621835346598345495,3.437059879302978515625000000000,2603,500,0.100000000000000005551115123126,0.595453247181469413895626985322
125,125_0,COMPLETED,BoTorch,GenerationStep_1,0.745033727334612261294921609078,3.574683666229248046875000000000,2252,290,0.100000000000000005551115123126,0.800000000000000044408920985006
126,126_0,COMPLETED,BoTorch,GenerationStep_1,0.744786187264063315183193481062,10.294945001602172851562500000000,3041,306,0.100000000000000005551115123126,0.500000000000000000000000000000
127,127_0,COMPLETED,BoTorch,GenerationStep_1,0.740330465994182840283599489339,8.209368705749511718750000000000,925,269,0.100000000000000005551115123126,0.775900393757729012200741181005
128,128_0,COMPLETED,BoTorch,GenerationStep_1,0.747447243022464236084090316581,3.567324876785278320312500000000,2536,451,0.693669315962611610082433344360,0.500000000000000000000000000000
129,129_0,COMPLETED,BoTorch,GenerationStep_1,0.737916950306330865494430781837,1.671604394912719726562500000000,3758,500,1.000000000000000000000000000000,0.800000000000000044408920985006
130,130_0,COMPLETED,BoTorch,GenerationStep_1,0.748127978216473810135767052998,4.132918119430541992187500000000,2485,327,0.100000000000000005551115123126,0.500000000000000000000000000000
131,131_0,COMPLETED,BoTorch,GenerationStep_1,0.745838232563896252891311178246,4.295659065246582031250000000000,2663,418,0.100000000000000005551115123126,0.617148910719188981133243032673
132,132_0,COMPLETED,BoTorch,GenerationStep_1,0.746395197722631298375972619397,9.798187732696533203125000000000,3463,384,1.000000000000000000000000000000,0.500000000000000000000000000000
133,133_0,COMPLETED,BoTorch,GenerationStep_1,0.745157497369886789861936904344,5.558305740356445312500000000000,1093,500,0.100000000000000005551115123126,0.800000000000000044408920985006
134,134_0,COMPLETED,BoTorch,GenerationStep_1,0.743734141964230488497378246393,3.422290086746215820312500000000,2471,346,0.682322775953409510485414557479,0.616598287662781907592091101833
135,135_0,COMPLETED,BoTorch,GenerationStep_1,0.750912804010149148581376721268,7.974772930145263671875000000000,3123,432,0.100000000000000005551115123126,0.613369213307905503107519962214
136,136_0,COMPLETED,BoTorch,GenerationStep_1,0.740825546135280621484753282857,4.104442119598388671875000000000,1698,274,0.747562948141095473530981507793,0.800000000000000044408920985006
137,137_0,COMPLETED,BoTorch,GenerationStep_1,0.743300946840769860557429637993,10.489744663238525390625000000000,1734,375,1.000000000000000000000000000000,0.500000000000000000000000000000
138,138_0,COMPLETED,BoTorch,GenerationStep_1,0.747694783093013182195818444598,5.346828460693359375000000000000,472,239,0.100000000000000005551115123126,0.800000000000000044408920985006
139,139_0,COMPLETED,BoTorch,GenerationStep_1,0.734637044371557634825364857534,1.248261213302612304687500000000,1336,415,1.000000000000000000000000000000,0.800000000000000044408920985006
140,140_0,COMPLETED,BoTorch,GenerationStep_1,0.733832539142273643228975288366,1.811891794204711914062500000000,2547,352,1.000000000000000000000000000000,0.662883980916453841025770543638
141,141_0,COMPLETED,BoTorch,GenerationStep_1,0.743362831858407124840937285626,11.415911197662353515625000000000,913,187,1.000000000000000000000000000000,0.500000000000000000000000000000
142,142_0,COMPLETED,BoTorch,GenerationStep_1,0.744043567052416587870311559527,8.164391279220581054687500000000,3673,500,1.000000000000000000000000000000,0.500000000000000000000000000000
143,143_0,COMPLETED,BoTorch,GenerationStep_1,0.746890277863729190599428875430,4.822856664657592773437500000000,2366,181,1.000000000000000000000000000000,0.683403738315074504861001969402
144,144_0,COMPLETED,BoTorch,GenerationStep_1,0.746333312704994145114767434279,8.618905782699584960937500000000,2781,252,0.100000000000000005551115123126,0.800000000000000044408920985006
145,145_0,COMPLETED,BoTorch,GenerationStep_1,0.742867751717309232617481029592,14.871916055679321289062500000000,1781,352,0.100000000000000005551115123126,0.598747121218595745872903535201
146,146_0,COMPLETED,BoTorch,GenerationStep_1,0.735874744724302254361703035102,18.665063381195068359375000000000,1117,150,1.000000000000000000000000000000,0.500000000000000000000000000000
147,147_0,COMPLETED,BoTorch,GenerationStep_1,0.744043567052416587870311559527,15.854224443435668945312500000000,1520,277,0.100000000000000005551115123126,0.800000000000000044408920985006
148,148_0,COMPLETED,BoTorch,GenerationStep_1,0.743672256946593224213870598760,13.357019424438476562500000000000,3738,330,0.100000000000000005551115123126,0.500000000000000000000000000000
149,149_0,COMPLETED,BoTorch,GenerationStep_1,0.746457082740268562659480267030,4.311033487319946289062500000000,2585,408,1.000000000000000000000000000000,0.500000000000000000000000000000
150,150_0,COMPLETED,BoTorch,GenerationStep_1,0.729562472925304739135299314512,1.646525859832763671875000000000,2263,308,0.649702835616558505016371327656,0.751553534209445817104722209478
151,151_0,COMPLETED,BoTorch,GenerationStep_1,0.731666563524970614551534708880,1.464430570602416992187500000000,1753,344,1.000000000000000000000000000000,0.790678688895548265058721426612
152,152_0,COMPLETED,BoTorch,GenerationStep_1,0.747694783093013182195818444598,4.373811721801757812500000000000,2206,142,0.100000000000000005551115123126,0.649396025192932824232627808669
153,153_0,COMPLETED,BoTorch,GenerationStep_1,0.747014047899003608144141708181,5.053992986679077148437500000000,432,242,0.371414851254861955176522769762,0.518539728111135800325826039625
154,154_0,COMPLETED,BoTorch,GenerationStep_1,0.745095612352249525578429256711,4.238352298736572265625000000000,615,480,0.408540840774158697801254902515,0.598730497478769385644170597516
155,155_0,COMPLETED,BoTorch,GenerationStep_1,0.744909957299337843750208776328,6.328864574432373046875000000000,556,285,0.100000000000000005551115123126,0.655601098459196562906470262533
156,156_0,COMPLETED,BoTorch,GenerationStep_1,0.742620211646760286505752901576,9.207936525344848632812500000000,3355,412,0.100000000000000005551115123126,0.732067951088689938821119085333
157,157_0,COMPLETED,BoTorch,GenerationStep_1,0.746890277863729190599428875430,3.685358285903930664062500000000,558,426,0.467625035879469741484371070328,0.500000000000000000000000000000
158,158_0,COMPLETED,BoTorch,GenerationStep_1,0.741320626276378513708209538891,3.506933450698852539062500000000,492,332,0.445350988427553884374532344737,0.771927414091979957611044937948
159,159_0,COMPLETED,BoTorch,GenerationStep_1,0.731480908472058932723314228497,1.300581455230712890625000000000,2471,285,1.000000000000000000000000000000,0.800000000000000044408920985006
160,160_0,COMPLETED,BoTorch,GenerationStep_1,0.741939476452750823476378627674,7.336583852767944335937500000000,867,291,1.000000000000000000000000000000,0.500000000000000000000000000000
161,161_0,COMPLETED,BoTorch,GenerationStep_1,0.733028033912989651632585719199,1.022905349731445312500000000000,234,345,0.955727622311423163914412270969,0.800000000000000044408920985006
162,162_0,COMPLETED,BoTorch,GenerationStep_1,0.746952162881366454882936523063,6.178628683090209960937500000000,536,237,0.100000000000000005551115123126,0.689439476969329168021261011745
163,163_0,COMPLETED,BoTorch,GenerationStep_1,0.732347298718980188603211445297,1.422397851943969726562500000000,99,334,1.000000000000000000000000000000,0.578724362460181884770804572327
164,164_0,COMPLETED,BoTorch,GenerationStep_1,0.743734141964230488497378246393,2.571712017059326171875000000000,308,411,0.171197660771112342148470020220,0.500000000000000000000000000000
165,165_0,COMPLETED,BoTorch,GenerationStep_1,0.732780493842440705520857591182,1.027423143386840820312500000000,2086,328,1.000000000000000000000000000000,0.800000000000000044408920985006
166,166_0,COMPLETED,BoTorch,GenerationStep_1,0.734327619283371535452431544400,1.898241996765136718750000000000,664,500,0.573173905213251511092664713942,0.711943687478496012310813512158
167,167_0,COMPLETED,BoTorch,GenerationStep_1,0.746333312704994145114767434279,7.437020301818847656250000000000,752,289,0.470797211758464229092169262003,0.500000000000000000000000000000
168,168_0,COMPLETED,BoTorch,GenerationStep_1,0.746209542669719616547752139013,5.405806779861450195312500000000,538,277,0.100000000000000005551115123126,0.500000000000000000000000000000
169,169_0,COMPLETED,BoTorch,GenerationStep_1,0.747880438145924864024038924981,4.662485837936401367187500000000,805,500,0.100000000000000005551115123126,0.585558472736425916771452193643
170,170_0,COMPLETED,BoTorch,GenerationStep_1,0.746457082740268562659480267030,4.913915872573852539062500000000,2578,315,1.000000000000000000000000000000,0.500000000000000000000000000000
171,171_0,COMPLETED,BoTorch,GenerationStep_1,0.748808713410483273165141326899,5.065740823745727539062500000000,281,210,0.100000000000000005551115123126,0.500000000000000000000000000000
172,172_0,COMPLETED,BoTorch,GenerationStep_1,0.734327619283371535452431544400,1.995362758636474609375000000000,2640,299,0.672840166432513542282833896024,0.790132734247312895625725559512
173,173_0,COMPLETED,BoTorch,GenerationStep_1,0.736926790024135192069820732286,3.984994173049926757812500000000,3490,264,1.000000000000000000000000000000,0.719540459967451084821732365526
174,174_0,COMPLETED,BoTorch,GenerationStep_1,0.748437403304659909508700366132,4.555063009262084960937500000000,457,369,0.100000000000000005551115123126,0.599149560920241408545905414940
175,175_0,COMPLETED,BoTorch,GenerationStep_1,0.730552633207500412559909364063,1.260746240615844726562500000000,301,412,1.000000000000000000000000000000,0.705402243652485050340317229711
176,176_0,COMPLETED,BoTorch,GenerationStep_1,0.744167337087691116437326854793,5.904136657714843750000000000000,840,412,0.731196703116650970066814352322,0.500000000000000000000000000000
177,177_0,COMPLETED,BoTorch,GenerationStep_1,0.745962002599170781458326473512,5.952266931533813476562500000000,925,354,1.000000000000000000000000000000,0.565411757042408869011751448852
178,178_0,COMPLETED,BoTorch,GenerationStep_1,0.744538647193514480093767815561,5.744604349136352539062500000000,568,270,0.125434545740826464133022000169,0.572114654597391969481634532713
179,179_0,COMPLETED,BoTorch,GenerationStep_1,0.728943622748932429367130225728,2.031710386276245117187500000000,4000,293,1.000000000000000000000000000000,0.742883720725427187936418249592
180,180_0,COMPLETED,BoTorch,GenerationStep_1,0.746952162881366454882936523063,4.846801042556762695312500000000,2466,351,0.100000000000000005551115123126,0.800000000000000044408920985006
181,181_0,COMPLETED,BoTorch,GenerationStep_1,0.738968995606163803202548479021,3.089865684509277343750000000000,409,223,0.728035438225800191069936317945,0.767572352436558746902051098004
182,182_0,COMPLETED,BoTorch,GenerationStep_1,0.746890277863729190599428875430,3.565519094467163085937500000000,448,436,0.100000000000000005551115123126,0.707284568340927233265347240376
183,183_0,COMPLETED,BoTorch,GenerationStep_1,0.747571013057738764651105611847,6.085816383361816406250000000000,2367,177,0.448738805988256383994183806863,0.687116930713041029754606370261
184,184_0,COMPLETED,BoTorch,GenerationStep_1,0.727025187202178346801417774259,1.288736820220947265625000000000,30,249,1.000000000000000000000000000000,0.586574453405463880351078387321
185,185_0,COMPLETED,BoTorch,GenerationStep_1,0.725725601831796574003874411574,1.444747686386108398437500000000,24,182,0.589139268022315087947049505601,0.742071187590371716957804437698
186,186_0,COMPLETED,BoTorch,GenerationStep_1,0.746766507828454773054716042680,6.893637657165527343750000000000,3273,500,0.100000000000000005551115123126,0.631977398471462392670616736723
187,187_0,COMPLETED,BoTorch,GenerationStep_1,0.736864905006497927786313084653,2.397611141204833984375000000000,3529,334,1.000000000000000000000000000000,0.688381594432957544249518377910
188,188_0,COMPLETED,BoTorch,GenerationStep_1,0.732161643666068395752688502398,1.426753520965576171875000000000,3624,303,1.000000000000000000000000000000,0.800000000000000044408920985006
189,189_0,COMPLETED,BoTorch,GenerationStep_1,0.746333312704994145114767434279,3.875694513320922851562500000000,2677,500,1.000000000000000000000000000000,0.500000000000000000000000000000
190,190_0,COMPLETED,BoTorch,GenerationStep_1,0.743053406770220914445701509976,10.767284631729125976562500000000,1531,500,0.496785917745189320449128445034,0.500000000000000000000000000000
191,191_0,COMPLETED,BoTorch,GenerationStep_1,0.739959155888359476627158528572,7.945672750473022460937500000000,1569,500,0.100000000000000005551115123126,0.558390753208332979440342569433
192,192_0,COMPLETED,BoTorch,GenerationStep_1,0.733832539142273643228975288366,0.907146215438842773437500000000,10,457,1.000000000000000000000000000000,0.800000000000000044408920985006
193,193_0,COMPLETED,BoTorch,GenerationStep_1,0.750046413763227892701479504467,5.824539899826049804687500000000,3082,500,0.100000000000000005551115123126,0.500000000000000000000000000000
194,194_0,RUNNING,BoTorch,GenerationStep_1,,,4000,247,0.100000000000000005551115123126,0.687832456139463643829401462426
195,195_0,COMPLETED,BoTorch,GenerationStep_1,0.732842378860077969804365238815,1.533497095108032226562500000000,1984,433,1.000000000000000000000000000000,0.800000000000000044408920985006
196,196_0,COMPLETED,BoTorch,GenerationStep_1,0.748561173339934438075715661398,4.198185205459594726562500000000,183,127,1.000000000000000000000000000000,0.618417984189900016289698214678
197,197_0,COMPLETED,BoTorch,GenerationStep_1,0.723683396249767962871146664838,1.190914630889892578125000000000,2251,500,1.000000000000000000000000000000,0.695907352527174838385803923302
198,198_0,COMPLETED,BoTorch,GenerationStep_1,0.748561173339934438075715661398,9.189648389816284179687500000000,1837,466,0.100000000000000005551115123126,0.571391621765147572631349248695
199,199_0,COMPLETED,BoTorch,GenerationStep_1,0.746642737793180244487700747413,6.273688316345214843750000000000,930,220,1.000000000000000000000000000000,0.800000000000000044408920985006
200,200_0,COMPLETED,BoTorch,GenerationStep_1,0.741011201188192303312973763241,2.962178468704223632812500000000,2529,417,1.000000000000000000000000000000,0.602241390149755861926905708970
201,201_0,COMPLETED,BoTorch,GenerationStep_1,0.744848072281700579466701128695,5.576772928237915039062500000000,2898,406,0.391248426956507688867503702568,0.500000000000000000000000000000
202,202_0,COMPLETED,BoTorch,GenerationStep_1,0.737298100129958555726261693053,25.139543294906616210937500000000,1338,160,0.100000000000000005551115123126,0.615179789134131849159814464656
203,203_0,COMPLETED,BoTorch,GenerationStep_1,0.711739587845782506470015960076,2.056615352630615234375000000000,10,146,0.293487783626195153363624967824,0.772063106787775788042438307457
204,204_0,COMPLETED,BoTorch,GenerationStep_1,0.747509128040101500367597964214,4.014353275299072265625000000000,616,491,0.100000000000000005551115123126,0.500000000000000000000000000000
205,205_0,COMPLETED,BoTorch,GenerationStep_1,0.743672256946593224213870598760,3.070026636123657226562500000000,2251,345,0.100000000000000005551115123126,0.715799530901314873254648318834
206,206_0,COMPLETED,BoTorch,GenerationStep_1,0.739897270870722212343650880939,4.830780029296875000000000000000,3383,402,1.000000000000000000000000000000,0.614139689138636035714569061383
207,207_0,COMPLETED,BoTorch,GenerationStep_1,0.745838232563896252891311178246,12.100521802902221679687500000000,1662,500,1.000000000000000000000000000000,0.500000000000000000000000000000
208,208_0,COMPLETED,BoTorch,GenerationStep_1,0.737978835323968018755635966954,18.912549257278442382812500000000,1511,191,0.100000000000000005551115123126,0.646667075682613945453169890243
209,209_0,COMPLETED,BoTorch,GenerationStep_1,0.745157497369886789861936904344,6.903050422668457031250000000000,3043,338,1.000000000000000000000000000000,0.583982619375754019586111098761
210,210_0,COMPLETED,BoTorch,GenerationStep_1,0.746766507828454773054716042680,5.282370090484619140625000000000,299,217,1.000000000000000000000000000000,0.561485619855812689849017260713
211,211_0,COMPLETED,BoTorch,GenerationStep_1,0.737669410235781919382702653820,1.481028318405151367187500000000,3546,489,1.000000000000000000000000000000,0.754259069874067655803173693130
212,212_0,COMPLETED,BoTorch,GenerationStep_1,0.744105452070053852153819207160,8.664343595504760742187500000000,2451,163,1.000000000000000000000000000000,0.606597441618285548869948797801
213,213_0,COMPLETED,BoTorch,GenerationStep_1,0.746766507828454773054716042680,3.785945653915405273437500000000,389,375,0.100000000000000005551115123126,0.712598098599154683441270208277
214,214_0,COMPLETED,BoTorch,GenerationStep_1,0.746333312704994145114767434279,3.667917728424072265625000000000,323,287,0.680094391563868971850581601757,0.567248749723189948923618430854
215,215_0,COMPLETED,BoTorch,GenerationStep_1,0.747571013057738764651105611847,9.941710472106933593750000000000,4000,485,0.100000000000000005551115123126,0.717261478665195184589720156509
216,216_0,COMPLETED,BoTorch,GenerationStep_1,0.743796026981867641758583431510,6.802497148513793945312500000000,3110,455,1.000000000000000000000000000000,0.500000000000000000000000000000
217,217_0,COMPLETED,BoTorch,GenerationStep_1,0.736431709883037299846364476252,18.696664333343505859375000000000,4000,237,0.100000000000000005551115123126,0.800000000000000044408920985006
218,218_0,COMPLETED,BoTorch,GenerationStep_1,0.744786187264063315183193481062,3.313830375671386718750000000000,465,419,0.100000000000000005551115123126,0.560255059692759793676941626472
219,219_0,COMPLETED,BoTorch,GenerationStep_1,0.716009654062751410563691933930,93.111581325531005859375000000000,4000,50,0.100000000000000005551115123126,0.500000000000000000000000000000
220,220_0,COMPLETED,BoTorch,GenerationStep_1,0.735070239495018262765313465934,2.311625242233276367187500000000,1038,269,1.000000000000000000000000000000,0.741787043312515770310255902587
221,221_0,RUNNING,BoTorch,GenerationStep_1,,,3978,214,0.100000000000000005551115123126,0.626503714927654442590210237540
222,222_0,COMPLETED,BoTorch,GenerationStep_1,0.746395197722631298375972619397,3.478796243667602539062500000000,515,500,1.000000000000000000000000000000,0.500000000000000000000000000000
223,223_0,COMPLETED,BoTorch,GenerationStep_1,0.714462528621820691654420443228,152.567648172378540039062500000000,4000,50,0.661268154783933637119730519771,0.500000000000000000000000000000
224,224_0,COMPLETED,BoTorch,GenerationStep_1,0.729562472925304739135299314512,1.802689313888549804687500000000,1018,317,1.000000000000000000000000000000,0.740167626371919129546483873128
225,225_0,COMPLETED,BoTorch,GenerationStep_1,0.740887431152917885768260930490,3.405369043350219726562500000000,2784,500,1.000000000000000000000000000000,0.643246320842205898671295472013
226,226_0,COMPLETED,BoTorch,GenerationStep_1,0.746642737793180244487700747413,3.978531360626220703125000000000,2624,500,0.474882696212986621375762297248,0.500000000000000000000000000000
227,227_0,COMPLETED,BoTorch,GenerationStep_1,0.747137817934278136711157003447,3.306615591049194335937500000000,354,336,0.100000000000000005551115123126,0.500000000000000000000000000000
228,228_0,COMPLETED,BoTorch,GenerationStep_1,0.737855065288693601210923134204,3.255117654800415039062500000000,1079,457,0.439679578392530689967543366947,0.800000000000000044408920985006
229,229_0,COMPLETED,BoTorch,GenerationStep_1,0.743672256946593224213870598760,2.731062412261962890625000000000,411,500,0.100000000000000005551115123126,0.777772251127402669546029301273
230,230_0,COMPLETED,BoTorch,GenerationStep_1,0.743857911999504906042091079144,2.837200880050659179687500000000,1306,500,1.000000000000000000000000000000,0.707334518508394904934277747088
231,231_0,COMPLETED,BoTorch,GenerationStep_1,0.744538647193514480093767815561,2.942617177963256835937500000000,369,382,0.539434902377766145598059210897,0.545652214530319312757455918472
232,232_0,COMPLETED,BoTorch,GenerationStep_1,0.742620211646760286505752901576,2.731566190719604492187500000000,1605,500,1.000000000000000000000000000000,0.709861955533884869673499906639
233,233_0,COMPLETED,BoTorch,GenerationStep_1,0.741691936382201877364650499658,15.654021739959716796875000000000,935,146,1.000000000000000000000000000000,0.674335382359083190806359198177
234,234_0,COMPLETED,BoTorch,GenerationStep_1,0.743610371928955959930362951127,3.855747461318969726562500000000,624,500,1.000000000000000000000000000000,0.500000000000000000000000000000
235,235_0,COMPLETED,BoTorch,GenerationStep_1,0.742558326629123133244547716458,8.773682355880737304687500000000,2997,368,0.100000000000000005551115123126,0.619460710586128837640274014120
236,236_0,COMPLETED,BoTorch,GenerationStep_1,0.722012500773562715394859878870,56.382985115051269531250000000000,3740,95,1.000000000000000000000000000000,0.500000000000000000000000000000
237,237_0,COMPLETED,BoTorch,GenerationStep_1,0.751531654186521458349545810051,9.969277381896972656250000000000,4000,500,0.100000000000000005551115123126,0.500000000000000000000000000000
238,238_0,COMPLETED,BoTorch,GenerationStep_1,0.731790333560245032096247541631,33.814918756484985351562500000000,4000,139,0.100000000000000005551115123126,0.500000000000000000000000000000
239,239_0,COMPLETED,BoTorch,GenerationStep_1,0.745652577510984571063090697862,3.037131071090698242187500000000,2640,500,0.727267823757964948505616575858,0.619853400953993660671415000252
240,240_0,COMPLETED,BoTorch,GenerationStep_1,0.742310786558574187132819588442,2.765832662582397460937500000000,2154,202,0.643683486209903787944597297610,0.656723001307556120131891930214
241,241_0,COMPLETED,BoTorch,GenerationStep_1,0.746395197722631298375972619397,5.554446935653686523437500000000,2923,500,0.100000000000000005551115123126,0.564931950655728321031290306564
242,242_0,COMPLETED,BoTorch,GenerationStep_1,0.743424716876044278102142470743,8.590234994888305664062500000000,3117,315,0.100000000000000005551115123126,0.800000000000000044408920985006
243,243_0,COMPLETED,BoTorch,GenerationStep_1,0.734451389318645952997144377150,1.234405040740966796875000000000,2986,343,1.000000000000000000000000000000,0.795978713802497295226601181639
244,244_0,COMPLETED,BoTorch,GenerationStep_1,0.738597685500340328523805055738,15.926228761672973632812500000000,3449,226,1.000000000000000000000000000000,0.500000000000000000000000000000
245,245_0,COMPLETED,BoTorch,GenerationStep_1,0.744229222105328269698532039911,2.654918909072875976562500000000,2180,236,1.000000000000000000000000000000,0.502779744383782589700615517359
246,246_0,COMPLETED,BoTorch,GenerationStep_1,0.737236215112321291442754045420,2.473019123077392578125000000000,3100,456,1.000000000000000000000000000000,0.680261061258535915108325298206
247,247_0,COMPLETED,BoTorch,GenerationStep_1,0.739402190729624320120194624906,17.507919073104858398437500000000,4000,265,0.100000000000000005551115123126,0.500000000000000000000000000000
248,248_0,COMPLETED,BoTorch,GenerationStep_1,0.740454236029457257828312322090,13.620818138122558593750000000000,3281,235,1.000000000000000000000000000000,0.500000000000000000000000000000
249,249_0,COMPLETED,BoTorch,GenerationStep_1,0.744848072281700579466701128695,6.366532087326049804687500000000,3048,500,0.100000000000000005551115123126,0.586027371815299402690868646459
250,250_0,COMPLETED,BoTorch,GenerationStep_1,0.744476762175877215810260167927,3.326280355453491210937500000000,2185,222,0.702890572117330747481389607856,0.500000000000000000000000000000
251,251_0,COMPLETED,BoTorch,GenerationStep_1,0.740021040905996629888363713690,3.416557312011718750000000000000,33,50,0.528799107530974255020339569455,0.500000000000000000000000000000
252,252_0,COMPLETED,BoTorch,GenerationStep_1,0.748932483445757801732156622165,10.035173416137695312500000000000,1990,500,0.100000000000000005551115123126,0.800000000000000044408920985006
253,253_0,COMPLETED,BoTorch,GenerationStep_1,0.740763661117643468223548097740,15.611873626708984375000000000000,3576,237,1.000000000000000000000000000000,0.500000000000000000000000000000
254,254_0,COMPLETED,BoTorch,GenerationStep_1,0.731109598366235569066873267730,1.781194925308227539062500000000,2091,193,0.865969572808975573963152783108,0.800000000000000044408920985006
255,255_0,COMPLETED,BoTorch,GenerationStep_1,0.738968995606163803202548479021,2.032835960388183593750000000000,2166,320,1.000000000000000000000000000000,0.500000000000000000000000000000
256,256_0,COMPLETED,BoTorch,GenerationStep_1,0.733461229036450279572534327599,1.352512836456298828125000000000,3021,276,1.000000000000000000000000000000,0.800000000000000044408920985006
257,257_0,COMPLETED,BoTorch,GenerationStep_1,0.748932483445757801732156622165,9.768106460571289062500000000000,3954,500,0.654822903850048820828533280292,0.500000000000000000000000000000
258,258_0,COMPLETED,BoTorch,GenerationStep_1,0.747509128040101500367597964214,5.133829355239868164062500000000,2965,500,0.366356304482046313264476111726,0.573028594402745450331337906391
259,259_0,COMPLETED,BoTorch,GenerationStep_1,0.730552633207500412559909364063,1.905603885650634765625000000000,2170,500,0.100000000000000005551115123126,0.800000000000000044408920985006
260,260_0,COMPLETED,BoTorch,GenerationStep_1,0.745095612352249525578429256711,10.439121484756469726562500000000,1402,327,0.100000000000000005551115123126,0.500000000000000000000000000000
261,261_0,COMPLETED,BoTorch,GenerationStep_1,0.739835385853084948060143233306,2.443003177642822265625000000000,2133,235,1.000000000000000000000000000000,0.589973680499330410675895564054
262,262_0,COMPLETED,BoTorch,GenerationStep_1,0.750170183798502421268494799733,9.189017772674560546875000000000,1819,500,0.100000000000000005551115123126,0.800000000000000044408920985006
263,263_0,COMPLETED,BoTorch,GenerationStep_1,0.746766507828454773054716042680,5.032561063766479492187500000000,2866,500,0.100000000000000005551115123126,0.545778361317176274880580422177
264,264_0,COMPLETED,BoTorch,GenerationStep_1,0.729438702890030321590586481761,1.559983968734741210937500000000,2049,247,1.000000000000000000000000000000,0.663810156305402410126248469169
265,265_0,COMPLETED,BoTorch,GenerationStep_1,0.746828392846091926315921227797,6.220527410507202148437500000000,85,50,0.100000000000000005551115123126,0.500000000000000000000000000000
266,266_0,COMPLETED,BoTorch,GenerationStep_1,0.732594838789529023692637110798,1.693706989288330078125000000000,2115,422,1.000000000000000000000000000000,0.500000000000000000000000000000
267,267_0,COMPLETED,BoTorch,GenerationStep_1,0.741258741258741249424701891257,19.600237607955932617187500000000,3243,179,1.000000000000000000000000000000,0.500000000000000000000000000000
268,268_0,COMPLETED,BoTorch,GenerationStep_1,0.733151803948264180199601014465,1.768087863922119140625000000000,2202,500,1.000000000000000000000000000000,0.500000000000000000000000000000
269,269_0,COMPLETED,BoTorch,GenerationStep_1,0.730985828330961040499857972463,2.610733270645141601562500000000,10,50,1.000000000000000000000000000000,0.500000000000000000000000000000
270,270_0,COMPLETED,BoTorch,GenerationStep_1,0.737298100129958555726261693053,3.025635957717895507812500000000,1490,500,0.444660581211333005846597643540,0.800000000000000044408920985006
271,271_0,COMPLETED,BoTorch,GenerationStep_1,0.743239061823132596273921990360,8.539481639862060546875000000000,3501,500,0.121635640139749715005201835538,0.500000000000000000000000000000
272,272_0,COMPLETED,BoTorch,GenerationStep_1,0.733832539142273643228975288366,1.172165632247924804687500000000,1412,282,1.000000000000000000000000000000,0.800000000000000044408920985006
273,273_0,COMPLETED,BoTorch,GenerationStep_1,0.745714462528621835346598345495,5.313325405120849609375000000000,3190,275,1.000000000000000000000000000000,0.683162059455073022995463816187
274,274_0,COMPLETED,BoTorch,GenerationStep_1,0.720279720279720314657367907785,1.501877784729003906250000000000,10,149,0.699559418695595902626394035906,0.500000000000000000000000000000
275,275_0,COMPLETED,BoTorch,GenerationStep_1,0.732347298718980188603211445297,3.400255680084228515625000000000,19,50,0.100000000000000005551115123126,0.640668170005193826632705622615
276,276_0,COMPLETED,BoTorch,GenerationStep_1,0.736679249953586245958092604269,2.486107349395751953125000000000,2292,500,0.100000000000000005551115123126,0.662199400160807361004344784305
277,277_0,COMPLETED,BoTorch,GenerationStep_1,0.747818553128287599740531277348,5.017153263092041015625000000000,748,500,0.100000000000000005551115123126,0.800000000000000044408920985006
278,278_0,COMPLETED,BoTorch,GenerationStep_1,0.741196856241103985141194243624,2.389697074890136718750000000000,2231,376,0.100000000000000005551115123126,0.500000000000000000000000000000
279,279_0,COMPLETED,BoTorch,GenerationStep_1,0.740763661117643468223548097740,9.321518898010253906250000000000,1308,391,1.000000000000000000000000000000,0.500000000000000000000000000000
280,280_0,COMPLETED,BoTorch,GenerationStep_1,0.748313633269385491963987533381,10.719771146774291992187500000000,1426,500,0.100000000000000005551115123126,0.800000000000000044408920985006
281,281_0,COMPLETED,BoTorch,GenerationStep_1,0.727334612290364557196653549909,1.624090194702148437500000000000,170,449,0.334376785322584302306836434582,0.800000000000000044408920985006
282,282_0,COMPLETED,BoTorch,GenerationStep_1,0.742929636734946496900988677226,11.305749893188476562500000000000,2853,143,1.000000000000000000000000000000,0.800000000000000044408920985006
283,283_0,COMPLETED,BoTorch,GenerationStep_1,0.726096911937619937660315372341,2.202797889709472656250000000000,99,500,0.100000000000000005551115123126,0.800000000000000044408920985006
284,284_0,COMPLETED,BoTorch,GenerationStep_1,0.744229222105328269698532039911,10.965194702148437500000000000000,3426,435,0.100000000000000005551115123126,0.500000000000000000000000000000
285,285_0,COMPLETED,BoTorch,GenerationStep_1,0.747447243022464236084090316581,6.683629751205444335937500000000,191,129,0.607390144318669000789157053077,0.500000000000000000000000000000
286,286_0,COMPLETED,BoTorch,GenerationStep_1,0.749798873692679057612053838966,7.431198120117187500000000000000,782,418,0.100000000000000005551115123126,0.800000000000000044408920985006
287,287_0,COMPLETED,BoTorch,GenerationStep_1,0.744724302246426161921988295944,12.062621355056762695312500000000,1251,334,0.100000000000000005551115123126,0.633144772953738610432594668964
288,288_0,COMPLETED,BoTorch,GenerationStep_1,0.722755120985209442707741800405,1.446439504623413085937500000000,306,500,1.000000000000000000000000000000,0.800000000000000044408920985006
289,289_0,COMPLETED,BoTorch,GenerationStep_1,0.739649730800173266231922752922,2.885374069213867187500000000000,2110,163,0.100000000000000005551115123126,0.500000000000000000000000000000
290,290_0,COMPLETED,BoTorch,GenerationStep_1,0.739897270870722212343650880939,2.384321689605712890625000000000,307,500,0.100000000000000005551115123126,0.599405710423752458027024658804
291,291_0,COMPLETED,BoTorch,GenerationStep_1,0.739154650659075485030768959405,8.757351636886596679687500000000,143,50,0.100000000000000005551115123126,0.636355373423645009900440072670
292,292_0,COMPLETED,BoTorch,GenerationStep_1,0.747014047899003608144141708181,7.284784555435180664062500000000,1337,438,0.100000000000000005551115123126,0.800000000000000044408920985006
293,293_0,COMPLETED,BoTorch,GenerationStep_1,0.740268580976545576000091841706,12.310627222061157226562500000000,4000,398,1.000000000000000000000000000000,0.500000000000000000000000000000
294,294_0,COMPLETED,BoTorch,GenerationStep_1,0.744105452070053852153819207160,8.017669439315795898437500000000,2905,312,1.000000000000000000000000000000,0.500000000000000000000000000000
295,295_0,COMPLETED,BoTorch,GenerationStep_1,0.745900117581533517174818825879,10.682255506515502929687500000000,1312,342,1.000000000000000000000000000000,0.500000000000000000000000000000
296,296_0,COMPLETED,BoTorch,GenerationStep_1,0.744291107122965533982039687544,8.775542736053466796875000000000,3441,500,0.438845016985066505021961802413,0.500000000000000000000000000000
297,297_0,COMPLETED,BoTorch,GenerationStep_1,0.741939476452750823476378627674,13.041456937789916992187500000000,1332,280,1.000000000000000000000000000000,0.500000000000000000000000000000
298,298_0,COMPLETED,BoTorch,GenerationStep_1,0.720589145367906414030301220919,1.543576955795288085937500000000,10,148,0.181167805566056161481469644059,0.500000000000000000000000000000
299,299_0,COMPLETED,BoTorch,GenerationStep_1,0.726839532149266664973197293875,35.528059244155883789062500000000,2802,52,1.000000000000000000000000000000,0.800000000000000044408920985006
300,300_0,COMPLETED,BoTorch,GenerationStep_1,0.733770654124636378945467640733,1.424285888671875000000000000000,207,262,1.000000000000000000000000000000,0.739810515584726213766941782524
301,301_0,COMPLETED,BoTorch,GenerationStep_1,0.733275573983538597744313847215,1.301212310791015625000000000000,1617,445,0.787083905988200105419139163132,0.800000000000000044408920985006
302,302_0,COMPLETED,BoTorch,GenerationStep_1,0.729376817872393057307078834128,1.274068593978881835937500000000,3292,445,1.000000000000000000000000000000,0.800000000000000044408920985006
303,303_0,COMPLETED,BoTorch,GenerationStep_1,0.738040720341605283039143614587,2.565800428390502929687500000000,2814,238,1.000000000000000000000000000000,0.800000000000000044408920985006
304,304_0,COMPLETED,BoTorch,GenerationStep_1,0.739092765641438220747261311772,2.453517198562622070312500000000,4000,381,1.000000000000000000000000000000,0.708543437019951705124753971177
305,305_0,COMPLETED,BoTorch,GenerationStep_1,0.742805866699671968333973381959,3.727214097976684570312500000000,974,500,0.377506412868706842100863241285,0.700766988280826730317585315788
306,306_0,COMPLETED,BoTorch,GenerationStep_1,0.740268580976545576000091841706,22.774493694305419921875000000000,3656,201,0.100000000000000005551115123126,0.500000000000000000000000000000
307,307_0,COMPLETED,BoTorch,GenerationStep_1,0.733337459001175862027821494848,1.338424444198608398437500000000,2156,367,1.000000000000000000000000000000,0.623455483026802537160904194025
308,308_0,COMPLETED,BoTorch,GenerationStep_1,0.737545640200507501837989821070,1.967074394226074218750000000000,239,500,0.674457511303785728351556372218,0.500000000000000000000000000000
309,309_0,COMPLETED,BoTorch,GenerationStep_1,0.748251748251748227680479885748,4.066711664199829101562500000000,2211,156,0.664206942122479881973617921176,0.500000000000000000000000000000
310,310_0,COMPLETED,BoTorch,GenerationStep_1,0.733832539142273643228975288366,0.939930915832519531250000000000,731,412,1.000000000000000000000000000000,0.800000000000000044408920985006
311,311_0,COMPLETED,BoTorch,GenerationStep_1,0.748127978216473810135767052998,3.332074642181396484375000000000,2382,354,0.609010501676018001226964315720,0.500000000000000000000000000000
312,312_0,COMPLETED,BoTorch,GenerationStep_1,0.734265734265734271168923896767,2.269889593124389648437500000000,2191,406,0.104403470187370728261555541394,0.800000000000000044408920985006
313,313_0,COMPLETED,BoTorch,GenerationStep_1,0.726963302184541082517910126626,1.146847009658813476562500000000,2358,500,1.000000000000000000000000000000,0.800000000000000044408920985006
314,314_0,COMPLETED,BoTorch,GenerationStep_1,0.727767807413825074114299695793,2.157419681549072265625000000000,10,72,1.000000000000000000000000000000,0.800000000000000044408920985006
315,315_0,COMPLETED,BoTorch,GenerationStep_1,0.728139117519648437770740656561,2.615963459014892578125000000000,10,50,1.000000000000000000000000000000,0.659674446760891819430128180102
316,316_0,COMPLETED,BoTorch,GenerationStep_1,0.745528807475710153518377865112,3.852577924728393554687500000000,325,256,0.100000000000000005551115123126,0.608844407328238079735172050277
317,317_0,COMPLETED,BoTorch,GenerationStep_1,0.745157497369886789861936904344,6.580857992172241210937500000000,306,146,0.100000000000000005551115123126,0.800000000000000044408920985006
318,318_0,COMPLETED,BoTorch,GenerationStep_1,0.746890277863729190599428875430,5.530467510223388671875000000000,911,471,0.100000000000000005551115123126,0.691559374804923243651444408897
319,319_0,COMPLETED,BoTorch,GenerationStep_1,0.731542793489696197006821876130,1.753268003463745117187500000000,2780,396,1.000000000000000000000000000000,0.697174199148628659372661786620
320,320_0,COMPLETED,BoTorch,GenerationStep_1,0.746580852775543091226495562296,6.220865964889526367187500000000,1192,500,1.000000000000000000000000000000,0.544640593472297762644984686631
321,321_0,COMPLETED,BoTorch,GenerationStep_1,0.737483755182870237554482173437,3.202265977859497070312500000000,1135,317,0.536657434871448124624748743372,0.800000000000000044408920985006
322,322_0,COMPLETED,BoTorch,GenerationStep_1,0.732904263877715234087872886448,1.607423782348632812500000000000,4000,352,1.000000000000000000000000000000,0.800000000000000044408920985006
323,323_0,COMPLETED,BoTorch,GenerationStep_1,0.745900117581533517174818825879,7.858701705932617187500000000000,2879,221,1.000000000000000000000000000000,0.735951123064549461716410405643
324,324_0,COMPLETED,BoTorch,GenerationStep_1,0.737978835323968018755635966954,15.755581378936767578125000000000,3438,220,0.100000000000000005551115123126,0.500000000000000000000000000000
325,325_0,COMPLETED,BoTorch,GenerationStep_1,0.744909957299337843750208776328,5.164891958236694335937500000000,755,419,0.100000000000000005551115123126,0.644147734893559475999325059092
326,326_0,COMPLETED,BoTorch,GenerationStep_1,0.737174330094684027159246397787,1.665718078613281250000000000000,1407,500,1.000000000000000000000000000000,0.800000000000000044408920985006
327,327_0,COMPLETED,BoTorch,GenerationStep_1,0.743672256946593224213870598760,2.427412748336791992187500000000,2292,441,0.433938396833774664429483891581,0.585693170414351427233157210139
328,328_0,COMPLETED,BoTorch,GenerationStep_1,0.737793180271056336927415486571,2.530473709106445312500000000000,1320,346,1.000000000000000000000000000000,0.689972308315075277818095855764
329,329_0,COMPLETED,BoTorch,GenerationStep_1,0.733089918930626915916093366832,1.479937791824340820312500000000,752,434,1.000000000000000000000000000000,0.742715567755878325328922073822
330,330_0,COMPLETED,BoTorch,GenerationStep_1,0.743300946840769860557429637993,3.268395185470581054687500000000,3289,500,1.000000000000000000000000000000,0.707446221212495229835326426837
331,331_0,COMPLETED,BoTorch,GenerationStep_1,0.744105452070053852153819207160,3.406678676605224609375000000000,337,422,1.000000000000000000000000000000,0.500000000000000000000000000000
332,332_0,COMPLETED,BoTorch,GenerationStep_1,0.728943622748932429367130225728,1.271301746368408203125000000000,3572,500,0.677545013377921945263437919493,0.800000000000000044408920985006
333,333_0,COMPLETED,BoTorch,GenerationStep_1,0.732223528683705660036196150031,1.279465675354003906250000000000,2182,495,0.601995355470574811107553614420,0.800000000000000044408920985006
334,334_0,COMPLETED,BoTorch,GenerationStep_1,0.745776347546259099630105993128,4.729415655136108398437500000000,2202,144,0.590123512324204457790699507314,0.746122141786460191248409046239
335,335_0,COMPLETED,BoTorch,GenerationStep_1,0.740516121047094522111819969723,3.795612812042236328125000000000,2265,165,1.000000000000000000000000000000,0.800000000000000044408920985006
336,336_0,COMPLETED,BoTorch,GenerationStep_1,0.721331765579553141343183142453,0.993578910827636718750000000000,10,500,0.829009830884969933784134354937,0.740162805103873444600992570486
337,337_0,COMPLETED,BoTorch,GenerationStep_1,0.744600532211151633354973000678,3.113425493240356445312500000000,2446,500,1.000000000000000000000000000000,0.500000000000000000000000000000
338,338_0,COMPLETED,BoTorch,GenerationStep_1,0.734575159353920370541857209901,1.720879077911376953125000000000,281,500,0.544594996491820193540434047463,0.710125057328648501275836224522
339,339_0,COMPLETED,BoTorch,GenerationStep_1,0.743857911999504906042091079144,3.379592418670654296875000000000,2365,285,1.000000000000000000000000000000,0.570372654893695707478684653324
340,340_0,COMPLETED,BoTorch,GenerationStep_1,0.740392351011819993544804674457,5.918169260025024414062500000000,3424,500,1.000000000000000000000000000000,0.615408472258257122078362044704
341,341_0,COMPLETED,BoTorch,GenerationStep_1,0.718794479856426749009301602200,1.401491641998291015625000000000,10,153,1.000000000000000000000000000000,0.800000000000000044408920985006
342,342_0,COMPLETED,BoTorch,GenerationStep_1,0.748313633269385491963987533381,3.316820621490478515625000000000,2421,418,0.100000000000000005551115123126,0.500000000000000000000000000000
343,343_0,COMPLETED,BoTorch,GenerationStep_1,0.746209542669719616547752139013,3.525189876556396484375000000000,2277,277,0.100000000000000005551115123126,0.500000000000000000000000000000
344,344_0,COMPLETED,BoTorch,GenerationStep_1,0.729810012995853685247027442529,21.659368515014648437500000000000,2439,50,1.000000000000000000000000000000,0.500000000000000000000000000000
345,345_0,COMPLETED,BoTorch,GenerationStep_1,0.732471068754254606147924278048,1.788453102111816406250000000000,1860,268,1.000000000000000000000000000000,0.753704869178963066111975876993
346,346_0,COMPLETED,BoTorch,GenerationStep_1,0.740887431152917885768260930490,2.660411596298217773437500000000,224,265,0.411083703538572209357226938664,0.800000000000000044408920985006
347,347_0,COMPLETED,BoTorch,GenerationStep_1,0.746023887616807934719531658629,2.854417800903320312500000000000,260,312,0.100000000000000005551115123126,0.800000000000000044408920985006
348,348_0,COMPLETED,BoTorch,GenerationStep_1,0.746457082740268562659480267030,2.938203334808349609375000000000,2461,500,0.531371740279026449904620221787,0.500000000000000000000000000000
349,349_0,COMPLETED,BoTorch,GenerationStep_1,0.732904263877715234087872886448,1.166739225387573242187500000000,2589,379,1.000000000000000000000000000000,0.800000000000000044408920985006
350,350_0,COMPLETED,BoTorch,GenerationStep_1,0.748127978216473810135767052998,4.535629987716674804687500000000,2244,144,0.530298777188056624787293458212,0.800000000000000044408920985006
351,351_0,COMPLETED,BoTorch,GenerationStep_1,0.734018194195185325057195768750,1.820490360260009765625000000000,3821,336,0.825543193466987346162966332486,0.757983523074193477064852686453
352,352_0,COMPLETED,BoTorch,GenerationStep_1,0.731914103595519560663262836897,2.217083215713500976562500000000,3384,500,0.730940892649055151686354747653,0.710175630388983569751815139171
353,353_0,COMPLETED,BoTorch,GenerationStep_1,0.749798873692679057612053838966,4.913234472274780273437500000000,2439,275,0.100000000000000005551115123126,0.800000000000000044408920985006
354,354_0,COMPLETED,BoTorch,GenerationStep_1,0.745838232563896252891311178246,2.324838638305664062500000000000,350,500,0.100000000000000005551115123126,0.500000000000000000000000000000
355,355_0,COMPLETED,BoTorch,GenerationStep_1,0.743734141964230488497378246393,13.551481962203979492187500000000,2847,147,0.100000000000000005551115123126,0.800000000000000044408920985006
356,356_0,COMPLETED,BoTorch,GenerationStep_1,0.720403490314994732202080740535,1.592994213104248046875000000000,10,110,0.628758888022790007887863339420,0.598068165780375138318447625352
357,357_0,COMPLETED,BoTorch,GenerationStep_1,0.732409183736617341864416630415,1.211205244064331054687500000000,625,500,1.000000000000000000000000000000,0.800000000000000044408920985006
358,358_0,COMPLETED,BoTorch,GenerationStep_1,0.729995668048765367075247922912,0.916050910949707031250000000000,10,500,1.000000000000000000000000000000,0.691196119380128926046324977506
359,359_0,COMPLETED,BoTorch,GenerationStep_1,0.735689089671390572533482554718,4.335514068603515625000000000000,3800,308,1.000000000000000000000000000000,0.695785259601619965330598915898
</pre>
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<button onclick='download_as_file("tab_results_csv_table_pre", "results.csv")'> Download »results.csv« as file</button>
<script>
createTable(tab_results_csv_json, tab_results_headers_json, 'tab_results_csv_table');</script>
<h1> Args Overview</h1>
<h2>Arguments Overview: </h2><table cellspacing="0" cellpadding="5"><thead><tr><th> Key</th><th>Value </th></tr></thead><tbody><tr><td> config_yaml</td><td>None </td></tr><tr><td> config_toml</td><td>None </td></tr><tr><td> config_json</td><td>None </td></tr><tr><td> num_random_steps</td><td>20 </td></tr><tr><td> max_eval</td><td>500 </td></tr><tr><td> run_program</td><td>[['bW9kdWxlIGxvYWQgR0NDY29yZS8xMC4zLjAgUHl0aG9uICYmIHNvdXJjZSAvZGF0YS9ob3JzZS93cy9zNDEyMjQ4NS1jb21wUGVyZkREL2JlbmNobWFyay92ZW52L2Jpbi9hY3RpdmF0ZSAmJiBw… </td></tr><tr><td> experiment_name</td><td>D3_NOAAWeather_HoeffdingTreeClassifier_ACC-RUNTIME </td></tr><tr><td> mem_gb</td><td>32 </td></tr><tr><td> parameter</td><td>[['recent_samples_size', 'range', '10', '4000', 'int'], ['n_reference_samples', 'range', '50', '500', 'int'], ['recent_samples_proportion', 'range', </td></tr><tr><td></td><td>'0.1', '1.0', 'float'], ['threshold', 'range', '0.5', '0.8', 'float']] </td></tr><tr><td> continue_previous_job</td><td>None </td></tr><tr><td> maximize</td><td>False </td></tr><tr><td> experiment_constraints</td><td>None </td></tr><tr><td> stderr_to_stdout</td><td>False </td></tr><tr><td> run_dir</td><td>runs </td></tr><tr><td> seed</td><td>None </td></tr><tr><td> decimalrounding</td><td>12 </td></tr><tr><td> enforce_sequential_optimization</td><td>False </td></tr><tr><td> verbose_tqdm</td><td>False </td></tr><tr><td> model</td><td>BOTORCH_MODULAR </td></tr><tr><td> gridsearch</td><td>False </td></tr><tr><td> occ</td><td>False </td></tr><tr><td> show_sixel_scatter</td><td>False </td></tr><tr><td> show_sixel_general</td><td>False </td></tr><tr><td> show_sixel_trial_index_result</td><td>False </td></tr><tr><td> follow</td><td>False </td></tr><tr><td> send_anonymized_usage_stats</td><td>True </td></tr><tr><td> ui_url</td><td>None </td></tr><tr><td> root_venv_dir</td><td>/home/s4122485 </td></tr><tr><td> exclude</td><td>None </td></tr><tr><td> main_process_gb</td><td>8 </td></tr><tr><td> pareto_front_confidence</td><td>1 </td></tr><tr><td> max_nr_of_zero_results</td><td>50 </td></tr><tr><td> disable_search_space_exhaustion_detection</td><td>False </td></tr><tr><td> abbreviate_job_names</td><td>False </td></tr><tr><td> orchestrator_file</td><td>None </td></tr><tr><td> checkout_to_latest_tested_version</td><td>False </td></tr><tr><td> live_share</td><td>False </td></tr><tr><td> disable_tqdm</td><td>False </td></tr><tr><td> workdir</td><td>False </td></tr><tr><td> max_parallelism</td><td>max_eval_times_thousand_plus_thousand </td></tr><tr><td> occ_type</td><td>euclid </td></tr><tr><td> result_names</td><td>['ACCURACY=max', 'RUNTIME=min'] </td></tr><tr><td> minkowski_p</td><td>2 </td></tr><tr><td> signed_weighted_euclidean_weights</td><td></td></tr><tr><td> generation_strategy</td><td>None </td></tr><tr><td> generate_all_jobs_at_once</td><td>True </td></tr><tr><td> revert_to_random_when_seemingly_exhausted</td><td>True </td></tr><tr><td> num_parallel_jobs</td><td>30 </td></tr><tr><td> worker_timeout</td><td>30 </td></tr><tr><td> slurm_use_srun</td><td>False </td></tr><tr><td> time</td><td>1260 </td></tr><tr><td> partition</td><td>romeo </td></tr><tr><td> reservation</td><td>None </td></tr><tr><td> force_local_execution</td><td>False </td></tr><tr><td> slurm_signal_delay_s</td><td>0 </td></tr><tr><td> nodes_per_job</td><td>1 </td></tr><tr><td> cpus_per_task</td><td>1 </td></tr><tr><td> account</td><td>None </td></tr><tr><td> gpus</td><td>0 </td></tr><tr><td> run_mode</td><td>local </td></tr><tr><td> verbose</td><td>False </td></tr><tr><td> verbose_break_run_search_table</td><td>False </td></tr><tr><td> debug</td><td>False </td></tr><tr><td> no_sleep</td><td>False </td></tr><tr><td> tests</td><td>False </td></tr><tr><td> show_worker_percentage_table_at_end</td><td>False </td></tr><tr><td> auto_exclude_defective_hosts</td><td>False </td></tr><tr><td> run_tests_that_fail_on_taurus</td><td>False </td></tr><tr><td> raise_in_eval</td><td>False </td></tr><tr><td> show_ram_every_n_seconds</td><td>False </td></tr></tbody></table>
<h1> Worker-Usage</h1>
<div class='invert_in_dark_mode' id='workerUsagePlot'></div><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("pre_tab_worker_usage")'> Copy raw data to clipboard</button>
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1742444913.9167829,30,10,33
1742444914.087252,30,10,33
1742444915.2345471,30,9,30
1742444915.4233122,30,9,30
1742444916.5161521,30,8,27
1742444916.7291574,30,8,27
1742444917.7820995,30,7,23
1742444917.9806833,30,7,23
1742444919.143007,30,6,20
1742444919.3354342,30,6,20
1742444920.437689,30,5,17
1742444920.610089,30,5,17
1742444922.0305214,30,4,13
1742444922.2163181,30,4,13
1742444923.3442848,30,3,10
1742444923.5581188,30,3,10
1742444924.6588042,30,2,7
1742444924.8716106,30,2,7
1742444927.3645735,30,1,3
1742444927.569664,30,1,3
1742444930.5539978,30,1,3
1742444937.5351558,30,1,3
1742444943.0642164,30,1,3
1742444943.237245,30,1,3
1742444945.7028253,30,0,0
1742444947.8081577,30,0,0
1742444949.4468005,30,0,0
1742445196.671332,30,0,0
1742445863.5253768,30,0,0
1742446853.8765519,30,0,0
1742447150.961735,30,0,0
1742447683.3651469,30,0,0
1742448084.5464084,30,0,0
1742448692.9409022,30,0,0
1742449206.2854762,30,0,0
1742449666.8879194,30,0,0
1742450020.7428753,30,0,0
1742450296.8797703,30,0,0
1742450644.0469494,30,0,0
1742451023.8779607,30,0,0
1742451344.0065415,30,0,0
1742451813.6591911,30,0,0
1742452191.0558763,30,0,0
1742452636.8330154,30,0,0
1742453082.327495,30,0,0
1742453355.427193,30,0,0
1742453623.6000946,30,0,0
1742453979.5548558,30,0,0
1742454484.9495533,30,0,0
1742454720.0447192,30,0,0
1742454991.718443,30,0,0
1742455306.059267,30,0,0
1742455840.9671412,30,0,0
1742456124.1432052,30,0,0
1742456587.962987,30,0,0
1742457087.8648522,30,0,0
1742457402.1207414,30,0,0
1742457402.531341,30,0,0
1742457405.137319,30,1,3
1742457405.3037913,30,1,3
1742457405.7252796,30,1,3
1742457407.660918,30,2,7
1742457407.7104118,30,2,7
1742457408.1313703,30,2,7
1742457410.135903,30,3,10
1742457410.1979184,30,3,10
1742457410.6457508,30,3,10
1742457412.5301056,30,4,13
1742457412.5892575,30,4,13
1742457412.9966328,30,4,13
1742457415.1112776,30,5,17
1742457415.2085414,30,5,17
1742457415.5919862,30,5,17
1742457417.5380166,30,6,20
1742457417.6143827,30,6,20
1742457417.9996343,30,6,20
1742457420.1685364,30,7,23
1742457420.217907,30,7,23
1742457420.6636798,30,7,23
1742457422.6222382,30,8,27
1742457422.6809387,30,8,27
1742457423.0890949,30,8,27
1742457425.1369944,30,9,30
1742457425.188423,30,9,30
1742457425.5848637,30,9,30
1742457427.6726234,30,10,33
1742457427.7263615,30,10,33
1742457428.1365798,30,10,33
1742457431.1658235,30,11,37
1742457431.22968,30,11,37
1742457431.664812,30,11,37
1742457433.5678136,30,12,40
1742457433.6191463,30,12,40
1742457434.0348914,30,12,40
1742457436.4692225,30,13,43
1742457436.525462,30,13,43
1742457436.972161,30,13,43
1742457439.078657,30,14,47
1742457439.1661832,30,14,47
1742457439.563612,30,14,47
1742457441.4915674,30,15,50
1742457441.5364783,30,15,50
1742457441.8766727,30,15,50
1742457443.7069752,30,16,53
1742457443.777041,30,16,53
1742457444.1605198,30,16,53
1742457446.0973372,30,17,57
1742457446.1491644,30,17,57
1742457446.706236,30,17,57
1742457450.1503496,30,18,60
1742457450.1982234,30,18,60
1742457450.6044116,30,18,60
1742457452.472397,30,19,63
1742457452.5543265,30,19,63
1742457452.910491,30,19,63
1742457454.7908974,30,20,67
1742457454.8422618,30,20,67
1742457455.236823,30,20,67
1742457457.1424446,30,21,70
1742457457.2087684,30,21,70
1742457457.5949173,30,21,70
1742457459.4155202,30,22,73
1742457459.4694018,30,22,73
1742457459.8779745,30,22,73
1742457462.2143698,30,23,77
1742457462.2649102,30,23,77
1742457462.6372154,30,23,77
1742457464.3758898,30,24,80
1742457464.4227881,30,24,80
1742457464.7769723,30,24,80
1742457466.7291343,30,25,83
1742457466.7731855,30,25,83
1742457467.3553348,30,25,83
1742457469.6073964,30,26,87
1742457469.6873863,30,26,87
1742457470.0535653,30,26,87
1742457472.1459801,30,27,90
1742457472.1907303,30,27,90
1742457472.5589125,30,27,90
1742457474.4714878,30,28,93
1742457474.5221486,30,28,93
1742457474.914211,30,28,93
1742457476.7144341,30,29,97
1742457476.7597847,30,29,97
1742457477.1026125,30,29,97
1742457479.1904607,30,30,100
1742457479.9441152,30,30,100
1742457480.2322397,30,30,100
1742457481.3452485,30,29,97
1742457481.5164652,30,29,97
1742457482.678075,30,28,93
1742457482.8785355,30,28,93
1742457484.0697894,30,27,90
1742457484.2688718,30,27,90
1742457485.511322,30,26,87
1742457485.7650902,30,26,87
1742457487.2042837,30,25,83
1742457487.3919053,30,25,83
1742457488.5976186,30,24,80
1742457488.7801776,30,24,80
1742457490.327617,30,23,77
1742457490.499412,30,23,77
1742457491.6190436,30,22,73
1742457491.8379996,30,22,73
1742457492.9898815,30,21,70
1742457493.1859593,30,21,70
1742457494.3640442,30,20,67
1742457494.5812194,30,20,67
1742457495.7599752,30,19,63
1742457495.9319968,30,19,63
1742457497.1026626,30,18,60
1742457497.2569792,30,18,60
1742457498.4425013,30,17,57
1742457498.6702213,30,17,57
1742457500.1872551,30,16,53
1742457500.3821156,30,16,53
1742457501.5694513,30,15,50
1742457501.941543,30,15,50
1742457503.1027052,30,14,47
1742457503.3039918,30,14,47
1742457504.5552635,30,13,43
1742457504.7148125,30,13,43
1742457505.8981345,30,12,40
1742457506.0699096,30,12,40
1742457507.21839,30,11,37
1742457507.446941,30,11,37
1742457508.614402,30,10,33
1742457508.7979107,30,10,33
1742457510.3466363,30,9,30
1742457510.5356388,30,9,30
1742457511.757828,30,8,27
1742457511.9598625,30,8,27
1742457513.100466,30,7,23
1742457513.269811,30,7,23
1742457514.4983802,30,6,20
1742457514.7126095,30,6,20
1742457515.8332114,30,5,17
1742457516.0074832,30,5,17
1742457517.114605,30,4,13
1742457517.291196,30,4,13
1742457518.5059102,30,3,10
1742457518.6962764,30,3,10
1742457519.8218389,30,2,7
1742457520.085042,30,2,7
1742457521.6059763,30,1,3
1742457521.7861195,30,1,3
1742457524.0754964,30,0,0
1742457524.2190285,30,0,0
1742457529.0350375,30,0,0
1742457530.921726,30,0,0
1742457881.273785,30,0,0
1742458509.3447988,30,0,0
1742458765.7883465,30,0,0
1742459139.9260664,30,0,0
1742459724.7826831,30,0,0
1742460208.0148973,30,0,0
1742460663.5829475,30,0,0
1742461052.8472142,30,0,0
1742461528.7054582,30,0,0
1742461798.9069474,30,0,0
1742462250.9887178,30,0,0
1742462689.8000355,30,0,0
1742463003.0211303,30,0,0
1742463646.6457582,30,0,0
1742464056.626026,30,0,0
1742464483.1987932,30,0,0
1742464986.3351355,30,0,0
1742465232.8356104,30,0,0
1742465718.482331,30,0,0
1742466131.4329374,30,0,0
1742466910.4471862,30,0,0
1742467296.1661184,30,0,0
1742467737.2694495,30,0,0
1742468082.0633366,30,0,0
1742468434.1965315,30,0,0
1742468950.9767785,30,0,0
1742469337.6624496,30,0,0
1742469929.716286,30,0,0
1742470233.1279128,30,0,0
1742470792.349093,30,0,0
1742470792.763188,30,0,0
1742470795.6193528,30,1,3
1742470795.8459704,30,1,3
1742470796.304631,30,1,3
1742470798.4891722,30,2,7
1742470798.5504,30,2,7
1742470799.012914,30,2,7
1742470801.026129,30,3,10
1742470801.0855317,30,3,10
1742470801.5934281,30,3,10
1742470804.1820707,30,4,13
1742470804.2281268,30,4,13
1742470804.7952254,30,4,13
1742470807.1092203,30,5,17
1742470807.3134177,30,5,17
1742470807.762119,30,5,17
1742470810.1518667,30,6,20
1742470810.2540631,30,6,20
1742470810.7200966,30,6,20
1742470812.6166043,30,7,23
1742470812.6730807,30,7,23
1742470813.2505379,30,7,23
1742470815.592527,30,8,27
1742470815.644487,30,8,27
1742470816.1088712,30,8,27
1742470818.1952815,30,9,30
1742470818.2974894,30,9,30
1742470818.7335038,30,9,30
1742470820.6550589,30,10,33
1742470820.712284,30,10,33
1742470821.202698,30,10,33
1742470823.2504172,30,11,37
1742470823.3508117,30,11,37
1742470823.826131,30,11,37
1742470826.0454993,30,12,40
1742470826.1014616,30,12,40
1742470826.6288612,30,12,40
1742470828.7283628,30,13,43
1742470828.8096023,30,13,43
1742470829.2699013,30,13,43
1742470831.623856,30,14,47
1742470831.7130022,30,14,47
1742470832.1095145,30,14,47
1742470834.6468556,30,15,50
1742470834.7593997,30,15,50
1742470835.2206147,30,15,50
1742470838.623362,30,16,53
1742470838.6722116,30,16,53
1742470839.1503117,30,16,53
1742470841.4841497,30,17,57
1742470841.6039379,30,17,57
1742470842.049157,30,17,57
1742470845.5306103,30,18,60
1742470845.58431,30,18,60
1742470846.0353544,30,18,60
1742470848.5184653,30,19,63
1742470848.6019106,30,19,63
1742470849.086412,30,19,63
1742470851.4988368,30,20,67
1742470851.5704014,30,20,67
1742470852.0204554,30,20,67
1742470854.2563753,30,21,70
1742470854.3727486,30,21,70
1742470854.791268,30,21,70
1742470857.1302736,30,22,73
1742470857.1814187,30,22,73
1742470857.651736,30,22,73
1742470859.5343344,30,23,77
1742470859.6914186,30,23,77
1742470860.1596763,30,23,77
1742470862.4873793,30,24,80
1742470862.5483875,30,24,80
1742470863.0436552,30,24,80
1742470865.293317,30,25,83
1742470865.3426383,30,25,83
1742470865.7191255,30,25,83
1742470867.5358937,30,26,87
1742470867.6491947,30,26,87
1742470868.079199,30,26,87
1742470870.1526818,30,27,90
1742470870.266651,30,27,90
1742470870.6894999,30,27,90
1742470872.6505525,30,28,93
1742470872.7350223,30,28,93
1742470873.1459534,30,28,93
1742470876.1910589,30,29,97
1742470876.3960347,30,29,97
1742470876.8110988,30,29,97
1742470878.9463818,30,30,100
1742470879.798576,30,30,100
1742470880.1059806,30,30,100
1742470881.5893273,30,29,97
1742470881.846873,30,29,97
1742470883.233581,30,28,93
1742470884.6656659,30,28,93
1742470886.0074306,30,27,90
1742470886.3005338,30,27,90
1742470888.1247885,30,26,87
1742470888.4431608,30,26,87
1742470889.911202,30,25,83
1742470890.189952,30,25,83
1742470891.6798377,30,24,80
1742470892.0283551,30,24,80
1742470893.5083325,30,23,77
1742470893.9568808,30,23,77
1742470895.4905293,30,22,73
1742470895.7257876,30,22,73
1742470897.1382012,30,21,70
1742470897.4332535,30,21,70
1742470898.8007615,30,20,67
1742470899.0918303,30,20,67
1742470900.9347126,30,19,63
1742470901.1448727,30,19,63
1742470902.8624277,30,18,60
1742470903.0948303,30,18,60
1742470904.5118074,30,17,57
1742470904.7824035,30,17,57
1742470906.3095794,30,16,53
1742470906.5948157,30,16,53
1742470908.2405667,30,15,50
1742470908.5975082,30,15,50
1742470909.959956,30,14,47
1742470910.1687849,30,14,47
1742470911.4606984,30,13,43
1742470911.6408806,30,13,43
1742470913.401957,30,12,40
1742470913.6995592,30,12,40
1742470915.131399,30,11,37
1742470915.375563,30,11,37
1742470916.6251729,30,10,33
1742470916.8132699,30,10,33
1742470918.1302354,30,9,30
1742470918.3204467,30,9,30
1742470919.6687727,30,8,27
1742470919.9046845,30,8,27
1742470921.2927961,30,7,23
1742470921.5772736,30,7,23
1742470922.839834,30,6,20
1742470923.0511706,30,6,20
1742470924.773511,30,5,17
1742470925.0368485,30,5,17
1742470926.4492972,30,4,13
1742470926.665474,30,4,13
1742470927.9164739,30,3,10
1742470928.1871128,30,3,10
1742470929.5352292,30,2,7
1742470929.780916,30,2,7
1742470931.1170034,30,1,3
1742470931.3473086,30,1,3
1742470934.313807,30,0,0
1742470934.4837058,30,0,0
</pre><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("pre_tab_worker_usage")'> Copy raw data to clipboard</button>
<button onclick='download_as_file("pre_tab_worker_usage", "worker_usage.csv")'> Download »worker_usage.csv« as file</button>
<h1> CPU/RAM-Usage (main)</h1>
<div class='invert_in_dark_mode' id='mainWorkerCPURAM'></div><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("pre_tab_main_worker_cpu_ram")'> Copy raw data to clipboard</button>
<button onclick='download_as_file("pre_tab_main_worker_cpu_ram", "cpu_ram_usage.csv")'> Download »cpu_ram_usage.csv« as file</button>
<pre id="pre_tab_main_worker_cpu_ram">timestamp,ram_usage_mb,cpu_usage_percent
1742404030,592.78125,0.2
1742404030,592.78125,1.5
1742404030,592.78125,0.7
1742404030,592.78125,0.0
1742404030,592.78125,0.0
1742404030,592.78125,1.0
1742404030,592.78125,0.0
1742404121,606.2109375,1.3
1742404121,606.2109375,3.5
1742404121,606.2109375,0.8
1742404121,606.2109375,3.8
1742406667,673.56640625,2.9
1742406667,673.56640625,2.7
1742406667,673.56640625,4.6
1742406667,673.56640625,5.4
1742408181,675.43359375,5.5
1742408181,675.43359375,2.5
1742408181,675.43359375,5.8
1742408181,675.43359375,5.9
1742411011,689.11328125,6.3
1742411011,689.11328125,7.7
1742411011,689.11328125,6.2
1742411011,689.11328125,7.4
1742414076,703.265625,6.4
1742414076,703.265625,5.3
1742414076,703.265625,5.3
1742414076,703.265625,5.4
1742418479,699.10546875,6.6
1742418479,699.10546875,6.2
1742418479,699.10546875,6.8
1742418479,699.10546875,6.6
1742423689,740.2734375,7.0
1742423689,740.2734375,7.8
1742423689,740.2734375,7.6
1742423689,740.2734375,11.6
1742431972,767.03125,7.3
1742431972,767.03125,6.5
1742431972,767.28125,6.5
1742431972,767.28125,9.3
1742437250,812.609375,7.5
1742437250,812.609375,6.8
1742437250,812.609375,7.0
1742437250,812.609375,7.0
1742444930,796.546875,5.6
1742444930,796.546875,6.5
1742444930,796.546875,6.6
1742444930,796.546875,7.0
1742457527,784.20703125,4.9
1742457527,784.20703125,3.1
1742457527,784.20703125,3.4
1742457527,784.20703125,5.1
1742470937,778.75,4.7
1742470937,778.75,3.9
1742470937,778.75,3.9
1742470937,778.75,2.6
</pre><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("pre_tab_main_worker_cpu_ram")'> Copy raw data to clipboard</button>
<button onclick='download_as_file("pre_tab_main_worker_cpu_ram", "cpu_ram_usage.csv")'> Download »cpu_ram_usage.csv« as file</button>
<h1> Parallel Plot</h1>
<div class="invert_in_dark_mode" id="parallel-plot"></div>
<h1> Scatter-2D</h1>
<div class='invert_in_dark_mode' id='plotScatter2d'></div>
<h1> Scatter-3D</h1>
<div class='invert_in_dark_mode' id='plotScatter3d'></div>
<h1> Job Status Distribution</h1>
<div class="invert_in_dark_mode" id="plotJobStatusDistribution"></div>
<h1> Boxplots</h1>
<div class="invert_in_dark_mode" id="plotBoxplot"></div>
<h1> Violin</h1>
<div class="invert_in_dark_mode" id="plotViolin"></div>
<h1> Histogram</h1>
<div class="invert_in_dark_mode" id="plotHistogram"></div>
<h1> Heatmap</h1>
<div class="invert_in_dark_mode" id="plotHeatmap"></div><br>
<h1>Correlation Heatmap Explanation</h1>
<p>
This is a heatmap that visualizes the correlation between numerical columns in a dataset. The values represented in the heatmap show the strength and direction of relationships between different variables.
</p>
<h2>How It Works</h2>
<p>
The heatmap uses a matrix to represent correlations between each pair of numerical columns. The calculation behind this is based on the concept of "correlation," which measures how strongly two variables are related. A correlation can be positive, negative, or zero:
</p>
<ul>
<li><strong>Positive correlation</strong>: Both variables increase or decrease together (e.g., if the temperature rises, ice cream sales increase).</li>
<li><strong>Negative correlation</strong>: As one variable increases, the other decreases (e.g., as the price of a product rises, the demand for it decreases).</li>
<li><strong>Zero correlation</strong>: There is no relationship between the two variables (e.g., height and shoe size might show zero correlation in some contexts).</li>
</ul>
<h2>Color Scale: Yellow to Purple (Viridis)</h2>
<p>
The heatmap uses a color scale called "Viridis," which ranges from yellow to purple. Here's what the colors represent:
</p>
<ul>
<li><strong>Yellow (brightest)</strong>: A strong positive correlation (close to +1). This indicates that as one variable increases, the other increases in a very predictable manner.</li>
<li><strong>Green</strong>: A moderate positive correlation. Variables are still positively related, but the relationship is not as strong.</li>
<li><strong>Blue</strong>: A weak or near-zero correlation. There is a small or no discernible relationship between the variables.</li>
<li><strong>Purple (darkest)</strong>: A strong negative correlation (close to -1). This indicates that as one variable increases, the other decreases in a very predictable manner.</li>
</ul>
<h2>What the Heatmap Shows</h2>
<p>
In the heatmap, each cell represents the correlation between two numerical columns. The color of the cell is determined by the correlation coefficient: from yellow for strong positive correlations, through green and blue for weaker correlations, to purple for strong negative correlations.
</p>
<h1> Result-Pairs</h1>
<div class="invert_in_dark_mode" id="plotResultPairs"></div>
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