Experiment overview:

Job Summary per Generation Node

Experiment parameters:

Number of evaluations

Result names and types

Git-Version

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trial_index,arm_name,trial_status,generation_method,generation_node,ACCURACY,RUNTIME,recent_samples_size,n_samples,const,max_depth,threshold
0,0_0,COMPLETED,Sobol,GenerationStep_0,0.700000000000000066613381477509,3,1620,4143,7.982919480681419877043936139671,4,0.882287493586540239043358724302
1,1_0,COMPLETED,Sobol,GenerationStep_0,0.729999999999999982236431605997,27,2909,109,4.800845133917406748480516398558,11,0.40107114133797583388485463729
2,2_0,COMPLETED,Sobol,GenerationStep_0,0.690000000000000057731597280508,5,4528,3583,6.474530969013460257599490432767,10,0.237508180126547813193482738825
3,3_0,COMPLETED,Sobol,GenerationStep_0,0.640000000000000013322676295502,3,660,2012,0.743997874721884722148956825549,18,0.719203989632427709288720052427
4,4_0,COMPLETED,Sobol,GenerationStep_0,0.670000000000000039968028886506,2,610,3005,3.434259827704169154571900435258,20,0.50902685163170102722318688393
5,5_0,COMPLETED,Sobol,GenerationStep_0,0.690000000000000057731597280508,5,4243,1412,8.803615154411643217713390185963,7,0.027323190048336984392385318188
6,6_0,COMPLETED,Sobol,GenerationStep_0,0.690000000000000057731597280508,3,3323,4896,2.422758724032901156419939070474,14,0.363399862712249166474265393845
7,7_0,COMPLETED,Sobol,GenerationStep_0,0.670000000000000039968028886506,2,2111,844,5.3410730496998883864989693393,2,0.844608367530629067232439410873
8,8_0,COMPLETED,Sobol,GenerationStep_0,0.719999999999999973354647408996,2,2373,3438,1.583753850243054372981532651465,6,0.496270950065925697813895567378
9,9_0,COMPLETED,Sobol,GenerationStep_0,0.670000000000000039968028886506,5,3740,2470,6.181586962176487176634509523865,19,0.981872573265805792530613871349
10,10_0,COMPLETED,Sobol,GenerationStep_0,0.690000000000000057731597280508,3,3991,3996,2.554970862218179039615506553673,3,0.631299002546817034087212050508
11,11_0,COMPLETED,Sobol,GenerationStep_0,0.640000000000000013322676295502,779,203,569,9.681962460685522131598190753721,15,0.146191584344953301455305449963
12,12_0,COMPLETED,Sobol,GenerationStep_0,0.670000000000000039968028886506,2,1029,4419,7.001067092803307190251871361397,12,0.123132070150226355376155140675
13,13_0,COMPLETED,Sobol,GenerationStep_0,0.680000000000000048849813083507,7,4740,1009,0.215952712245285532999261590703,5,0.608246388662606496389173571515
14,14_0,COMPLETED,Sobol,GenerationStep_0,0.640000000000000013322676295502,4,2530,2525,8.549739444735459770186025707517,17,0.757068918446078931161480340961
15,15_0,COMPLETED,Sobol,GenerationStep_0,0.709999999999999964472863211995,4,1398,1579,4.23496657764352946173858072143,8,0.271474195556715147681359212584
16,16_0,COMPLETED,Sobol,GenerationStep_0,0.640000000000000013322676295502,3,1420,2727,5.798992267700843861177872895496,14,0.713214073034003415152426441637
17,17_0,COMPLETED,Sobol,GenerationStep_0,0.660000000000000031086244689504,3,2786,1759,1.359719537043943882181906701589,1,0.196430429929867395033582511132
18,18_0,COMPLETED,Sobol,GenerationStep_0,0.660000000000000031086244689504,3,4952,4549,9.905882232663222097812649735715,20,0.406744123253971356923841540265
19,19_0,COMPLETED,Sobol,GenerationStep_0,0.700000000000000066613381477509,5,1163,1123,2.93768009791523221352349537483,8,0.923048313748091486807823002891
20,20_0,COMPLETED,Sobol,GenerationStep_0,0.670000000000000039968028886506,2,108,3875,0.618076498725451561888633023045,10,0.838893450241535942879522735893
21,21_0,COMPLETED,Sobol,GenerationStep_0,0.739999999999999991118215802999,427,3818,466,7.244630460757762513424040662358,17,0.322597111824899918097742101963
22,22_0,COMPLETED,Sobol,GenerationStep_0,0.670000000000000039968028886506,3,3445,3227,3.991517750910483552928553763195,3,0.033332207048311829344910961481
23,23_0,COMPLETED,Sobol,GenerationStep_0,0.660000000000000031086244689504,5,2312,2280,8.147501117033883133444760460407,11,0.550123702229931899054804489424
24,24_0,COMPLETED,Sobol,GenerationStep_0,0.600000000000000088817841970013,3,1938,4697,4.402382960229181740885451290524,16,0.171402555687353019830965195069
25,25_0,COMPLETED,Sobol,GenerationStep_0,0.719999999999999973354647408996,8,3228,663,7.738135410612449582856697816169,9,0.68380093248747286782673882044
26,26_0,COMPLETED,Sobol,GenerationStep_0,0.680000000000000048849813083507,4,4182,2872,0.988667450130917169204280980921,13,0.956375116348266551824508496793
27,27_0,COMPLETED,Sobol,GenerationStep_0,0.719999999999999973354647408996,3,314,1301,6.873107385929674961744240135886,5,0.443482534550130369499498783625
28,28_0,COMPLETED,Sobol,GenerationStep_0,0.680000000000000048849813083507,3,916,3706,9.18254827334452450315893656807,2,0.296960047237575075484983244678
29,29_0,COMPLETED,Sobol,GenerationStep_0,0.729999999999999982236431605997,8,4550,2113,3.659514554336666947165213059634,15,0.809845728725194891062244550994
30,30_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,17,4400,385,0.001000000000000000020816681712,16,0.622981179772556292739693617477
31,31_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,6093,4308,1,3.276977116741448536885172870825,9,0.540530483495147429096050473163
32,32_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,4,5000,3004,10,16,0.9989999999999999991118215803
33,33_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,7,4818,1094,0.001000000000000000020816681712,16,0.001000000000000000020816681712
34,34_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,6437,4339,1,2.265543431698116449979352182709,15,0.9989999999999999991118215803
35,35_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,1193,3456,1,0.001000000000000000020816681712,10,0.001000000000000000020816681712
36,36_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,4,1923,2487,10,6,0.9989999999999999991118215803
37,37_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,919,1989,1,2.578764743662740777097042155219,6,0.001000000000000000020816681712
38,38_0,RUNNING,BoTorch,GenerationStep_1,,,4872,1,0.001000000000000000020816681712,17,0.9989999999999999991118215803
39,39_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,6246,4648,1,3.180047443483558389232257468393,12,0.9989999999999999991118215803
40,40_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,1602,3901,1,0.001000000000000000020816681712,15,0.001000000000000000020816681712
41,41_0,RUNNING,BoTorch,GenerationStep_1,,,5000,1,4.666129939426686412673461745726,7,0.538852263434716705070570696989
42,42_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,6,5000,1430,10,16,0.9989999999999999991118215803
43,43_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,2,616,5000,0.001000000000000000020816681712,6,0.001000000000000000020816681712
44,44_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,6,5000,2192,10,7,0.9989999999999999991118215803
45,45_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,1601,5000,1,0.001000000000000000020816681712,15,0.001000000000000000020816681712
46,46_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,3,5000,3630,10,15,0.9989999999999999991118215803
47,47_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,4647,3534,1,0.001000000000000000020816681712,15,0.9989999999999999991118215803
48,48_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,4,5000,2644,0.001000000000000000020816681712,16,0.001000000000000000020816681712
49,49_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,1133,2509,1,0.001000000000000000020816681712,9,0.001000000000000000020816681712
50,50_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,4448,3447,1,0.250661656278794942043219862171,10,0.72648258415193145420829523573
51,51_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,0.001000000000000000020816681712,19,0.9989999999999999991118215803
52,52_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,1237,4861,1,2.389658232350520439268848349457,10,0.290515780915859611610585488961
53,53_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,8,4378,948,0.001000000000000000020816681712,16,0.9989999999999999991118215803
54,54_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,623,5000,1,4.717391478144433492047937761527,3,0.001000000000000000020816681712
55,55_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,5,1,4070,10,20,0.9989999999999999991118215803
56,56_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,856,1,1,0.001000000000000000020816681712,6,0.001000000000000000020816681712
57,57_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,3,4210,5000,0.001000000000000000020816681712,7,0.9989999999999999991118215803
58,58_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,3,4996,5000,10,7,0.9989999999999999991118215803
59,59_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,5645,4875,1,4.1817771977717752562853092968,10,0.9989999999999999991118215803
60,60_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,9,4121,871,4.737237682826629381338534585666,12,0.746379054643187656026270815346
61,61_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,220,3966,391,4.281001358386227195751416729763,12,0.782628618028717637500335513323
62,62_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,873,4142,832,4.512901898045180715257629344705,14,0.424933727214824696893913369422
63,63_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,11,3968,677,4.329518160703052842563920421526,10,0.974637108877582591937027700624
64,64_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,4,4810,1939,4.731987813585218916045960213523,18,0.001000000000000000020816681712
65,65_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,6,3151,1169,1.710987595333870903147044373327,10,0.9989999999999999991118215803
66,66_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,9,4524,1084,5.540201882018855883416108554229,13,0.650193741919587564481730623811
67,67_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,101,3837,58,3.940393271600024505119108653162,12,0.783080509550259207252054238779
68,68_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,2,2403,4549,0.001000000000000000020816681712,6,0.9989999999999999991118215803
69,69_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,19,4162,537,5.227232416292206806929243612103,12,0.720108349124189861534262036002
70,70_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,20,4336,697,4.469019307521158168583497172222,16,0.101451945355955253091906342888
71,71_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,2,529,2611,3.235030082427177600123968659318,5,0.001000000000000000020816681712
72,72_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,8,4668,865,4.749001571517728059745877544628,19,0.387654585785973115896752005938
73,73_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,3,1724,4018,0.001000000000000000020816681712,6,0.001000000000000000020816681712
74,74_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,112,4146,210,5.159089695636138728218611504417,12,0.777361697396022677253313304391
75,75_0,COMPLETED,BoTorch,GenerationStep_1,0.650000000000000022204460492503,2,142,3762,2.798503527274313729122923177783,4,0.001000000000000000020816681712
76,76_0,COMPLETED,BoTorch,GenerationStep_1,0.660000000000000031086244689504,3,1061,2075,1.273547759532380529989836759341,5,0.001000000000000000020816681712
77,77_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,9,4331,738,5.281514468881145063505755388178,6,0.9989999999999999991118215803
78,78_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,2,1028,4700,0.001000000000000000020816681712,1,0.63869692033149094712030091614
79,79_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,2,1769,4844,0.001000000000000000020816681712,7,0.789442482276320078860010198696
80,80_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,244,4884,531,4.681426275597865505062600277597,19,0.001000000000000000020816681712
81,81_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,8,4297,1046,5.409622681335242155853393342113,9,0.9989999999999999991118215803
82,82_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,2,126,3311,2.037391858099973251938763496582,1,0.416910559381018286373432601977
83,83_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,138,3650,625,3.274577835351026422472386911977,12,0.74463974196755977619233135556
84,84_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,36,4080,168,4.448208025023618894522314803908,13,0.615572563694329888406286954705
85,85_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,2,1,2163,4.04088502781231362348535185447,5,0.001000000000000000020816681712
86,86_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,3,2675,1669,0.001000000000000000020816681712,11,0.9989999999999999991118215803
87,87_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,5,950,737,0.001000000000000000020816681712,3,0.082896226059125388552217827964
88,88_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,13,3581,399,3.173088074710329387073670659447,11,0.9989999999999999991118215803
89,89_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,3,203,564,3.828762672031267300098988926038,1,0.001000000000000000020816681712
90,90_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,26,4118,243,0.001000000000000000020816681712,9,0.752417292137260496076578419888
91,91_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,21,3562,239,0.001000000000000000020816681712,8,0.492397450899787592071277231298
92,92_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,36,4555,176,0.001000000000000000020816681712,9,0.876069924333020000339899979735
93,93_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,23,3204,229,10,8,0.320699357511880833726536366157
94,94_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,55,3743,98,0.001000000000000000020816681712,8,0.684354840095635408303564872767
95,95_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,49,3919,127,10,8,0.650300433938824529178646116634
96,96_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,267,3284,227,10,20,0.147185548161598206418076983937
97,97_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,86,3439,259,10,18,0.874223527231546171378795406781
98,98_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,19,5000,317,0.001000000000000000020816681712,10,0.9989999999999999991118215803
99,99_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,113,2993,242,10,20,0.431090765841456946549925532963
100,100_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,19,3367,228,0.001000000000000000020816681712,19,0.686551640685817310405525404349
101,101_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,85,4834,261,10,8,0.786640028901444576803214658867
102,102_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,14,2991,894,10,20,0.23163600967767905558503116481
103,103_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,13,2882,217,0.001000000000000000020816681712,2,0.001000000000000000020816681712
104,104_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,25,3442,178,10,16,0.9989999999999999991118215803
105,105_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,83,4186,226,10,18,0.238953446056642954120619037894
106,106_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,12,2750,222,0.001000000000000000020816681712,19,0.001000000000000000020816681712
107,107_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,17,2642,249,0.001000000000000000020816681712,20,0.257520447919497852407033633426
108,108_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,23,3430,181,10,8,0.844401695336755464538214255299
109,109_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,34,2375,267,10,17,0.9989999999999999991118215803
110,110_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,607,2420,226,10,20,0.001000000000000000020816681712
111,111_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,5,2228,211,0.001000000000000000020816681712,7,0.556912880219845640716869183962
112,112_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,33,1169,236,10,7,0.478200749972826855138663404432
113,113_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,56,4333,109,0.001000000000000000020816681712,9,0.9989999999999999991118215803
114,114_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,20,3587,234,0.001000000000000000020816681712,8,0.276431854471228144465300147203
115,115_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,3,2833,1588,10,20,0.001000000000000000020816681712
116,116_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,2,1,3288,0.001000000000000000020816681712,1,0.9989999999999999991118215803
117,117_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,2,165,2764,0.001000000000000000020816681712,3,0.953445738882684024062541539024
118,118_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,40,3978,218,10,6,0.001000000000000000020816681712
119,119_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,50,386,233,10,9,0.327898151490232547811132235438
120,120_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,6112,4325,1,9.240970085710779713394913414959,14,0.9989999999999999991118215803
121,121_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,5854,4295,1,10,10,0.9989999999999999991118215803
122,122_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,6018,4652,1,1.144559977551155016683992471371,14,0.9989999999999999991118215803
123,123_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,57,4269,116,3.802424638221551855821189747076,14,0.9989999999999999991118215803
124,124_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,4541,3610,1,5.287318965134845782927186519373,14,0.9989999999999999991118215803
125,125_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,6495,4141,1,8.450454359390683123365306528285,15,0.9989999999999999991118215803
126,126_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,6140,5000,1,7.963138802523596737614752782974,14,0.9989999999999999991118215803
127,127_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,5901,4886,1,1.440499818300766010636948522006,11,0.9989999999999999991118215803
128,128_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,5985,5000,1,10,18,0.964048382756507948876389946236
129,129_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,6258,4715,1,3.757648139152261368423069143319,13,0.9989999999999999991118215803
130,130_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,5035,3837,1,8.817784042301807900798849004786,10,0.9989999999999999991118215803
131,131_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,5946,3753,1,4.891569274927675792241643648595,13,0.9989999999999999991118215803
132,132_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,5721,5000,1,9.34414356224242581561156839598,10,0.9989999999999999991118215803
133,133_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,6251,4894,1,9.603028786093549484803588711657,9,0.9989999999999999991118215803
134,134_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,5889,4677,1,3.789011124056584023378491110634,17,0.665606424561819065566226072406
135,135_0,COMPLETED,BoTorch,GenerationStep_1,0.75,1349,2436,1,7.295827559415337226766951062018,12,0.9989999999999999991118215803
136,136_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,6366,5000,1,7.018118190626157826272901729681,13,0.9989999999999999991118215803
137,137_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,590,2045,1,10,3,0.001000000000000000020816681712
138,138_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,925,259,1,7.453475295456022386986205674475,11,0.9989999999999999991118215803
139,139_0,COMPLETED,BoTorch,GenerationStep_1,0.75,4452,3317,1,10,14,0.9989999999999999991118215803
140,140_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,7123,4039,1,1.394294525377878235516959648521,14,0.9989999999999999991118215803
141,141_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,4571,3605,1,6.793581062365734446473197749583,11,0.9989999999999999991118215803
142,142_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,5797,4066,1,7.603845877818301346451335120946,14,0.9989999999999999991118215803
143,143_0,COMPLETED,BoTorch,GenerationStep_1,0.810000000000000053290705182008,86,1,1,8.128844705391392366777836286929,5,0.949762501759429222936148562439
144,144_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,5999,3986,1,0.914544451382904299840959083667,10,0.9989999999999999991118215803
145,145_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,458,5000,1,9.927025514602602740410475234967,1,0.001000000000000000020816681712
146,146_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,674,785,1,9.136554769997795588665212562773,4,0.392999771239976980474750689609
147,147_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,7136,4314,1,9.538527820295886527901529916562,15,0.9989999999999999991118215803
148,148_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,260,4681,29,6.619682501764320825543563842075,16,0.875265281512327963930886198796
149,149_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,793,3700,8,6.791362354011568847056423692266,16,0.659972849961133034568661059893
150,150_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,7,146,76,10,1,0.928794402383602446526822404849
151,151_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,2,1,2392,10,1,0.9989999999999999991118215803
152,152_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,23,1273,365,10,4,0.475100751189052428191672561297
153,153_0,COMPLETED,BoTorch,GenerationStep_1,0.660000000000000031086244689504,3,5000,4314,0.001000000000000000020816681712,20,0.9989999999999999991118215803
154,154_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,4,30,40,8.500455674269851158442179439589,1,0.916073047935597961632936403475
155,155_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,3,2102,345,0.001000000000000000020816681712,1,0.001000000000000000020816681712
156,156_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,2,1,95,10,1,0.990203077059072178656151663745
157,157_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,2,1,893,0.001000000000000000020816681712,1,0.001000000000000000020816681712
158,158_0,COMPLETED,BoTorch,GenerationStep_1,0.660000000000000031086244689504,3,5000,4262,0.001000000000000000020816681712,1,0.001000000000000000020816681712
159,159_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,1129,1,974,10,20,0.687703988583119429911505449127
160,160_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,48,4949,128,0.001000000000000000020816681712,16,0.433844804334918399124632060193
161,161_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,20,235,377,10,6,0.558309114438343745412396401662
162,162_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,2,1,1443,0.001000000000000000020816681712,8,0.42966630196892480197945474174
163,163_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,2,1,66,0.016403244478537575001819703857,1,0.94691982783591299721592804417
164,164_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,6,5000,4160,10,20,0.001000000000000000020816681712
165,165_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,1379,1,1091,10,20,0.001000000000000000020816681712
166,166_0,COMPLETED,BoTorch,GenerationStep_1,0.660000000000000031086244689504,3,5000,4313,0.001000000000000000020816681712,7,0.9989999999999999991118215803
167,167_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,3,5000,4179,0.737992334921896753208159225323,1,0.001000000000000000020816681712
168,168_0,COMPLETED,BoTorch,GenerationStep_1,0.630000000000000004440892098501,2,1,1145,0.001000000000000000020816681712,10,0.001000000000000000020816681712
169,169_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,2,1,97,0.001000000000000000020816681712,2,0.940788194640071573360273760045
170,170_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,3,5000,3350,10,20,0.9989999999999999991118215803
171,171_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,3,1920,4221,0.001000000000000000020816681712,1,0.001000000000000000020816681712
172,172_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,68,5000,106,10,20,0.001000000000000000020816681712
173,173_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,2,743,3529,0.001000000000000000020816681712,1,0.670857494395666442699166509556
174,174_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,2,1,996,10,1,0.001000000000000000020816681712
175,175_0,COMPLETED,BoTorch,GenerationStep_1,0.660000000000000031086244689504,2,1,4198,0.001000000000000000020816681712,8,0.001000000000000000020816681712
176,176_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,48,5000,120,0.001000000000000000020816681712,1,0.001000000000000000020816681712
177,177_0,COMPLETED,BoTorch,GenerationStep_1,0.630000000000000004440892098501,3,4998,4247,0.001000000000000000020816681712,20,0.019640795788235857616266244463
178,178_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,17,1,4298,10,20,0.9989999999999999991118215803
179,179_0,COMPLETED,BoTorch,GenerationStep_1,0.650000000000000022204460492503,18,5000,4319,10,20,0.001000000000000000020816681712
180,180_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,3,1,98,10,7,0.9989999999999999991118215803
181,181_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,45,5000,146,10,13,0.9989999999999999991118215803
182,182_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,51,1,482,10,6,0.9989999999999999991118215803
183,183_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,76,4254,83,10,12,0.9989999999999999991118215803
184,184_0,COMPLETED,BoTorch,GenerationStep_1,0.810000000000000053290705182008,113,1,1,10,7,0.9989999999999999991118215803
185,185_0,COMPLETED,BoTorch,GenerationStep_1,0.650000000000000022204460492503,21,1,701,10,6,0.9989999999999999991118215803
186,186_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,31,5000,197,10,20,0.9989999999999999991118215803
187,187_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,3054,1115,1,10,7,0.9989999999999999991118215803
188,188_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,2,1,1808,10,6,0.9989999999999999991118215803
189,189_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,36,1905,154,10,8,0.9989999999999999991118215803
190,190_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,2,1,1446,10,5,0.9989999999999999991118215803
191,191_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,2,1,136,10,6,0.9989999999999999991118215803
192,192_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,14,5000,1275,10,20,0.001000000000000000020816681712
193,193_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,144,5000,525,10,14,0.9989999999999999991118215803
194,194_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,98,5000,62,10,13,0.9989999999999999991118215803
195,195_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,32,4643,196,10,12,0.9989999999999999991118215803
196,196_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,2,1,1283,10,5,0.9989999999999999991118215803
197,197_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,39,5000,153,0.001000000000000000020816681712,20,0.9989999999999999991118215803
198,198_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,4,5000,1831,0.001000000000000000020816681712,20,0.9989999999999999991118215803
199,199_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,9,5000,1265,10,11,0.9989999999999999991118215803
200,200_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,4,5000,2400,10,20,0.001000000000000000020816681712
201,201_0,COMPLETED,BoTorch,GenerationStep_1,0.619999999999999995559107901499,2,1,2177,10,5,0.9989999999999999991118215803
202,202_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,9,5000,1701,10,20,0.001000000000000000020816681712
203,203_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,2,2690,5000,10,1,0.001000000000000000020816681712
204,204_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,3,1,363,10,7,0.9989999999999999991118215803
205,205_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,38,3243,94,10,10,0.9989999999999999991118215803
206,206_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,19,5000,416,10,12,0.9989999999999999991118215803
207,207_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,6,5000,1204,0.001000000000000000020816681712,20,0.9989999999999999991118215803
208,208_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,3,5000,4734,10,1,0.9989999999999999991118215803
209,209_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,7,5000,2151,10,17,0.001000000000000000020816681712
210,210_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,23,3096,324,10,5,0.751929411459826724239974282682
211,211_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,6,5000,4020,10,19,0.001000000000000000020816681712
212,212_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,4,5000,2021,10,13,0.9989999999999999991118215803
213,213_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,7,5000,3905,10,20,0.001000000000000000020816681712
214,214_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,499,5000,741,10,17,0.9989999999999999991118215803
215,215_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,12,2852,351,10,3,0.9989999999999999991118215803
216,216_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,3,772,3389,4.688031202139906206127761834068,10,0.001000000000000000020816681712
217,217_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,4,5000,3076,10,20,0.001000000000000000020816681712
218,218_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,6,3319,3939,10,20,0.001000000000000000020816681712
219,219_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,5,2530,4048,10,20,0.001000000000000000020816681712
220,220_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,62,3764,124,10,20,0.628633443953452553110139433556
221,221_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,4,5000,3789,10,1,0.9989999999999999991118215803
222,222_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,2,1,2431,10,1,0.001000000000000000020816681712
223,223_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,3,2887,3367,0.001000000000000000020816681712,13,0.001000000000000000020816681712
224,224_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,2,2850,4109,10,1,0.001000000000000000020816681712
225,225_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,5,5000,4070,10,20,0.9989999999999999991118215803
226,226_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,6,5000,3821,10,20,0.865597619125430539632759519009
227,227_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,4,5000,4070,10,12,0.001000000000000000020816681712
228,228_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,51,4965,155,7.434874648367184590824763290584,1,0.9989999999999999991118215803
229,229_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,45,3282,103,9.730597639996600989320540975314,1,0.001000000000000000020816681712
230,230_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,4,5000,2949,10,1,0.001000000000000000020816681712
231,231_0,COMPLETED,BoTorch,GenerationStep_1,0.650000000000000022204460492503,4,5000,2043,0.001000000000000000020816681712,8,0.9989999999999999991118215803
232,232_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,3,5000,3153,10,20,0.959879516593710846450449025724
233,233_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,4,5000,2621,10,1,0.9989999999999999991118215803
234,234_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,4,5000,2920,10,20,0.001000000000000000020816681712
235,235_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,3,5000,3092,10,8,0.9989999999999999991118215803
236,236_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,2,1,3403,10,20,0.001000000000000000020816681712
237,237_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,9,3695,664,0.001000000000000000020816681712,2,0.001000000000000000020816681712
238,238_0,COMPLETED,BoTorch,GenerationStep_1,0.660000000000000031086244689504,4,1,4048,10,20,0.001000000000000000020816681712
239,239_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,2,497,2448,0.001000000000000000020816681712,1,0.493029689135264459487473232002
240,240_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,5,2743,3821,10,20,0.001000000000000000020816681712
241,241_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,48,3605,104,0.001000000000000000020816681712,1,0.001000000000000000020816681712
242,242_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,5,2804,3949,10,20,0.9989999999999999991118215803
243,243_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,8,5000,935,0.001000000000000000020816681712,20,0.001000000000000000020816681712
244,244_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,5,5000,1555,0.001000000000000000020816681712,20,0.379514692210152937423828234387
245,245_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,10,1,1664,10,17,0.001000000000000000020816681712
246,246_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,4,5000,2237,0.001000000000000000020816681712,18,0.9989999999999999991118215803
247,247_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,7,1,33,10,6,0.9989999999999999991118215803
248,248_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,5,5000,1548,0.001000000000000000020816681712,1,0.9989999999999999991118215803
249,249_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,6,5000,1533,0.001000000000000000020816681712,20,0.001000000000000000020816681712
250,250_0,COMPLETED,BoTorch,GenerationStep_1,0.630000000000000004440892098501,2,1,2555,10,1,0.9989999999999999991118215803
251,251_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,4,3539,1554,0.001000000000000000020816681712,20,0.781966169970413904621864276123
252,252_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,3,3923,3755,10,20,0.001000000000000000020816681712
253,253_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,312,2549,304,10,12,0.001000000000000000020816681712
254,254_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,3,1,52,10,6,0.9989999999999999991118215803
255,255_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,5,1511,3838,10,20,0.001000000000000000020816681712
256,256_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,3,5000,3926,0.001000000000000000020816681712,13,0.9989999999999999991118215803
257,257_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,2,1,3162,10,1,0.001000000000000000020816681712
258,258_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,3,1322,1684,0.001000000000000000020816681712,20,0.001000000000000000020816681712
259,259_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,2,1,1708,10,8,0.001000000000000000020816681712
260,260_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,2,1,1364,10,1,0.001000000000000000020816681712
261,261_0,COMPLETED,BoTorch,GenerationStep_1,0.640000000000000013322676295502,4,2274,3820,10,20,0.680607056223083484169933399244
262,262_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,3,1795,3759,10,20,0.9989999999999999991118215803
263,263_0,COMPLETED,BoTorch,GenerationStep_1,0.650000000000000022204460492503,3,1,1774,10,20,0.001000000000000000020816681712
264,264_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,2,245,1591,7.258732981560813257715381041635,20,0.9989999999999999991118215803
265,265_0,COMPLETED,BoTorch,GenerationStep_1,0.640000000000000013322676295502,2,1,4568,0.001000000000000000020816681712,1,0.001000000000000000020816681712
266,266_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,23,5000,930,10,16,0.001000000000000000020816681712
267,267_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,15,5000,565,0.001000000000000000020816681712,2,0.9989999999999999991118215803
268,268_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,3,3353,3796,0.001000000000000000020816681712,20,0.001000000000000000020816681712
269,269_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,2,1,3627,0.001000000000000000020816681712,20,0.9989999999999999991118215803
270,270_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,19,4853,312,10,1,0.324107845528441240734451866956
271,271_0,COMPLETED,BoTorch,GenerationStep_1,0.75,2386,791,1,10,20,0.9989999999999999991118215803
272,272_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,4596,1848,1,10,1,0.9989999999999999991118215803
273,273_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,8,5000,735,10,1,0.001000000000000000020816681712
274,274_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,22,1,13,10,20,0.9989999999999999991118215803
275,275_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,3,5000,2788,0.001000000000000000020816681712,20,0.001000000000000000020816681712
276,276_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,67,217,34,10,20,0.997342226009621635185453669692
277,277_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,18,5000,335,0.001000000000000000020816681712,1,0.036815009015031534278517000303
278,278_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,4971,1348,1,0.001000000000000000020816681712,20,0.9989999999999999991118215803
279,279_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,10,4928,631,10,1,0.310479712580486455486550312344
280,280_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,17,4908,358,10,1,0.48468617535697983145226430679
281,281_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,8,5000,759,0.001000000000000000020816681712,1,0.001000000000000000020816681712
282,282_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,1193,5000,468,10,20,0.713048423636191586183485924266
283,283_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,49,4792,123,10,1,0.574778725787663757884615733929
284,284_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,153,5000,320,0.001000000000000000020816681712,20,0.001000000000000000020816681712
285,285_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,1586,559,1,10,1,0.9989999999999999991118215803
286,286_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,11,5000,657,0.001000000000000000020816681712,20,0.001000000000000000020816681712
287,287_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,3,5000,3467,0.001000000000000000020816681712,1,0.9989999999999999991118215803
288,288_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,31,5000,202,10,1,0.041771049228403481223814708301
289,289_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,350,4964,328,10,20,0.535972939947676918492902586877
290,290_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,5851,1975,1,10,20,0.9989999999999999991118215803
291,291_0,COMPLETED,BoTorch,GenerationStep_1,0.810000000000000053290705182008,39,1,1,10,1,0.9989999999999999991118215803
292,292_0,COMPLETED,BoTorch,GenerationStep_1,0.75,12,84,48,10,20,0.729200166445189368324975021096
293,293_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,9,5000,706,0.001000000000000000020816681712,20,0.383369379065453708133048849049
294,294_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,4745,1333,1,10,20,0.9989999999999999991118215803
295,295_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,6,5000,1386,0.001000000000000000020816681712,1,0.614093313713399369113687953359
296,296_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,21,5000,295,10,1,0.001000000000000000020816681712
297,297_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,2,1,5000,10,20,0.750692936862546345011537596292
298,298_0,COMPLETED,BoTorch,GenerationStep_1,0.810000000000000053290705182008,328,1,1,10,20,0.9989999999999999991118215803
299,299_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,2272,2749,1,10,20,0.9989999999999999991118215803
300,300_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,6,1,58,10,20,0.526205523606941949488202681096
301,301_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,11,55,44,10,20,0.9989999999999999991118215803
302,302_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,52,4927,120,10,1,0.294210468070871755674744463249
303,303_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,79,694,27,10,1,0.821331474805523376048199679644
304,304_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,8,5000,813,0.001000000000000000020816681712,20,0.001000000000000000020816681712
305,305_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,6,1,1500,10,20,0.001000000000000000020816681712
306,306_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,2,1,4572,10,20,0.9989999999999999991118215803
307,307_0,COMPLETED,BoTorch,GenerationStep_1,0.810000000000000053290705182008,32,1,1,0.001000000000000000020816681712,1,0.9989999999999999991118215803
308,308_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,45,5000,132,10,20,0.571829070582599130467826853419
309,309_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,13,5000,445,0.001000000000000000020816681712,20,0.001000000000000000020816681712
310,310_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,13,5000,457,0.001000000000000000020816681712,1,0.9989999999999999991118215803
311,311_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,3,5000,3452,10,1,0.001000000000000000020816681712
312,312_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,2,1,4853,0.001000000000000000020816681712,1,0.9989999999999999991118215803
313,313_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,53,5000,108,10,1,0.001000000000000000020816681712
314,314_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,5,69,59,10,1,0.544298329667322722258404610329
315,315_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,6,5000,1183,10,1,0.065111813925307876482762026171
316,316_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,17,5000,355,10,1,0.9989999999999999991118215803
317,317_0,COMPLETED,BoTorch,GenerationStep_1,0.75,3338,1307,1,10,1,0.9989999999999999991118215803
318,318_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,2,1,3403,10,20,0.9989999999999999991118215803
319,319_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,19,1248,317,0.001000000000000000020816681712,20,0.001000000000000000020816681712
320,320_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,19,5000,301,0.001000000000000000020816681712,1,0.508224399172210627995127651957
321,321_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,40,5000,150,10,20,0.001000000000000000020816681712
322,322_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,15,5000,410,10,1,0.001000000000000000020816681712
323,323_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,12,5000,490,0.001000000000000000020816681712,1,0.282821587358941917145216393692
324,324_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,27,1,22,0.001000000000000000020816681712,20,0.8780895479983349405372905494
325,325_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,6,2,68,10,20,0.371622995797189159539186675829
326,326_0,COMPLETED,BoTorch,GenerationStep_1,0.810000000000000053290705182008,555,1,1,0.001000000000000000020816681712,20,0.9989999999999999991118215803
327,327_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,9,1,4788,10,20,0.9989999999999999991118215803
328,328_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,907,232,1,10,20,0.737454734779045772974370720476
329,329_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,3,1,18,10,1,0.9989999999999999991118215803
330,330_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,2182,600,1,0.001000000000000000020816681712,20,0.9989999999999999991118215803
331,331_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,13,3404,1290,10,20,0.9989999999999999991118215803
332,332_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,10,5000,1295,10,20,0.631208425811755846623896104575
333,333_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,2,1,39,10,1,0.9989999999999999991118215803
334,334_0,COMPLETED,BoTorch,GenerationStep_1,0.640000000000000013322676295502,3,5000,3543,0.001000000000000000020816681712,20,0.9989999999999999991118215803
335,335_0,COMPLETED,BoTorch,GenerationStep_1,0.640000000000000013322676295502,2,1,4455,0.001000000000000000020816681712,1,0.9989999999999999991118215803
336,336_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,2,1,2832,0.001000000000000000020816681712,1,0.001000000000000000020816681712
337,337_0,COMPLETED,BoTorch,GenerationStep_1,0.660000000000000031086244689504,2,1,4945,0.001000000000000000020816681712,1,0.001000000000000000020816681712
338,338_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,1003,5000,604,10,20,0.9989999999999999991118215803
339,339_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,7,5000,1136,10,1,0.9989999999999999991118215803
340,340_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,4,1,13,0.001000000000000000020816681712,1,0.9989999999999999991118215803
341,341_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,16,1917,350,0.001000000000000000020816681712,20,0.9989999999999999991118215803
342,342_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,3,5000,4105,0.001000000000000000020816681712,1,0.9989999999999999991118215803
343,343_0,COMPLETED,BoTorch,GenerationStep_1,0.75,2389,898,1,0.001000000000000000020816681712,1,0.9989999999999999991118215803
344,344_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,18,5000,351,0.001000000000000000020816681712,20,0.9989999999999999991118215803
345,345_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,10,5000,582,10,1,0.001000000000000000020816681712
346,346_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,12,5000,559,0.001000000000000000020816681712,1,0.001000000000000000020816681712
347,347_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,4,3011,1360,10,1,0.9989999999999999991118215803
348,348_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,2,1,30,0.001000000000000000020816681712,1,0.9989999999999999991118215803
349,349_0,COMPLETED,BoTorch,GenerationStep_1,0.640000000000000013322676295502,2,1,4661,10,1,0.9989999999999999991118215803
350,350_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,3,1,21,0.001000000000000000020816681712,1,0.9989999999999999991118215803
351,351_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,3,5000,5000,10,1,0.001000000000000000020816681712
352,352_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,2,1,5000,10,20,0.001000000000000000020816681712
353,353_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,6,5000,1162,10,1,0.70191396969361197211156877529
354,354_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,16,5000,1645,10,20,0.9989999999999999991118215803
355,355_0,COMPLETED,BoTorch,GenerationStep_1,0.640000000000000013322676295502,2,1,4726,0.001000000000000000020816681712,1,0.9989999999999999991118215803
356,356_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,15,5000,1047,10,20,0.9989999999999999991118215803
357,357_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,27,5000,224,0.001000000000000000020816681712,1,0.001000000000000000020816681712
358,358_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,10,5000,630,10,1,0.9989999999999999991118215803
359,359_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,3,1643,2869,0.001000000000000000020816681712,1,0.001000000000000000020816681712
360,360_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,48,5000,123,10,20,0.9989999999999999991118215803
361,361_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,6,1,74,0.001000000000000000020816681712,20,0.9989999999999999991118215803
362,362_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,256,4534,28,0.001000000000000000020816681712,1,0.9989999999999999991118215803
363,363_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,6,1,67,10,20,0.9989999999999999991118215803
364,364_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,483,5000,348,10,20,0.001000000000000000020816681712
365,365_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,64,5000,100,10,20,0.9989999999999999991118215803
366,366_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,71,4951,93,0.001000000000000000020816681712,20,0.9989999999999999991118215803
367,367_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,7,1,50,10,20,0.9989999999999999991118215803
368,368_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,1053,2130,1,0.001000000000000000020816681712,20,0.9989999999999999991118215803
369,369_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,15,3611,349,0.001000000000000000020816681712,1,0.001000000000000000020816681712
370,370_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,21,1,23,10,20,0.9989999999999999991118215803
371,371_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,41,4,33,10,20,0.9989999999999999991118215803
372,372_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,58,2930,55,0.001000000000000000020816681712,20,0.9989999999999999991118215803
373,373_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,8,5000,794,0.001000000000000000020816681712,1,0.9989999999999999991118215803
374,374_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,42,5000,145,0.001000000000000000020816681712,1,0.9989999999999999991118215803
375,375_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,43,3965,147,10,20,0.9989999999999999991118215803
376,376_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,8,5000,858,0.001000000000000000020816681712,1,0.9989999999999999991118215803
377,377_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,57,5000,124,0.001000000000000000020816681712,20,0.9989999999999999991118215803
378,378_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,16,5000,899,10,20,0.9989999999999999991118215803
379,379_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,2,1,70,10,1,0.9989999999999999991118215803
380,380_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,51,5000,125,10,1,0.9989999999999999991118215803
381,381_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,5,1,87,10,20,0.9989999999999999991118215803
382,382_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,162,4884,42,0.001000000000000000020816681712,20,0.652229103029153156612096609024
383,383_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,2,1,59,10,1,0.9989999999999999991118215803
384,384_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,110,5000,380,0.001000000000000000020816681712,20,0.001000000000000000020816681712
385,385_0,COMPLETED,BoTorch,GenerationStep_1,0.75,1235,375,1,10,20,0.9989999999999999991118215803
386,386_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,31,5000,178,0.001000000000000000020816681712,1,0.9989999999999999991118215803
387,387_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,18,5000,385,0.001000000000000000020816681712,1,0.001000000000000000020816681712
388,388_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,51,1,12,0.001000000000000000020816681712,20,0.9989999999999999991118215803
389,389_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,63,5000,104,0.001000000000000000020816681712,20,0.001000000000000000020816681712
390,390_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,19,3664,313,0.001000000000000000020816681712,20,0.537757348633142728822065237182
391,391_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,4,2426,753,0.001000000000000000020816681712,20,0.001000000000000000020816681712
392,392_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,1660,2581,1,0.001000000000000000020816681712,1,0.9989999999999999991118215803
393,393_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,54,5000,108,10,1,0.9989999999999999991118215803
394,394_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,45,4212,128,0.001000000000000000020816681712,1,0.653947647460837444555181718897
395,395_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,44,5000,339,0.001000000000000000020816681712,20,0.389993087749901434779786768559
396,396_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,60,5000,95,0.001000000000000000020816681712,1,0.001000000000000000020816681712
397,397_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,6,5000,1125,0.001000000000000000020816681712,1,0.001000000000000000020816681712
398,398_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,2,1,298,10,1,0.001000000000000000020816681712
399,399_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,379,4758,20,10,1,0.9989999999999999991118215803
400,400_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,55,5000,129,0.001000000000000000020816681712,20,0.603269904114436261721721166396
401,401_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,8,3248,494,10,1,0.9989999999999999991118215803
402,402_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,5,1,9,10,1,0.9989999999999999991118215803
403,403_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,59,5000,262,0.001000000000000000020816681712,20,0.001000000000000000020816681712
404,404_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,2,1,1525,0.001000000000000000020816681712,1,0.001000000000000000020816681712
405,405_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,2,1,5000,0.001000000000000000020816681712,1,0.9989999999999999991118215803
406,406_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,68,5000,118,0.001000000000000000020816681712,1,0.552642418235704591111812078452
407,407_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,4,1,21,0.001000000000000000020816681712,1,0.591806268175156580113593918213
408,408_0,COMPLETED,BoTorch,GenerationStep_1,0.619999999999999995559107901499,2,1,3128,0.001000000000000000020816681712,1,0.9989999999999999991118215803
409,409_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,29,3044,127,0.001000000000000000020816681712,1,0.9989999999999999991118215803
410,410_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,39,1,8,10,20,0.9989999999999999991118215803
411,411_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,45,5000,129,10,1,0.744294579166857594998418790055
412,412_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,15,3358,302,10,1,0.001000000000000000020816681712
413,413_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,833,501,2,10,1,0.9989999999999999991118215803
414,414_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,3,5000,3279,0.001000000000000000020816681712,20,0.9989999999999999991118215803
415,415_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,9,2919,333,0.001000000000000000020816681712,1,0.9989999999999999991118215803
416,416_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,7,5000,967,10,1,0.001000000000000000020816681712
417,417_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,5,5000,1832,10,20,0.001000000000000000020816681712
418,418_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,311,5000,261,10,20,0.001000000000000000020816681712
419,419_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,19,4535,302,10,1,0.9989999999999999991118215803
420,420_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,6117,5000,1,0.001000000000000000020816681712,1,0.9989999999999999991118215803
421,421_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,57,3529,91,10,20,0.379869534478735393356885197136
422,422_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,42,4373,140,10,14,0.001000000000000000020816681712
423,423_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,146,5000,43,0.001000000000000000020816681712,1,0.9989999999999999991118215803
424,424_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,58,3932,111,0.001000000000000000020816681712,20,0.001000000000000000020816681712
425,425_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,77,5000,77,0.001000000000000000020816681712,1,0.9989999999999999991118215803
426,426_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,249,4480,322,10,10,0.001000000000000000020816681712
427,427_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,144,5000,289,10,10,0.001000000000000000020816681712
428,428_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,66,4498,90,0.001000000000000000020816681712,1,0.9989999999999999991118215803
429,429_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,65,4015,96,10,20,0.610641175041206074602939679608
430,430_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,54,4438,115,0.001000000000000000020816681712,20,0.406247287637847120933543010324
431,431_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,48,3217,77,0.001000000000000000020816681712,20,0.748587045121917316059523272997
432,432_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,14,3973,428,10,1,0.508145961518002953205552785221
433,433_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,79,4665,74,10,1,0.9989999999999999991118215803
434,434_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,43,4123,142,0.001000000000000000020816681712,20,0.001000000000000000020816681712
435,435_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,238,2872,12,10,20,0.9989999999999999991118215803
436,436_0,COMPLETED,BoTorch,GenerationStep_1,0.75,2724,3015,1,10,1,0.9989999999999999991118215803
437,437_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,58,4145,106,10,1,0.9989999999999999991118215803
438,438_0,COMPLETED,BoTorch,GenerationStep_1,0.75,2736,2855,1,0.001000000000000000020816681712,20,0.9989999999999999991118215803
439,439_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,5716,5000,1,10,1,0.9989999999999999991118215803
440,440_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,24,5000,330,0.001000000000000000020816681712,10,0.001000000000000000020816681712
441,441_0,COMPLETED,BoTorch,GenerationStep_1,0.810000000000000053290705182008,32,1,1,10,1,0.68382688226986376722749128021
442,442_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,51,5000,614,0.001000000000000000020816681712,11,0.001000000000000000020816681712
443,443_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,308,4917,25,10,1,0.9989999999999999991118215803
444,444_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,30,3461,327,10,20,0.001000000000000000020816681712
445,445_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,12,3142,408,10,20,0.9989999999999999991118215803
446,446_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,56,3893,103,0.001000000000000000020816681712,20,0.398515044119732209093598385152
447,447_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,45,3294,89,0.001000000000000000020816681712,20,0.60850328822462373956625469873
448,448_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,154,2943,23,10,20,0.9989999999999999991118215803
449,449_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,3,2892,1531,10,1,0.001000000000000000020816681712
450,450_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,4,5000,2108,0.001000000000000000020816681712,20,0.49502739334053147413072792915
451,451_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,2,1,1589,0.001000000000000000020816681712,20,0.001000000000000000020816681712
452,452_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,37,1,4187,10,20,0.9989999999999999991118215803
453,453_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,2,1,4332,0.001000000000000000020816681712,20,0.001000000000000000020816681712
454,454_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,4,5000,2016,10,1,0.122659812476311566586950618785
455,455_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,3,1,279,0.001000000000000000020816681712,20,0.9989999999999999991118215803
456,456_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,3,5000,4630,10,20,0.9989999999999999991118215803
457,457_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,3,4882,3402,10,1,0.68712820760523307672684723002
458,458_0,COMPLETED,BoTorch,GenerationStep_1,0.619999999999999995559107901499,3,5000,4570,0.001000000000000000020816681712,1,0.9989999999999999991118215803
459,459_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,1,1,2907,10,1,0.9989999999999999991118215803
460,460_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,7,5000,994,0.001000000000000000020816681712,1,0.9989999999999999991118215803
461,461_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,3,5000,2731,10,1,0.001000000000000000020816681712
462,462_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,3,2330,1041,0.001000000000000000020816681712,20,0.9989999999999999991118215803
463,463_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,2,1,49,10,1,0.001000000000000000020816681712
464,464_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,3,5000,2501,0.001000000000000000020816681712,1,0.001000000000000000020816681712
465,465_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,3,1664,2305,0.001000000000000000020816681712,20,0.001000000000000000020816681712
466,466_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,2,1,3007,0.001000000000000000020816681712,1,0.001000000000000000020816681712
467,467_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,8,4926,787,0.001000000000000000020816681712,1,0.579928974447770695377357696998
468,468_0,COMPLETED,BoTorch,GenerationStep_1,0.660000000000000031086244689504,2,1,4922,10,20,0.9989999999999999991118215803
469,469_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,3,4652,3647,0.001000000000000000020816681712,1,0.001000000000000000020816681712
470,470_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,3,5000,3342,10,1,0.544521993908610224544020184112
471,471_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,4,5000,2849,0.001000000000000000020816681712,20,0.459898420131524154896851541707
472,472_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,5,4960,1661,0.001000000000000000020816681712,1,0.479550643227101058840844416409
473,473_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,1,1,735,10,1,0.001000000000000000020816681712
474,474_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,2,1,131,10,1,0.001000000000000000020816681712
475,475_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,2,471,1609,0.001000000000000000020816681712,1,0.512815672247756149104702672048
476,476_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,3,3069,2362,10,1,0.9989999999999999991118215803
477,477_0,COMPLETED,BoTorch,GenerationStep_1,0.75,34,157,15,10,1,0.708495654541757891031750205002
478,478_0,COMPLETED,BoTorch,GenerationStep_1,0.640000000000000013322676295502,4,5000,2556,0.001000000000000000020816681712,1,0.001000000000000000020816681712
479,479_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,4,5000,1913,10,1,0.36967625831732991992240044965
480,480_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,3,5000,4853,10,1,0.9989999999999999991118215803
481,481_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,3,5000,3712,10,1,0.9989999999999999991118215803
482,482_0,COMPLETED,BoTorch,GenerationStep_1,0.660000000000000031086244689504,3,2205,452,0.001000000000000000020816681712,1,0.001000000000000000020816681712
483,483_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,2,1,1407,0.001000000000000000020816681712,1,0.001000000000000000020816681712
484,484_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,8,1,45,0.001000000000000000020816681712,20,0.47325975342876747120612890285
485,485_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,6,5000,1259,0.001000000000000000020816681712,1,0.618848468925940031759580506332
486,486_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,3,5000,3011,0.001000000000000000020816681712,1,0.001000000000000000020816681712
487,487_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,27,5000,4870,10,20,0.001000000000000000020816681712
488,488_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,4,5000,2391,0.001000000000000000020816681712,1,0.9989999999999999991118215803
489,489_0,COMPLETED,BoTorch,GenerationStep_1,0.660000000000000031086244689504,16,1,3528,10,20,0.001000000000000000020816681712
490,490_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,11,5000,4802,10,20,0.9989999999999999991118215803
491,491_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,2,1,4011,0.001000000000000000020816681712,1,0.9989999999999999991118215803
492,492_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,6,3701,993,0.001000000000000000020816681712,20,0.001000000000000000020816681712
493,493_0,COMPLETED,BoTorch,GenerationStep_1,0.75,10,105,35,10,1,0.459702317922291325835715269932
494,494_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,5,4196,1307,0.001000000000000000020816681712,1,0.001000000000000000020816681712
495,495_0,COMPLETED,BoTorch,GenerationStep_1,0.660000000000000031086244689504,3,5000,4798,0.001000000000000000020816681712,1,0.001000000000000000020816681712
496,496_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,7,2120,419,10,20,0.001000000000000000020816681712
497,497_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,3,5000,3913,0.001000000000000000020816681712,1,0.001000000000000000020816681712
498,498_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,12,4552,504,0.001000000000000000020816681712,1,0.671565545696383714435739875626
499,499_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,3,5000,3691,10,20,0.001000000000000000020816681712
500,500_0,COMPLETED,BoTorch,GenerationStep_1,0.660000000000000031086244689504,6,4154,4135,10,20,0.9989999999999999991118215803
501,501_0,COMPLETED,Sobol,SOBOL,0.670000000000000039968028886506,5,2179,1989,6.339154988110066391016061970731,15,0.352086401164531714869099232601
502,502_0,COMPLETED,Sobol,SOBOL,0.670000000000000039968028886506,3,4346,3767,1.599037038854323355963060748763,2,0.508519689962267928962091900758
503,503_0,COMPLETED,Sobol,SOBOL,0.719999999999999973354647408996,25,3144,692,7.999197697264142981055101699894,18,0.869680724795907744706369157939
504,504_0,COMPLETED,Sobol,SOBOL,0.709999999999999964472863211995,4,351,2627,2.751298817995004419856286403956,6,0.028082407308742403373447160675
505,505_0,COMPLETED,Sobol,SOBOL,0.729999999999999982236431605997,23,929,164,0.879464920552447515511573783442,8,0.184992928236722947721304421975
506,506_0,COMPLETED,Sobol,SOBOL,0.709999999999999964472863211995,4,3097,3385,6.126140797570348794920391810592,16,0.964215541193261693742044826649
507,507_0,COMPLETED,Sobol,SOBOL,0.709999999999999964472863211995,6,4395,1543,4.726855416050181446507849614136,5,0.671276746211573516198711786274
508,508_0,COMPLETED,Sobol,SOBOL,0.619999999999999995559107901499,5,1602,4609,9.465750577237457719093072228134,12,0.452470112781971689486226750887
509,509_0,COMPLETED,Sobol,SOBOL,0.689999999999999946709294817992,17,1446,1107,4.252041721758433645561581215588,18,0.585175745114684064951404707244
510,510_0,COMPLETED,Sobol,SOBOL,0.650000000000000022204460492503,5,4903,3081,9.003164298015645883310753561091,9,0.304969444179907456238254326308
511,511_0,COMPLETED,Sobol,SOBOL,0.709999999999999964472863211995,4,2607,2462,0.092191714056767529172908837154,11,0.067339671744033699485321164957
512,512_0,COMPLETED,Sobol,SOBOL,0.670000000000000039968028886506,4,1025,4280,5.351056862986647288948915957008,4,0.785161170955747333977114976733
513,513_0,COMPLETED,Sobol,SOBOL,0.699999999999999955591079014994,3,197,1665,8.473990234022959810999964247458,1,0.877752062806859578714124836551
514,514_0,COMPLETED,Sobol,SOBOL,0.709999999999999964472863211995,3,3654,4691,3.213906850736588438621765817516,14,0.222303412824869150998807754149
515,515_0,COMPLETED,Sobol,SOBOL,0.719999999999999973354647408996,38,3858,383,7.126444798426703641780477482826,8,0.391709993641823517318556469036
516,516_0,COMPLETED,Sobol,SOBOL,0.660000000000000031086244689504,23,2276,3566,2.374103987812996141570920372033,20,0.734294397113844699021001360961
517,517_0,COMPLETED,Sobol,SOBOL,0.680000000000000048849813083507,7,2361,615,9.1234677623445161742665732163,4,0.060721655867993828969986225275
518,518_0,COMPLETED,Sobol,SOBOL,0.709999999999999964472863211995,6,3942,3641,3.873127646467648510508752224268,13,0.840875119226053402421428017988
519,519_0,COMPLETED,Sobol,SOBOL,0.719999999999999973354647408996,10,3587,1755,5.275914785933681017127128143329,9,0.545027724390849455105012566491
520,520_0,COMPLETED,Sobol,SOBOL,0.699999999999999955591079014994,2,130,4937,0.533355534884147330920711738145,16,0.32720900276675818352245528331
521,521_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,586,5000,732,10,20,0.245634936326524389027525785423
522,522_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,48,3204,99,10,1,0.511834643775753383998505796626
523,523_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,90,4703,91,10,1,0.703182209900971022520366204844
524,524_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.75,1140,2400,1,0.001000000000000000020816681712,1,0.87239483130999662119364757018
525,525_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.75,9,19,20,10,1,0.743013895005972369034452640335
526,526_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,2,1,36,0.001000000000000000020816681712,1,0.654063620888167496225662489451
527,527_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.660000000000000031086244689504,47,2164,411,0.001000000000000000020816681712,20,0.9989999999999999991118215803
528,528_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,3,1,51,0.001000000000000000020816681712,1,0.9989999999999999991118215803
529,529_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,69,4856,101,0.001000000000000000020816681712,1,0.212369043718389410857483312611
530,530_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,10,5000,657,0.001000000000000000020816681712,1,0.574242193265003142421676329832
531,531_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,6,17,25,10,1,0.679590873412631801819827614963
532,532_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.75,15,5000,389,0.001000000000000000020816681712,1,0.9989999999999999991118215803
533,533_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,28,2769,109,10,1,0.9989999999999999991118215803
534,534_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.75,1268,353,1,0.001000000000000000020816681712,1,0.9989999999999999991118215803
535,535_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,49,5000,306,10,20,0.922439141435058673756941516331
536,536_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,6,1,13,10,1,0.9989999999999999991118215803
537,537_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,21,1758,267,10,1,0.001000000000000000020816681712
538,538_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,212,4860,42,10,20,0.9989999999999999991118215803
539,539_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.760000000000000008881784197001,2538,888,1,10,1,0.9989999999999999991118215803
540,540_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,60,4876,103,10,1,0.573173764211009517666184365225
541,541_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,24,5000,268,10,1,0.417222937999819243337640273239
542,542_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,54,4431,126,0.001000000000000000020816681712,1,0.9989999999999999991118215803
543,543_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,95,4147,85,10,1,0.001000000000000000020816681712
544,544_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,8,1359,789,10,1,0.001000000000000000020816681712
545,545_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,12,5000,665,10,1,0.001000000000000000020816681712
546,546_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,854,2293,1,10,1,0.9989999999999999991118215803
547,547_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.689999999999999946709294817992,82,1,305,10,20,0.9989999999999999991118215803
548,548_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,2,1,49,0.001000000000000000020816681712,1,0.465272569699275162502516423046
549,549_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,1265,5000,963,10,20,0.9989999999999999991118215803
550,550_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,6,5000,1436,0.001000000000000000020816681712,20,0.001000000000000000020816681712
551,551_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.760000000000000008881784197001,5041,1463,1,10,20,0.79232441330972536164267694403
552,552_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,22,4041,348,0.001000000000000000020816681712,1,0.9989999999999999991118215803
553,553_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.619999999999999995559107901499,5,5000,4908,10,20,0.9989999999999999991118215803
554,554_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,15,3624,398,10,1,0.001000000000000000020816681712
555,555_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,9,5000,842,0.001000000000000000020816681712,1,0.001000000000000000020816681712
556,556_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.810000000000000053290705182008,39,1,1,0.001000000000000000020816681712,1,0.833089458393135862124267987383
557,557_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,13,3115,272,0.001000000000000000020816681712,1,0.001000000000000000020816681712
558,558_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.699999999999999955591079014994,196,1,251,10,20,0.001000000000000000020816681712
559,559_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,13,1,7,10,1,0.655204694743940607715160240332
560,560_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.660000000000000031086244689504,2,1,2366,10,20,0.001000000000000000020816681712
561,561_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,16,2428,124,0.001000000000000000020816681712,1,0.001000000000000000020816681712
562,562_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,90,4686,95,10,1,0.001000000000000000020816681712
563,563_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.689999999999999946709294817992,6,1261,1349,0.001000000000000000020816681712,20,0.477971208118471047043840371771
564,564_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,22,827,148,10,1,0.001000000000000000020816681712
565,565_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.660000000000000031086244689504,2,2168,2974,10,20,0.001000000000000000020816681712
566,566_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,28,2914,112,10,19,0.001000000000000000020816681712
567,567_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,15,753,210,10,1,0.001000000000000000020816681712
568,568_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,48,4660,132,10,11,0.9989999999999999991118215803
569,569_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,11,768,247,0.001000000000000000020816681712,1,0.9989999999999999991118215803
570,570_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.660000000000000031086244689504,4,4159,2330,0.001000000000000000020816681712,1,0.001000000000000000020816681712
571,571_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,12,3891,572,0.001000000000000000020816681712,1,0.609563190669008103661496988934
572,572_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.660000000000000031086244689504,4,633,1462,10,1,0.176956774151419360396886304443
573,573_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,2,2027,601,0.001000000000000000020816681712,20,0.9989999999999999991118215803
574,574_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,38,1962,181,0.001000000000000000020816681712,1,0.001000000000000000020816681712
575,575_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,22,5000,398,10,1,0.483924614518907558746718677867
576,576_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.699999999999999955591079014994,5,2428,470,0.001000000000000000020816681712,1,0.9989999999999999991118215803
577,577_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,24,3006,141,0.001000000000000000020816681712,1,0.001000000000000000020816681712
578,578_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,17,620,131,0.001000000000000000020816681712,1,0.001000000000000000020816681712
579,579_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,542,1,1,10,1,0.434691910990370689038542195703
580,580_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.699999999999999955591079014994,3,5000,4693,0.001000000000000000020816681712,20,0.9989999999999999991118215803
581,581_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,13,2786,206,0.001000000000000000020816681712,1,0.82459947590846516263241028355
582,582_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.680000000000000048849813083507,6,1114,761,0.001000000000000000020816681712,20,0.001000000000000000020816681712
583,583_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,28,3262,145,0.001000000000000000020816681712,20,0.340978332306642428761733754072
584,584_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,249,2411,340,10,20,0.306529417826031269633801912278
585,585_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.689999999999999946709294817992,7,5000,1601,10,1,0.001000000000000000020816681712
586,586_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.699999999999999955591079014994,3,1699,3383,0.001000000000000000020816681712,1,0.9989999999999999991118215803
587,587_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.75,27,2798,88,0.001000000000000000020816681712,1,0.001000000000000000020816681712
588,588_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.650000000000000022204460492503,2,938,4019,0.001000000000000000020816681712,1,0.9989999999999999991118215803
589,589_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.689999999999999946709294817992,6,4397,2124,0.001000000000000000020816681712,20,0.489555788275771841533412498393
590,590_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,29,1658,299,0.001000000000000000020816681712,1,0.814747126481145889087542855123
591,591_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,1874,508,1,0.001000000000000000020816681712,9,0.889151595706708208766144707624
592,592_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,27,1325,167,0.001000000000000000020816681712,1,0.001000000000000000020816681712
593,593_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,9,676,331,0.001000000000000000020816681712,1,0.9989999999999999991118215803
594,594_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,1743,2645,1,0.001000000000000000020816681712,1,0.84160322933948139567661428373
595,595_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,24,2784,100,0.001000000000000000020816681712,1,0.317238452579041707579676767637
596,596_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,54,4629,117,0.001000000000000000020816681712,1,0.801362576583848018607625363074
597,597_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,54,4359,292,10,20,0.9989999999999999991118215803
598,598_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.689999999999999946709294817992,4,2407,749,0.001000000000000000020816681712,1,0.267898607587085668679804939529
599,599_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,27,4247,314,0.001000000000000000020816681712,1,0.9989999999999999991118215803
600,600_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,19,4552,328,0.001000000000000000020816681712,1,0.301035903296336115886333573144
601,601_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,18,4465,381,0.001000000000000000020816681712,1,0.9989999999999999991118215803
602,602_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,81,5000,110,0.001000000000000000020816681712,1,0.9989999999999999991118215803
603,603_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,128,5000,82,10,1,0.001000000000000000020816681712
604,604_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,27,3855,256,0.001000000000000000020816681712,20,0.001000000000000000020816681712
605,605_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,45,3143,96,0.001000000000000000020816681712,20,0.001000000000000000020816681712
606,606_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,65,4498,104,0.001000000000000000020816681712,1,0.001000000000000000020816681712
607,607_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,20,2476,119,10,1,0.306376112390076227320889756811
608,608_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.660000000000000031086244689504,5,5000,4055,0.001000000000000000020816681712,1,0.001000000000000000020816681712
609,609_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,7,3481,1045,10,1,0.9989999999999999991118215803
610,610_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,15,4079,562,10,20,0.555283005892674208503478894272
611,611_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,21,1376,238,10,1,0.778259612273463408094187343522
612,612_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,20,5000,1192,10,20,0.001000000000000000020816681712
613,613_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,22,2977,153,0.001000000000000000020816681712,20,0.9989999999999999991118215803
614,614_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,10,2657,198,10,1,0.9989999999999999991118215803
615,615_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,3,810,2375,0.001000000000000000020816681712,20,0.9989999999999999991118215803
616,616_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,32,1173,160,10,20,0.001000000000000000020816681712
617,617_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,6,5000,1740,10,1,0.9989999999999999991118215803
618,618_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,53,4554,144,0.001000000000000000020816681712,20,0.9989999999999999991118215803
619,619_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,7,4485,1127,0.001000000000000000020816681712,20,0.9989999999999999991118215803
620,620_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,62,4181,112,10,5,0.001000000000000000020816681712
621,621_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.650000000000000022204460492503,3,3753,5000,0.001000000000000000020816681712,20,0.001000000000000000020816681712
622,622_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.699999999999999955591079014994,13,3905,1238,10,20,0.001000000000000000020816681712
623,623_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,5,1768,1791,10,20,0.9989999999999999991118215803
624,624_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,7,157,159,0.001000000000000000020816681712,20,0.001000000000000000020816681712
625,625_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,11,4040,562,10,1,0.9989999999999999991118215803
626,626_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,24,1252,206,10,1,0.001000000000000000020816681712
627,627_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,21,3646,251,10,1,0.9989999999999999991118215803
628,628_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,11,3131,578,10,20,0.898966143345196089242676862341
629,629_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.689999999999999946709294817992,10,3461,824,0.001000000000000000020816681712,1,0.001000000000000000020816681712
630,630_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,29,2850,119,10,1,0.001000000000000000020816681712
631,631_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,27,4209,302,10,1,0.001000000000000000020816681712
632,632_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.650000000000000022204460492503,3,2735,1835,10,20,0.9989999999999999991118215803
633,633_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,21,587,97,0.001000000000000000020816681712,1,0.001000000000000000020816681712
634,634_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.650000000000000022204460492503,3,3227,2737,0.001000000000000000020816681712,20,0.001000000000000000020816681712
635,635_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.699999999999999955591079014994,4,5000,2749,10,1,0.399549027042126081443740304167
636,636_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,4,5000,2811,0.001000000000000000020816681712,1,0.9989999999999999991118215803
637,637_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,28,1953,256,10,1,0.9989999999999999991118215803
638,638_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,23,4601,447,0.001000000000000000020816681712,6,0.001000000000000000020816681712
639,639_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,26,2724,94,0.001000000000000000020816681712,20,0.001000000000000000020816681712
640,640_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.660000000000000031086244689504,4,1100,2397,10,1,0.9989999999999999991118215803
641,641_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,65,4710,123,10,1,0.9989999999999999991118215803
642,642_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.660000000000000031086244689504,3,2003,193,10,1,0.066506047225541042866581165072
643,643_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,15,4133,444,10,1,0.9989999999999999991118215803
644,644_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,25,3993,324,0.001000000000000000020816681712,20,0.9989999999999999991118215803
645,645_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,14,3466,359,10,1,0.9989999999999999991118215803
646,646_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,65,4936,95,0.001000000000000000020816681712,1,0.740938988071501491994297339261
647,647_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,33,2991,100,10,20,0.708250873695595473122921248432
648,648_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,98,4963,99,0.001000000000000000020816681712,1,0.535274927770195918519391398149
649,649_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,30,4195,252,0.001000000000000000020816681712,1,0.001000000000000000020816681712
650,650_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,65,4739,119,10,20,0.718101548461065108952539048914
651,651_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,44,2969,82,0.001000000000000000020816681712,1,0.9989999999999999991118215803
652,652_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,2356,2637,1,0.001000000000000000020816681712,20,0.837597901368810404676423786441
653,653_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,1864,2642,1,10,1,0.9989999999999999991118215803
654,654_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,14,4719,461,10,1,0.9989999999999999991118215803
655,655_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,81,4750,95,10,1,0.332820391595666120743146620953
656,656_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,5,2301,327,10,1,0.702284497640657590089574568992
657,657_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,58,4827,120,0.001000000000000000020816681712,1,0.9989999999999999991118215803
658,658_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,11,4433,574,10,1,0.379181975211485000620825758233
659,659_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,19,3748,280,0.001000000000000000020816681712,1,0.541517016357464964215751024312
660,660_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,26,3814,275,10,1,0.001000000000000000020816681712
661,661_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,16,1026,275,0.001000000000000000020816681712,1,0.001000000000000000020816681712
662,662_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,78,4700,91,0.001000000000000000020816681712,20,0.001000000000000000020816681712
663,663_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,12,4354,573,0.001000000000000000020816681712,20,0.9989999999999999991118215803
664,664_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,13,5000,463,10,1,0.497019975702735095079987104327
665,665_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,23,4552,273,0.001000000000000000020816681712,20,0.768544828625439824243414932425
666,666_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,49,4630,130,10,20,0.9989999999999999991118215803
667,667_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,47,4306,127,0.001000000000000000020816681712,1,0.312113596243715984979161248702
668,668_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,33,3269,128,0.001000000000000000020816681712,20,0.001000000000000000020816681712
669,669_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,14,4569,408,10,1,0.001000000000000000020816681712
670,670_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,14,4584,415,0.001000000000000000020816681712,1,0.300457206894607808944641647031
671,671_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,28,2922,103,10,1,0.598808355859835828027826210018
672,672_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,25,1966,244,0.001000000000000000020816681712,20,0.9989999999999999991118215803
673,673_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,24,3530,274,0.001000000000000000020816681712,20,0.9989999999999999991118215803
674,674_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,14,509,182,0.001000000000000000020816681712,1,0.001000000000000000020816681712
675,675_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,10,4571,743,10,1,0.9989999999999999991118215803
676,676_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,1219,4491,679,10,20,0.9989999999999999991118215803
677,677_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,8,2651,296,10,1,0.9989999999999999991118215803
678,678_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.699999999999999955591079014994,11,3964,760,0.001000000000000000020816681712,20,0.9989999999999999991118215803
679,679_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.680000000000000048849813083507,2,1176,5000,10,1,0.9989999999999999991118215803
680,680_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,46,3835,151,10,1,0.9989999999999999991118215803
681,681_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,36,3040,105,0.001000000000000000020816681712,1,0.63331442458999631650584660747
682,682_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,36,4021,187,0.001000000000000000020816681712,20,0.9989999999999999991118215803
683,683_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,32,2982,129,10,20,0.558450464044279781816726426769
684,684_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,40,3148,92,10,20,0.001000000000000000020816681712
685,685_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,321,1,340,10,20,0.001000000000000000020816681712
686,686_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,35,3174,189,0.001000000000000000020816681712,20,0.9989999999999999991118215803
687,687_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,41,1920,212,0.001000000000000000020816681712,20,0.001000000000000000020816681712
688,688_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,25,4417,515,10,20,0.9989999999999999991118215803
689,689_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.699999999999999955591079014994,13,3627,665,0.001000000000000000020816681712,20,0.001000000000000000020816681712
690,690_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,6,4013,1073,10,1,0.181381220827376454796109328527
691,691_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.670000000000000039968028886506,4,5000,2730,0.001000000000000000020816681712,1,0.9989999999999999991118215803
692,692_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,15,4393,495,0.001000000000000000020816681712,1,0.001000000000000000020816681712
693,693_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,234,4429,813,10,20,0.001000000000000000020816681712
694,694_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.699999999999999955591079014994,6,4870,1329,10,1,0.298351141975666256378474372468
695,695_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,10,4495,640,0.001000000000000000020816681712,20,0.401580952597170415252492148284
696,696_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,72,4983,100,10,1,0.448722694738025285055016411206
697,697_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,19,4133,364,10,1,0.001000000000000000020816681712
698,698_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.660000000000000031086244689504,2,2078,1467,0.001000000000000000020816681712,1,0.001000000000000000020816681712
699,699_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,15,4410,590,0.001000000000000000020816681712,1,0.870171527359448915284190206876
700,700_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,8,3348,597,0.001000000000000000020816681712,1,0.9989999999999999991118215803
701,701_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,52,3701,118,10,20,0.001000000000000000020816681712
702,702_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,32,2806,83,10,1,0.001000000000000000020816681712
703,703_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,16,2646,178,10,19,0.001000000000000000020816681712
704,704_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.75,2267,2636,1,4.921976815304446972731966525316,7,0.9989999999999999991118215803
705,705_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,61,4467,105,10,20,0.001000000000000000020816681712
706,706_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,19,4371,328,0.001000000000000000020816681712,20,0.344346372391821253788890544456
707,707_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.680000000000000048849813083507,3,2639,1019,0.001000000000000000020816681712,1,0.001000000000000000020816681712
708,708_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,40,4021,155,10,1,0.512448908516001222501756728889
709,709_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,124,4625,342,0.001000000000000000020816681712,20,0.001000000000000000020816681712
710,710_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,19,4122,341,0.001000000000000000020816681712,20,0.001000000000000000020816681712
711,711_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,22,3430,476,10,15,0.571862652029844542589387401677
712,712_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,16,2912,200,10,1,0.299831029075891930535391338708
713,713_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,12,2970,245,0.001000000000000000020816681712,1,0.9989999999999999991118215803
714,714_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,17,3468,342,0.001000000000000000020816681712,1,0.583546579005764454173288413585
715,715_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.699999999999999955591079014994,3,2900,1236,10,1,0.001000000000000000020816681712
716,716_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.660000000000000031086244689504,4,591,1217,0.001000000000000000020816681712,20,0.9989999999999999991118215803
717,717_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,28,3081,138,10,20,0.9989999999999999991118215803
718,718_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.680000000000000048849813083507,7,4452,1168,0.001000000000000000020816681712,20,0.001000000000000000020816681712
719,719_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,19,4174,330,10,1,0.60111839789288656898946783258
720,720_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,11,756,254,0.001000000000000000020816681712,1,0.646657403882320069854472421866
721,721_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,13,4857,548,10,1,0.433787173300875905646023511508
722,722_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,11,4256,686,0.001000000000000000020816681712,1,0.322861775014304908104634250776
723,723_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,87,5000,94,10,1,0.9989999999999999991118215803
724,724_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,38,3045,100,0.001000000000000000020816681712,20,0.313685111955037676523261325201
725,725_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,13,5000,499,10,1,0.001000000000000000020816681712
726,726_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,30,2938,111,10,20,0.203936735715402300828102966079
727,727_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,28,3112,122,10,1,0.24452129227070557027090558222
728,728_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,9,2392,155,0.001000000000000000020816681712,1,0.001000000000000000020816681712
729,729_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.680000000000000048849813083507,4,5000,2940,0.001000000000000000020816681712,1,0.9989999999999999991118215803
730,730_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.660000000000000031086244689504,2,1,1581,10,1,0.001000000000000000020816681712
731,731_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,89,4747,85,0.001000000000000000020816681712,1,0.001000000000000000020816681712
732,732_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,75,4518,111,10,1,0.554330860559730909109532603907
733,733_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,37,3721,143,10,20,0.373391704001361346421106190974
734,734_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,15,5000,399,0.001000000000000000020816681712,1,0.704850887822567662155393009016
735,735_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.680000000000000048849813083507,4,1,2523,10,20,0.001000000000000000020816681712
736,736_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,35,3633,217,10,20,0.9989999999999999991118215803
737,737_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,32,1300,142,0.001000000000000000020816681712,1,0.001000000000000000020816681712
738,738_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,22,789,121,10,20,0.001000000000000000020816681712
739,739_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,25,3394,175,10,1,0.9989999999999999991118215803
740,740_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,87,5000,84,0.001000000000000000020816681712,20,0.001000000000000000020816681712
741,741_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,13,5000,562,10,1,0.699408648939845778436108503229
742,742_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.699999999999999955591079014994,9,4904,844,10,1,0.518198819678064914739934465615
743,743_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,44,3221,92,0.001000000000000000020816681712,1,0.416289831274359201085388804131
744,744_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,14,4311,455,0.001000000000000000020816681712,1,0.001000000000000000020816681712
745,745_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,42,3819,146,0.001000000000000000020816681712,20,0.760232300414082518003056065936
746,746_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,142,2619,237,0.001000000000000000020816681712,20,0.871299359665128614338414081431
747,747_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,38,3733,145,10,20,0.001000000000000000020816681712
748,748_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,61,2956,230,10,20,0.9989999999999999991118215803
749,749_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,83,4378,114,0.001000000000000000020816681712,20,0.001000000000000000020816681712
750,750_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,19,1178,253,0.001000000000000000020816681712,20,0.9989999999999999991118215803
751,751_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,55,1764,131,10,1,0.001000000000000000020816681712
752,752_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,50,3150,74,10,1,0.001000000000000000020816681712
753,753_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,34,3503,129,10,1,0.001000000000000000020816681712
754,754_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,28,3369,153,0.001000000000000000020816681712,1,0.9989999999999999991118215803
755,755_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,46,4409,129,10,1,0.9989999999999999991118215803
756,756_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,49,4182,129,0.001000000000000000020816681712,1,0.001000000000000000020816681712
757,757_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,30,1216,181,0.001000000000000000020816681712,16,0.001000000000000000020816681712
758,758_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,15,4000,404,10,1,0.80381453551418768910252765636
759,759_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,5,1,24,10,1,0.9989999999999999991118215803
760,760_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.689999999999999946709294817992,5,5000,1274,10,1,0.001000000000000000020816681712
761,761_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,42,1851,193,0.001000000000000000020816681712,1,0.501014092058657434236579319986
762,762_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,12,2421,115,10,1,0.001000000000000000020816681712
763,763_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,54,4916,116,0.001000000000000000020816681712,9,0.9989999999999999991118215803
764,764_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,80,4560,112,10,20,0.430548858944595602693539149186
765,765_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.630000000000000004440892098501,3,3544,3336,10,1,0.9989999999999999991118215803
766,766_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,60,4803,109,0.001000000000000000020816681712,1,0.721383144694819233855298534763
767,767_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,15,4322,512,0.001000000000000000020816681712,20,0.484864940369024721711355141451
768,768_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,10,2500,180,10,1,0.001000000000000000020816681712
769,769_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,23,5000,282,10,1,0.9989999999999999991118215803
770,770_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.680000000000000048849813083507,2,2085,1730,10,1,0.9989999999999999991118215803
771,771_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,63,5000,102,0.001000000000000000020816681712,8,0.6689841333411876700409948171
772,772_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,69,4951,94,10,10,0.001000000000000000020816681712
773,773_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,28,5000,365,10,1,0.202313529667489194752150183376
774,774_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,74,4844,86,10,20,0.405525821871942471208427605234
775,775_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,27,4337,242,0.001000000000000000020816681712,1,0.9989999999999999991118215803
776,776_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,25,4642,379,0.001000000000000000020816681712,1,0.650655401607157068966102997365
777,777_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.699999999999999955591079014994,127,241,270,10,20,0.244930271577782687764113234152
778,778_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,39,3157,106,0.001000000000000000020816681712,20,0.9989999999999999991118215803
779,779_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,4,1,15,10,1,0.9989999999999999991118215803
780,780_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,23,4445,1393,10,20,0.628040210117312369675346417353
781,781_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,17,1255,256,10,1,0.9989999999999999991118215803
782,782_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.609999999999999986677323704498,2,1,1445,0.001000000000000000020816681712,20,0.001000000000000000020816681712
783,783_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,50,4525,132,10,20,0.703990613204510840006378202816
784,784_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,141,2754,24,10,1,0.9989999999999999991118215803
785,785_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,75,2789,38,10,1,0.9989999999999999991118215803
786,786_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,173,2700,13,10,1,0.9989999999999999991118215803
787,787_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,49,2825,51,10,1,0.9989999999999999991118215803
788,788_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.760000000000000008881784197001,3201,2999,1,0.001000000000000000020816681712,1,0.9989999999999999991118215803
789,789_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,100,2746,28,0.001000000000000000020816681712,1,0.9989999999999999991118215803
790,790_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,53,2829,80,10,1,0.9989999999999999991118215803
791,791_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.75,3534,3082,1,10,20,0.9989999999999999991118215803
792,792_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,173,5000,64,10,1,0.9989999999999999991118215803
793,793_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,299,2839,27,0.001000000000000000020816681712,20,0.9989999999999999991118215803
794,794_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,639,2761,1,10,1,0.001000000000000000020816681712
795,795_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.699999999999999955591079014994,10,5000,4734,10,20,0.001000000000000000020816681712
796,796_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,107,5000,78,10,20,0.9989999999999999991118215803
797,797_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,35,2875,96,10,1,0.9989999999999999991118215803
798,798_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.760000000000000008881784197001,4456,3390,1,10,20,0.9989999999999999991118215803
799,799_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,131,5000,62,10,20,0.9989999999999999991118215803
800,800_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,293,5000,36,0.001000000000000000020816681712,20,0.9989999999999999991118215803
801,801_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,173,5000,65,0.001000000000000000020816681712,20,0.9989999999999999991118215803
802,802_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,48,2883,69,10,20,0.9989999999999999991118215803
803,803_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,331,2663,7,10,1,0.9989999999999999991118215803
804,804_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,3,431,3941,0.001000000000000000020816681712,1,0.001000000000000000020816681712
805,805_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,91,2800,47,0.001000000000000000020816681712,1,0.9989999999999999991118215803
806,806_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,583,200,1,10,1,0.9989999999999999991118215803
807,807_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.689999999999999946709294817992,17,3942,1640,10,20,0.324149023957811810436879795816
808,808_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.689999999999999946709294817992,2,1,3929,0.001000000000000000020816681712,1,0.001000000000000000020816681712
809,809_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,86,2892,38,10,20,0.9989999999999999991118215803
810,810_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.810000000000000053290705182008,131,1,1,10,7,0.845880908435667766553933688556
811,811_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,60,5000,109,0.001000000000000000020816681712,20,0.956603391153051263451345676003
812,812_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,4,3736,4773,10,1,0.9989999999999999991118215803
813,813_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,4,4109,2856,0.001000000000000000020816681712,1,0.001000000000000000020816681712
814,814_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,57,2780,68,10,1,0.9989999999999999991118215803
815,815_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.670000000000000039968028886506,3,2631,4671,0.001000000000000000020816681712,20,0.9989999999999999991118215803
816,816_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.670000000000000039968028886506,2,2524,3315,0.001000000000000000020816681712,20,0.489114074826769995585351580303
817,817_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,624,2657,5,10,20,0.9989999999999999991118215803
818,818_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,6,5000,1405,0.001000000000000000020816681712,20,0.598335188031162812372087955737
819,819_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,78,1909,96,10,20,0.9989999999999999991118215803
820,820_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.75,1700,5000,4,10,20,0.9989999999999999991118215803
821,821_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,19,403,86,10,10,0.001000000000000000020816681712
822,822_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,15,2512,110,0.001000000000000000020816681712,10,0.001000000000000000020816681712
823,823_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,117,5000,556,10,10,0.001000000000000000020816681712
824,824_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,6,5000,1355,10,11,0.9989999999999999991118215803
825,825_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.689999999999999946709294817992,5,5000,1725,0.001000000000000000020816681712,10,0.001000000000000000020816681712
826,826_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,4,1,75,0.001000000000000000020816681712,11,0.001000000000000000020816681712
827,827_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.689999999999999946709294817992,5,5000,2007,10,20,0.001000000000000000020816681712
828,828_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.699999999999999955591079014994,8,5000,1161,0.001000000000000000020816681712,11,0.9989999999999999991118215803
829,829_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,8,5000,930,0.001000000000000000020816681712,1,0.9989999999999999991118215803
830,830_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.660000000000000031086244689504,3,2338,3952,10,10,0.001000000000000000020816681712
831,831_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,4,5000,2892,0.001000000000000000020816681712,10,0.001000000000000000020816681712
832,832_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,4,1,82,0.001000000000000000020816681712,12,0.9989999999999999991118215803
833,833_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,11,4987,1224,10,11,0.366253154210592180017869168296
834,834_0,RUNNING,BoTorch,BOTORCH_MODULAR,,,3772,1,10,1,0.9989999999999999991118215803
835,835_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,2,1,3181,0.001000000000000000020816681712,20,0.001000000000000000020816681712
836,836_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.689999999999999946709294817992,2,1,1005,10,1,0.9989999999999999991118215803
837,837_0,RUNNING,BoTorch,BOTORCH_MODULAR,,,5000,57,0.001000000000000000020816681712,1,0.9989999999999999991118215803

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start_time,end_time,run_time,program_string,recent_samples_size,n_samples,const,max_depth,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
1745405659,1745405679,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2179 n_samples 1989 const 6.339154988110066 max_depth 15 threshold 0.3520864011645317,2179,1989,6.339154988110066,15,0.3520864011645317,0.67,5,0,None,i7185,5,482.40625,482.21484375,-1,0.5030938308090137,4621074
1745405661,1745405681,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4346 n_samples 3767 const 1.5990370388543234 max_depth 2 threshold 0.5085196899622679,4346,3767,1.5990370388543234,2,0.5085196899622679,0.67,3,0,None,i7185,3,483.09375,482.91796875,-1,0.5017085334318434,4621089
1745405705,1745405751,46,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3144 n_samples 692 const 7.999197697264143 max_depth 18 threshold 0.8696807247959077,3144,692,7.999197697264143,18,0.8696807247959077,0.72,25,0,None,i7185,25,483.40625,483.29921875,-1,0.990579977835242,4621115
1745405725,1745405751,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 351 n_samples 2627 const 2.7512988179950044 max_depth 6 threshold 0.028082407308742403,351,2627,2.7512988179950044,6,0.028082407308742403,0.71,4,0,None,i7185,4,482.3359375,482.15625,-1,0.06483191725157,4621140
1745405766,1745405786,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3097 n_samples 3385 const 6.126140797570349 max_depth 16 threshold 0.9642155411932617,3097,3385,6.126140797570349,16,0.9642155411932617,0.71,4,0,None,i7184,4,471.29296875,471.1015625,-1,0.4290265977096417,4621196
1745405748,1745405800,52,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 929 n_samples 164 const 0.8794649205524475 max_depth 8 threshold 0.18499292823672295,929,164,0.8794649205524475,8,0.18499292823672295,0.73,23,0,None,i7184,23,482.83203125,477.80546875,-1,0.9996305873660879,4621166
1745405835,1745405861,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1602 n_samples 4609 const 9.465750577237458 max_depth 12 threshold 0.4524701127819717,1602,4609,9.465750577237458,12,0.4524701127819717,0.62,5,0,None,i7184,5,484.26953125,483.8763020833333,-1,0.14794975988178796,4621270
1745405843,1745405869,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4903 n_samples 3081 const 9.003164298015646 max_depth 9 threshold 0.30496944417990746,4903,3081,9.003164298015646,9,0.30496944417990746,0.65,5,0,None,i7182,5,482.93359375,482.4661458333333,-1,0.7924131880310307,4621343
1745405835,1745405873,38,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4395 n_samples 1543 const 4.7268554160501814 max_depth 5 threshold 0.6712767462115735,4395,1543,4.7268554160501814,5,0.6712767462115735,0.71,6,0,None,i7183,6,484.41015625,484.2526041666667,-1,0.9975064647210935,4621227
1745405836,1745405876,40,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1446 n_samples 1107 const 4.252041721758434 max_depth 18 threshold 0.5851757451146841,1446,1107,4.252041721758434,18,0.5851757451146841,0.69,17,0,None,i7184,17,482.046875,481.986328125,-1,0.63432766900628,4621299
1745405879,1745405899,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1025 n_samples 4280 const 5.351056862986647 max_depth 4 threshold 0.7851611709557473,1025,4280,5.351056862986647,4,0.7851611709557473,0.67,4,0,None,i7184,4,483.01953125,482.8229166666667,-1,0.11832748429996306,4621427
1745405907,1745405946,39,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2607 n_samples 2462 const 0.09219171405676753 max_depth 11 threshold 0.0673396717440337,2607,2462,0.09219171405676753,11,0.0673396717440337,0.71,4,0,None,i7185,4,483.1015625,482.91015625,-1,0.481529368304396,4621390
1745405933,1745405952,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 197 n_samples 1665 const 8.47399023402296 max_depth 1 threshold 0.8777520628068596,197,1665,8.47399023402296,1,0.8777520628068596,0.7,3,0,None,i7184,3,483.65234375,483.4088541666667,-1,0.05912910971555227,4621466
1745405974,1745405994,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3654 n_samples 4691 const 3.2139068507365884 max_depth 14 threshold 0.22230341282486915,3654,4691,3.2139068507365884,14,0.22230341282486915,0.71,3,0,None,i7182,3,482.79296875,482.6341145833333,-1,0.3374584410786849,4621513
1745406028,1745406080,52,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3858 n_samples 383 const 7.126444798426704 max_depth 8 threshold 0.3917099936418235,3858,383,7.126444798426704,8,0.3917099936418235,0.72,38,0,None,i7182,38,488.85546875,484.4752604166667,-1,0.990903213889915,4621558
1745406087,1745406126,39,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2276 n_samples 3566 const 2.374103987812996 max_depth 20 threshold 0.7342943971138447,2276,3566,2.374103987812996,20,0.7342943971138447,0.66,23,0,None,i7182,23,485.07421875,484.18671875,-1,0.3152936830439601,4621605
1745406169,1745406220,51,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3587 n_samples 1755 const 5.275914785933681 max_depth 9 threshold 0.5450277243908495,3587,1755,5.275914785933681,9,0.5450277243908495,0.72,10,0,None,i7180,10,482.90625,481.6575520833333,-1,0.9724787587735501,4621783
1745406204,1745406267,63,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 130 n_samples 4937 const 0.5333555348841473 max_depth 16 threshold 0.3272090027667582,130,4937,0.5333555348841473,16,0.3272090027667582,0.7,2,0,None,i7179,2,482.34765625,482.1341145833333,-1,0.012005910602142593,4621836
1745406674,1745406848,174,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3942 n_samples 3641 const 3.8731276464676485 max_depth 13 threshold 0.8408751192260534,3942,3641,3.8731276464676485,13,0.8408751192260534,0.71,6,0,None,i7181,6,483.23046875,482.8424479166667,-1,0.4550701884004433,4621721
1745406674,1745406848,174,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2361 n_samples 615 const 9.123467762344516 max_depth 4 threshold 0.06072165586799383,2361,615,9.123467762344516,4,0.06072165586799383,0.68,7,0,None,i7181,7,483.3515625,482.9466145833333,-1,0.9939508681196897,4621669
1745407816,1745407888,72,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3204 n_samples 99 const 10 max_depth 1 threshold 0.5118346437757534,3204,99,10,1,0.5118346437757534,0.73,48,0,None,i7174,48,502.97265625,490.55301339285717,-1,0.9965829331363133,4623895
1745407558,1745408204,646,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 732 const 10 max_depth 20 threshold 0.2456349363265244,5000,732,10,20,0.2456349363265244,0.71,586,0,None,i7172,586,483.2421875,425.3040471311475,-1,0.9814601034355375,4623460
1745408173,1745408277,104,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4703 n_samples 91 const 10 max_depth 1 threshold 0.703182209900971,4703,91,10,1,0.703182209900971,0.74,90,0,None,i7173,90,529.81640625,499.22265625,-1,0.9958902844477281,4624269
1745409049,1745409069,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 19 n_samples 20 const 10 max_depth 1 threshold 0.7430138950059724,19,20,10,1,0.7430138950059724,0.75,9,0,None,i7185,9,482.328125,482.13671875,-1,0.4746490579977835,4625047
1745409435,1745409454,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1 n_samples 36 const 0.001 max_depth 1 threshold 0.6540636208881675,1,36,0.001,1,0.6540636208881675,0.72,2,0,None,i7177,2,483.03515625,482.86328125,-1,0.013876062061322497,4625440
1745408613,1745409789,1176,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2400 n_samples 1 const 0.001 max_depth 1 threshold 0.8723948313099966,2400,1,0.001,1,0.8723948313099966,0.75,1140,0,None,i7178,1140,591.421875,539.8322332974138,-1,1,4624625
1745409977,1745410041,64,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2164 n_samples 411 const 0.001 max_depth 20 threshold 0.999,2164,411,0.001,20,0.999,0.66,47,0,None,i7175,47,482.92578125,482.8515625,-1,0.9871167343923162,4625892
1745410527,1745410559,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1 n_samples 51 const 0.001 max_depth 1 threshold 0.999,1,51,0.001,1,0.999,0.73,3,0,None,i7172,3,481.5859375,481.4088541666667,-1,0.009789434798670114,4626315
1745410890,1745410974,84,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4856 n_samples 101 const 0.001 max_depth 1 threshold 0.2123690437183894,4856,101,0.001,1,0.2123690437183894,0.72,69,0,None,i7185,69,523.99609375,496.78472222222223,-1,0.9980605836719616,4626643
1745411315,1745411341,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 657 const 0.001 max_depth 1 threshold 0.5742421932650031,5000,657,0.001,1,0.5742421932650031,0.72,10,0,None,i7177,10,483.28515625,482.7643229166667,-1,0.9708164019209456,4627005
1745411733,1745411758,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 17 n_samples 25 const 10 max_depth 1 threshold 0.6795908734126318,17,25,10,1,0.6795908734126318,0.73,6,0,None,i7177,6,482.84375,482.6106770833333,-1,0.33990579977835245,4627364
1745412151,1745412183,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 389 const 0.001 max_depth 1 threshold 0.999,5000,389,0.001,1,0.999,0.75,15,0,None,i7177,15,488.71484375,484.1650390625,-1,0.9879479128186184,4627744
1745412654,1745412699,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2769 n_samples 109 const 10 max_depth 1 threshold 0.999,2769,109,10,1,0.999,0.73,28,0,None,i7182,28,493.8828125,486.9546875,-1,0.9965829331363133,4628160
1745413695,1745413768,73,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 306 const 10 max_depth 20 threshold 0.9224391414350587,5000,306,10,20,0.9224391414350587,0.73,49,0,None,i7186,49,493.8515625,486.3125,-1,0.9891023272995937,4629185
1745414229,1745414256,27,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1 n_samples 13 const 10 max_depth 1 threshold 0.999,1,13,10,1,0.999,0.73,6,0,None,i7182,6,482.69921875,482.52734375,-1,0.038442002216475805,4629834
1745413151,1745414433,1282,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 353 n_samples 1 const 0.001 max_depth 1 threshold 0.999,353,1,0.001,1,0.999,0.75,1268,0,None,i7186,1268,596.29296875,539.0713117732558,-1,1,4628607
1745414813,1745414852,39,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1758 n_samples 267 const 10 max_depth 1 threshold 0.001,1758,267,10,1,0.001,0.73,21,0,None,i7175,21,494.8359375,488.2328125,-1,0.9992149981529368,4630584
1745415174,1745415402,228,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4860 n_samples 42 const 10 max_depth 20 threshold 0.999,4860,42,10,20,0.999,0.73,212,0,None,i7173,212,562.35546875,517.3544921875,-1,0.9987994089397857,4631151
1745416071,1745416147,76,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4876 n_samples 103 const 10 max_depth 1 threshold 0.5731737642110095,4876,103,10,1,0.5731737642110095,0.74,60,0,None,i7169,60,517.2578125,490.79248046875,-1,0.9987994089397857,4632077
1745415706,1745418261,2555,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 888 n_samples 1 const 10 max_depth 1 threshold 0.999,888,1,10,1,0.999,0.76,2538,0,None,i7167,2538,557.54296875,518.8934936523438,-1,1,4631664
1745418713,1745418751,38,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 268 const 10 max_depth 1 threshold 0.41722293799981924,5000,268,10,1,0.41722293799981924,0.72,24,0,None,i7180,24,496.0078125,488.00703125,-1,0.9900258588843739,4634698
1745419213,1745419284,71,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4431 n_samples 126 const 0.001 max_depth 1 threshold 0.999,4431,126,0.001,1,0.999,0.73,54,0,None,i7180,54,516.14453125,494.646484375,-1,0.9949205762837089,4635599
1745419613,1745419723,110,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4147 n_samples 85 const 10 max_depth 1 threshold 0.001,4147,85,10,1,0.001,0.73,95,0,None,i7180,95,531.3984375,501.4521484375,-1,0.9969523457702253,4635927
1745420012,1745420031,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1359 n_samples 789 const 10 max_depth 1 threshold 0.001,1359,789,10,1,0.001,0.72,8,0,None,i7180,8,482.46875,482.3111979166667,-1,0.8471786110084965,4636242
1745420588,1745420614,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 665 const 10 max_depth 1 threshold 0.001,5000,665,10,1,0.001,0.71,12,0,None,i7185,12,484.44921875,484.1962890625,-1,0.983907462135205,4637086
1745422113,1745422291,178,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1 n_samples 305 const 10 max_depth 20 threshold 0.999,1,305,10,20,0.999,0.69,82,0,None,i7182,82,489.16796875,451.4353693181818,-1,0.001616180273365349,4637673
1745422407,1745422561,154,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1 n_samples 49 const 0.001 max_depth 1 threshold 0.46527256969927516,1,49,0.001,1,0.46527256969927516,0.72,2,0,None,i7178,2,483.1796875,483.0833333333333,-1,0.010181935722201699,4637940
1745421777,1745422744,967,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2293 n_samples 1 const 10 max_depth 1 threshold 0.999,2293,1,10,1,0.999,0.74,854,0,None,i7186,854,589.95703125,536.4295987215909,-1,1,4637395
1745422905,1745422924,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 1436 const 0.001 max_depth 20 threshold 0.001,5000,1436,0.001,20,0.001,0.71,6,0,None,i7180,6,484.04296875,483.8463541666667,-1,0.9946435168082749,4639626
1745422442,1745423727,1285,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 963 const 10 max_depth 20 threshold 0.999,5000,963,10,20,0.999,0.71,1265,0,None,i7182,1265,482.46875,480.4722020348837,-1,0.9803056889545623,4638722
1745424205,1745424352,147,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4041 n_samples 348 const 0.001 max_depth 1 threshold 0.999,4041,348,0.001,1,0.999,0.73,22,0,None,i7173,22,477.11328125,464.6703125,-1,0.9963058736608792,4641031
1745424586,1745424624,38,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 4908 const 10 max_depth 20 threshold 0.999,5000,4908,10,20,0.999,0.62,5,0,None,i7174,5,482.85546875,482.5013020833333,-1,0.46176579239009974,4641782
1745424670,1745424696,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3624 n_samples 398 const 10 max_depth 1 threshold 0.001,3624,398,10,1,0.001,0.73,15,0,None,i7178,15,488.15234375,485.1748046875,-1,0.9924270410048024,4642039
1745425248,1745425275,27,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 842 const 0.001 max_depth 1 threshold 0.001,5000,842,0.001,1,0.001,0.71,9,0,None,i7182,9,483,482.8020833333333,-1,0.97201699298116,4642489
1745425859,1745425912,53,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1 n_samples 1 const 0.001 max_depth 1 threshold 0.8330894583931359,1,1,0.001,1,0.8330894583931359,0.81,39,0,None,i7182,39,483.74609375,483.6692708333333,-1,0.5,4642992
1745426407,1745426432,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3115 n_samples 272 const 0.001 max_depth 1 threshold 0.001,3115,272,0.001,1,0.001,0.73,13,0,None,i7174,13,487.22265625,484.8369140625,-1,0.9922423346878463,4643450
1745427061,1745427268,207,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1 n_samples 251 const 10 max_depth 20 threshold 0.001,1,251,10,20,0.001,0.7,196,0,None,i7175,196,483.32421875,483.3011363636364,-1,0.001985592907277429,4643973
1745427843,1745427863,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1 n_samples 7 const 10 max_depth 1 threshold 0.6552046947439406,1,7,10,1,0.6552046947439406,0.74,13,0,None,i7183,13,482.875,482.7548828125,-1,0.07141207979312893,4644567
1745423419,1745428486,5067,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1463 n_samples 1 const 10 max_depth 20 threshold 0.7923244133097254,1463,1,10,20,0.7923244133097254,0.76,5041,0,None,i7176,5041,579.04296875,538.1672816823123,-1,1,4640116
1745428525,1745428538,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1 n_samples 2366 const 10 max_depth 20 threshold 0.001,1,2366,10,20,0.001,0.66,2,0,None,i7185,2,483.19140625,483.015625,-1,0.0002077946065755449,4645091
1745429165,1745429191,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2428 n_samples 124 const 0.001 max_depth 1 threshold 0.001,2428,124,0.001,1,0.001,0.74,16,0,None,i7185,16,485.6796875,484.060546875,-1,0.9963058736608792,4645604
1745429668,1745429773,105,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4686 n_samples 95 const 10 max_depth 1 threshold 0.001,4686,95,10,1,0.001,0.74,90,0,None,i7185,90,527.90625,498.5074573863636,-1,0.9957979312892501,4646061
1745430272,1745430292,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1261 n_samples 1349 const 0.001 max_depth 20 threshold 0.47797120811847105,1261,1349,0.001,20,0.47797120811847105,0.69,6,0,None,i7182,6,484.60546875,484.4309895833333,-1,0.4658293313631326,4646597
1745430730,1745430769,39,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 827 n_samples 148 const 10 max_depth 1 threshold 0.001,827,148,10,1,0.001,0.74,22,0,None,i7180,22,490.19140625,485.7578125,-1,0.9977835241965275,4647058
1745431224,1745431237,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2168 n_samples 2974 const 10 max_depth 20 threshold 0.001,2168,2974,10,20,0.001,0.66,2,0,None,i7178,2,482.53125,482.359375,-1,0.35038788326560766,4647515
1745431688,1745431758,70,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2914 n_samples 112 const 10 max_depth 19 threshold 0.001,2914,112,10,19,0.001,0.73,28,0,None,i7174,28,484.98828125,480.48203125,-1,0.9981529368304396,4648000
1745432359,1745432473,114,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 753 n_samples 210 const 10 max_depth 1 threshold 0.001,753,210,10,1,0.001,0.73,15,0,None,i7173,15,483.2421875,468.1455078125,-1,0.9987994089397857,4648419
1745432715,1745432779,64,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4660 n_samples 132 const 10 max_depth 11 threshold 0.999,4660,132,10,11,0.999,0.73,48,0,None,i7173,48,512.640625,492.92075892857144,-1,0.9996305873660879,4648840
1745433218,1745433238,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 768 n_samples 247 const 0.001 max_depth 1 threshold 0.999,768,247,0.001,1,0.999,0.72,11,0,None,i7174,11,485.12890625,484.193359375,-1,0.9922885112670853,4649218
1745433793,1745433806,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4159 n_samples 2330 const 0.001 max_depth 1 threshold 0.001,4159,2330,0.001,1,0.001,0.66,4,0,None,i7178,4,483.81640625,483.6184895833333,-1,0.8642177687476912,4649629
1745434336,1745434362,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3891 n_samples 572 const 0.001 max_depth 1 threshold 0.6095631906690081,3891,572,0.001,1,0.6095631906690081,0.73,12,0,None,i7174,12,485.02734375,483.619140625,-1,0.9772811230144071,4650019
1745434814,1745434833,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 633 n_samples 1462 const 10 max_depth 1 threshold 0.17695677415141936,633,1462,10,1,0.17695677415141936,0.66,4,0,None,i7173,4,483.203125,483.0442708333333,-1,0.2046084226080532,4650370
1745435411,1745435431,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2027 n_samples 601 const 0.001 max_depth 20 threshold 0.999,2027,601,0.001,20,0.999,0.71,2,0,None,i7183,2,484.515625,484.33984375,-1,0.9990764684152198,4650818
1745435933,1745435984,51,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1962 n_samples 181 const 0.001 max_depth 1 threshold 0.001,1962,181,0.001,1,0.001,0.74,38,0,None,i7173,38,502.95703125,489.9453125,-1,0.9945973402290358,4651205
1745436392,1745436425,33,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 398 const 10 max_depth 1 threshold 0.48392461451890756,5000,398,10,1,0.48392461451890756,0.74,22,0,None,i7185,22,489.2421875,485.08515625,-1,0.9924270410048024,4651531
1745436948,1745436968,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2428 n_samples 470 const 0.001 max_depth 1 threshold 0.999,2428,470,0.001,1,0.999,0.7,5,0,None,i7186,5,484.2578125,484.0807291666667,-1,0.9983376431473956,4651911
1745437564,1745437603,39,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3006 n_samples 141 const 0.001 max_depth 1 threshold 0.001,3006,141,0.001,1,0.001,0.74,24,0,None,i7183,24,494.796875,487.94140625,-1,0.9961673439231622,4652400
1745438053,1745438085,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 620 n_samples 131 const 0.001 max_depth 1 threshold 0.001,620,131,0.001,1,0.001,0.73,17,0,None,i7183,17,487.625,483.712890625,-1,0.9981067602512006,4652782
1745438588,1745439141,553,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1 n_samples 1 const 10 max_depth 1 threshold 0.4346919109903707,1,1,10,1,0.4346919109903707,0.71,542,0,None,i7180,542,482.8046875,482.7946134868421,-1,0,4653279
1745439149,1745439162,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 4693 const 0.001 max_depth 20 threshold 0.999,5000,4693,0.001,20,0.999,0.7,3,0,None,i7180,3,483.26171875,483.0859375,-1,0.46176579239009974,4653746
1745439731,1745439756,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2786 n_samples 206 const 0.001 max_depth 1 threshold 0.8245994759084652,2786,206,0.001,1,0.8245994759084652,0.73,13,0,None,i7176,13,482.93359375,481.4697265625,-1,0.9987994089397857,4654254
1745440152,1745440172,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1114 n_samples 761 const 0.001 max_depth 20 threshold 0.001,1114,761,0.001,20,0.001,0.68,6,0,None,i7176,6,482.625,482.4505208333333,-1,0.7201699298115996,4654636
1745440652,1745440778,126,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3262 n_samples 145 const 0.001 max_depth 20 threshold 0.34097833230664243,3262,145,0.001,20,0.34097833230664243,0.74,28,0,None,i7174,28,482.58203125,468.14375,-1,0.9976449944588105,4655060
1745441313,1745441572,259,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2411 n_samples 340 const 10 max_depth 20 threshold 0.30652941782603127,2411,340,10,20,0.30652941782603127,0.71,249,0,None,i7175,249,482.95703125,482.935474537037,-1,0.990533801256003,4655565
1745441861,1745441881,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 1601 const 10 max_depth 1 threshold 0.001,5000,1601,10,1,0.001,0.69,7,0,None,i7175,7,483.890625,483.7083333333333,-1,0.9610731437015146,4655946
1745442494,1745442514,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1699 n_samples 3383 const 0.001 max_depth 1 threshold 0.999,1699,3383,0.001,1,0.999,0.7,3,0,None,i7182,3,483.578125,483.4049479166667,-1,0.23536202438123383,4656377
1745443016,1745443055,39,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2798 n_samples 88 const 0.001 max_depth 1 threshold 0.001,2798,88,0.001,1,0.001,0.75,27,0,None,i7180,27,496.98046875,487.809375,-1,0.9996305873660879,4656739
1745443541,1745443610,69,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 938 n_samples 4019 const 0.001 max_depth 1 threshold 0.999,938,4019,0.001,1,0.999,0.65,2,0,None,i7173,2,483.51171875,482.73046875,-1,0.10828407831547839,4657078
1745444094,1745444114,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4397 n_samples 2124 const 0.001 max_depth 20 threshold 0.48955578827577184,4397,2124,0.001,20,0.48955578827577184,0.69,6,0,None,i7185,6,482.640625,482.4401041666667,-1,0.9807905430365719,4657427
1745444638,1745444685,47,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1658 n_samples 299 const 0.001 max_depth 1 threshold 0.8147471264811459,1658,299,0.001,1,0.8147471264811459,0.73,29,0,None,i7186,29,490.421875,484.64375,-1,0.9940893978574067,4657807
1745445706,1745445745,39,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1325 n_samples 167 const 0.001 max_depth 1 threshold 0.001,1325,167,0.001,1,0.001,0.73,27,0,None,i7186,27,496.390625,488.26328125,-1,0.9947820465459919,4658608
1745446213,1745446245,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 676 n_samples 331 const 0.001 max_depth 1 threshold 0.999,676,331,0.001,1,0.999,0.72,9,0,None,i7182,9,483.5078125,483.3151041666667,-1,0.9934891023272996,4658952
1745445181,1745447072,1891,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 508 n_samples 1 const 0.001 max_depth 9 threshold 0.8891515957067082,508,1,0.001,9,0.8891515957067082,0.74,1874,0,None,i7186,1874,587.89453125,540.5243009868421,-1,1,4658211
1745447290,1745447322,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2784 n_samples 100 const 0.001 max_depth 1 threshold 0.3172384525790417,2784,100,0.001,1,0.3172384525790417,0.73,24,0,None,i7180,24,493.78515625,486.60625,-1,0.9974141115626154,4659794
1745447790,1745447855,65,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4629 n_samples 117 const 0.001 max_depth 1 threshold 0.801362576583848,4629,117,0.001,1,0.801362576583848,0.73,54,0,None,i7183,54,517.76171875,496.4013671875,-1,0.9994920576283709,4660197
1745448346,1745448411,65,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4359 n_samples 292 const 10 max_depth 20 threshold 0.999,4359,292,10,20,0.999,0.73,54,0,None,i7176,54,494.50390625,486.39697265625,-1,0.9981298485408201,4660662
1745446697,1745448453,1756,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2645 n_samples 1 const 0.001 max_depth 1 threshold 0.8416032293394814,2645,1,0.001,1,0.8416032293394814,0.74,1743,0,None,i7180,1743,590.80859375,546.6090881002825,-1,1,4659354
1745448886,1745448899,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2407 n_samples 749 const 0.001 max_depth 1 threshold 0.26789860758708567,2407,749,0.001,1,0.26789860758708567,0.69,4,0,None,i7176,4,483.515625,483.33984375,-1,0.9684152198005171,4661087
1745449421,1745449460,39,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4247 n_samples 314 const 0.001 max_depth 1 threshold 0.999,4247,314,0.001,1,0.999,0.73,27,0,None,i7185,27,493.984375,487.14375,-1,0.985962319911341,4661472
1745449930,1745449963,33,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4552 n_samples 328 const 0.001 max_depth 1 threshold 0.3010359032963361,4552,328,0.001,1,0.3010359032963361,0.73,19,0,None,i7175,19,492.8125,485.7724609375,-1,0.9996305873660879,4661818
1745450491,1745450518,27,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4465 n_samples 381 const 0.001 max_depth 1 threshold 0.999,4465,381,0.001,1,0.999,0.72,18,0,None,i7175,18,490.29296875,484.474609375,-1,0.9852234946435168,4662172
1745450974,1745451072,98,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 110 const 0.001 max_depth 1 threshold 0.999,5000,110,0.001,1,0.999,0.73,81,0,None,i7185,81,521.1484375,499.0276988636364,-1,0.995567048393055,4662487
1745451492,1745451637,145,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 82 const 10 max_depth 1 threshold 0.001,5000,82,10,1,0.001,0.73,128,0,None,i7186,128,533.3828125,502.70286458333334,-1,0.9996305873660879,4662806
1745452053,1745452092,39,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3855 n_samples 256 const 0.001 max_depth 20 threshold 0.001,3855,256,0.001,20,0.001,0.72,27,0,None,i7186,27,494.46875,486.36484375,-1,0.9929811599556705,4663173
1745452692,1745452750,58,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3143 n_samples 96 const 0.001 max_depth 20 threshold 0.001,3143,96,0.001,20,0.001,0.73,45,0,None,i7186,45,505.03515625,491.30189732142856,-1,0.9974141115626154,4663596
1745453621,1745453698,77,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4498 n_samples 104 const 0.001 max_depth 1 threshold 0.001,4498,104,0.001,1,0.001,0.74,65,0,None,i7183,65,523.0546875,497.6705729166667,-1,0.9988917620982638,4664219
1745454222,1745454255,33,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2476 n_samples 119 const 10 max_depth 1 threshold 0.3063761123900762,2476,119,10,1,0.3063761123900762,0.73,20,0,None,i7186,20,485.78515625,483.6484375,-1,0.9945973402290358,4664650
1745454792,1745454812,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 4055 const 0.001 max_depth 1 threshold 0.001,5000,4055,0.001,1,0.001,0.66,5,0,None,i7186,5,482.76171875,482.5833333333333,-1,0.5772072404876247,4665071
1745455421,1745455441,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3481 n_samples 1045 const 10 max_depth 1 threshold 0.999,3481,1045,10,1,0.999,0.71,7,0,None,i7180,7,482.27734375,482.1015625,-1,0.9650905060953084,4665523
1745456072,1745456098,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4079 n_samples 562 const 10 max_depth 20 threshold 0.5552830058926742,4079,562,10,20,0.5552830058926742,0.72,15,0,None,i7180,15,485.54296875,483.6513671875,-1,0.986147026228297,4665981
1745456675,1745456708,33,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1376 n_samples 238 const 10 max_depth 1 threshold 0.7782596122734634,1376,238,10,1,0.7782596122734634,0.73,21,0,None,i7178,21,492.0859375,487.2109375,-1,0.9891023272995937,4666446
1745457282,1745457315,33,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 1192 const 10 max_depth 20 threshold 0.001,5000,1192,10,20,0.001,0.73,20,0,None,i7176,20,484.23046875,484.1171875,-1,0.990764684152198,4666902
1745458034,1745458066,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2977 n_samples 153 const 0.001 max_depth 20 threshold 0.999,2977,153,0.001,20,0.999,0.73,22,0,None,i7174,22,493.73828125,487.73125,-1,0.9961673439231622,4667423
1745458612,1745458632,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2657 n_samples 198 const 10 max_depth 1 threshold 0.999,2657,198,10,1,0.999,0.73,10,0,None,i7175,10,484.5546875,483.8037109375,-1,0.9965829331363133,4667783
1745459323,1745459336,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 810 n_samples 2375 const 0.001 max_depth 20 threshold 0.999,810,2375,0.001,20,0.999,0.71,3,0,None,i7175,3,483.87109375,483.6953125,-1,0.16831363132619134,4668222
1745459983,1745460029,46,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1173 n_samples 160 const 10 max_depth 20 threshold 0.001,1173,160,10,20,0.001,0.73,32,0,None,i7185,32,494.44140625,487.064453125,-1,0.9974141115626154,4668629
1745460654,1745460674,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 1740 const 10 max_depth 1 threshold 0.999,5000,1740,10,1,0.999,0.71,6,0,None,i7186,6,482.37109375,482.17578125,-1,0.9641669745105282,4669029
1745461274,1745461339,65,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4554 n_samples 144 const 0.001 max_depth 20 threshold 0.999,4554,144,0.001,20,0.999,0.73,53,0,None,i7186,53,511.2265625,494.052734375,-1,0.9974141115626154,4669427
1745461903,1745461923,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4485 n_samples 1127 const 0.001 max_depth 20 threshold 0.999,4485,1127,0.001,20,0.999,0.72,7,0,None,i7183,7,482.6484375,482.47265625,-1,0.9887790912449206,4669904
1745462623,1745462694,71,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4181 n_samples 112 const 10 max_depth 5 threshold 0.001,4181,112,10,5,0.001,0.74,62,0,None,i7182,62,521.24609375,498.2213541666667,-1,0.9981529368304396,4670418
1745463395,1745463408,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3753 n_samples 5000 const 0.001 max_depth 20 threshold 0.001,3753,5000,0.001,20,0.001,0.65,3,0,None,i7182,3,483.828125,483.65625,-1,0.34660140376800885,4670938
1745464114,1745464141,27,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3905 n_samples 1238 const 10 max_depth 20 threshold 0.001,3905,1238,10,20,0.001,0.7,13,0,None,i7180,13,483.87890625,483.7314453125,-1,0.971832286664204,4671432
1745464975,1745464988,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1768 n_samples 1791 const 10 max_depth 20 threshold 0.999,1768,1791,10,20,0.999,0.71,5,0,None,i7178,5,482.9140625,482.7161458333333,-1,0.4898411525674178,4672055
1745465564,1745465584,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 157 n_samples 159 const 0.001 max_depth 20 threshold 0.001,157,159,0.001,20,0.001,0.71,7,0,None,i7176,7,483.98828125,483.828125,-1,0.4929811599556705,4672479
1745466155,1745466174,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4040 n_samples 562 const 10 max_depth 1 threshold 0.999,4040,562,10,1,0.999,0.72,11,0,None,i7175,11,484.61328125,483.236328125,-1,0.986147026228297,4672885
1745466835,1745466868,33,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1252 n_samples 206 const 10 max_depth 1 threshold 0.001,1252,206,10,1,0.001,0.73,24,0,None,i7185,24,491.3984375,485.98671875,-1,0.9987994089397857,4673324
1745467615,1745467648,33,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3646 n_samples 251 const 10 max_depth 1 threshold 0.999,3646,251,10,1,0.999,0.73,21,0,None,i7175,21,492.69921875,486.5015625,-1,0.9967676394532693,4673807
1745468277,1745468297,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3131 n_samples 578 const 10 max_depth 20 threshold 0.8989661433451961,3131,578,10,20,0.8989661433451961,0.71,11,0,None,i7186,11,484.453125,484.26953125,-1,0.9875323236054673,4674193
1745468926,1745468953,27,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3461 n_samples 824 const 0.001 max_depth 1 threshold 0.001,3461,824,0.001,1,0.001,0.69,10,0,None,i7186,10,483.1484375,482.9990234375,-1,0.9892870336165497,4674566
1745469616,1745469656,40,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2850 n_samples 119 const 10 max_depth 1 threshold 0.001,2850,119,10,1,0.001,0.74,29,0,None,i7185,29,494.046875,486.44921875,-1,0.9945973402290358,4674988
1745470236,1745470276,40,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4209 n_samples 302 const 10 max_depth 1 threshold 0.001,4209,302,10,1,0.001,0.72,27,0,None,i7183,27,494.24609375,487.52890625,-1,0.9942510158847433,4675430
1745470836,1745470849,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2735 n_samples 1835 const 10 max_depth 20 threshold 0.999,2735,1835,10,20,0.999,0.65,3,0,None,i7182,3,484.06640625,483.875,-1,0.6946111932028075,4675816
1745471537,1745471570,33,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 587 n_samples 97 const 0.001 max_depth 1 threshold 0.001,587,97,0.001,1,0.001,0.73,21,0,None,i7182,21,492.41796875,487.15,-1,0.9988455855190248,4676249
1745472227,1745472240,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3227 n_samples 2737 const 0.001 max_depth 20 threshold 0.001,3227,2737,0.001,20,0.001,0.65,3,0,None,i7182,3,483.98046875,483.8059895833333,-1,0.5215413742149981,4676685
1745472977,1745472990,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 2749 const 10 max_depth 1 threshold 0.3995490270421261,5000,2749,10,1,0.3995490270421261,0.7,4,0,None,i7182,4,484.27734375,484.0169270833333,-1,0.8080901366826746,4677125
1745473717,1745473730,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 2811 const 0.001 max_depth 1 threshold 0.999,5000,2811,0.001,1,0.999,0.71,4,0,None,i7178,4,482.36328125,482.1666666666667,-1,0.8080901366826746,4677627
1745474338,1745474376,38,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1953 n_samples 256 const 10 max_depth 1 threshold 0.999,1953,256,10,1,0.999,0.73,28,0,None,i7176,28,497.5234375,488.30859375,-1,0.9929811599556705,4678027
1745475139,1745475179,40,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4601 n_samples 447 const 0.001 max_depth 6 threshold 0.001,4601,447,0.001,6,0.001,0.73,23,0,None,i7186,23,488.99609375,485.50234375,-1,0.990764684152198,4678538
1745475917,1745475955,38,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2724 n_samples 94 const 0.001 max_depth 20 threshold 0.001,2724,94,0.001,20,0.001,0.73,26,0,None,i7181,26,493.234375,485.9171875,-1,0.9983376431473956,4678952
1745476619,1745476632,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1100 n_samples 2397 const 10 max_depth 1 threshold 0.999,1100,2397,10,1,0.999,0.66,4,0,None,i7186,4,482.91015625,482.7135416666667,-1,0.22857406723309937,4679306
1745477319,1745477398,79,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4710 n_samples 123 const 10 max_depth 1 threshold 0.999,4710,123,10,1,0.999,0.74,65,0,None,i7185,65,515.875,495.10590277777777,-1,0.9996305873660879,4679684
1745477808,1745477822,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2003 n_samples 193 const 10 max_depth 1 threshold 0.06650604722554104,2003,193,10,1,0.06650604722554104,0.66,3,0,None,i7185,3,483.21484375,483.0598958333333,-1,0.9981529368304396,4679982
1745478498,1745478525,27,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4133 n_samples 444 const 10 max_depth 1 threshold 0.999,4133,444,10,1,0.999,0.73,15,0,None,i7182,15,487.15625,483.8662109375,-1,0.9841152567417806,4680411
1745479159,1745479199,40,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3993 n_samples 324 const 0.001 max_depth 20 threshold 0.999,3993,324,0.001,20,0.999,0.72,25,0,None,i7185,25,492.66015625,486.25703125,-1,0.9874399704469893,4680811
1745479878,1745479904,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3466 n_samples 359 const 10 max_depth 1 threshold 0.999,3466,359,10,1,0.999,0.73,14,0,None,i7183,14,486.56640625,483.541015625,-1,0.9946435168082749,4681240
1745480499,1745480576,77,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4936 n_samples 95 const 0.001 max_depth 1 threshold 0.7409389880715015,4936,95,0.001,1,0.7409389880715015,0.74,65,0,None,i7181,65,527.62109375,499.39539930555554,-1,0.9957979312892501,4682187
1745481531,1745481576,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2991 n_samples 100 const 10 max_depth 20 threshold 0.7082508736955955,2991,100,10,20,0.7082508736955955,0.73,33,0,None,i7182,33,499.6953125,489.7962239583333,-1,0.9974141115626154,4682612
1745482282,1745482394,112,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4963 n_samples 99 const 0.001 max_depth 1 threshold 0.5352749277701959,4963,99,0.001,1,0.5352749277701959,0.74,98,0,None,i7186,98,524.1171875,498.373046875,-1,0.9965829331363133,4682865
1745483123,1745483162,39,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4195 n_samples 252 const 0.001 max_depth 1 threshold 0.001,4195,252,0.001,1,0.001,0.73,30,0,None,i7185,30,496.5390625,487.3234375,-1,0.9891023272995937,4683148
1745483875,1745483952,77,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4739 n_samples 119 const 10 max_depth 20 threshold 0.7181015484610651,4739,119,10,20,0.7181015484610651,0.74,65,0,None,i7186,65,516.54296875,495.1953125,-1,0.9945973402290358,4683397
1745484506,1745484564,58,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2969 n_samples 82 const 0.001 max_depth 1 threshold 0.999,2969,82,0.001,1,0.999,0.73,44,0,None,i7186,44,502.8125,491.23549107142856,-1,0.9996305873660879,4683608
1745486459,1745486485,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4719 n_samples 461 const 10 max_depth 1 threshold 0.999,4719,461,10,1,0.999,0.73,14,0,None,i7182,14,486.75390625,483.8125,-1,0.9792205393424455,4684273
1745487132,1745487230,98,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4750 n_samples 95 const 10 max_depth 1 threshold 0.3328203915956661,4750,95,10,1,0.3328203915956661,0.74,81,0,None,i7185,81,529.06640625,501.8746448863636,-1,0.9957979312892501,4684494
1745485287,1745487656,2369,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2637 n_samples 1 const 0.001 max_depth 20 threshold 0.8375979013688104,2637,1,0.001,20,0.8375979013688104,0.74,2356,0,None,i7183,2356,593.16796875,548.358078387605,-1,1,4683877
1745485888,1745487763,1875,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2642 n_samples 1 const 10 max_depth 1 threshold 0.999,2642,1,10,1,0.999,0.74,1864,0,None,i7182,1864,602.25,549.6724950396825,-1,1,4684078
1745487783,1745487796,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2301 n_samples 327 const 10 max_depth 1 threshold 0.7022844976406576,2301,327,10,1,0.7022844976406576,0.71,5,0,None,i7182,5,484.41015625,484.2356770833333,-1,0.9966060214259328,4684724
1745488565,1745488635,70,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4827 n_samples 120 const 0.001 max_depth 1 threshold 0.999,4827,120,0.001,1,0.999,0.73,58,0,None,i7181,58,517.94140625,495.529296875,-1,0.9974141115626154,4684986
1745489198,1745489224,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4433 n_samples 574 const 10 max_depth 1 threshold 0.379181975211485,4433,574,10,1,0.379181975211485,0.71,11,0,None,i7180,11,484.6015625,483.6748046875,-1,0.9806981898780939,4685193
1745489889,1745489915,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3748 n_samples 280 const 0.001 max_depth 1 threshold 0.541517016357465,3748,280,0.001,1,0.541517016357465,0.72,19,0,None,i7181,19,492.94921875,486.185546875,-1,0.995567048393055,4685422
1745490552,1745490592,40,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3814 n_samples 275 const 10 max_depth 1 threshold 0.001,3814,275,10,1,0.001,0.72,26,0,None,i7185,26,493.22265625,486.459375,-1,0.9909263021795346,4685644
1745492093,1745492126,33,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1026 n_samples 275 const 0.001 max_depth 1 threshold 0.001,1026,275,0.001,1,0.001,0.72,16,0,None,i7186,16,484.52734375,483.1728515625,-1,0.990487624676764,4686152
1745492788,1745492885,97,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4700 n_samples 91 const 0.001 max_depth 20 threshold 0.001,4700,91,0.001,20,0.001,0.74,78,0,None,i7186,78,531.34375,500.9765625,-1,0.9958902844477281,4686384
1745493535,1745493555,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4354 n_samples 573 const 0.001 max_depth 20 threshold 0.999,4354,573,0.001,20,0.999,0.73,12,0,None,i7180,12,484.41796875,482.986328125,-1,0.9789896564462505,4686642
1745494374,1745494399,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 463 const 10 max_depth 1 threshold 0.4970199757027351,5000,463,10,1,0.4970199757027351,0.73,13,0,None,i7181,13,487.3046875,484.4541015625,-1,0.9834687846324345,4686920
1745495039,1745495078,39,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4552 n_samples 273 const 0.001 max_depth 20 threshold 0.7685448286254398,4552,273,0.001,20,0.7685448286254398,0.73,23,0,None,i7176,23,494.98828125,487.040625,-1,0.9958902844477281,4687138
1745495751,1745495809,58,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4630 n_samples 130 const 10 max_depth 20 threshold 0.999,4630,130,10,20,0.999,0.73,49,0,None,i7180,49,515.94921875,494.61216517857144,-1,0.9964905799778352,4687383
1745496383,1745496441,58,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4306 n_samples 127 const 0.001 max_depth 1 threshold 0.312113596243716,4306,127,0.001,1,0.312113596243716,0.73,47,0,None,i7181,47,517.56640625,496.0044642857143,-1,0.9969523457702253,4687598
1745497105,1745497151,46,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3269 n_samples 128 const 0.001 max_depth 20 threshold 0.001,3269,128,0.001,20,0.001,0.74,33,0,None,i7176,33,500.8984375,490.2760416666667,-1,0.9988917620982638,4687836
1745497802,1745497827,25,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4569 n_samples 408 const 10 max_depth 1 threshold 0.001,4569,408,10,1,0.001,0.72,14,0,None,i7175,14,489.0234375,484.734375,-1,0.9985223494643517,4688072
1745498395,1745498421,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4584 n_samples 415 const 0.001 max_depth 1 threshold 0.3004572068946078,4584,415,0.001,1,0.3004572068946078,0.72,14,0,None,i7175,14,488.88671875,484.712890625,-1,0.9964905799778352,4688266
1745498938,1745498976,38,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2922 n_samples 103 const 10 max_depth 1 threshold 0.5988083558598358,2922,103,10,1,0.5988083558598358,0.74,28,0,None,i7181,28,498.5859375,488.85625,-1,0.9987994089397857,4688489
1745499126,1745499170,44,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1966 n_samples 244 const 0.001 max_depth 20 threshold 0.999,1966,244,0.001,20,0.999,0.73,25,0,None,i7175,25,493.8515625,486.3921875,-1,0.9915035094200222,4688714
1745499385,1745499424,39,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3530 n_samples 274 const 0.001 max_depth 20 threshold 0.999,3530,274,0.001,20,0.999,0.72,24,0,None,i7185,24,489.59375,484.88515625,-1,0.9995382342076099,4688924
1745500137,1745500164,27,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 509 n_samples 182 const 0.001 max_depth 1 threshold 0.001,509,182,0.001,1,0.001,0.73,14,0,None,i7186,14,482.59375,482.2705078125,-1,0.9916882157369782,4689243
1745501157,1745501176,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4571 n_samples 743 const 10 max_depth 1 threshold 0.999,4571,743,10,1,0.999,0.72,10,0,None,i7186,10,483.9140625,483.779296875,-1,0.9949667528629479,4689632
1745502667,1745502687,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2651 n_samples 296 const 10 max_depth 1 threshold 0.999,2651,296,10,1,0.999,0.73,8,0,None,i7182,8,482.375,482.2018229166667,-1,0.9977835241965275,4690379
1745501883,1745503113,1230,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4491 n_samples 679 const 10 max_depth 20 threshold 0.999,4491,679,10,20,0.999,0.73,1219,0,None,i7183,1219,484.4765625,484.1462638608871,-1,0.9754340598448467,4689957
1745503346,1745503373,27,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3964 n_samples 760 const 0.001 max_depth 20 threshold 0.999,3964,760,0.001,20,0.999,0.7,11,0,None,i7182,11,484.32421875,484.193359375,-1,0.9826376062061323,4690722
1745504126,1745504139,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1176 n_samples 5000 const 10 max_depth 1 threshold 0.999,1176,5000,10,1,0.999,0.68,2,0,None,i7180,2,484.296875,484.13671875,-1,0.10860731437015146,4691159
1745504909,1745504969,60,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3835 n_samples 151 const 10 max_depth 1 threshold 0.999,3835,151,10,1,0.999,0.73,46,0,None,i7185,46,504.7890625,491.29017857142856,-1,0.9970908755079424,4691578
1745505657,1745505703,46,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3040 n_samples 105 const 0.001 max_depth 1 threshold 0.6333144245899963,3040,105,0.001,1,0.6333144245899963,0.74,36,0,None,i7181,36,499.4765625,489.0442708333333,-1,0.9987994089397857,4691974
1745506347,1745506392,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4021 n_samples 187 const 0.001 max_depth 20 threshold 0.999,4021,187,0.001,20,0.999,0.73,36,0,None,i7180,36,503.63671875,490.6634114583333,-1,0.9930273365349095,4692344
1745507099,1745507145,46,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2982 n_samples 129 const 10 max_depth 20 threshold 0.5584504640442798,2982,129,10,20,0.5584504640442798,0.74,32,0,None,i7186,32,494.3046875,487.1106770833333,-1,0.9947820465459919,4692772
1745508029,1745508081,52,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3148 n_samples 92 const 10 max_depth 20 threshold 0.001,3148,92,10,20,0.001,0.74,40,0,None,i7176,40,504.84765625,492.703125,-1,0.9983376431473956,4693265
1745508807,1745509136,329,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1 n_samples 340 const 10 max_depth 20 threshold 0.001,1,340,10,20,0.001,0.72,321,0,None,i7176,321,483.98828125,483.975,-1,0.0014545622460288142,4693756
1745509710,1745509763,53,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3174 n_samples 189 const 0.001 max_depth 20 threshold 0.999,3174,189,0.001,20,0.999,0.72,35,0,None,i7186,35,492.37890625,486.0904947916667,-1,0.9949205762837089,4694201
1745510519,1745510572,53,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1920 n_samples 212 const 0.001 max_depth 20 threshold 0.001,1920,212,0.001,20,0.001,0.72,41,0,None,i7185,41,500.44921875,490.33984375,-1,0.9985223494643517,4694616
1745511226,1745511265,39,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4417 n_samples 515 const 10 max_depth 20 threshold 0.999,4417,515,10,20,0.999,0.73,25,0,None,i7181,25,485.7109375,483.35390625,-1,0.9987994089397857,4694992
1745511930,1745511956,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3627 n_samples 665 const 0.001 max_depth 20 threshold 0.001,3627,665,0.001,20,0.001,0.7,13,0,None,i7186,13,483.69140625,483.54296875,-1,0.9826376062061323,4695362
1745512586,1745512605,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4013 n_samples 1073 const 10 max_depth 1 threshold 0.18138122082737645,4013,1073,10,1,0.18138122082737645,0.71,6,0,None,i7180,6,483.58984375,483.4010416666667,-1,0.9909493904691541,4695697
1745513279,1745513292,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 2730 const 0.001 max_depth 1 threshold 0.999,5000,2730,0.001,1,0.999,0.67,4,0,None,i7180,4,482.56640625,482.4114583333333,-1,0.8080901366826746,4696089
1745513926,1745513952,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4393 n_samples 495 const 0.001 max_depth 1 threshold 0.001,4393,495,0.001,1,0.001,0.72,15,0,None,i7181,15,486.640625,484.16015625,-1,0.9828684891023273,4696411
1745514719,1745514971,252,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4429 n_samples 813 const 10 max_depth 20 threshold 0.001,4429,813,10,20,0.001,0.71,234,0,None,i7180,234,484.05078125,484.0276442307692,-1,0.9766808274843,4696778
1745515487,1745515507,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4870 n_samples 1329 const 10 max_depth 1 threshold 0.29835114197566626,4870,1329,10,1,0.29835114197566626,0.7,6,0,None,i7176,6,483.60546875,483.40625,-1,0.9818987809383081,4697194
1745516295,1745516321,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4495 n_samples 640 const 0.001 max_depth 20 threshold 0.4015809525971704,4495,640,0.001,20,0.4015809525971704,0.72,10,0,None,i7176,10,483.96484375,483.3828125,-1,0.9752493535278907,4697624
1745517068,1745517152,84,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4983 n_samples 100 const 10 max_depth 1 threshold 0.4487226947380253,4983,100,10,1,0.4487226947380253,0.73,72,0,None,i7186,72,526.0703125,500.59609375,-1,0.9974141115626154,4697998
1745517829,1745517861,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4133 n_samples 364 const 10 max_depth 1 threshold 0.001,4133,364,10,1,0.001,0.72,19,0,None,i7186,19,490.453125,485.107421875,-1,0.9918729220539343,4698346
1745518680,1745518693,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2078 n_samples 1467 const 0.001 max_depth 1 threshold 0.001,2078,1467,0.001,1,0.001,0.66,2,0,None,i7186,2,482.65234375,482.46484375,-1,0.6716845216106391,4698716
1745519412,1745519438,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4410 n_samples 590 const 0.001 max_depth 1 threshold 0.8701715273594489,4410,590,0.001,1,0.8701715273594489,0.72,15,0,None,i7182,15,485.140625,483.794921875,-1,0.9807905430365719,4699055
1745520213,1745520232,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3348 n_samples 597 const 0.001 max_depth 1 threshold 0.999,3348,597,0.001,1,0.999,0.72,8,0,None,i7176,8,482.96875,482.7669270833333,-1,0.9924270410048024,4699457
1745520951,1745521016,65,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3701 n_samples 118 const 10 max_depth 20 threshold 0.001,3701,118,10,20,0.001,0.74,52,0,None,i7186,52,510.5859375,494.2705078125,-1,0.9971370520871814,4699829
1745521512,1745521557,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2806 n_samples 83 const 10 max_depth 1 threshold 0.001,2806,83,10,1,0.001,0.74,32,0,None,i7181,32,497.87890625,488.3977864583333,-1,0.9964905799778352,4700154
1745522211,1745522238,27,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2646 n_samples 178 const 10 max_depth 19 threshold 0.001,2646,178,10,19,0.001,0.74,16,0,None,i7181,16,485.02734375,483.669921875,-1,0.9945511636497968,4700505
1745523963,1745524034,71,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4467 n_samples 105 const 10 max_depth 20 threshold 0.001,4467,105,10,20,0.001,0.74,61,0,None,i7176,61,525.25390625,500.8767361111111,-1,0.9987994089397857,4701431
1745524553,1745524585,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4371 n_samples 328 const 0.001 max_depth 20 threshold 0.34434637239182125,4371,328,0.001,20,0.34434637239182125,0.73,19,0,None,i7183,19,492.5625,485.5830078125,-1,0.9996305873660879,4701758
1745525311,1745525324,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2639 n_samples 1019 const 0.001 max_depth 1 threshold 0.001,2639,1019,0.001,1,0.001,0.68,3,0,None,i7176,3,483.25390625,483.0963541666667,-1,0.9881326191355745,4702154
1745523091,1745525373,2282,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2636 n_samples 1 const 4.921976815304447 max_depth 7 threshold 0.999,2636,1,4.921976815304447,7,0.999,0.75,2267,0,None,i7185,2267,595.53125,544.5530328875545,-1,1,4700949
1745526071,1745526123,52,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4021 n_samples 155 const 10 max_depth 1 threshold 0.5124489085160012,4021,155,10,1,0.5124489085160012,0.73,40,0,None,i7183,40,511.01171875,492.787109375,-1,0.9948743997044699,4702520
1745526780,1745526917,137,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4625 n_samples 342 const 0.001 max_depth 20 threshold 0.001,4625,342,0.001,20,0.001,0.73,124,0,None,i7182,124,491.76953125,487.7473958333333,-1,0.9955439601034355,4702857
1745527553,1745527585,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4122 n_samples 341 const 0.001 max_depth 20 threshold 0.001,4122,341,0.001,20,0.001,0.72,19,0,None,i7182,19,492.1796875,485.6513671875,-1,0.9920114517916513,4703210
1745528272,1745528306,34,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3430 n_samples 476 const 10 max_depth 15 threshold 0.5718626520298445,3430,476,10,15,0.5718626520298445,0.72,22,0,None,i7186,22,483.359375,483.04375,-1,0.9891023272995937,4703552
1745529193,1745529220,27,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2912 n_samples 200 const 10 max_depth 1 threshold 0.29983102907589193,2912,200,10,1,0.29983102907589193,0.71,16,0,None,i7181,16,488.109375,484.8193359375,-1,0.9974141115626154,4704019
1745529932,1745529951,19,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2970 n_samples 245 const 0.001 max_depth 1 threshold 0.999,2970,245,0.001,1,0.999,0.73,12,0,None,i7183,12,485.25,483.3486328125,-1,0.995567048393055,4704382
1745530714,1745530740,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3468 n_samples 342 const 0.001 max_depth 1 threshold 0.5835465790057645,3468,342,0.001,1,0.5835465790057645,0.72,17,0,None,i7185,17,487.90625,484.40234375,-1,0.9949205762837089,4704748
1745531522,1745531535,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2900 n_samples 1236 const 10 max_depth 1 threshold 0.001,2900,1236,10,1,0.001,0.7,3,0,None,i7183,3,484.421875,484.2669270833333,-1,0.9702622829700775,4705125
1745532393,1745532406,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 591 n_samples 1217 const 0.001 max_depth 20 threshold 0.999,591,1217,0.001,20,0.999,0.66,4,0,None,i7185,4,482.7109375,482.53515625,-1,0.2319680458071666,4705531
1745533259,1745533298,39,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3081 n_samples 138 const 10 max_depth 20 threshold 0.999,3081,138,10,20,0.999,0.74,28,0,None,i7182,28,496.2265625,487.1421875,-1,0.9940893978574067,4705989
1745533983,1745534003,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4452 n_samples 1168 const 0.001 max_depth 20 threshold 0.001,4452,1168,0.001,20,0.001,0.68,7,0,None,i7176,7,483.03515625,482.8372395833333,-1,0.9708164019209456,4706361
1745534833,1745534865,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4174 n_samples 330 const 10 max_depth 1 threshold 0.6011183978928866,4174,330,10,1,0.6011183978928866,0.72,19,0,None,i7176,19,491.484375,484.7373046875,-1,0.990487624676764,4706778
1745535603,1745535623,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 756 n_samples 254 const 0.001 max_depth 1 threshold 0.6466574038823201,756,254,0.001,1,0.6466574038823201,0.71,11,0,None,i7182,11,485.0625,484.3408203125,-1,0.9969523457702253,4707150
1745536493,1745536519,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4857 n_samples 548 const 10 max_depth 1 threshold 0.4337871733008759,4857,548,10,1,0.4337871733008759,0.72,13,0,None,i7186,13,485.84765625,483.876953125,-1,0.9868858514961212,4707559
1745537134,1745537154,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4256 n_samples 686 const 0.001 max_depth 1 threshold 0.3228617750143049,4256,686,0.001,1,0.3228617750143049,0.72,11,0,None,i7185,11,482.8671875,482.68359375,-1,0.9819911340967861,4707868
1745537774,1745537871,97,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 94 const 10 max_depth 1 threshold 0.999,5000,94,10,1,0.999,0.74,87,0,None,i7185,87,527.95703125,499.17649147727275,-1,0.9983376431473956,4708212
1745538473,1745538519,46,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3045 n_samples 100 const 0.001 max_depth 20 threshold 0.3136851119550377,3045,100,0.001,20,0.3136851119550377,0.73,38,0,None,i7181,38,499.59765625,488.326171875,-1,0.9974141115626154,4708563
1745539133,1745539159,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 499 const 10 max_depth 1 threshold 0.001,5000,499,10,1,0.001,0.72,13,0,None,i7178,13,485.6953125,483.51171875,-1,0.990810860731437,4708877
1745539834,1745539873,39,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2938 n_samples 111 const 10 max_depth 20 threshold 0.2039367357154023,2938,111,10,20,0.2039367357154023,0.73,30,0,None,i7183,30,496.5234375,487.0984375,-1,0.9994920576283709,4709203
1745540579,1745540618,39,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3112 n_samples 122 const 10 max_depth 1 threshold 0.24452129227070557,3112,122,10,1,0.24452129227070557,0.73,28,0,None,i7183,28,497.375,487.32265625,-1,0.9971370520871814,4709528
1745541394,1745541414,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2392 n_samples 155 const 0.001 max_depth 1 threshold 0.001,2392,155,0.001,1,0.001,0.73,9,0,None,i7180,9,483.4765625,483.2825520833333,-1,0.9948743997044699,4709909
1745542235,1745542249,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 2940 const 0.001 max_depth 1 threshold 0.999,5000,2940,0.001,1,0.999,0.68,4,0,None,i7180,4,484.4140625,484.23828125,-1,0.8080901366826746,4710334
1745542995,1745543008,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1 n_samples 1581 const 10 max_depth 1 threshold 0.001,1,1581,10,1,0.001,0.66,2,0,None,i7185,2,482.83984375,482.66796875,-1,0.00030014776505356484,4710700
1745543915,1745544013,98,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4747 n_samples 85 const 0.001 max_depth 1 threshold 0.001,4747,85,0.001,1,0.001,0.73,89,0,None,i7185,89,531.19140625,499.9612926136364,-1,0.9969523457702253,4711147
1745544665,1745544750,85,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4518 n_samples 111 const 10 max_depth 1 threshold 0.5543308605597309,4518,111,10,1,0.5543308605597309,0.74,75,0,None,i7185,75,519.33203125,496.015234375,-1,0.9994920576283709,4711511
1745545374,1745545419,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3721 n_samples 143 const 10 max_depth 20 threshold 0.37339170400136135,3721,143,10,20,0.37339170400136135,0.73,37,0,None,i7183,37,505.76171875,490.994140625,-1,0.9970908755079424,4711822
1745546165,1745546191,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 399 const 0.001 max_depth 1 threshold 0.7048508878225677,5000,399,0.001,1,0.7048508878225677,0.73,15,0,None,i7181,15,489.01953125,484.5234375,-1,0.9949205762837089,4712230
1745547117,1745547131,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1 n_samples 2523 const 10 max_depth 20 threshold 0.001,1,2523,10,20,0.001,0.68,4,0,None,i7181,4,483.2109375,483.0572916666667,-1,0.0001847063169560399,4712716
1745547956,1745548001,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3633 n_samples 217 const 10 max_depth 20 threshold 0.999,3633,217,10,20,0.999,0.73,35,0,None,i7182,35,496.875,488.3098958333333,-1,0.9920114517916513,4713111
1745548736,1745548781,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1300 n_samples 142 const 0.001 max_depth 1 threshold 0.001,1300,142,0.001,1,0.001,0.74,32,0,None,i7183,32,499.54296875,490.1901041666667,-1,0.9966752862947913,4713459
1745549466,1745549498,32,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 789 n_samples 121 const 10 max_depth 20 threshold 0.001,789,121,10,20,0.001,0.73,22,0,None,i7182,22,492.00390625,486.84921875,-1,0.9945511636497968,4713793
1745550236,1745550275,39,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3394 n_samples 175 const 10 max_depth 1 threshold 0.999,3394,175,10,1,0.999,0.74,25,0,None,i7180,25,495.08984375,487.159375,-1,0.9939508681196897,4714144
1745551017,1745551119,102,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 84 const 0.001 max_depth 20 threshold 0.001,5000,84,0.001,20,0.001,0.74,87,0,None,i7178,87,496.39453125,477.13991477272725,-1,0.9968599926117473,4714515
1745552077,1745552103,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 562 const 10 max_depth 1 threshold 0.6994086489398458,5000,562,10,1,0.6994086489398458,0.72,13,0,None,i7180,13,485.94921875,484.3447265625,-1,0.986147026228297,4715003
1745552837,1745552857,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4904 n_samples 844 const 10 max_depth 1 threshold 0.5181988196780649,4904,844,10,1,0.5181988196780649,0.7,9,0,None,i7181,9,484.234375,484.0130208333333,-1,0.9743258219431105,4715344
1745553697,1745553749,52,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3221 n_samples 92 const 0.001 max_depth 1 threshold 0.4162898312743592,3221,92,0.001,1,0.4162898312743592,0.73,44,0,None,i7183,44,505.82421875,491.38169642857144,-1,0.9983376431473956,4715755
1745554577,1745554603,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4311 n_samples 455 const 0.001 max_depth 1 threshold 0.001,4311,455,0.001,1,0.001,0.71,14,0,None,i7181,14,488.32421875,485.1787109375,-1,0.9874861470262283,4716191
1745555527,1745555579,52,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3819 n_samples 146 const 0.001 max_depth 20 threshold 0.7602323004140825,3819,146,0.001,20,0.7602323004140825,0.73,42,0,None,i7180,42,505.82421875,491.87779017857144,-1,0.9977835241965275,4716661
1745556380,1745556532,152,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2619 n_samples 237 const 0.001 max_depth 20 threshold 0.8712993596651286,2619,237,0.001,20,0.8712993596651286,0.73,142,0,None,i7180,142,484.00390625,483.97288602941177,-1,0.9972986701145179,4717063
1745557320,1745557371,51,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3733 n_samples 145 const 10 max_depth 20 threshold 0.001,3733,145,10,20,0.001,0.74,38,0,None,i7181,38,502.70703125,489.7877604166667,-1,0.9976449944588105,4717463
1745558200,1745558272,72,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2956 n_samples 230 const 10 max_depth 20 threshold 0.999,2956,230,10,20,0.999,0.72,61,0,None,i7182,61,483.3359375,480.45616319444446,-1,0.9989148503878833,4717870
1745559061,1745559160,99,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4378 n_samples 114 const 0.001 max_depth 20 threshold 0.001,4378,114,0.001,20,0.001,0.73,83,0,None,i7185,83,517.0078125,496.34090909090907,-1,0.9949205762837089,4718247
1745559879,1745559912,33,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1178 n_samples 253 const 0.001 max_depth 20 threshold 0.999,1178,253,0.001,20,0.999,0.72,19,0,None,i7185,19,489.5234375,485.69140625,-1,0.9930273365349095,4718613
1745560920,1745560985,65,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1764 n_samples 131 const 10 max_depth 1 threshold 0.001,1764,131,10,1,0.001,0.74,55,0,None,i7185,55,510.48828125,492.919921875,-1,0.9981067602512006,4719070
1745561940,1745561998,58,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3150 n_samples 74 const 10 max_depth 1 threshold 0.001,3150,74,10,1,0.001,0.73,50,0,None,i7183,50,512.5703125,493.55189732142856,-1,0.9977835241965275,4719512
1745562819,1745562864,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3503 n_samples 129 const 10 max_depth 1 threshold 0.001,3503,129,10,1,0.001,0.74,34,0,None,i7183,34,503.8125,491.2701822916667,-1,0.9947820465459919,4719907
1745563720,1745563759,39,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3369 n_samples 153 const 0.001 max_depth 1 threshold 0.999,3369,153,0.001,1,0.999,0.73,28,0,None,i7182,28,497.55078125,487.45625,-1,0.9961673439231622,4720332
1745564739,1745564797,58,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4409 n_samples 129 const 10 max_depth 1 threshold 0.999,4409,129,10,1,0.999,0.73,46,0,None,i7180,46,514.8359375,494.4765625,-1,0.9947820465459919,4720844
1745565700,1745565758,58,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4182 n_samples 129 const 0.001 max_depth 1 threshold 0.001,4182,129,0.001,1,0.001,0.73,49,0,None,i7182,49,513.94921875,492.91908482142856,-1,0.9947820465459919,4721314
1745566661,1745566707,46,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1216 n_samples 181 const 0.001 max_depth 16 threshold 0.001,1216,181,0.001,16,0.001,0.73,30,0,None,i7185,30,493.30859375,487.5598958333333,-1,0.9945973402290358,4721759
1745567499,1745567525,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4000 n_samples 404 const 10 max_depth 1 threshold 0.8038145355141877,4000,404,10,1,0.8038145355141877,0.72,15,0,None,i7183,15,489.28125,485.1376953125,-1,0.9889176209826376,4722116
1745568361,1745568381,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1 n_samples 24 const 10 max_depth 1 threshold 0.999,1,24,10,1,0.999,0.71,5,0,None,i7176,5,482.90625,482.66796875,-1,0.0208256372367935,4722502
1745569500,1745569513,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 1274 const 10 max_depth 1 threshold 0.001,5000,1274,10,1,0.001,0.69,5,0,None,i7170,5,482.40234375,482.2473958333333,-1,0.9412633912079793,4723005
1745570401,1745570454,53,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1851 n_samples 193 const 0.001 max_depth 1 threshold 0.5010140920586574,1851,193,0.001,1,0.5010140920586574,0.73,42,0,None,i7186,42,500.5703125,489.9888392857143,-1,0.9981529368304396,4723406
1745571081,1745571101,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2421 n_samples 115 const 10 max_depth 1 threshold 0.001,2421,115,10,1,0.001,0.73,12,0,None,i7181,12,485.34375,484.0732421875,-1,0.9983376431473956,4723724
1745572099,1745572163,64,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4916 n_samples 116 const 0.001 max_depth 9 threshold 0.999,4916,116,0.001,9,0.999,0.73,54,0,None,i7181,54,519.7734375,496.3740234375,-1,0.9963058736608792,4724151
1745572902,1745572994,92,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4560 n_samples 112 const 10 max_depth 20 threshold 0.4305488589445956,4560,112,10,20,0.4305488589445956,0.74,80,0,None,i7185,80,521.93359375,499.0269886363636,-1,0.9981529368304396,4724478
1745574001,1745574014,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3544 n_samples 3336 const 10 max_depth 1 threshold 0.999,3544,3336,10,1,0.999,0.63,3,0,None,i7181,3,483.41015625,483.2174479166667,-1,0.49094939046915403,4724985
1745574941,1745575013,72,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4803 n_samples 109 const 0.001 max_depth 1 threshold 0.7213831446948192,4803,109,0.001,1,0.7213831446948192,0.74,60,0,None,i7181,60,521.484375,495.81396484375,-1,0.9965829331363133,4725428
1745576221,1745576248,27,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4322 n_samples 512 const 0.001 max_depth 20 threshold 0.4848649403690247,4322,512,0.001,20,0.4848649403690247,0.72,15,0,None,i7180,15,485.921875,483.396484375,-1,0.9929811599556705,4726014
1745577161,1745577181,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2500 n_samples 180 const 10 max_depth 1 threshold 0.001,2500,180,10,1,0.001,0.73,10,0,None,i7181,10,484.37109375,484.1588541666667,-1,0.9974141115626154,4726414
1745577962,1745577995,33,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 282 const 10 max_depth 1 threshold 0.999,5000,282,10,1,0.999,0.73,23,0,None,i7181,23,495.3046875,488.04609375,-1,0.9896564462504618,4726767
1745579062,1745579075,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2085 n_samples 1730 const 10 max_depth 1 threshold 0.999,2085,1730,10,1,0.999,0.68,2,0,None,i7176,2,482.875,482.7096354166667,-1,0.5776690062800148,4727288
1745580183,1745580254,71,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 102 const 0.001 max_depth 8 threshold 0.6689841333411877,5000,102,0.001,8,0.6689841333411877,0.74,63,0,None,i7182,63,526.3359375,500.44227430555554,-1,0.9985223494643517,4727778
1745581242,1745581319,77,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4951 n_samples 94 const 10 max_depth 10 threshold 0.001,4951,94,10,10,0.001,0.74,69,0,None,i7183,69,529.02734375,499.63715277777777,-1,0.9983376431473956,4728233
1745581995,1745582034,39,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 365 const 10 max_depth 1 threshold 0.2023135296674892,5000,365,10,1,0.2023135296674892,0.72,28,0,None,i7186,28,491.77734375,486.26171875,-1,0.9970216106390839,4728547
1745582763,1745582846,83,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4844 n_samples 86 const 10 max_depth 20 threshold 0.40552582187194247,4844,86,10,20,0.40552582187194247,0.74,74,0,None,i7181,74,534.81640625,503.15234375,-1,0.9967676394532693,4728883
1745583783,1745583822,39,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4337 n_samples 242 const 0.001 max_depth 1 threshold 0.999,4337,242,0.001,1,0.999,0.73,27,0,None,i7183,27,497.79296875,487.71015625,-1,0.9945511636497968,4729343
1745584604,1745584643,39,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4642 n_samples 379 const 0.001 max_depth 1 threshold 0.6506554016071571,4642,379,0.001,1,0.6506554016071571,0.74,25,0,None,i7186,25,490.8671875,485.953125,-1,0.9975526413003325,4729702
1745585483,1745585619,136,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 241 n_samples 270 const 10 max_depth 20 threshold 0.2449302715777827,241,270,10,20,0.2449302715777827,0.7,127,0,None,i7183,127,484.48046875,484.44140625,-1,0.44514222386405616,4730092
1745586524,1745586576,52,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3157 n_samples 106 const 0.001 max_depth 20 threshold 0.999,3157,106,0.001,20,0.999,0.73,39,0,None,i7186,39,503.23046875,490.8287760416667,-1,0.9985223494643517,4730545
1745587424,1745587437,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1 n_samples 15 const 10 max_depth 1 threshold 0.999,1,15,10,1,0.999,0.74,4,0,None,i7186,4,483.43359375,483.2447916666667,-1,0.0333164019209457,4730954
1745588565,1745588598,33,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4445 n_samples 1393 const 10 max_depth 20 threshold 0.6280402101173124,4445,1393,10,20,0.6280402101173124,0.73,23,0,None,i7186,23,483.1328125,483.0140625,-1,0.9648596231991134,4731427
1745589905,1745589931,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1255 n_samples 256 const 10 max_depth 1 threshold 0.999,1255,256,10,1,0.999,0.73,17,0,None,i7186,17,488.67578125,484.4765625,-1,0.9929811599556705,4731999
1745590964,1745590978,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1 n_samples 1445 const 0.001 max_depth 20 threshold 0.001,1,1445,0.001,20,0.001,0.61,2,0,None,i7183,2,482.5,482.30859375,-1,0.0003232360546730698,4732429
1745591836,1745591901,65,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4525 n_samples 132 const 10 max_depth 20 threshold 0.7039906132045108,4525,132,10,20,0.7039906132045108,0.73,50,0,None,i7182,50,513.52734375,495.650390625,-1,0.9996305873660879,4732766
1745592467,1745592625,158,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2754 n_samples 24 const 10 max_depth 1 threshold 0.999,2754,24,10,1,0.999,0.73,141,0,None,i7186,141,536.3125,504.11925551470586,-1,0.9996305873660879,4733003
1745593107,1745593191,84,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2789 n_samples 38 const 10 max_depth 1 threshold 0.999,2789,38,10,1,0.999,0.74,75,0,None,i7186,75,521.06640625,498.2296875,-1,0.9984299963058737,4733289
1745593756,1745593942,186,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2700 n_samples 13 const 10 max_depth 1 threshold 0.999,2700,13,10,1,0.999,0.72,173,0,None,i7181,173,555.7421875,515.93125,-1,0.9994920576283709,4733563
1745594385,1745594443,58,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2825 n_samples 51 const 10 max_depth 1 threshold 0.999,2825,51,10,1,0.999,0.74,49,0,None,i7181,49,510.578125,492.72935267857144,-1,0.9985223494643517,4733834
1745595706,1745595816,110,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2746 n_samples 28 const 0.001 max_depth 1 threshold 0.999,2746,28,0.001,1,0.999,0.73,100,0,None,i7180,100,528.1953125,497.9567057291667,-1,0.9994458810491319,4734400
1745596187,1745596253,66,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2829 n_samples 80 const 10 max_depth 1 threshold 0.999,2829,80,10,1,0.999,0.73,53,0,None,i7186,53,498.9765625,488.8701171875,-1,0.9974141115626154,4734619
1745597718,1745597904,186,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 64 const 10 max_depth 1 threshold 0.999,5000,64,10,1,0.999,0.73,173,0,None,i7186,173,545.67578125,507.8689453125,-1,0.9988917620982638,4735266
1745595006,1745598221,3215,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2999 n_samples 1 const 0.001 max_depth 1 threshold 0.999,2999,1,0.001,1,0.999,0.76,3201,0,None,i7181,3201,582.82421875,542.5685534743789,-1,1,4734090
1745598189,1745598500,311,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2839 n_samples 27 const 0.001 max_depth 20 threshold 0.999,2839,27,0.001,20,0.999,0.73,299,0,None,i7185,299,533.31640625,494.28759765625,-1,0.9994920576283709,4735449
1745598917,1745599569,652,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2761 n_samples 1 const 10 max_depth 1 threshold 0.001,2761,1,10,1,0.001,0.71,639,0,None,i7186,639,483.59375,482.721650094697,-1,0,4735743
1745600249,1745600269,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 4734 const 10 max_depth 20 threshold 0.001,5000,4734,10,20,0.001,0.7,10,0,None,i7181,10,483.75,483.60546875,-1,0.46176579239009974,4736301
1745596999,1745600546,3547,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3082 n_samples 1 const 10 max_depth 20 threshold 0.999,3082,1,10,20,0.999,0.75,3534,0,None,i7176,3534,591.84765625,549.3393390098314,-1,1,4734988
1745600909,1745601031,122,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 78 const 10 max_depth 20 threshold 0.999,5000,78,10,20,0.999,0.73,107,0,None,i7183,107,534.85546875,502.42728365384613,-1,0.9976911710380495,4736558
1745601528,1745601573,45,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2875 n_samples 96 const 10 max_depth 1 threshold 0.999,2875,96,10,1,0.999,0.74,35,0,None,i7183,35,497.86328125,488.2389322916667,-1,0.9974141115626154,4736803
1745602728,1745602872,144,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 62 const 10 max_depth 20 threshold 0.999,5000,62,10,20,0.999,0.73,131,0,None,i7185,131,545.34765625,508.426025390625,-1,0.9991688215736978,4737284
1745603290,1745603702,412,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 36 const 0.001 max_depth 20 threshold 0.999,5000,36,0.001,20,0.999,0.74,293,0,None,i7178,293,499.23046875,474.0235595703125,-1,0.9991226449944588,4737511
1745602149,1745606613,4464,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3390 n_samples 1 const 10 max_depth 20 threshold 0.999,3390,1,10,20,0.999,0.76,4456,0,None,i7183,4456,588.60546875,547.485613141741,-1,1,4737046
1745607350,1745607534,184,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 65 const 0.001 max_depth 20 threshold 0.999,5000,65,0.001,20,0.999,0.73,173,0,None,i7186,173,547.03125,509.5810546875,-1,0.9994920576283709,4739250
1745607910,1745607968,58,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2883 n_samples 69 const 10 max_depth 20 threshold 0.999,2883,69,10,20,0.999,0.73,48,0,None,i7176,48,504.68359375,490.70814732142856,-1,0.9972755818248984,4739473
1745608669,1745609011,342,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2663 n_samples 7 const 10 max_depth 1 threshold 0.999,2663,7,10,1,0.999,0.73,331,0,None,i7186,331,574.03515625,523.984375,-1,0.999769117103805,4739795
1745610621,1745610641,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 431 n_samples 3941 const 0.001 max_depth 1 threshold 0.001,431,3941,0.001,1,0.001,0.73,3,0,None,i7007,3,476.33203125,476.2135416666667,-1,0.04975526413003325,4741238
1745611312,1745611417,105,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2800 n_samples 47 const 0.001 max_depth 1 threshold 0.999,2800,47,0.001,1,0.999,0.73,91,0,None,i7186,91,514.3359375,495.87109375,-1,0.9983376431473956,4741631
1745611891,1745612483,592,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 200 n_samples 1 const 10 max_depth 1 threshold 0.999,200,1,10,1,0.999,0.74,583,0,None,i7183,583,590.0859375,535.8772412909836,-1,1,4742116
1745613612,1745613638,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3942 n_samples 1640 const 10 max_depth 20 threshold 0.3241490239578118,3942,1640,10,20,0.3241490239578118,0.69,17,0,None,i7181,17,484.25,484.0693359375,-1,0.9844846693756927,4742908
1745615271,1745615284,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1 n_samples 3929 const 0.001 max_depth 1 threshold 0.001,1,3929,0.001,1,0.001,0.69,2,0,None,i7181,2,483.04296875,482.83203125,-1,0.00011544144809752494,4743595
1745615932,1745616028,96,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2892 n_samples 38 const 10 max_depth 20 threshold 0.999,2892,38,10,20,0.999,0.73,86,0,None,i7180,86,525.96875,498.2734375,-1,0.9984299963058737,4743886
1745617492,1745617634,142,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1 n_samples 1 const 10 max_depth 7 threshold 0.8458809084356678,1,1,10,7,0.8458809084356678,0.81,131,0,None,i7178,131,483.203125,483.067626953125,-1,0.5,4744507
1745618904,1745618974,70,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 109 const 0.001 max_depth 20 threshold 0.9566033911530513,5000,109,0.001,20,0.9566033911530513,0.74,60,0,None,i7176,60,521.9609375,496.30029296875,-1,0.9965829331363133,4745100
1745620583,1745620603,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 3736 n_samples 4773 const 10 max_depth 1 threshold 0.999,3736,4773,10,1,0.999,0.72,4,0,None,i7186,4,483.40234375,483.2252604166667,-1,0.3450314000738825,4745782
1745622372,1745622386,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4109 n_samples 2856 const 0.001 max_depth 1 threshold 0.001,4109,2856,0.001,1,0.001,0.72,4,0,None,i7186,4,483.4609375,483.2630208333333,-1,0.664088474325822,4746504
1745623165,1745623238,73,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2780 n_samples 68 const 10 max_depth 1 threshold 0.999,2780,68,10,1,0.999,0.74,57,0,None,i7186,57,501.4453125,489.4755859375,-1,0.9985223494643517,4746847
1745625095,1745625108,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2631 n_samples 4671 const 0.001 max_depth 20 threshold 0.999,2631,4671,0.001,20,0.999,0.67,3,0,None,i7178,3,482.6640625,482.4869791666667,-1,0.2429811599556705,4747635
1745626913,1745626926,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2524 n_samples 3315 const 0.001 max_depth 20 threshold 0.48911407482677,2524,3315,0.001,20,0.48911407482677,0.67,2,0,None,i7176,2,483.734375,483.5377604166667,-1,0.3496490579977835,4748373
1745627655,1745628288,633,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2657 n_samples 5 const 10 max_depth 20 threshold 0.999,2657,5,10,20,0.999,0.73,624,0,None,i7185,624,559.3203125,524.0936899038461,-1,0.999953823420761,4748647
1745629614,1745629627,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 1405 const 0.001 max_depth 20 threshold 0.5983351880311628,5000,1405,0.001,20,0.5983351880311628,0.72,6,0,None,i7180,6,483.5078125,483.33203125,-1,0.9731714074621352,4749438
1745630434,1745630525,91,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1909 n_samples 96 const 10 max_depth 20 threshold 0.999,1909,96,10,20,0.999,0.73,78,0,None,i7186,78,523.46484375,497.10859375,-1,0.9974141115626154,4749767
1745631235,1745632944,1709,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 4 const 10 max_depth 20 threshold 0.999,5000,4,10,20,0.999,0.75,1700,0,None,i7181,1700,591.30078125,546.6815952034884,-1,1,4750082
1745635035,1745635068,33,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 403 n_samples 86 const 10 max_depth 10 threshold 0.001,403,86,10,10,0.001,0.73,19,0,None,i7185,19,487.53125,484.451171875,-1,0.9967676394532693,4751533
1745636816,1745636842,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2512 n_samples 110 const 0.001 max_depth 10 threshold 0.001,2512,110,0.001,10,0.001,0.73,15,0,None,i7181,15,487.99609375,484.4169921875,-1,0.995567048393055,4752213
1745638706,1745638836,130,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 556 const 10 max_depth 10 threshold 0.001,5000,556,10,10,0.001,0.72,117,0,None,i7180,117,485.8671875,484.3013392857143,-1,0.9767039157739195,4752978
1745640776,1745640796,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 1355 const 10 max_depth 11 threshold 0.999,5000,1355,10,11,0.999,0.72,6,0,None,i7186,6,483.734375,483.53515625,-1,0.9385389730328777,4753834
1745643087,1745643100,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 1725 const 0.001 max_depth 10 threshold 0.001,5000,1725,0.001,10,0.001,0.69,5,0,None,i7183,5,484.01953125,483.8229166666667,-1,0.9558551902475064,4754741
1745645357,1745645370,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1 n_samples 75 const 0.001 max_depth 11 threshold 0.001,1,75,0.001,11,0.001,0.72,4,0,None,i7181,4,483.19921875,483.01171875,-1,0.0066494274104174364,4755612
1745647827,1745647840,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 2007 const 10 max_depth 20 threshold 0.001,5000,2007,10,20,0.001,0.69,5,0,None,i7180,5,484.1953125,484.01953125,-1,0.9267639453269302,4756560
1745650278,1745650298,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 1161 const 0.001 max_depth 11 threshold 0.999,5000,1161,0.001,11,0.999,0.7,8,0,None,i7178,8,482.46875,482.29296875,-1,0.9649981529368304,4757538
1745652698,1745652724,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 930 const 0.001 max_depth 1 threshold 0.999,5000,930,0.001,1,0.999,0.71,8,0,None,i7178,8,483.9921875,483.7526041666667,-1,0.9877170299224234,4758476
1745655139,1745655152,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 2338 n_samples 3952 const 10 max_depth 10 threshold 0.001,2338,3952,10,10,0.001,0.66,3,0,None,i7186,3,484.140625,483.9049479166667,-1,0.2699021056520133,4759360
1745657459,1745657473,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 2892 const 0.001 max_depth 10 threshold 0.001,5000,2892,0.001,10,0.001,0.71,4,0,None,i7185,4,482.94921875,482.7942708333333,-1,0.8080901366826746,4760211
1745658239,1745658252,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1 n_samples 82 const 0.001 max_depth 12 threshold 0.999,1,82,0.001,12,0.999,0.71,4,0,None,i7183,4,483.55859375,483.4036458333333,-1,0.006095308459549317,4760498
1745660820,1745660840,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 4987 n_samples 1224 const 10 max_depth 11 threshold 0.3662531542105922,4987,1224,10,11,0.3662531542105922,0.71,11,0,None,i7185,11,483.0703125,482.9111328125,-1,0.9608422608053195,4761482
1745663970,1745663984,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1 n_samples 3181 const 0.001 max_depth 20 threshold 0.001,1,3181,0.001,20,0.001,0.71,2,0,None,i7185,2,483.83203125,483.6770833333333,-1,0.00013852973771702993,4762735
1745666661,1745666674,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 1 n_samples 1005 const 10 max_depth 1 threshold 0.999,1,1005,10,1,0.999,0.69,2,0,None,i7180,2,483.2109375,483.01171875,-1,0.00048485408200960473,4763740
1745667480,1745667623,143,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/main.py 1 1 0 Electricity 2000 HoeffdingTreeClassifier BNDM recent_samples_size 5000 n_samples 57 const 0.001 max_depth 1 threshold 0.999,5000,57,0.001,1,0.999,0.74,129,0,None,i7186,129,551.140625,509.75755208333334,-1,0.9975526413003325,4764041

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timestamp,ram_usage_mb,cpu_usage_percent
1745405554,633.96484375,34.9
1745405554,633.96875,42.6
1745405554,633.96875,42.4
1745405554,633.96875,44.7
1745405554,633.96875,33.3
1745405554,633.96875,45.5
1745405554,633.96875,42.6
1745406104,683.34375,44.6
1745406104,683.34375,35.0
1745406104,683.34375,42.0
1745406104,683.34375,48.8
1745416073,924.0703125,42.2
1745416073,924.0703125,44.2
1745416073,924.0703125,44.2
1745416073,924.0703125,43.2
1745428529,968.9609375,37.5
1745428529,968.9609375,34.7
1745428529,968.9609375,33.1
1745428529,968.9609375,34.0
1745439158,980.9921875,42.2
1745439158,980.9921875,43.1
1745439158,980.9921875,42.9
1745439158,980.9921875,45.0
1745449944,1057.578125,40.8
1745449944,1057.578125,38.0
1745449944,1057.578125,39.9
1745449944,1057.578125,25.8
1745462646,1016.5703125,41.4
1745462646,1016.5703125,44.6
1745462646,1016.5703125,43.7
1745462646,1016.5703125,43.7
1745476633,1030.59375,42.8
1745476633,1030.59375,36.9
1745476633,1030.59375,37.8
1745476633,1030.59375,23.7
1745489592,1063.625,40.1
1745489592,1063.625,39.3
1745489592,1063.625,40.7
1745489592,1063.625,45.6
1745504911,1135.8046875,36.1
1745504911,1135.8046875,31.8
1745504911,1135.8046875,33.3
1745504911,1135.8046875,29.9
1745520226,1158.01171875,37.3
1745520227,1158.01171875,36.0
1745520227,1158.01171875,35.2
1745520227,1158.01171875,35.3
1745535616,1170.546875,37.6
1745535616,1170.546875,39.8
1745535616,1170.546875,38.1
1745535616,1170.546875,43.3
1745551038,1186.0234375,36.7
1745551038,1186.0234375,37.5
1745551038,1186.0234375,38.1
1745551038,1186.0234375,33.3
1745569523,1195.8828125,37.3
1745569523,1195.8828125,39.8
1745569523,1195.8828125,39.9
1745569523,1195.8828125,37.3
1745588579,1220.015625,37.6
1745588579,1220.015625,37.1
1745588579,1220.015625,36.5
1745588579,1220.015625,34.6
1745603313,1275.97265625,36.8
1745603313,1275.97265625,38.8
1745603313,1275.97265625,38.2
1745603313,1275.97265625,44.2
1745631246,1300.24609375,37.3
1745631246,1300.24609375,37.7
1745631246,1300.24609375,36.5
1745631246,1300.24609375,35.3

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Visualization for result: ACCURACY (goal: maximize)

Best value: 0.81
Achieved at:
- RUNTIME = 86
- recent_samples_size = 1
- n_samples = 1
- const = 8.1288447053914
- max_depth = 5
- threshold = 0.94976250175943

Visualization for result: RUNTIME (goal: minimize)

Best value: 1
Achieved at:
- ACCURACY = 0.67
- recent_samples_size = 1
- n_samples = 2907
- const = 10
- max_depth = 1
- threshold = 0.999

Parameter statistics

Correlation Heatmap Explanation

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.

How It Works

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:

• Positive correlation: Both variables increase or decrease together (e.g., if the temperature rises, ice cream sales increase).
• Negative correlation: As one variable increases, the other decreases (e.g., as the price of a product rises, the demand for it decreases).
• Zero correlation: There is no relationship between the two variables (e.g., height and shoe size might show zero correlation in some contexts).

Color Scale: Yellow to Purple (Viridis)

The heatmap uses a color scale called "Viridis," which ranges from yellow to purple. Here's what the colors represent:

• Yellow (brightest): A strong positive correlation (close to +1). This indicates that as one variable increases, the other increases in a very predictable manner.
• Green: A moderate positive correlation. Variables are still positively related, but the relationship is not as strong.
• Blue: A weak or near-zero correlation. There is a small or no discernible relationship between the variables.
• Purple (darkest): A strong negative correlation (close to -1). This indicates that as one variable increases, the other decreases in a very predictable manner.

What the Heatmap Shows

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.

•  Job-Infos

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

body {
	font-variant: oldstyle-nums;
	font-family: sans-serif;
	background-color: #fafafa;
	text-shadow: 0 0.05em 0.1em rgba(0,0,0,0.2);
	scroll-behavior: smooth;
	text-wrap: balance;
	text-rendering: optimizeLegibility;
	-webkit-font-smoothing: antialiased;
	-moz-osx-font-smoothing: grayscale;
	font-feature-settings: "ss02", "liga", "onum";
}

.marked_text {
	background-color: yellow;
}

.time_picker_container {
	font-variant: small-caps;
	width: 100%;
}

.time_picker_container > input {
	width: 50px;
}

#loader {
	display: grid;
	justify-content: center;
	align-items: center;
	height: 100%;
}

.no_linebreak {
	line-break: auto;
}

.dark_code_bg {
	background-color: #363636;
	color: white;
}

.code_bg {
	background-color: #C0C0C0;
}

#commands {
	line-break: anywhere;
}

.color_red {
	color: red;
}

.color_orange {
	color: orange;
}

table > tbody > tr:nth-child(odd) {
	background-color: #fafafa;
}

table > tbody > tr:nth-child(even) {
	background-color: #ddd;
}

table {
	border-collapse: collapse;
	margin: 0 0;
	min-width: 200px;
}

th {
	background-color: #4eae46;
	color: #ffffff;
	text-align: left;
	border: 0px;
}

.error_element {
	background-color: #e57373;
	border-radius: 10px;
	padding: 4px;
	display: none;
}

button {
	background-color: #4eae46;
	border: 1px solid #2A8387;
	border-radius: 4px;
	box-shadow: rgba(0, 0, 0, 0.12) 0 1px 1px;
	cursor: pointer;
	display: block;
	line-height: 100%;
	outline: 0;
	padding: 11px 15px 12px;
	text-align: center;
	transition: box-shadow .05s ease-in-out, opacity .05s ease-in-out;
	user-select: none;
	-webkit-user-select: none;
	touch-action: manipulation;
	font-family: sans-serif;
}

button:hover {
	box-shadow: rgba(255, 255, 255, 0.3) 0 0 2px inset, rgba(0, 0, 0, 0.4) 0 1px 2px;
	text-decoration: none;
	transition-duration: .15s, .15s;
}

button:active {
	box-shadow: rgba(0, 0, 0, 0.15) 0 2px 4px inset, rgba(0, 0, 0, 0.4) 0 1px 1px;
}

button:disabled {
	cursor: not-allowed;
	opacity: .6;
}

button:disabled:active {
	pointer-events: none;
}

button:disabled:hover {
	box-shadow: none;
}

.half_width_td {
	vertical-align: baseline;
	width: 50%;
}

#scads_bar {
	width: 100%;
	margin: 0;
	padding: 0;
	user-select: none;
	user-drag: none;
	-webkit-user-drag: none;
	user-select: none;
	-moz-user-select: none;
	-webkit-user-select: none;
	-ms-user-select: none;
	display: -webkit-box;
}

.tab {
	display: inline-block;
	padding: 0px;
	margin: 0px;
	font-size: 16px;
	font-weight: bold;
	text-align: center;
	border-radius: 25px;
	text-decoration: none !important;
	transition: background-color 0.3s, color 0.3s;
	color: unset !important;
}

.tooltipster-base {
	border: 1px solid black;
	position: absolute;
	border-radius: 8px;
	padding: 2px;
	color: white;
	background-color: #61686f;
	width: 70%;
	min-width: 200px;
	pointer-events: none;
}

td {
	padding-top: 3px;
	padding-bottom: 3px;
}

.left_side {
	text-align: right;
}

.right_side {
	text-align: left;
}

.spinner {
	border: 8px solid rgba(0, 0, 0, 0.1);
	border-left: 8px solid #3498db;
	border-radius: 50%;
	width: 50px;
	height: 50px;
	animation: spin 1s linear infinite;
}

@keyframes spin {
	0% {
		transform: rotate(0deg);
	}

	100% {
		transform: rotate(360deg);
	}
}

#spinner-overlay {
	-webkit-text-stroke: 1px black;
	white !important;
	position: fixed;
	top: 0;
	left: 0;
	width: 100%;
	height: 100%;
	display: flex;
	justify-content: center;
	align-items: center;
	z-index: 9999;
}

#spinner-container {
	text-align: center;
	color: #fff;
	display: contents;
}

#spinner-text {
	font-size: 3vw;
	margin-left: 10px;
}

a, a:visited, a:active, a:hover, a:link {
	color: #007bff;
	text-decoration: none;
}

.copy-container {
	display: inline-block;
	position: relative;
	cursor: pointer;
	margin-left: 10px;
	color: blue;
}

.copy-container:hover {
	text-decoration: underline;
}

.clipboard-icon {
	position: absolute;
	top: 5px;
	right: 5px;
	font-size: 1.5em;
}

#main_tab {
	overflow: scroll;
	width: max-content;
}

.ui-tabs .ui-tabs-nav li {
	user-select: none;
}

.stacktrace_table {
	background-color: black !important;
	color: white !important;
}

#breadcrumb {
	user-select: none;
}

#statusBar {
	user-select: none;
}

.error_line {
	background-color: red !important;
	color: white !important;
}

.header_table {
	border: 0px !important;
	padding: 0px !important;
	width: revert !important;
	min-width: revert !important;
}

.img_auto_width {
	max-width: revert !important;
}

#main_dir_or_plot_view {
	display: inline-grid;
}

#refresh_button {
	width: 300px;
}

._share_link {
	color: black !important;
}

#footer_element {
	height: 30px;
	background-color: #f8f9fa;
	padding: 0px;
	text-align: center;
	border-top: 1px solid #dee2e6;
	width: 100%;
	box-sizing: border-box;
	position: fixed;
	bottom: 0;
	z-index: 2;
	margin-left: -9px;
	z-index: 99;
}

.switch {
	position: relative;
	display: inline-block;
	width: 50px;
	height: 26px;
}

.switch input {
	opacity: 0;
	width: 0;
	height: 0;
}

.slider {
	position: absolute;
	cursor: pointer;
	top: 0;
	left: 0;
	right: 0;
	bottom: 0;
	background-color: #ccc;
	transition: .4s;
	border-radius: 26px;
}

.slider:before {
	position: absolute;
	content: "";
	height: 20px;
	width: 20px;
	left: 3px;
	bottom: 3px;
	background-color: white;
	transition: .4s;
	border-radius: 50%;
}

input:checked + .slider {
	background-color: #444;
}

input:checked + .slider:before {
	transform: translateX(24px);
}

.mode-text {
	position: absolute;
	top: 5px;
	left: 65px;
	font-size: 14px;
	color: black;
	transition: .4s;
	width: 65px;
	display: block;
	font-size: 0.7rem;
	text-align: center;
}

input:checked + .slider .mode-text {
	content: "Dark Mode";
	color: white;
}

#mainContent {
	height: fit-content;
	min-height: 100%;
}

li {
	text-align: left;
}

#share_path {
	margin-bottom: 20px;
	margin-top: 20px;
}

#sortForm {
	margin-bottom: 20px;
}

.share_folder_buttons {
	margin-top: 10px;
	margin-bottom: 10px;
}

.nav_tab_button {
	margin: 10px;
}

.header_table {
	margin: 10px;
}

.no_border {
	border: unset !important;
}

.gui_table {
	padding: 5px !important;
}

.gui_parameter_row {
}

.gui_parameter_row_cell {
	border: unset !important;
}

.gui_param_table {
	width: 95%;
	margin: unset !important;
}

table td, table tr,
.parameterRow table {
	padding: 2px !important;
}

.parameterRow table {
	margin: 0px;
	border: unset;
}

.parameterRow > td {
	border: 0px !important;
}

.parameter_config_table td, .parameter_config_table tr, #config_table th, #config_table td, #hidden_config_table th, #hidden_config_table td {
	border: 0px !important;
}

.green_text {
	color: green;
}

.remove_parameter {
	white-space: pre;
}

select {
	appearance: none;
	-webkit-appearance: none;
	-moz-appearance: none;
	background-color: #fff;
	color: #222;
	padding: 5px 30px 5px 5px;
	border: 1px solid #555;
	border-radius: 5px;
	cursor: pointer;
	outline: none;
	transition: all 0.3s ease;
	background:
		url("data:image/svg+xml;charset=UTF-8,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 10 6'%3E%3Cpath fill='%23888' d='M0 0l5 6 5-6z'/%3E%3C/svg%3E")
		no-repeat right 10px center,
	linear-gradient(180deg, #fff, #ecebe5 86%, #d8d0c4);
	background-size: 12px, auto;
}

select:hover {
	border-color: #888;
}

select:focus {
	border-color: #4caf50;
	box-shadow: 0 0 5px rgba(76, 175, 80, 0.5);
}

select::-ms-expand {
	display: none;
}

input, textarea {
	border-radius: 5px;
	border: solid 1px;
}

#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: sans-serif;
}

.gridjs-th-content {
	overflow: visible !important;
}

.error_text {
	color: red;
}

h1, h2, h3, h4, h5, h6 {
	margin-top: 1em;
	font-weight: bold;
	color: #333;
	border-left: 5px solid #ccc;
	padding-left: 0.5em;
}

.no_cursive {
	font-style: normal;	
}

.caveat {
	background-color: #fff8b3;
	border: 1px solid #f2d600;
	padding: 1em 1em 1em 70px;
	position: relative;
	font-family: sans-serif;
	color: #665500;
	margin: 1em 0;
	border-radius: 4px;
}

.caveat h1, .caveat h2, .caveat h3, .caveat h4 {
	margin-top: 0;
	margin-bottom: 0.5em;
	font-weight: bold;
}

.caveat::before {
	content: "⚠️";
	font-size: 50px;
	line-height: 1;
	position: absolute;
	left: 10px;
	top: 50%;
	transform: translateY(-50%);
	pointer-events: none;
	user-select: none;
}

.caveat.warning::before { content: "⚠️"; }
.caveat.stop::before { content: "🛑"; }
.caveat.exclamation::before { content: "❗"; }
.caveat.alarm::before { content: "🚨"; }
.caveat.tip::before { content: "💡"; }

.tutorial_icon {
	display: inline-block;
	font-size: 1.3em;
	line-height: 1;
	vertical-align: middle;
	transform: translateY(-10%);
	padding: 0.2em 0;
}

.highlight {
	background-color: yellow;
	font-weight: bold;
}

#searchResults li {
	opacity: 0;
	transform: translateY(8px);
	animation: fadeInUp 0.3s ease-out forwards;
	animation-delay: 0.05s;
	list-style: none;
	margin-bottom: 5px;
}

@keyframes fadeInUp {
	to {
		opacity: 1;
		transform: translateY(0);
	}
}

.search_headline {
	font-weight: bold;
	margin-top: 1em;
	margin-bottom: 0.3em;
	color: #444;
}

.search_share_path {
	color: black;
	display: block ruby;
	margin-top: 20px;
}

@media print {
	#scads_bar {
		display: none !important;
	}
}

/*! XP.css v0.2.6 - https: //botoxparty.github.io/XP.css/ */
body{
	color: #222
}

.surface{
	background: #ece9d8
}

u{
	text-decoration: none;
	border-bottom: .5px solid #222
}

a{
	color: #00f
}

a: focus{
	outline: 1px dotted #00f
}

code,code *{
	font-family: monospace
}

pre{
	display: block;
	padding: 12px 8px;
	background-color: #000;
	color: silver;
	font-size: 1rem;
	margin: 0;
	overflow: scroll;
}

summary: focus{
	outline: 1px dotted #000
}

: :-webkit-scrollbar{
	width: 16px
}

: :-webkit-scrollbar: horizontal{
	height: 17px
}

: :-webkit-scrollbar-track{
	background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='2' height='2' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M1 0H0v1h1v1h1V1H1V0z' fill='silver'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 0H1v1H0v1h1V1h1V0z' fill='%23fff'/%3E%3C/svg%3E")
}

: :-webkit-scrollbar-thumb{
	background-color: #dfdfdf;
	box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #fff,inset -2px -2px grey,inset 2px 2px #dfdfdf
}

: :-webkit-scrollbar-button: horizontal: end: increment,: :-webkit-scrollbar-button: horizontal: start: decrement,: :-webkit-scrollbar-button: vertical: end: increment,: :-webkit-scrollbar-button: vertical: start: decrement{
	display: block
}

: :-webkit-scrollbar-button: vertical: start{
	background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 6H7v1H6v1H5v1H4v1h7V9h-1V8H9V7H8V6z' fill='%23000'/%3E%3C/svg%3E")
}

: :-webkit-scrollbar-button: vertical: end{
	background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 6H4v1h1v1h1v1h1v1h1V9h1V8h1V7h1V6z' fill='%23000'/%3E%3C/svg%3E")
}

: :-webkit-scrollbar-button: horizontal: start{
	width: 16px;
	background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 4H8v1H7v1H6v1H5v1h1v1h1v1h1v1h1V4z' fill='%23000'/%3E%3C/svg%3E")
}

: :-webkit-scrollbar-button: horizontal: end{
	width: 16px;
	background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M7 4H6v7h1v-1h1V9h1V8h1V7H9V6H8V5H7V4z' fill='%23000'/%3E%3C/svg%3E")
}

button{
	border: none;
	background: #ece9d8;
	box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #fff,inset -2px -2px grey,inset 2px 2px #dfdfdf;
	border-radius: 0;
	min-width: 75px;
	min-height: 23px;
	padding: 0 12px
}

button: not(: disabled).active,button: not(: disabled): active{
	box-shadow: inset -1px -1px #fff,inset 1px 1px #0a0a0a,inset -2px -2px #dfdfdf,inset 2px 2px grey
}

button.focused,button: focus{
	outline: 1px dotted #000;
	outline-offset: -4px
}

label{
	display: inline-flex;
	align-items: center
}

textarea{
	padding: 3px 4px;
	border: none;
	background-color: #fff;
	box-sizing: border-box;
	-webkit-appearance: none;
	-moz-appearance: none;
	appearance: none;
	border-radius: 0
}

textarea: focus{
	outline: none
}

select: focus option{
	color: #000;
	background-color: #fff
}

.vertical-bar{
	width: 4px;
	height: 20px;
	background: silver;
	box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #fff,inset -2px -2px grey,inset 2px 2px #dfdfdf
}

&: disabled,&: disabled+label{
	color: grey;
	text-shadow: 1px 1px 0 #fff
}

input[type=radio]+label{
	line-height: 13px;
	position: relative;
	margin-left: 19px
}

input[type=radio]+label: before{
	content: "";
	position: absolute;
	top: 0;
	left: -19px;
	display: inline-block;
	width: 13px;
	height: 13px;
	margin-right: 6px;
	background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='12' height='12' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 0H4v1H2v1H1v2H0v4h1v2h1V8H1V4h1V2h2V1h4v1h2V1H8V0z' fill='gray'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 1H4v1H2v2H1v4h1v1h1V8H2V4h1V3h1V2h4v1h2V2H8V1z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 3h1v1H9V3zm1 5V4h1v4h-1zm-2 2V9h1V8h1v2H8zm-4 0v1h4v-1H4zm0 0V9H2v1h2z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 2h-1v2h1v4h-1v2H8v1H4v-1H2v1h2v1h4v-1h2v-1h1V8h1V4h-1V2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M4 2h4v1h1v1h1v4H9v1H8v1H4V9H3V8H2V4h1V3h1V2z' fill='%23fff'/%3E%3C/svg%3E")
}

input[type=radio]: active+label: before{
	background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='12' height='12' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 0H4v1H2v1H1v2H0v4h1v2h1V8H1V4h1V2h2V1h4v1h2V1H8V0z' fill='gray'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 1H4v1H2v2H1v4h1v1h1V8H2V4h1V3h1V2h4v1h2V2H8V1z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 3h1v1H9V3zm1 5V4h1v4h-1zm-2 2V9h1V8h1v2H8zm-4 0v1h4v-1H4zm0 0V9H2v1h2z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 2h-1v2h1v4h-1v2H8v1H4v-1H2v1h2v1h4v-1h2v-1h1V8h1V4h-1V2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M4 2h4v1h1v1h1v4H9v1H8v1H4V9H3V8H2V4h1V3h1V2z' fill='silver'/%3E%3C/svg%3E")
}

input[type=radio]: checked+label: after{
	content: "";
	display: block;
	width: 5px;
	height: 5px;
	top: 5px;
	left: -14px;
	position: absolute;
	background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='4' height='4' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M3 0H1v1H0v2h1v1h2V3h1V1H3V0z' fill='%23000'/%3E%3C/svg%3E")
}

input[type=radio][disabled]+label: before{
	background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='12' height='12' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 0H4v1H2v1H1v2H0v4h1v2h1V8H1V4h1V2h2V1h4v1h2V1H8V0z' fill='gray'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 1H4v1H2v2H1v4h1v1h1V8H2V4h1V3h1V2h4v1h2V2H8V1z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 3h1v1H9V3zm1 5V4h1v4h-1zm-2 2V9h1V8h1v2H8zm-4 0v1h4v-1H4zm0 0V9H2v1h2z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 2h-1v2h1v4h-1v2H8v1H4v-1H2v1h2v1h4v-1h2v-1h1V8h1V4h-1V2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M4 2h4v1h1v1h1v4H9v1H8v1H4V9H3V8H2V4h1V3h1V2z' fill='silver'/%3E%3C/svg%3E")
}

input[type=radio][disabled]: checked+label: after{
	background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='4' height='4' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M3 0H1v1H0v2h1v1h2V3h1V1H3V0z' fill='gray'/%3E%3C/svg%3E")
}

input[type=email],input[type=password]{
	padding: 3px 4px;
	border: 1px solid #7f9db9;
	background-color: #fff;
	box-sizing: border-box;
	-webkit-appearance: none;
	-moz-appearance: none;
	appearance: none;
	border-radius: 0;
	height: 21px;
	line-height: 2
}

input[type=email]: focus,input[type=password]: focus{
	outline: none
}

input[type=range]{
	-webkit-appearance: none;
	width: 100%;
	background: transparent
}

input[type=range]: focus{
	outline: none
}

input[type=range]: :-webkit-slider-thumb{
	-webkit-appearance: none;
	background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v16h2v2h2v2h1v-1H3v-2H1V1h9V0z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M1 1v15h1v1h1v1h1v1h2v-1h1v-1h1v-1h1V1z' fill='%23C0C7C8'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v15H8v2H6v2H5v-1h2v-2h2z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v16H9v2H7v2H5v1h1v-2h2v-2h2z' fill='%23000'/%3E%3C/svg%3E")
}

input[type=range]: :-moz-range-thumb{
	background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v16h2v2h2v2h1v-1H3v-2H1V1h9V0z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M1 1v15h1v1h1v1h1v1h2v-1h1v-1h1v-1h1V1z' fill='%23C0C7C8'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v15H8v2H6v2H5v-1h2v-2h2z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v16H9v2H7v2H5v1h1v-2h2v-2h2z' fill='%23000'/%3E%3C/svg%3E")
}

input[type=range]: :-webkit-slider-runnable-track{
	background: #000;
	border-right: 1px solid grey;
	border-bottom: 1px solid grey;
	box-shadow: 1px 0 0 #fff,1px 1px 0 #fff,0 1px 0 #fff,-1px 0 0 #a9a9a9,-1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,-1px 1px 0 #fff,1px -1px #a9a9a9
}

input[type=range]: :-moz-range-track{
	background: #000;
	border-right: 1px solid grey;
	border-bottom: 1px solid grey;
	box-shadow: 1px 0 0 #fff,1px 1px 0 #fff,0 1px 0 #fff,-1px 0 0 #a9a9a9,-1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,-1px 1px 0 #fff,1px -1px #a9a9a9
}

input[type=range].has-box-indicator: :-webkit-slider-thumb{
	background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v20h1V1h9V0z' fill='%23fff'/%3E%3Cpath fill='%23C0C7C8' d='M1 1h8v18H1z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v19H1v-1h8z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v21H0v-1h10z' fill='%23000'/%3E%3C/svg%3E")
}

input[type=range].has-box-indicator: :-moz-range-thumb{
	background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v20h1V1h9V0z' fill='%23fff'/%3E%3Cpath fill='%23C0C7C8' d='M1 1h8v18H1z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v19H1v-1h8z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v21H0v-1h10z' fill='%23000'/%3E%3C/svg%3E")
}

.is-vertical{
	display: inline-block;
	width: 4px;
	height: 150px;
	transform: translateY(50%)
}

.is-vertical>input[type=range]{
	width: 150px;
	height: 4px;
	margin: 0 16px 0 10px;
	transform-origin: left;
	transform: rotate(270deg) translateX(calc(-50% + 8px))
}

.is-vertical>input[type=range]: :-webkit-slider-runnable-track{
	border-left: 1px solid grey;
	border-bottom: 1px solid grey;
	box-shadow: -1px 0 0 #fff,-1px 1px 0 #fff,0 1px 0 #fff,1px 0 0 #a9a9a9,1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,1px 1px 0 #fff,-1px -1px #a9a9a9
}

.is-vertical>input[type=range]: :-moz-range-track{
	border-left: 1px solid grey;
	border-bottom: 1px solid grey;
	box-shadow: -1px 0 0 #fff,-1px 1px 0 #fff,0 1px 0 #fff,1px 0 0 #a9a9a9,1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,1px 1px 0 #fff,-1px -1px #a9a9a9
}

.is-vertical>input[type=range]: :-webkit-slider-thumb{
	transform: translateY(-8px) scaleX(-1)
}

.is-vertical>input[type=range]: :-moz-range-thumb{
	transform: translateY(2px) scaleX(-1)
}

.is-vertical>input[type=range].has-box-indicator: :-webkit-slider-thumb{
	transform: translateY(-10px) scaleX(-1)
}

.is-vertical>input[type=range].has-box-indicator: :-moz-range-thumb{
	transform: translateY(0) scaleX(-1)
}

.window{
	font-size: 11px;
	box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #dfdfdf,inset -2px -2px grey,inset 2px 2px #fff;
	background: #ece9d8;
	padding: 3px
}

.window fieldset{
	margin-bottom: 9px
}

.title-bar{
	background: #000;
	padding: 3px 2px 3px 3px;
	display: flex;
	justify-content: space-between;
	align-items: center
}

.title-bar-text{
	font-weight: 700;
	color: #fff;
	letter-spacing: 0;
	margin-right: 24px
}

.title-bar-controls button{
	padding: 0;
	display: block;
	min-width: 16px;
	min-height: 14px
}

.title-bar-controls button: focus{
	outline: none
}

.window-body{
	margin: 8px
}

.window-body pre{
	margin: -8px
}

.status-bar{
	margin: 0 1px;
	display: flex;
	gap: 1px
}

.status-bar-field{
	box-shadow: inset -1px -1px #dfdfdf,inset 1px 1px grey;
	flex-grow: 1;
	padding: 2px 3px;
	margin: 0
}

ul.tree-view{
	display: block;
	background: #fff;
	padding: 6px;
	margin: 0
}

ul.tree-view li{
	list-style-type: none;
	margin-top: 3px
}

ul.tree-view a{
	text-decoration: none;
	color: #000
}

ul.tree-view a: focus{
	background-color: #2267cb;
	color: #fff
}

ul.tree-view ul{
	margin-top: 3px;
	margin-left: 16px;
	padding-left: 16px;
	border-left: 1px dotted grey
}

ul.tree-view ul>li{
	position: relative
}

ul.tree-view ul>li: before{
	content: "";
	display: block;
	position: absolute;
	left: -16px;
	top: 6px;
	width: 12px;
	border-bottom: 1px dotted grey
}

ul.tree-view ul>li: last-child: after{
	content: "";
	display: block;
	position: absolute;
	left: -20px;
	top: 7px;
	bottom: 0;
	width: 8px;
	background: #fff
}

ul.tree-view ul details>summary: before{
	margin-left: -22px;
	position: relative;
	z-index: 1
}

ul.tree-view details{
	margin-top: 0
}

ul.tree-view details>summary: before{
	text-align: center;
	display: block;
	float: left;
	content: "+";
	border: 1px solid grey;
	width: 8px;
	height: 9px;
	line-height: 9px;
	margin-right: 5px;
	padding-left: 1px;
	background-color: #fff
}

ul.tree-view details[open] summary{
	margin-bottom: 0
}

ul.tree-view details[open]>summary: before{
	content: "-"
}

fieldset{
	border-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='5' height='5' fill='gray' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0h5v5H0V2h2v1h1V2H0' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0h4v4H0V1h1v2h2V1H0'/%3E%3C/svg%3E") 2;
	padding: 10px;
	padding-block-start: 8px;
	margin: 0
}

legend{
	background: #ece9d8
}

menu[role=tablist]{
	position: relative;
	margin: 0 0 -2px;
	text-indent: 0;
	list-style-type: none;
	display: flex;
	padding-left: 3px
}

menu[role=tablist] button{
	z-index: 1;
	display: block;
	color: #222;
	text-decoration: none;
	min-width: unset
}

menu[role=tablist] button[aria-selected=true]{
	padding-bottom: 2px;margin-top: -2px;background-color: #ece9d8;position: relative;z-index: 8;margin-left: -3px;margin-bottom: 1px
}

menu[role=tablist] button: focus{
	outline: 1px dotted #222;outline-offset: -4px
}

menu[role=tablist].justified button{
	flex-grow: 1;text-align: center
}

[role=tabpanel]{
	padding: 14px;clear: both;background: linear-gradient(180deg,#fcfcfe,#f4f3ee);border: 1px solid #919b9c;position: relative;z-index: 2;margin-bottom: 9px
}

: :-webkit-scrollbar{
	width: 17px
}

: :-webkit-scrollbar-corner{
	background: #dfdfdf
}

: :-webkit-scrollbar-track: vertical{
	background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 17 1' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eeede5' d='M0 0h1m15 0h1'/%3E%3Cpath stroke='%23f3f1ec' d='M1 0h1'/%3E%3Cpath stroke='%23f4f1ec' d='M2 0h1'/%3E%3Cpath stroke='%23f4f3ee' d='M3 0h1'/%3E%3Cpath stroke='%23f5f4ef' d='M4 0h1'/%3E%3Cpath stroke='%23f6f5f0' d='M5 0h1'/%3E%3Cpath stroke='%23f7f7f3' d='M6 0h1'/%3E%3Cpath stroke='%23f9f8f4' d='M7 0h1'/%3E%3Cpath stroke='%23f9f9f7' d='M8 0h1'/%3E%3Cpath stroke='%23fbfbf8' d='M9 0h1'/%3E%3Cpath stroke='%23fbfbf9' d='M10 0h2'/%3E%3Cpath stroke='%23fdfdfa' d='M12 0h1'/%3E%3Cpath stroke='%23fefefb' d='M13 0h3'/%3E%3C/svg%3E")
}

: :-webkit-scrollbar-track: horizontal{
	background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 1 17' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eeede5' d='M0 0h1M0 16h1'/%3E%3Cpath stroke='%23f3f1ec' d='M0 1h1'/%3E%3Cpath stroke='%23f4f1ec' d='M0 2h1'/%3E%3Cpath stroke='%23f4f3ee' d='M0 3h1'/%3E%3Cpath stroke='%23f5f4ef' d='M0 4h1'/%3E%3Cpath stroke='%23f6f5f0' d='M0 5h1'/%3E%3Cpath stroke='%23f7f7f3' d='M0 6h1'/%3E%3Cpath stroke='%23f9f8f4' d='M0 7h1'/%3E%3Cpath stroke='%23f9f9f7' d='M0 8h1'/%3E%3Cpath stroke='%23fbfbf8' d='M0 9h1'/%3E%3Cpath stroke='%23fbfbf9' d='M0 10h1m-1 1h1'/%3E%3Cpath stroke='%23fdfdfa' d='M0 12h1'/%3E%3Cpath stroke='%23fefefb' d='M0 13h1m-1 1h1m-1 1h1'/%3E%3C/svg%3E")
}

: :-webkit-scrollbar-thumb{
	background-position: 50%;
	background-repeat: no-repeat;
	background-color: #c8d6fb;
	background-size: 7px;
	border: 1px solid #fff;
	border-radius: 2px;
	box-shadow: inset -3px 0 #bad1fc,inset 1px 1px #b7caf5
}

: :-webkit-scrollbar-thumb: vertical{
	background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 7 8' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eef4fe' d='M0 0h6M0 2h6M0 4h6M0 6h6'/%3E%3Cpath stroke='%23bad1fc' d='M6 0h1M6 2h1M6 4h1'/%3E%3Cpath stroke='%23c8d6fb' d='M0 1h1M0 3h1M0 5h1M0 7h1'/%3E%3Cpath stroke='%238cb0f8' d='M1 1h6M1 3h6M1 5h6M1 7h6'/%3E%3Cpath stroke='%23bad3fc' d='M6 6h1'/%3E%3C/svg%3E")
}

: :-webkit-scrollbar-thumb: horizontal{
	background-size: 8px;background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 8 7' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eef4fe' d='M0 0h1m1 0h1m1 0h1m1 0h1M0 1h1m1 0h1m1 0h1m1 0h1M0 2h1m1 0h1m1 0h1m1 0h1M0 3h1m1 0h1m1 0h1m1 0h1M0 4h1m1 0h1m1 0h1m1 0h1M0 5h1m1 0h1m1 0h1m1 0h1'/%3E%3Cpath stroke='%23c8d6fb' d='M1 0h1m1 0h1m1 0h1m1 0h1'/%3E%3Cpath stroke='%238cb0f8' d='M1 1h1m1 0h1m1 0h1m1 0h1M1 2h1m1 0h1m1 0h1m1 0h1M1 3h1m1 0h1m1 0h1m1 0h1M1 4h1m1 0h1m1 0h1m1 0h1M1 5h1m1 0h1m1 0h1m1 0h1M1 6h1m1 0h1m1 0h1m1 0h1'/%3E%3Cpath stroke='%23bad1fc' d='M0 6h1m1 0h1'/%3E%3Cpath stroke='%23bad3fc' d='M4 6h1m1 0h1'/%3E%3C/svg%3E")
}

: :-webkit-scrollbar-button: vertical: start{
	height: 17px;
	background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 17 17' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eeede5' d='M0 0h1m15 0h1M0 1h1M0 2h1M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m15 0h1M0 16h1m15 0h1'/%3E%3Cpath stroke='%23fdfdfa' d='M1 0h1'/%3E%3Cpath stroke='%23fff' d='M2 0h14M1 1h1m13 0h1M1 2h1m13 0h1M1 3h1m13 0h1M1 4h1m13 0h1M1 5h1m13 0h1M1 6h1m13 0h1M1 7h1m13 0h1M1 8h1m13 0h1M1 9h1m13 0h1M1 10h1m13 0h1M1 11h1m13 0h1M1 12h1m13 0h1M1 13h1m13 0h1M1 14h1m13 0h1M2 15h13'/%3E%3Cpath stroke='%23e6eefc' d='M2 1h1'/%3E%3Cpath stroke='%23d0dffc' d='M3 1h1M2 2h1'/%3E%3Cpath stroke='%23cad8f9' d='M4 1h1M2 3h1'/%3E%3Cpath stroke='%23c4d2f7' d='M5 1h1'/%3E%3Cpath stroke='%23c0d0f7' d='M6 1h1'/%3E%3Cpath stroke='%23bdcef7' d='M7 1h1M2 6h1'/%3E%3Cpath stroke='%23bbcdf5' d='M8 1h1'/%3E%3Cpath stroke='%23b8cbf6' d='M9 1h1M2 7h1'/%3E%3Cpath stroke='%23b7caf5' d='M10 1h1M2 8h1'/%3E%3Cpath stroke='%23b5c8f7' d='M11 1h1'/%3E%3Cpath stroke='%23b3c7f5' d='M12 1h1'/%3E%3Cpath stroke='%23afc5f4' d='M13 1h1'/%3E%3Cpath stroke='%23dce6f9' d='M14 1h1'/%3E%3Cpath stroke='%23dfe2e1' d='M16 1h1'/%3E%3Cpath stroke='%23e1eafe' d='M3 2h1'/%3E%3Cpath stroke='%23dae6fe' d='M4 2h1M3 3h1'/%3E%3Cpath stroke='%23d4e1fc' d='M5 2h1M3 4h1'/%3E%3Cpath stroke='%23d1e0fd' d='M6 2h1M4 4h1'/%3E%3Cpath stroke='%23d0ddfc' d='M7 2h1M3 5h1'/%3E%3Cpath stroke='%23cedbfd' d='M8 2h1M6 3h1'/%3E%3Cpath stroke='%23cad9fd' d='M9 2h1M7 3h1M5 5h1'/%3E%3Cpath stroke='%23c8d8fb' d='M10 2h1'/%3E%3Cpath stroke='%23c5d6fc' d='M11 2h1m-8 8h1m1 0h1'/%3E%3Cpath stroke='%23c2d3fc' d='M12 2h1m-2 1h1m-9 7h1m0 1h1'/%3E%3Cpath stroke='%23bccefa' d='M13 2h1m-1 2h1m-9 9h2'/%3E%3Cpath stroke='%23b9c9f3' d='M14 2h1M5 14h3'/%3E%3Cpath stroke='%23cfd7dd' d='M16 2h1'/%3E%3Cpath stroke='%23d8e3fc' d='M4 3h1'/%3E%3Cpath stroke='%23d1defd' d='M5 3h1'/%3E%3Cpath stroke='%23c9d8fc' d='M8 3h1M6 4h2M5 6h2M3 7h1'/%3E%3Cpath stroke='%23c5d5fc' d='M9 3h1M3 9h1m3 0h1'/%3E%3Cpath stroke='%23c5d3fc' d='M10 3h1'/%3E%3Cpath stroke='%23bed0fc' d='M12 3h1M9 4h1m-7 7h1m0 1h1'/%3E%3Cpath stroke='%23bccdfa' d='M13 3h1'/%3E%3Cpath stroke='%23baccf4' d='M14 3h1'/%3E%3Cpath stroke='%23bdcbda' d='M16 3h1'/%3E%3Cpath stroke='%23c4d4f7' d='M2 4h1'/%3E%3Cpath stroke='%23cddbfc' d='M5 4h1M3 6h1'/%3E%3Cpath stroke='%23c8d5fb' d='M8 4h1'/%3E%3Cpath stroke='%23bbcefd' d='M10 4h3M9 5h1'/%3E%3Cpath stroke='%23bcccf3' d='M14 4h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b1c2d5' d='M16 4h1'/%3E%3Cpath stroke='%23bed0f8' d='M2 5h1'/%3E%3Cpath stroke='%23ceddfd' d='M4 5h1'/%3E%3Cpath stroke='%23c8d6fb' d='M6 5h2M3 8h2'/%3E%3Cpath stroke='%234d6185' d='M8 5h1M7 6h3M6 7h5M5 8h3m1 0h3M4 9h3m3 0h3m-8 1h1m5 0h1'/%3E%3Cpath stroke='%23bacdfc' d='M10 5h1m1 0h2M3 12h1'/%3E%3Cpath stroke='%23b9cdfb' d='M11 5h1m-2 1h1m1 0h2m-1 1h1'/%3E%3Cpath stroke='%23a8bbd4' d='M16 5h1'/%3E%3Cpath stroke='%23cddafc' d='M4 6h1'/%3E%3Cpath stroke='%23b7cdfc' d='M11 6h1m0 1h1'/%3E%3Cpath stroke='%23a4b8d3' d='M16 6h1'/%3E%3Cpath stroke='%23cad8fd' d='M4 7h2'/%3E%3Cpath stroke='%23b6cefb' d='M11 7h1m0 1h1'/%3E%3Cpath stroke='%23bacbf4' d='M14 7h1'/%3E%3Cpath stroke='%23a0b5d3' d='M16 7h1m-1 1h1m-1 5h1'/%3E%3Cpath stroke='%23c1d3fb' d='M8 8h1'/%3E%3Cpath stroke='%23b6cdfb' d='M13 8h1m-5 5h1'/%3E%3Cpath stroke='%23b9cbf3' d='M14 8h1'/%3E%3Cpath stroke='%23b4c8f6' d='M2 9h1'/%3E%3Cpath stroke='%23c2d5fc' d='M8 9h1m-1 1h1m-3 1h2'/%3E%3Cpath stroke='%23bdd3fb' d='M9 9h1m-2 3h1'/%3E%3Cpath stroke='%23b5cdfa' d='M13 9h1'/%3E%3Cpath stroke='%23b5c9f3' d='M14 9h1'/%3E%3Cpath stroke='%239fb5d2' d='M16 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b1c7f6' d='M2 10h1'/%3E%3Cpath stroke='%23c3d5fd' d='M7 10h1'/%3E%3Cpath stroke='%23bad4fc' d='M9 10h1m-1 1h1'/%3E%3Cpath stroke='%23b2cffb' d='M10 10h1m1 0h1m-2 2h1'/%3E%3Cpath stroke='%23b1cbfa' d='M13 10h1'/%3E%3Cpath stroke='%23b3c8f5' d='M14 10h1m-6 4h2'/%3E%3Cpath stroke='%23adc3f6' d='M2 11h1'/%3E%3Cpath stroke='%23c3d3fd' d='M5 11h1'/%3E%3Cpath stroke='%23c1d5fb' d='M8 11h1'/%3E%3Cpath stroke='%23b7d3fc' d='M10 11h1m-2 1h1'/%3E%3Cpath stroke='%23b3d1fc' d='M11 11h1'/%3E%3Cpath stroke='%23afcefb' d='M12 11h1'/%3E%3Cpath stroke='%23aecafa' d='M13 11h1'/%3E%3Cpath stroke='%23b1c8f3' d='M14 11h1'/%3E%3Cpath stroke='%23acc2f5' d='M2 12h1'/%3E%3Cpath stroke='%23c1d2fb' d='M5 12h1'/%3E%3Cpath stroke='%23bed1fc' d='M6 12h2'/%3E%3Cpath stroke='%23b6d1fb' d='M10 12h1'/%3E%3Cpath stroke='%23afccfb' d='M12 12h1'/%3E%3Cpath stroke='%23adc9f9' d='M13 12h1m-2 1h1'/%3E%3Cpath stroke='%23b1c5f3' d='M14 12h1'/%3E%3Cpath stroke='%23aac0f3' d='M2 13h1'/%3E%3Cpath stroke='%23b7cbf9' d='M3 13h1'/%3E%3Cpath stroke='%23b9cefb' d='M4 13h1'/%3E%3Cpath stroke='%23bbcef9' d='M7 13h1'/%3E%3Cpath stroke='%23b9cffb' d='M8 13h1'/%3E%3Cpath stroke='%23b2cdfb' d='M10 13h1'/%3E%3Cpath stroke='%23b0cbf9' d='M11 13h1'/%3E%3Cpath stroke='%23aec8f7' d='M13 13h1'/%3E%3Cpath stroke='%23b0c5f2' d='M14 13h1'/%3E%3Cpath stroke='%23dbe3f8' d='M2 14h1'/%3E%3Cpath stroke='%23b7c6f1' d='M3 14h1'/%3E%3Cpath stroke='%23b8c9f2' d='M4 14h1m3 0h1'/%3E%3Cpath stroke='%23b2c8f4' d='M11 14h1'/%3E%3Cpath stroke='%23b1c6f3' d='M12 14h1'/%3E%3Cpath stroke='%23b0c4f2' d='M13 14h1'/%3E%3Cpath stroke='%23d9e3f6' d='M14 14h1'/%3E%3Cpath stroke='%23aec0d6' d='M16 14h1'/%3E%3Cpath stroke='%23c3d4e7' d='M1 15h1'/%3E%3Cpath stroke='%23aec4e5' d='M15 15h1'/%3E%3Cpath stroke='%23edf1f3' d='M1 16h1'/%3E%3Cpath stroke='%23aac0e1' d='M2 16h1'/%3E%3Cpath stroke='%2394b1d9' d='M3 16h1'/%3E%3Cpath stroke='%2388a7d8' d='M4 16h1'/%3E%3Cpath stroke='%2383a4d3' d='M5 16h1'/%3E%3Cpath stroke='%237da0d4' d='M6 16h1m3 0h3'/%3E%3Cpath stroke='%237e9fd2' d='M7 16h1'/%3E%3Cpath stroke='%237c9fd3' d='M8 16h2'/%3E%3Cpath stroke='%2382a4d6' d='M13 16h1'/%3E%3Cpath stroke='%2394b0dd' d='M14 16h1'/%3E%3Cpath stroke='%23ecf2f7' d='M15 16h1'/%3E%3C/svg%3E")
}

: :-webkit-scrollbar-button: vertical: end{
	height: 17px;
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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='%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%;
	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]): :-moz-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])::-moz-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])::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])::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;
}
Element {
}
progress:not([value]) {
	position: relative;
}
progress:not([value]) {
	-moz-box-shadow: inset 0 0 1px 0 #686868;
	-webkit-box-shadow: inset 0 0 1px 0 #686868;
	height: 14px;
}

		</style>
	</head>
	<body>
		<script>
			var log = console.log;
			var theme = 'light';

			var special_col_names = ["trial_index","arm_name","trial_status","generation_method","generation_node","hostname","run_time","start_time","exit_code","signal","end_time","program_string","submit_time","queue_time"]

var result_names = [
    "ACCURACY",
    "RUNTIME"
];
var result_min_max = [
    "max",
    "min"
];
var tab_results_headers_json = [
    "trial_index",
    "arm_name",
    "trial_status",
    "generation_method",
    "generation_node",
    "ACCURACY",
    "RUNTIME",
    "recent_samples_size",
    "n_samples",
    "const",
    "max_depth",
    "threshold"
];
var tab_results_csv_json = [
    [
        0,
        "0_0",
        "COMPLETED",
        "Sobol",
        "GenerationStep_0",
        0.7000000000000001,
        3,
        1620,
        4143,
        7.98291948068142,
        4,
        0.8822874935865402
    ],
    [
        1,
        "1_0",
        "COMPLETED",
        "Sobol",
        "GenerationStep_0",
        0.73,
        27,
        2909,
        109,
        4.800845133917407,
        11,
        0.40107114133797583
    ],
    [
        2,
        "2_0",
        "COMPLETED",
        "Sobol",
        "GenerationStep_0",
        0.6900000000000001,
        5,
        4528,
        3583,
        6.47453096901346,
        10,
        0.2375081801265478
    ],
    [
        3,
        "3_0",
        "COMPLETED",
        "Sobol",
        "GenerationStep_0",
        0.64,
        3,
        660,
        2012,
        0.7439978747218847,
        18,
        0.7192039896324277
    ],
    [
        4,
        "4_0",
        "COMPLETED",
        "Sobol",
        "GenerationStep_0",
        0.67,
        2,
        610,
        3005,
        3.434259827704169,
        20,
        0.509026851631701
    ],
    [
        5,
        "5_0",
        "COMPLETED",
        "Sobol",
        "GenerationStep_0",
        0.6900000000000001,
        5,
        4243,
        1412,
        8.803615154411643,
        7,
        0.027323190048336984
    ],
    [
        6,
        "6_0",
        "COMPLETED",
        "Sobol",
        "GenerationStep_0",
        0.6900000000000001,
        3,
        3323,
        4896,
        2.422758724032901,
        14,
        0.36339986271224917
    ],
    [
        7,
        "7_0",
        "COMPLETED",
        "Sobol",
        "GenerationStep_0",
        0.67,
        2,
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    [
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];
var tab_main_worker_cpu_ram_csv_json = [
    [
        1745405554,
        633.96484375,
        34.9
    ],
    [
        1745405554,
        633.96875,
        42.6
    ],
    [
        1745405554,
        633.96875,
        42.4
    ],
    [
        1745405554,
        633.96875,
        44.7
    ],
    [
        1745405554,
        633.96875,
        33.3
    ],
    [
        1745405554,
        633.96875,
        45.5
    ],
    [
        1745405554,
        633.96875,
        42.6
    ],
    [
        1745406104,
        683.34375,
        44.6
    ],
    [
        1745406104,
        683.34375,
        35
    ],
    [
        1745406104,
        683.34375,
        42
    ],
    [
        1745406104,
        683.34375,
        48.8
    ],
    [
        1745416073,
        924.0703125,
        42.2
    ],
    [
        1745416073,
        924.0703125,
        44.2
    ],
    [
        1745416073,
        924.0703125,
        44.2
    ],
    [
        1745416073,
        924.0703125,
        43.2
    ],
    [
        1745428529,
        968.9609375,
        37.5
    ],
    [
        1745428529,
        968.9609375,
        34.7
    ],
    [
        1745428529,
        968.9609375,
        33.1
    ],
    [
        1745428529,
        968.9609375,
        34
    ],
    [
        1745439158,
        980.9921875,
        42.2
    ],
    [
        1745439158,
        980.9921875,
        43.1
    ],
    [
        1745439158,
        980.9921875,
        42.9
    ],
    [
        1745439158,
        980.9921875,
        45
    ],
    [
        1745449944,
        1057.578125,
        40.8
    ],
    [
        1745449944,
        1057.578125,
        38
    ],
    [
        1745449944,
        1057.578125,
        39.9
    ],
    [
        1745449944,
        1057.578125,
        25.8
    ],
    [
        1745462646,
        1016.5703125,
        41.4
    ],
    [
        1745462646,
        1016.5703125,
        44.6
    ],
    [
        1745462646,
        1016.5703125,
        43.7
    ],
    [
        1745462646,
        1016.5703125,
        43.7
    ],
    [
        1745476633,
        1030.59375,
        42.8
    ],
    [
        1745476633,
        1030.59375,
        36.9
    ],
    [
        1745476633,
        1030.59375,
        37.8
    ],
    [
        1745476633,
        1030.59375,
        23.7
    ],
    [
        1745489592,
        1063.625,
        40.1
    ],
    [
        1745489592,
        1063.625,
        39.3
    ],
    [
        1745489592,
        1063.625,
        40.7
    ],
    [
        1745489592,
        1063.625,
        45.6
    ],
    [
        1745504911,
        1135.8046875,
        36.1
    ],
    [
        1745504911,
        1135.8046875,
        31.8
    ],
    [
        1745504911,
        1135.8046875,
        33.3
    ],
    [
        1745504911,
        1135.8046875,
        29.9
    ],
    [
        1745520226,
        1158.01171875,
        37.3
    ],
    [
        1745520227,
        1158.01171875,
        36
    ],
    [
        1745520227,
        1158.01171875,
        35.2
    ],
    [
        1745520227,
        1158.01171875,
        35.3
    ],
    [
        1745535616,
        1170.546875,
        37.6
    ],
    [
        1745535616,
        1170.546875,
        39.8
    ],
    [
        1745535616,
        1170.546875,
        38.1
    ],
    [
        1745535616,
        1170.546875,
        43.3
    ],
    [
        1745551038,
        1186.0234375,
        36.7
    ],
    [
        1745551038,
        1186.0234375,
        37.5
    ],
    [
        1745551038,
        1186.0234375,
        38.1
    ],
    [
        1745551038,
        1186.0234375,
        33.3
    ],
    [
        1745569523,
        1195.8828125,
        37.3
    ],
    [
        1745569523,
        1195.8828125,
        39.8
    ],
    [
        1745569523,
        1195.8828125,
        39.9
    ],
    [
        1745569523,
        1195.8828125,
        37.3
    ],
    [
        1745588579,
        1220.015625,
        37.6
    ],
    [
        1745588579,
        1220.015625,
        37.1
    ],
    [
        1745588579,
        1220.015625,
        36.5
    ],
    [
        1745588579,
        1220.015625,
        34.6
    ],
    [
        1745603313,
        1275.97265625,
        36.8
    ],
    [
        1745603313,
        1275.97265625,
        38.8
    ],
    [
        1745603313,
        1275.97265625,
        38.2
    ],
    [
        1745603313,
        1275.97265625,
        44.2
    ],
    [
        1745631246,
        1300.24609375,
        37.3
    ],
    [
        1745631246,
        1300.24609375,
        37.7
    ],
    [
        1745631246,
        1300.24609375,
        36.5
    ],
    [
        1745631246,
        1300.24609375,
        35.3
    ]
];
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 = [], reload = false) {
	try {
		if ($("#parallel-plot").data("loaded") === "true" && !reload) {
			return;
		}

		// Filter rows ohne leere Werte (wie in deinem Originalcode)
		dataArray = filterNonEmptyRows(dataArray);

		const ignoreSet = new Set(ignoreColumns);
		const numericalCols = [];
		const categoricalCols = [];
		const categoryMappings = {};
		const enable_slurm_id_if_exists = $("#enable_slurm_id_if_exists").is(":checked");

		// Spalten einteilen in numerisch oder kategorisch + category mappings aufbauen
		headers.forEach((header, colIndex) => {
			if (ignoreSet.has(header)) return;
			if (!enable_slurm_id_if_exists && header === "OO_Info_SLURM_JOB_ID") 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]));
			}
		});

		// Erzeuge UI für Checkboxen und Min/Max Inputs für numerische Spalten
		const controlContainerId = "parallel-plot-controls";
		let controlContainer = $("#" + controlContainerId);
		if (controlContainer.length === 0) {
			controlContainer = $('<div id="' + controlContainerId + '" style="margin-bottom:10px; display: flex;"></div>');
			$("#parallel-plot").before(controlContainer);
		} else {
			controlContainer.empty();
		}

		// Map um Checkbox-Zustände und Min/Max-Werte zu speichern
		const columnVisibility = {};
		const minMaxLimits = {};

		// Checkboxen + Min/Max Felder generieren mit Boxen, max-Breite, Umbruch und Zeilenumbruch nach jeder Box
		headers.forEach((header) => {
			try {
				if (ignoreSet.has(header)) return;
				if (!enable_slurm_id_if_exists && header === "OO_Info_SLURM_JOB_ID") return;

				const isNumerical = numericalCols.some(col => col.name === header);

				const checkboxId = `chk_${header}`;
				const minInputId = `min_${header}`;
				const maxInputId = `max_${header}`;

				columnVisibility[header] = true;
				minMaxLimits[header] = { min: null, max: null };

				// Wrapper Box mit max-Breite, Umbruch, Block-Level-Element für newline nach jeder Box
				const boxWrapper = $('<div></div>').css({
					border: "1px solid #ddd",
					borderRadius: "8px",
					padding: "12px 16px",
					marginBottom: "12px",
					boxShadow: "0 2px 6px rgba(0,0,0,0.1)",
					backgroundColor: "#fff",
					display: "flex",
					flexWrap: "wrap",
					alignItems: "center",
					gap: "15px",
					maxWidth: "350px",
					width: "100%", // damit bei kleinen Screens die Box maximal voll breit ist
					boxSizing: "border-box"
				});

				// Innerer Container mit Flexbox für Ausrichtung der Elemente, flex-grow damit Inputs genug Platz bekommen
				const container = $('<div></div>').css({
					display: "flex",
					alignItems: "center",
					gap: "10px",
					flexWrap: "wrap",
					flexGrow: 1,
					minWidth: "0" // wichtig für flexbox Overflow Handling
				});

				// Checkbox mit Label
				const checkbox = $(`<input type="checkbox" id="${checkboxId}" checked />`);
				const label = $(`<label for="${checkboxId}" style="font-weight: 600; min-width: 140px; cursor: pointer; white-space: nowrap;">${header}</label>`);

				container.append(checkbox).append(label);

				if (isNumerical) {
					// Werte ermitteln (nur gültige Zahlen)
					const numericValues = dataArray
						.map(row => parseFloat(row[headers.indexOf(header)]))
						.filter(val => !isNaN(val));

					const minVal = numericValues.length > 0 ? Math.min(...numericValues) : 0;
					const maxVal = numericValues.length > 0 ? Math.max(...numericValues) : 100;

					// Min Input mit Label
					const minWrapper = $('<div></div>').css({
						display: "flex",
						flexDirection: "column",
						alignItems: "flex-start",
						minWidth: "90px"
					});
					const minLabel = $('<label></label>').attr("for", minInputId).text("Min").css({
						fontSize: "0.75rem",
						color: "#555",
						marginBottom: "2px"
					});
					const minInput = $(`<input type="number" id="${minInputId}" placeholder="min" />`).css({
						width: "80px",
						padding: "5px 8px",
						borderRadius: "5px",
						border: "1px solid #ccc",
						boxShadow: "inset 0 1px 3px rgba(0,0,0,0.1)",
						transition: "border-color 0.3s ease"
					});
					minInput.attr("min", minVal);
					minInput.attr("max", maxVal);

					minInput.on("focus", function () {
						$(this).css("border-color", "#007BFF");
					});
					minInput.on("blur", function () {
						$(this).css("border-color", "#ccc");
					});

					minWrapper.append(minLabel).append(minInput);

					// Max Input mit Label
					const maxWrapper = $('<div></div>').css({
						display: "flex",
						flexDirection: "column",
						alignItems: "flex-start",
						minWidth: "90px"
					});
					const maxLabel = $('<label></label>').attr("for", maxInputId).text("Max").css({
						fontSize: "0.75rem",
						color: "#555",
						marginBottom: "2px"
					});
					const maxInput = $(`<input type="number" id="${maxInputId}" placeholder="max" />`).css({
						width: "80px",
						padding: "5px 8px",
						borderRadius: "5px",
						border: "1px solid #ccc",
						boxShadow: "inset 0 1px 3px rgba(0,0,0,0.1)",
						transition: "border-color 0.3s ease"
					});
					maxInput.attr("min", minVal);
					maxInput.attr("max", maxVal);

					maxInput.on("focus", function () {
						$(this).css("border-color", "#007BFF");
					});
					maxInput.on("blur", function () {
						$(this).css("border-color", "#ccc");
					});

					maxWrapper.append(maxLabel).append(maxInput);

					// Events für min/max Eingaben
					minInput.on("input", function () {
						const val = parseFloat($(this).val());
						minMaxLimits[header].min = isNaN(val) ? null : val;
						updatePlot();
					});

					maxInput.on("input", function () {
						const val = parseFloat($(this).val());
						minMaxLimits[header].max = isNaN(val) ? null : val;
						updatePlot();
					});

					container.append(minWrapper).append(maxWrapper);
				}

				// Checkbox Change Event
				checkbox.on("change", function () {
					columnVisibility[header] = $(this).is(":checked");
					updatePlot();
				});

				boxWrapper.append(container);

				// Jede Box bekommt ihren eigenen Block (also newline)
				controlContainer.append(boxWrapper);
			} catch (error) {
				console.error(`Fehler bei Header '${header}':`, error);
			}
		});



		// Erzeuge Ergebnis-Auswahl für Farbskala (color by result)
		const resultSelectId = "result-select";
		let resultSelect = $(`#${resultSelectId}`);
		if (resultSelect.length === 0) {
			resultSelect = $(`<select id="${resultSelectId}"></select>`);
			controlContainer.before(resultSelect);
		} else {
			resultSelect.empty();
		}

		resultSelect.append('<option value="none">No color</option>');

		for (let i = 0; i < resultNames.length; i++) {
			let minMaxInfo = "min [auto]";
			if (typeof result_min_max !== "undefined" && result_min_max[i] !== undefined) {
				minMaxInfo = result_min_max[i];
			}
			resultSelect.append(`<option value="${resultNames[i]}">${resultNames[i]} (${minMaxInfo})</option>`);
		}

		let colorValues = null;
		let colorScale = null;

		resultSelect.off("change").on("change", function () {
			const selectedResult = $(this).val();
			if (selectedResult === "none") {
				colorValues = null;
				colorScale = null;
			} else {
				const col = numericalCols.find(c => c.name.toLowerCase() === selectedResult.toLowerCase());
				if (!col) {
					colorValues = null;
					colorScale = null;
					updatePlot();
					return;
				}
				colorValues = dataArray.map(row => parseFloat(row[col.index]));

				let invertColor = false;
				if (typeof result_min_max !== "undefined") {
					const idx = resultNames.indexOf(selectedResult);
					if (idx !== -1) {
						invertColor = result_min_max[idx] === "max";
					}
				}

				colorScale = invertColor
					? [[0, 'red'], [1, 'green']]
					: [[0, 'green'], [1, 'red']];
			}
			updatePlot();
		});

		// Initial Auswahl: kein Farbwert, oder erstes Ergebnis falls nur eins
		if (resultNames.length === 1) {
			resultSelect.val(resultNames[0]).trigger("change");
		} else {
			resultSelect.val("none").trigger("change");
		}

		function updatePlot() {
			try {
				// Filter Spalten nach Checkboxen
				const filteredNumericalCols = numericalCols.filter(col => columnVisibility[col.name]);
				const filteredCategoricalCols = categoricalCols.filter(col => columnVisibility[col.name]);

				// Filtere die Datenzeilen, um nur die zu behalten, die innerhalb aller gesetzten Min/Max Limits liegen
				const filteredData = dataArray.filter(row => {
					for (let col of filteredNumericalCols) {
						const val = parseFloat(row[col.index]);
						if (isNaN(val)) return false; // ungültiger Wert raus

						const limits = minMaxLimits[col.name];
						if (limits.min !== null && val < limits.min) return false;
						if (limits.max !== null && val > limits.max) return false;
					}
					// Kategorische Werte ignorieren Filter (könntest hier evtl. erweitern)
					return true;
				});

				const dimensions = [];

				// Füge numerische Dimensionen hinzu mit Min/Max Limits (Range anhand gefilterter Daten)
				filteredNumericalCols.forEach(col => {
					let vals = filteredData.map(row => parseFloat(row[col.index]));

					// Fallback falls alle Werte NaN (sollte eigentlich nicht vorkommen)
					const realMin = vals.length > 0 ? Math.min(...vals) : 0;
					const realMax = vals.length > 0 ? Math.max(...vals) : 100;

					dimensions.push({
						label: col.name,
						values: vals,
						range: [realMin, realMax]
					});
				});

				// Kategorische Dimensionen (aus gefilterten Daten)
				filteredCategoricalCols.forEach(col => {
					const vals = filteredData.map(row => categoryMappings[col.name][row[col.index]]);
					dimensions.push({
						label: col.name,
						values: vals,
						tickvals: Object.values(categoryMappings[col.name]),
						ticktext: Object.keys(categoryMappings[col.name])
					});
				});

				// Linienfarbe bestimmen, falls Farbskala gesetzt ist
				let filteredColorValues = null;
				if (colorValues) {
					// Da colorValues für alle Daten sind, filtere sie auch entsprechend
					filteredColorValues = filteredData.map(row => {
						const col = numericalCols.find(c => c.name.toLowerCase() === resultSelect.val().toLowerCase());
						return col ? parseFloat(row[col.index]) : null;
					});
				}

				const trace = {
					type: 'parcoords',
					dimensions: dimensions,
					line: filteredColorValues ? { color: filteredColorValues, 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();
			} catch (error) {
				console.error("Fehler in updatePlot():", error);
			}
		}


		updatePlot();

		$("#parallel-plot").data("loaded", "true");

		make_text_in_parallel_plot_nicer();

	} catch (err) {
		console.error("Error in createParallelPlot:", err);
	}
}

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 true;
		}
		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_results_csv_json.map(row => row[tab_results_headers_json.indexOf("exit_code")]);

	var exitCodeCounts = exitCodes.reduce(function(counts, exitCode) {
		counts[exitCode] = (counts[exitCode] || 0) + 1;
		return counts;
	}, {});

	var labels = Object.keys(exitCodeCounts);
	var values = Object.values(exitCodeCounts);

	var plotDiv = document.getElementById("plotExitCodesPieChart");
	plotDiv.innerHTML = "";

	var trace = {
		labels: labels,
		values: values,
		type: 'pie',
		hoverinfo: 'label+percent',
		textinfo: 'label+value',
		marker: {
			colors: ['#ff9999','#66b3ff','#99ff99','#ffcc99','#c2c2f0']
		}
	};

	var layout = {
		title: 'Exit Code Distribution',
		showlegend: true
	};

	Plotly.newPlot(plotDiv, [trace], add_default_layout_data(layout));
	$("#plotExitCodesPieChart").data("loaded", "true");
}

function plotResultEvolution() {
	if ($("#plotResultEvolution").data("loaded") == "true") {
		return;
	}

	result_names.forEach(resultName => {
		var relevantColumns = tab_results_headers_json.filter(col =>
			!special_col_names.includes(col) && !col.startsWith("OO_Info") && col.toLowerCase() !== resultName.toLowerCase()
		);

		var xColumnIndex = tab_results_headers_json.indexOf("trial_index");
		var resultIndex = tab_results_headers_json.indexOf(resultName);

		let data = tab_results_csv_json.map(row => ({
			x: row[xColumnIndex],
			y: parseFloat(row[resultIndex])
		}));

		data.sort((a, b) => a.x - b.x);

		let xData = data.map(item => item.x);
		let yData = data.map(item => item.y);

		let trace = {
			x: xData,
			y: yData,
			mode: 'lines+markers',
			name: resultName,
			line: {
				shape: 'linear'
			},
			marker: {
				size: get_marker_size()
			}
		};

		let layout = {
			title: `Evolution of ${resultName} over time`,
			xaxis: {
				title: get_axis_title_data("Trial-Index")
			},
			yaxis: {
				title: get_axis_title_data(resultName)
			},
			showlegend: true
		};

		let subDiv = document.createElement("div");
		document.getElementById("plotResultEvolution").appendChild(subDiv);

		Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
	});

	$("#plotResultEvolution").data("loaded", "true");
}

function plotResultPairs() {
	if ($("#plotResultPairs").data("loaded") == "true") {
		return;
	}

	var plotDiv = document.getElementById("plotResultPairs");
	plotDiv.innerHTML = "";

	for (let i = 0; i < result_names.length; i++) {
		for (let j = i + 1; j < result_names.length; j++) {
			let xName = result_names[i];
			let yName = result_names[j];

			let xIndex = tab_results_headers_json.indexOf(xName);
			let yIndex = tab_results_headers_json.indexOf(yName);

			let data = tab_results_csv_json
				.filter(row => row[xIndex] !== "" && row[yIndex] !== "")
				.map(row => ({
					x: parseFloat(row[xIndex]),
					y: parseFloat(row[yIndex]),
					status: row[tab_results_headers_json.indexOf("trial_status")]
				}));

			let colors = data.map(d => d.status === "COMPLETED" ? 'green' : (d.status === "FAILED" ? 'red' : 'gray'));

			let trace = {
				x: data.map(d => d.x),
				y: data.map(d => d.y),
				mode: 'markers',
				marker: {
					size: get_marker_size(),
					color: colors
				},
				text: data.map(d => `Status: ${d.status}`),
				type: 'scatter',
				showlegend: false
			};

			let layout = {
				xaxis: {
					title: get_axis_title_data(xName)
				},
				yaxis: {
					title: get_axis_title_data(yName)
				},
				showlegend: false
			};

			let subDiv = document.createElement("div");
			plotDiv.appendChild(subDiv);

			Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
		}
	}

	$("#plotResultPairs").data("loaded", "true");
}

function add_up_down_arrows_for_scrolling () {
	const upArrow = document.createElement('div');
	const downArrow = document.createElement('div');

	const style = document.createElement('style');
	style.innerHTML = `
		.scroll-arrow {
			position: fixed;
			right: 10px;
			z-index: 100;
			cursor: pointer;
			font-size: 25px;
			display: none;
			background-color: green;
			color: white;
			padding: 5px;
			outline: 2px solid white;
			box-shadow: 0 0 10px rgba(0, 0, 0, 0.5);
			transition: background-color 0.3s, transform 0.3s;
		}
		.scroll-arrow:hover {
			background-color: darkgreen;
			transform: scale(1.1);
		}
		#up-arrow {
			top: 10px;
		}
		#down-arrow {
			bottom: 10px;
		}
	`;
	document.head.appendChild(style);

	upArrow.id = "up-arrow";
	upArrow.classList.add("scroll-arrow");
	upArrow.classList.add("invert_in_dark_mode");
	upArrow.innerHTML = "&#8593;";

	downArrow.id = "down-arrow";
	downArrow.classList.add("scroll-arrow");
	downArrow.classList.add("invert_in_dark_mode");
	downArrow.innerHTML = "&#8595;";

	document.body.appendChild(upArrow);
	document.body.appendChild(downArrow);

	function checkScrollPosition() {
		const scrollPosition = window.scrollY;
		const pageHeight = document.documentElement.scrollHeight;
		const windowHeight = window.innerHeight;

		if (scrollPosition > 0) {
			upArrow.style.display = "block";
		} else {
			upArrow.style.display = "none";
		}

		if (scrollPosition + windowHeight < pageHeight) {
			downArrow.style.display = "block";
		} else {
			downArrow.style.display = "none";
		}
	}

	window.addEventListener("scroll", checkScrollPosition);

	upArrow.addEventListener("click", function () {
		window.scrollTo({ top: 0, behavior: 'smooth' });
	});

	downArrow.addEventListener("click", function () {
		window.scrollTo({ top: document.documentElement.scrollHeight, behavior: 'smooth' });
	});

	checkScrollPosition();

	if (typeof apply_theme_based_on_system_preferences === 'function') {
		apply_theme_based_on_system_preferences();
	}
}

function plotGPUUsage() {
	if ($("#tab_gpu_usage").data("loaded") === "true") {
		return;
	}

	Object.keys(gpu_usage).forEach(node => {
		const nodeData = gpu_usage[node];

		var timestamps = [];
		var gpuUtilizations = [];
		var temperatures = [];

		nodeData.forEach(entry => {
			try {
				var timestamp = new Date(entry[0]* 1000);
				var utilization = parseFloat(entry[1]);
				var temperature = parseFloat(entry[2]);

				if (!isNaN(timestamp) && !isNaN(utilization) && !isNaN(temperature)) {
					timestamps.push(timestamp);
					gpuUtilizations.push(utilization);
					temperatures.push(temperature);
				} else {
					console.warn("Invalid data point:", entry);
				}
			} catch (error) {
				console.error("Error processing GPU data entry:", error, entry);
			}
		});

		var trace1 = {
			x: timestamps,
			y: gpuUtilizations,
			mode: 'lines+markers',
			marker: {
				size: get_marker_size(),
			},
			name: 'GPU Utilization (%)',
			type: 'scatter',
			yaxis: 'y1'
		};

		var trace2 = {
			x: timestamps,
			y: temperatures,
			mode: 'lines+markers',
			marker: {
				size: get_marker_size(),
			},
			name: 'GPU Temperature (°C)',
			type: 'scatter',
			yaxis: 'y2'
		};

		var layout = {
			title: 'GPU Usage Over Time - ' + node,
			xaxis: {
				title: get_axis_title_data("Timestamp", "date"),
				tickmode: 'array',
				tickvals: timestamps.filter((_, index) => index % Math.max(Math.floor(timestamps.length / 10), 1) === 0),
				ticktext: timestamps.filter((_, index) => index % Math.max(Math.floor(timestamps.length / 10), 1) === 0).map(t => t.toLocaleString()),
				tickangle: -45
			},
			yaxis: {
				title: get_axis_title_data("GPU Utilization (%)"),
				overlaying: 'y',
				rangemode: 'tozero'
			},
			yaxis2: {
				title: get_axis_title_data("GPU Temperature (°C)"),
				overlaying: 'y',
				side: 'right',
				position: 0.85,
				rangemode: 'tozero'
			},
			legend: {
				x: 0.1,
				y: 0.9
			}
		};

		var divId = 'gpu_usage_plot_' + node;

		if (!document.getElementById(divId)) {
			var div = document.createElement('div');
			div.id = divId;
			div.className = 'gpu-usage-plot';
			document.getElementById('tab_gpu_usage').appendChild(div);
		}

		var plotData = [trace1, trace2];

		Plotly.newPlot(divId, plotData, add_default_layout_data(layout));
	});

	$("#tab_gpu_usage").data("loaded", "true");
}

function plotResultsDistributionByGenerationMethod() {
	if ("true" === $("#plotResultsDistributionByGenerationMethod").data("loaded")) {
		return;
	}

	var res_col = result_names[0];
	var gen_method_col = "generation_node";

	var data = {};

	tab_results_csv_json.forEach(row => {
		var gen_method = row[tab_results_headers_json.indexOf(gen_method_col)];
		var result = row[tab_results_headers_json.indexOf(res_col)];

		if (!data[gen_method]) {
			data[gen_method] = [];
		}
		data[gen_method].push(result);
	});

	var traces = Object.keys(data).map(method => {
		return {
			y: data[method],
			type: 'box',
			name: method,
			boxpoints: 'outliers',
			jitter: 0.5,
			pointpos: 0
		};
	});

	var layout = {
		title: 'Distribution of Results by Generation Method',
		yaxis: {
			title: get_axis_title_data(res_col)
		},
		xaxis: {
			title: get_axis_title_data("Generation Method")
		},
		boxmode: 'group'
	};

	Plotly.newPlot("plotResultsDistributionByGenerationMethod", traces, add_default_layout_data(layout));
	$("#plotResultsDistributionByGenerationMethod").data("loaded", "true");
}

function plotJobStatusDistribution() {
	if ($("#plotJobStatusDistribution").data("loaded") === "true") {
		return;
	}

	var status_col = "trial_status";
	var status_counts = {};

	tab_results_csv_json.forEach(row => {
		var status = row[tab_results_headers_json.indexOf(status_col)];
		if (status) {
			status_counts[status] = (status_counts[status] || 0) + 1;
		}
	});

	var statuses = Object.keys(status_counts);
	var counts = Object.values(status_counts);

	var colors = statuses.map((status, i) =>
		status === "FAILED" ? "#FF0000" : `hsl(${30 + ((i * 137) % 330)}, 70%, 50%)`
	);

	var trace = {
		x: statuses,
		y: counts,
		type: 'bar',
		marker: { color: colors }
	};

	var layout = {
		title: 'Distribution of Job Status',
		xaxis: { title: 'Trial Status' },
		yaxis: { title: 'Nr. of jobs' }
	};

	Plotly.newPlot("plotJobStatusDistribution", [trace], add_default_layout_data(layout));
	$("#plotJobStatusDistribution").data("loaded", "true");
}

function _colorize_table_entries_by_generation_method () {
	document.querySelectorAll('[data-column-id="generation_node"]').forEach(el => {
		let text = el.textContent.toLowerCase();
		let color = text.includes("manual") ? "green" :
			text.includes("sobol") ? "orange" :
			text.includes("saasbo") ? "pink" :
			text.includes("uniform") ? "lightblue" :
			text.includes("legacy_gpei") ? "sienna" :
			text.includes("bo_mixed") ? "aqua" :
			text.includes("randomforest") ? "darkseagreen" :
			text.includes("external_generator") ? "purple" :
			text.includes("botorch") ? "yellow" : "";
		if (color !== "") {
			el.style.backgroundColor = color;
		}
		el.classList.add("invert_in_dark_mode");
	});
}

function _colorize_table_entries_by_trial_status () {
	document.querySelectorAll('[data-column-id="trial_status"]').forEach(el => {
		let color = el.textContent.includes("COMPLETED") ? "lightgreen" :
			el.textContent.includes("RUNNING") ? "orange" :
			el.textContent.includes("FAILED") ? "red" :
			el.textContent.includes("CANDIDATE") ? "lightblue" :
			el.textContent.includes("ABANDONED") ? "yellow" : "";
		if (color) el.style.backgroundColor = color;
		el.classList.add("invert_in_dark_mode");
	});
}

function _colorize_table_entries_by_queue_time() {
	let cells = [...document.querySelectorAll('[data-column-id="queue_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_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_queue_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();
	if (typeof apply_theme_based_on_system_preferences === 'function') {
		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;
}

function createResultParameterCanvases(this_res_name) {
	if (
		typeof special_col_names === "undefined" ||
		typeof result_names === "undefined" ||
		typeof result_min_max === "undefined" ||
		typeof tab_results_headers_json === "undefined" ||
		typeof tab_results_csv_json === "undefined"
	) {
		console.error("Missing one or more required global variables.");
		return null;
	}

	if (
		!Array.isArray(special_col_names) ||
		!Array.isArray(result_names) ||
		!Array.isArray(result_min_max) ||
		!Array.isArray(tab_results_headers_json) ||
		!Array.isArray(tab_results_csv_json)
	) {
		console.error("All inputs must be arrays.");
		return null;
	}

	function getColumnIndexMap(headers) {
		var map = {};
		for (var i = 0; i < headers.length; i++) {
			map[headers[i]] = i;
		}
		return map;
	}

	function getColumnData(data, index) {
		var result = [];
		for (var i = 0; i < data.length; i++) {
			result.push(data[i][index]);
		}
		return result;
	}

	function normalize(value, min, max) {
		if (max === min) {
			return 0.5;
		}
		return (value - min) / (max - min);
	}

	function interpolateColor(ratio, reverse) {
		var r = reverse ? ratio : 1 - ratio;
		var g = reverse ? 1 - ratio : ratio;
		var b = 0;
		r = Math.floor(r * 255);
		g = Math.floor(g * 255);
		return "rgb(" + r + "," + g + "," + b + ")";
	}

	function createCanvas(width, height) {
		var canvas = document.createElement("canvas");
		canvas.width = width;
		canvas.height = height;
		return canvas;
	}

	function isNumericArray(arr) {
		for (var i = 0; i < arr.length; i++) {
			var val = arr[i];
			if (typeof val !== "number" || isNaN(val)) {
				return false;
			}
		}
		return true;
	}

	function findBestRowIndex() {
		var bestIndex = 0;

		for (var i = 1; i < tab_results_csv_json.length; i++) {
			var better = false;

			for (var r = 0; r < result_names.length; r++) {
				var col = result_names[r];
				var colIdx = header_map[col];
				var goal = result_min_max[r]; // "min" or "max"

				var valCurrent = tab_results_csv_json[i][colIdx];
				var valBest = tab_results_csv_json[bestIndex][colIdx];

				if (goal === "min" && valCurrent < valBest) {
					better = true;
					break;
				}

				if (goal === "max" && valCurrent > valBest) {
					better = true;
					break;
				}
			}

			if (better) {
				bestIndex = i;
			}
		}

		return bestIndex;
	}

	var canvas_width = 1000;
	var canvas_height = 100;

	var header_map = getColumnIndexMap(tab_results_headers_json);

	var parameter_columns = tab_results_headers_json.filter(function (name) {
		return (
			!special_col_names.includes(name) &&
			!result_names.includes(name) &&
			!name.startsWith("OO_Info_")
		);
	});

	var container = document.createElement("div");

	for (var r = 0; r < result_names.length; r++) {
		var result_name = result_names[r];
		if (this_res_name == result_name) {
			var result_index = header_map[result_name];
			var result_goal = result_min_max[r]; // "min" or "max"

			var result_values = getColumnData(tab_results_csv_json, result_index);
			var result_min = Math.min.apply(null, result_values);
			var result_max = Math.max.apply(null, result_values);

			var heading = document.createElement("h2");
			heading.textContent = "Interpretation for result: " + result_name + " (goal: " + result_goal + ")";
			heading.style.fontFamily = "sans-serif";
			heading.style.marginTop = "24px";
			heading.style.marginBottom = "12px";
			container.appendChild(heading);

			var table = document.createElement("table");
			table.style.borderCollapse = "collapse";
			table.style.marginBottom = "32px";

			var thead = document.createElement("thead");
			var headRow = document.createElement("tr");

			var th1 = document.createElement("th");
			th1.textContent = "Parameter";
			th1.style.textAlign = "left";
			th1.style.padding = "6px 12px";
			var th2 = document.createElement("th");
			th2.textContent = "Distribution of result";
			th2.style.textAlign = "left";
			th2.style.padding = "6px 12px";

			headRow.appendChild(th1);
			headRow.appendChild(th2);
			thead.appendChild(headRow);
			table.appendChild(thead);

			var tbody = document.createElement("tbody");

			for (var p = 0; p < parameter_columns.length; p++) {
				var param_name = parameter_columns[p];
				var param_index = header_map[param_name];
				var param_values = getColumnData(tab_results_csv_json, param_index);

				if (!isNumericArray(param_values)) {
					continue;
				}

				var param_min = Math.min.apply(null, param_values);
				var param_max = Math.max.apply(null, param_values);

				var canvas = createCanvas(canvas_width, canvas_height);

				canvas.classList.add("invert_in_dark_mode");

				var ctx = canvas.getContext("2d");

				ctx.fillStyle = "white";
				ctx.fillRect(0, 0, canvas.width, canvas.height);

				var x_groups = {};

				for (var i = 0; i < tab_results_csv_json.length; i++) {
					var raw_param = tab_results_csv_json[i][param_index];
					var raw_result = tab_results_csv_json[i][result_index];

					var x_ratio = normalize(raw_param, param_min, param_max);
					var x = Math.floor(x_ratio * (canvas_width - 1));

					if (!x_groups[x]) {
						x_groups[x] = [];
					}

					x_groups[x].push(raw_result);
				}

				for (var x in x_groups) {
					var values = x_groups[x];
					values.sort(function (a, b) {
						return a - b;
					});

					var stripe_height = canvas_height / values.length;
					for (var i = 0; i < values.length; i++) {
						var y_start = i * stripe_height;
						var y_end = (i + 1) * stripe_height;

						var value = values[i];
						var result_ratio = normalize(value, result_min, result_max);
						var color = interpolateColor(result_ratio, result_goal === "min");

						ctx.beginPath();
						ctx.strokeStyle = color;
						ctx.lineWidth = 1;
						ctx.moveTo(Number(x) + 0.5, y_start);
						ctx.lineTo(Number(x) + 0.5, y_end);
						ctx.stroke();
					}
				}

				var row = document.createElement("tr");

				var cell_param = document.createElement("td");
				cell_param.textContent = param_name;
				cell_param.style.padding = "4px 12px";
				cell_param.style.verticalAlign = "top";
				cell_param.style.fontFamily = "monospace";
				cell_param.style.whiteSpace = "nowrap";

				var cell_canvas = document.createElement("td");
				cell_canvas.appendChild(canvas);
				cell_canvas.style.padding = "4px 12px";

				row.appendChild(cell_param);
				row.appendChild(cell_canvas);
				tbody.appendChild(row);
			}

			table.appendChild(tbody);
			container.appendChild(table);
		}
	}

	// === Summary: Best result ===
	var bestIndex = findBestRowIndex();
	var bestRow = tab_results_csv_json[bestIndex];

	var ul = document.createElement("ul");
	ul.style.margin = "0";
	ul.style.paddingLeft = "24px";

	// Alle Result-Spalten
	for (var i = 0; i < result_names.length; i++) {
		var name = result_names[i];
		var val = bestRow[header_map[name]];
		var li = document.createElement("li");
		li.textContent = name + " = " + val;
		ul.appendChild(li);
	}

	// Alle Parameter-Spalten (außer special_col_names)
	for (var i = 0; i < tab_results_headers_json.length; i++) {
		var name = tab_results_headers_json[i];
		if (special_col_names.includes(name) || name.startsWith("OO_Info_") || result_names.includes(name)) {
			continue;
		}

		var val = bestRow[header_map[name]];
		var li = document.createElement("li");
		li.textContent = name + " = " + val;
		ul.appendChild(li);
	}

	return container;
}

function initializeResultParameterVisualizations() {
        try {
                var elements = $('.result_parameter_visualization');

                if (!elements || elements.length === 0) {
                        console.warn('No .result_parameter_visualization elements found.');
                        return;
                }

                elements.each(function () {
                        var element = $(this);

                        if (element.data('initialized')) {
                                return; // Already initialized, skip
                        }

                        var resname = element.attr('data-resname');

                        if (!resname) {
                                console.error('Missing data-resname attribute for element:', this);
                                return;
                        }

                        try {
                                var html = createResultParameterCanvases(resname);

                                element.html(html);
                                element.data('initialized', true);

                        } catch (err) {
                                console.error('Error while calling createResultParameterCanvases for resname:', resname, err);
                        }
                });
        } catch (outerErr) {
                console.error('Failed to initialize result parameter visualizations:', outerErr);
        }
}

function plotParameterDistributionsByStatus() {
	const container = document.getElementById('parameter_by_status_distribution');
	if (!container) {
		console.error("Kein Container mit id 'parameter_by_status_distribution' gefunden.");
		return null;
	}

	if ($(container).data("loaded") === "true") {
		return;
	}

	if (
		typeof special_col_names === "undefined" ||
		typeof result_names === "undefined" ||
		typeof result_min_max === "undefined" ||
		typeof tab_results_headers_json === "undefined" ||
		typeof tab_results_csv_json === "undefined"
	) {
		console.error("Missing one or more required global variables.");
		return null;
	}

	if (
		!Array.isArray(special_col_names) ||
		!Array.isArray(result_names) ||
		!Array.isArray(result_min_max) ||
		!Array.isArray(tab_results_headers_json) ||
		!Array.isArray(tab_results_csv_json)
	) {
		console.error("All inputs must be arrays.");
		return null;
	}

	container.innerHTML = "";

	const statusIndex = tab_results_headers_json.indexOf("trial_status");
	if (statusIndex < 0) {
		container.textContent = "Kein 'trial_status' in den Daten gefunden.";
		return null;
	}

	const trialStatuses = [...new Set(tab_results_csv_json.map(row => row[statusIndex]))].filter(s => s != null);
	const paramCols = tab_results_headers_json.filter(col =>
		!special_col_names.includes(col) &&
		!result_names.includes(col)
	);

	for (const param of paramCols) {
		const paramIndex = tab_results_headers_json.indexOf(param);
		if (paramIndex < 0) continue;

		const traces = [];

		trialStatuses.forEach((status) => {
			const filteredValues = tab_results_csv_json
				.filter(row => row[statusIndex] === status)
				.map(row => row[paramIndex])
				.filter(val => val !== "" && val != null && !isNaN(val))
				.map(Number);

			if (filteredValues.length > 1) {
				// Histogramm-Bins automatisch mit Plotly bestimmen lassen oder eigene
				// Hier: bins in 20 Stück
				const nbins = 20;
				traces.push({
					type: 'histogram',
					x: filteredValues,
					name: status,
					opacity: 0.6,
					xbingroup: 0,
					marker: {color: getColorForStatus(status)},
					nbinsx: nbins,
					// für Overlay-Stil:
					// histfunc: 'count', // default
					// autobinx: false,
					// xbins: {start: Math.min(...filteredValues), end: Math.max(...filteredValues), size: (Math.max(...filteredValues) - Math.min(...filteredValues)) / nbins}
				});
			}
		});

		if (traces.length > 0) {
			const h2 = document.createElement('h2');
			if(!param.startsWith("OO_Info_")) {
				h2.textContent = `Histogram: ${param}`;
				container.appendChild(h2);

				const plotDiv = document.createElement('div');
				plotDiv.style.marginBottom = '30px';
				container.appendChild(plotDiv);

				Plotly.newPlot(plotDiv, traces, {
					barmode: 'overlay',  // 'stack' oder 'overlay'
					xaxis: {
						title: { text: String(param) },  // Sicherstellen, dass es ein Textobjekt ist
						automargin: true,
						tickangle: -45,                  // Optional: bessere Lesbarkeit
						titlefont: { size: 16 }          // Optional: größerer Titel
					},
					yaxis: {
						title: { text: 'Count' },        // Titel explizit als Objekt angeben
						automargin: true,
						titlefont: { size: 16 }          // Optional: größerer Titel
					},
					margin: {
						l: 60,
						r: 30,
						t: 30,
						b: 80                            // genug Platz für x-Achsentitel
					},
					legend: {
						orientation: "h"
					}
				}, {
					responsive: true
				});

			}
		}
	}

	$(container).data("loaded", "true");

	// Color mapping (falls nicht global)
	function getColorForStatus(status) {
		const baseAlpha = 0.5;
		switch(status.toUpperCase()) {
			case 'FAILED':      return `rgba(214, 39, 40, ${baseAlpha})`;
			case 'COMPLETED':   return `rgba(44, 160, 44, ${baseAlpha})`;
			case 'ABANDONED':   return `rgba(255, 215, 0, ${baseAlpha})`;
			case 'RUNNING':     return `rgba(50, 50, 44, ${baseAlpha})`;
			default:
				const otherColors = [
					`rgba(31, 119, 180, ${baseAlpha})`,
					`rgba(255, 127, 14, ${baseAlpha})`,
					`rgba(148, 103, 189, ${baseAlpha})`,
					`rgba(140, 86, 75, ${baseAlpha})`,
					`rgba(227, 119, 194, ${baseAlpha})`,
					`rgba(127, 127, 127, ${baseAlpha})`,
					`rgba(188, 189, 34, ${baseAlpha})`,
					`rgba(23, 190, 207, ${baseAlpha})`
				];
				let hash = 0;
				for (let i = 0; i < status.length; i++) {
					hash = status.charCodeAt(i) + ((hash << 5) - hash);
				}
				const index = Math.abs(hash) % otherColors.length;
				return otherColors[index];
		}
	}

	resizePlotlyCharts();
}

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);

	if (typeof apply_theme_based_on_system_preferences === 'function') {
		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();;
plotParameterDistributionsByStatus();;
initializeResultParameterVisualizations();
createParallelPlot(tab_results_csv_json, tab_results_headers_json, result_names, special_col_names);;
plotScatter2d();;
plotScatter3d();
plotJobStatusDistribution();;
plotBoxplot();;
plotViolin();;
plotHistogram();;
plotHeatmap();;
plotResultPairs();;
plotResultEvolution();

				colorize_table_entries();
			});
		</script>

		<h1><img class='invert_icon' src='i/overview.svg' style='height: 1em' />&nbsp;Overview</h1>
<h2>Experiment overview:               </h2><table cellspacing="0" cellpadding="5"><thead><tr><th> Setting</th><th>Value </th></tr></thead><tbody><tr><td> Max. nr. evaluations</td><td>50498 </td></tr><tr><td> Max. nr. evaluations (from arguments)</td><td>50000 </td></tr><tr><td> Number random steps</td><td>20    </td></tr><tr><td> Nr. of workers (parameter)</td><td>20    </td></tr><tr><td> Main process memory (GB)</td><td>8     </td></tr><tr><td> Worker memory (GB)</td><td>1     </td></tr><tr><td> Nr. imported jobs</td><td>498   </td></tr></tbody></table><h2>Job Summary per Generation Node</h2>
<table border='1' cellpadding='5' cellspacing='0'>
<thead><tr><th>Generation Node</th><th>Total</th><th>COMPLETED</th><th>FAILED</th><th>RUNNING</th></tr></thead>
<tbody>
<tr><td>GenerationStep_0</td><td>30</td><td>30</td><td>0</td><td>0</td></tr>
<tr><td>GenerationStep_1</td><td>471</td><td>468</td><td>1</td><td>2</td></tr>
<tr><td>SOBOL</td><td>20</td><td>20</td><td>0</td><td>0</td></tr>
<tr><td>BOTORCH_MODULAR</td><td>317</td><td>315</td><td>0</td><td>2</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>int</td><td>1</td><td>5000</td><td>int</td><td>No         </td></tr><tr><td> n_samples</td><td>int</td><td>1</td><td>5000</td><td>int</td><td>No         </td></tr><tr><td> const</td><td>float</td><td>0.001</td><td>10</td><td>float</td><td>No         </td></tr><tr><td> max_depth</td><td>int</td><td>1</td><td>20</td><td>int</td><td>No         </td></tr><tr><td> threshold</td><td>float</td><td>0.001</td><td>0.999</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>1</td>
<td>833</td>
<td>4</td>
<td>838</td>
</tr>
</tbody>
</table>
<h2>Result names and types</h2>
<table>
<tr><th>name</th><th>min/max</th></tr>
<tr>
<td>ACCURACY</td>
<td>max</td>
</tr>
<tr>
<td>RUNTIME</td>
<td>min</td>
</tr>
</table>
<br>
<h2>Git-Version</h2>
<tt>Commit: 2223ae6553abdd3e288f4b391080b763a7a48477
</tt>
<h1><img class='invert_icon' src='i/csv.svg' style='height: 1em' />&nbsp;Results</h1>
<div id='tab_results_csv_table'></div>
<button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("tab_results_csv_table_pre")'><img src='i/clipboard.svg' style='height: 1em'> Copy raw data to clipboard</button>
<button onclick='download_as_file("tab_results_csv_table_pre", "results.csv")'><img src='i/download.svg' style='height: 1em'> Download &raquo;results.csv&laquo; as file</button>
<pre id='tab_results_csv_table_pre'>trial_index,arm_name,trial_status,generation_method,generation_node,ACCURACY,RUNTIME,recent_samples_size,n_samples,const,max_depth,threshold
0,0_0,COMPLETED,Sobol,GenerationStep_0,0.700000000000000066613381477509,3,1620,4143,7.982919480681419877043936139671,4,0.882287493586540239043358724302
1,1_0,COMPLETED,Sobol,GenerationStep_0,0.729999999999999982236431605997,27,2909,109,4.800845133917406748480516398558,11,0.40107114133797583388485463729
2,2_0,COMPLETED,Sobol,GenerationStep_0,0.690000000000000057731597280508,5,4528,3583,6.474530969013460257599490432767,10,0.237508180126547813193482738825
3,3_0,COMPLETED,Sobol,GenerationStep_0,0.640000000000000013322676295502,3,660,2012,0.743997874721884722148956825549,18,0.719203989632427709288720052427
4,4_0,COMPLETED,Sobol,GenerationStep_0,0.670000000000000039968028886506,2,610,3005,3.434259827704169154571900435258,20,0.50902685163170102722318688393
5,5_0,COMPLETED,Sobol,GenerationStep_0,0.690000000000000057731597280508,5,4243,1412,8.803615154411643217713390185963,7,0.027323190048336984392385318188
6,6_0,COMPLETED,Sobol,GenerationStep_0,0.690000000000000057731597280508,3,3323,4896,2.422758724032901156419939070474,14,0.363399862712249166474265393845
7,7_0,COMPLETED,Sobol,GenerationStep_0,0.670000000000000039968028886506,2,2111,844,5.3410730496998883864989693393,2,0.844608367530629067232439410873
8,8_0,COMPLETED,Sobol,GenerationStep_0,0.719999999999999973354647408996,2,2373,3438,1.583753850243054372981532651465,6,0.496270950065925697813895567378
9,9_0,COMPLETED,Sobol,GenerationStep_0,0.670000000000000039968028886506,5,3740,2470,6.181586962176487176634509523865,19,0.981872573265805792530613871349
10,10_0,COMPLETED,Sobol,GenerationStep_0,0.690000000000000057731597280508,3,3991,3996,2.554970862218179039615506553673,3,0.631299002546817034087212050508
11,11_0,COMPLETED,Sobol,GenerationStep_0,0.640000000000000013322676295502,779,203,569,9.681962460685522131598190753721,15,0.146191584344953301455305449963
12,12_0,COMPLETED,Sobol,GenerationStep_0,0.670000000000000039968028886506,2,1029,4419,7.001067092803307190251871361397,12,0.123132070150226355376155140675
13,13_0,COMPLETED,Sobol,GenerationStep_0,0.680000000000000048849813083507,7,4740,1009,0.215952712245285532999261590703,5,0.608246388662606496389173571515
14,14_0,COMPLETED,Sobol,GenerationStep_0,0.640000000000000013322676295502,4,2530,2525,8.549739444735459770186025707517,17,0.757068918446078931161480340961
15,15_0,COMPLETED,Sobol,GenerationStep_0,0.709999999999999964472863211995,4,1398,1579,4.23496657764352946173858072143,8,0.271474195556715147681359212584
16,16_0,COMPLETED,Sobol,GenerationStep_0,0.640000000000000013322676295502,3,1420,2727,5.798992267700843861177872895496,14,0.713214073034003415152426441637
17,17_0,COMPLETED,Sobol,GenerationStep_0,0.660000000000000031086244689504,3,2786,1759,1.359719537043943882181906701589,1,0.196430429929867395033582511132
18,18_0,COMPLETED,Sobol,GenerationStep_0,0.660000000000000031086244689504,3,4952,4549,9.905882232663222097812649735715,20,0.406744123253971356923841540265
19,19_0,COMPLETED,Sobol,GenerationStep_0,0.700000000000000066613381477509,5,1163,1123,2.93768009791523221352349537483,8,0.923048313748091486807823002891
20,20_0,COMPLETED,Sobol,GenerationStep_0,0.670000000000000039968028886506,2,108,3875,0.618076498725451561888633023045,10,0.838893450241535942879522735893
21,21_0,COMPLETED,Sobol,GenerationStep_0,0.739999999999999991118215802999,427,3818,466,7.244630460757762513424040662358,17,0.322597111824899918097742101963
22,22_0,COMPLETED,Sobol,GenerationStep_0,0.670000000000000039968028886506,3,3445,3227,3.991517750910483552928553763195,3,0.033332207048311829344910961481
23,23_0,COMPLETED,Sobol,GenerationStep_0,0.660000000000000031086244689504,5,2312,2280,8.147501117033883133444760460407,11,0.550123702229931899054804489424
24,24_0,COMPLETED,Sobol,GenerationStep_0,0.600000000000000088817841970013,3,1938,4697,4.402382960229181740885451290524,16,0.171402555687353019830965195069
25,25_0,COMPLETED,Sobol,GenerationStep_0,0.719999999999999973354647408996,8,3228,663,7.738135410612449582856697816169,9,0.68380093248747286782673882044
26,26_0,COMPLETED,Sobol,GenerationStep_0,0.680000000000000048849813083507,4,4182,2872,0.988667450130917169204280980921,13,0.956375116348266551824508496793
27,27_0,COMPLETED,Sobol,GenerationStep_0,0.719999999999999973354647408996,3,314,1301,6.873107385929674961744240135886,5,0.443482534550130369499498783625
28,28_0,COMPLETED,Sobol,GenerationStep_0,0.680000000000000048849813083507,3,916,3706,9.18254827334452450315893656807,2,0.296960047237575075484983244678
29,29_0,COMPLETED,Sobol,GenerationStep_0,0.729999999999999982236431605997,8,4550,2113,3.659514554336666947165213059634,15,0.809845728725194891062244550994
30,30_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,17,4400,385,0.001000000000000000020816681712,16,0.622981179772556292739693617477
31,31_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,6093,4308,1,3.276977116741448536885172870825,9,0.540530483495147429096050473163
32,32_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,4,5000,3004,10,16,0.9989999999999999991118215803
33,33_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,7,4818,1094,0.001000000000000000020816681712,16,0.001000000000000000020816681712
34,34_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,6437,4339,1,2.265543431698116449979352182709,15,0.9989999999999999991118215803
35,35_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,1193,3456,1,0.001000000000000000020816681712,10,0.001000000000000000020816681712
36,36_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,4,1923,2487,10,6,0.9989999999999999991118215803
37,37_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,919,1989,1,2.578764743662740777097042155219,6,0.001000000000000000020816681712
38,38_0,RUNNING,BoTorch,GenerationStep_1,,,4872,1,0.001000000000000000020816681712,17,0.9989999999999999991118215803
39,39_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,6246,4648,1,3.180047443483558389232257468393,12,0.9989999999999999991118215803
40,40_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,1602,3901,1,0.001000000000000000020816681712,15,0.001000000000000000020816681712
41,41_0,RUNNING,BoTorch,GenerationStep_1,,,5000,1,4.666129939426686412673461745726,7,0.538852263434716705070570696989
42,42_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,6,5000,1430,10,16,0.9989999999999999991118215803
43,43_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,2,616,5000,0.001000000000000000020816681712,6,0.001000000000000000020816681712
44,44_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,6,5000,2192,10,7,0.9989999999999999991118215803
45,45_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,1601,5000,1,0.001000000000000000020816681712,15,0.001000000000000000020816681712
46,46_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,3,5000,3630,10,15,0.9989999999999999991118215803
47,47_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,4647,3534,1,0.001000000000000000020816681712,15,0.9989999999999999991118215803
48,48_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,4,5000,2644,0.001000000000000000020816681712,16,0.001000000000000000020816681712
49,49_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,1133,2509,1,0.001000000000000000020816681712,9,0.001000000000000000020816681712
50,50_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,4448,3447,1,0.250661656278794942043219862171,10,0.72648258415193145420829523573
51,51_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,0.001000000000000000020816681712,19,0.9989999999999999991118215803
52,52_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,1237,4861,1,2.389658232350520439268848349457,10,0.290515780915859611610585488961
53,53_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,8,4378,948,0.001000000000000000020816681712,16,0.9989999999999999991118215803
54,54_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,623,5000,1,4.717391478144433492047937761527,3,0.001000000000000000020816681712
55,55_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,5,1,4070,10,20,0.9989999999999999991118215803
56,56_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,856,1,1,0.001000000000000000020816681712,6,0.001000000000000000020816681712
57,57_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,3,4210,5000,0.001000000000000000020816681712,7,0.9989999999999999991118215803
58,58_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,3,4996,5000,10,7,0.9989999999999999991118215803
59,59_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,5645,4875,1,4.1817771977717752562853092968,10,0.9989999999999999991118215803
60,60_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,9,4121,871,4.737237682826629381338534585666,12,0.746379054643187656026270815346
61,61_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,220,3966,391,4.281001358386227195751416729763,12,0.782628618028717637500335513323
62,62_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,873,4142,832,4.512901898045180715257629344705,14,0.424933727214824696893913369422
63,63_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,11,3968,677,4.329518160703052842563920421526,10,0.974637108877582591937027700624
64,64_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,4,4810,1939,4.731987813585218916045960213523,18,0.001000000000000000020816681712
65,65_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,6,3151,1169,1.710987595333870903147044373327,10,0.9989999999999999991118215803
66,66_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,9,4524,1084,5.540201882018855883416108554229,13,0.650193741919587564481730623811
67,67_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,101,3837,58,3.940393271600024505119108653162,12,0.783080509550259207252054238779
68,68_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,2,2403,4549,0.001000000000000000020816681712,6,0.9989999999999999991118215803
69,69_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,19,4162,537,5.227232416292206806929243612103,12,0.720108349124189861534262036002
70,70_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,20,4336,697,4.469019307521158168583497172222,16,0.101451945355955253091906342888
71,71_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,2,529,2611,3.235030082427177600123968659318,5,0.001000000000000000020816681712
72,72_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,8,4668,865,4.749001571517728059745877544628,19,0.387654585785973115896752005938
73,73_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,3,1724,4018,0.001000000000000000020816681712,6,0.001000000000000000020816681712
74,74_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,112,4146,210,5.159089695636138728218611504417,12,0.777361697396022677253313304391
75,75_0,COMPLETED,BoTorch,GenerationStep_1,0.650000000000000022204460492503,2,142,3762,2.798503527274313729122923177783,4,0.001000000000000000020816681712
76,76_0,COMPLETED,BoTorch,GenerationStep_1,0.660000000000000031086244689504,3,1061,2075,1.273547759532380529989836759341,5,0.001000000000000000020816681712
77,77_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,9,4331,738,5.281514468881145063505755388178,6,0.9989999999999999991118215803
78,78_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,2,1028,4700,0.001000000000000000020816681712,1,0.63869692033149094712030091614
79,79_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,2,1769,4844,0.001000000000000000020816681712,7,0.789442482276320078860010198696
80,80_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,244,4884,531,4.681426275597865505062600277597,19,0.001000000000000000020816681712
81,81_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,8,4297,1046,5.409622681335242155853393342113,9,0.9989999999999999991118215803
82,82_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,2,126,3311,2.037391858099973251938763496582,1,0.416910559381018286373432601977
83,83_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,138,3650,625,3.274577835351026422472386911977,12,0.74463974196755977619233135556
84,84_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,36,4080,168,4.448208025023618894522314803908,13,0.615572563694329888406286954705
85,85_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,2,1,2163,4.04088502781231362348535185447,5,0.001000000000000000020816681712
86,86_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,3,2675,1669,0.001000000000000000020816681712,11,0.9989999999999999991118215803
87,87_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,5,950,737,0.001000000000000000020816681712,3,0.082896226059125388552217827964
88,88_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,13,3581,399,3.173088074710329387073670659447,11,0.9989999999999999991118215803
89,89_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,3,203,564,3.828762672031267300098988926038,1,0.001000000000000000020816681712
90,90_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,26,4118,243,0.001000000000000000020816681712,9,0.752417292137260496076578419888
91,91_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,21,3562,239,0.001000000000000000020816681712,8,0.492397450899787592071277231298
92,92_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,36,4555,176,0.001000000000000000020816681712,9,0.876069924333020000339899979735
93,93_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,23,3204,229,10,8,0.320699357511880833726536366157
94,94_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,55,3743,98,0.001000000000000000020816681712,8,0.684354840095635408303564872767
95,95_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,49,3919,127,10,8,0.650300433938824529178646116634
96,96_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,267,3284,227,10,20,0.147185548161598206418076983937
97,97_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,86,3439,259,10,18,0.874223527231546171378795406781
98,98_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,19,5000,317,0.001000000000000000020816681712,10,0.9989999999999999991118215803
99,99_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,113,2993,242,10,20,0.431090765841456946549925532963
100,100_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,19,3367,228,0.001000000000000000020816681712,19,0.686551640685817310405525404349
101,101_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,85,4834,261,10,8,0.786640028901444576803214658867
102,102_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,14,2991,894,10,20,0.23163600967767905558503116481
103,103_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,13,2882,217,0.001000000000000000020816681712,2,0.001000000000000000020816681712
104,104_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,25,3442,178,10,16,0.9989999999999999991118215803
105,105_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,83,4186,226,10,18,0.238953446056642954120619037894
106,106_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,12,2750,222,0.001000000000000000020816681712,19,0.001000000000000000020816681712
107,107_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,17,2642,249,0.001000000000000000020816681712,20,0.257520447919497852407033633426
108,108_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,23,3430,181,10,8,0.844401695336755464538214255299
109,109_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,34,2375,267,10,17,0.9989999999999999991118215803
110,110_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,607,2420,226,10,20,0.001000000000000000020816681712
111,111_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,5,2228,211,0.001000000000000000020816681712,7,0.556912880219845640716869183962
112,112_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,33,1169,236,10,7,0.478200749972826855138663404432
113,113_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,56,4333,109,0.001000000000000000020816681712,9,0.9989999999999999991118215803
114,114_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,20,3587,234,0.001000000000000000020816681712,8,0.276431854471228144465300147203
115,115_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,3,2833,1588,10,20,0.001000000000000000020816681712
116,116_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,2,1,3288,0.001000000000000000020816681712,1,0.9989999999999999991118215803
117,117_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,2,165,2764,0.001000000000000000020816681712,3,0.953445738882684024062541539024
118,118_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,40,3978,218,10,6,0.001000000000000000020816681712
119,119_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,50,386,233,10,9,0.327898151490232547811132235438
120,120_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,6112,4325,1,9.240970085710779713394913414959,14,0.9989999999999999991118215803
121,121_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,5854,4295,1,10,10,0.9989999999999999991118215803
122,122_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,6018,4652,1,1.144559977551155016683992471371,14,0.9989999999999999991118215803
123,123_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,57,4269,116,3.802424638221551855821189747076,14,0.9989999999999999991118215803
124,124_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,4541,3610,1,5.287318965134845782927186519373,14,0.9989999999999999991118215803
125,125_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,6495,4141,1,8.450454359390683123365306528285,15,0.9989999999999999991118215803
126,126_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,6140,5000,1,7.963138802523596737614752782974,14,0.9989999999999999991118215803
127,127_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,5901,4886,1,1.440499818300766010636948522006,11,0.9989999999999999991118215803
128,128_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,5985,5000,1,10,18,0.964048382756507948876389946236
129,129_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,6258,4715,1,3.757648139152261368423069143319,13,0.9989999999999999991118215803
130,130_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,5035,3837,1,8.817784042301807900798849004786,10,0.9989999999999999991118215803
131,131_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,5946,3753,1,4.891569274927675792241643648595,13,0.9989999999999999991118215803
132,132_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,5721,5000,1,9.34414356224242581561156839598,10,0.9989999999999999991118215803
133,133_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,6251,4894,1,9.603028786093549484803588711657,9,0.9989999999999999991118215803
134,134_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,5889,4677,1,3.789011124056584023378491110634,17,0.665606424561819065566226072406
135,135_0,COMPLETED,BoTorch,GenerationStep_1,0.75,1349,2436,1,7.295827559415337226766951062018,12,0.9989999999999999991118215803
136,136_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,6366,5000,1,7.018118190626157826272901729681,13,0.9989999999999999991118215803
137,137_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,590,2045,1,10,3,0.001000000000000000020816681712
138,138_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,925,259,1,7.453475295456022386986205674475,11,0.9989999999999999991118215803
139,139_0,COMPLETED,BoTorch,GenerationStep_1,0.75,4452,3317,1,10,14,0.9989999999999999991118215803
140,140_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,7123,4039,1,1.394294525377878235516959648521,14,0.9989999999999999991118215803
141,141_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,4571,3605,1,6.793581062365734446473197749583,11,0.9989999999999999991118215803
142,142_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,5797,4066,1,7.603845877818301346451335120946,14,0.9989999999999999991118215803
143,143_0,COMPLETED,BoTorch,GenerationStep_1,0.810000000000000053290705182008,86,1,1,8.128844705391392366777836286929,5,0.949762501759429222936148562439
144,144_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,5999,3986,1,0.914544451382904299840959083667,10,0.9989999999999999991118215803
145,145_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,458,5000,1,9.927025514602602740410475234967,1,0.001000000000000000020816681712
146,146_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,674,785,1,9.136554769997795588665212562773,4,0.392999771239976980474750689609
147,147_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,7136,4314,1,9.538527820295886527901529916562,15,0.9989999999999999991118215803
148,148_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,260,4681,29,6.619682501764320825543563842075,16,0.875265281512327963930886198796
149,149_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,793,3700,8,6.791362354011568847056423692266,16,0.659972849961133034568661059893
150,150_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,7,146,76,10,1,0.928794402383602446526822404849
151,151_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,2,1,2392,10,1,0.9989999999999999991118215803
152,152_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,23,1273,365,10,4,0.475100751189052428191672561297
153,153_0,COMPLETED,BoTorch,GenerationStep_1,0.660000000000000031086244689504,3,5000,4314,0.001000000000000000020816681712,20,0.9989999999999999991118215803
154,154_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,4,30,40,8.500455674269851158442179439589,1,0.916073047935597961632936403475
155,155_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,3,2102,345,0.001000000000000000020816681712,1,0.001000000000000000020816681712
156,156_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,2,1,95,10,1,0.990203077059072178656151663745
157,157_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,2,1,893,0.001000000000000000020816681712,1,0.001000000000000000020816681712
158,158_0,COMPLETED,BoTorch,GenerationStep_1,0.660000000000000031086244689504,3,5000,4262,0.001000000000000000020816681712,1,0.001000000000000000020816681712
159,159_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,1129,1,974,10,20,0.687703988583119429911505449127
160,160_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,48,4949,128,0.001000000000000000020816681712,16,0.433844804334918399124632060193
161,161_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,20,235,377,10,6,0.558309114438343745412396401662
162,162_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,2,1,1443,0.001000000000000000020816681712,8,0.42966630196892480197945474174
163,163_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,2,1,66,0.016403244478537575001819703857,1,0.94691982783591299721592804417
164,164_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,6,5000,4160,10,20,0.001000000000000000020816681712
165,165_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,1379,1,1091,10,20,0.001000000000000000020816681712
166,166_0,COMPLETED,BoTorch,GenerationStep_1,0.660000000000000031086244689504,3,5000,4313,0.001000000000000000020816681712,7,0.9989999999999999991118215803
167,167_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,3,5000,4179,0.737992334921896753208159225323,1,0.001000000000000000020816681712
168,168_0,COMPLETED,BoTorch,GenerationStep_1,0.630000000000000004440892098501,2,1,1145,0.001000000000000000020816681712,10,0.001000000000000000020816681712
169,169_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,2,1,97,0.001000000000000000020816681712,2,0.940788194640071573360273760045
170,170_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,3,5000,3350,10,20,0.9989999999999999991118215803
171,171_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,3,1920,4221,0.001000000000000000020816681712,1,0.001000000000000000020816681712
172,172_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,68,5000,106,10,20,0.001000000000000000020816681712
173,173_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,2,743,3529,0.001000000000000000020816681712,1,0.670857494395666442699166509556
174,174_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,2,1,996,10,1,0.001000000000000000020816681712
175,175_0,COMPLETED,BoTorch,GenerationStep_1,0.660000000000000031086244689504,2,1,4198,0.001000000000000000020816681712,8,0.001000000000000000020816681712
176,176_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,48,5000,120,0.001000000000000000020816681712,1,0.001000000000000000020816681712
177,177_0,COMPLETED,BoTorch,GenerationStep_1,0.630000000000000004440892098501,3,4998,4247,0.001000000000000000020816681712,20,0.019640795788235857616266244463
178,178_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,17,1,4298,10,20,0.9989999999999999991118215803
179,179_0,COMPLETED,BoTorch,GenerationStep_1,0.650000000000000022204460492503,18,5000,4319,10,20,0.001000000000000000020816681712
180,180_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,3,1,98,10,7,0.9989999999999999991118215803
181,181_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,45,5000,146,10,13,0.9989999999999999991118215803
182,182_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,51,1,482,10,6,0.9989999999999999991118215803
183,183_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,76,4254,83,10,12,0.9989999999999999991118215803
184,184_0,COMPLETED,BoTorch,GenerationStep_1,0.810000000000000053290705182008,113,1,1,10,7,0.9989999999999999991118215803
185,185_0,COMPLETED,BoTorch,GenerationStep_1,0.650000000000000022204460492503,21,1,701,10,6,0.9989999999999999991118215803
186,186_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,31,5000,197,10,20,0.9989999999999999991118215803
187,187_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,3054,1115,1,10,7,0.9989999999999999991118215803
188,188_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,2,1,1808,10,6,0.9989999999999999991118215803
189,189_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,36,1905,154,10,8,0.9989999999999999991118215803
190,190_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,2,1,1446,10,5,0.9989999999999999991118215803
191,191_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,2,1,136,10,6,0.9989999999999999991118215803
192,192_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,14,5000,1275,10,20,0.001000000000000000020816681712
193,193_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,144,5000,525,10,14,0.9989999999999999991118215803
194,194_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,98,5000,62,10,13,0.9989999999999999991118215803
195,195_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,32,4643,196,10,12,0.9989999999999999991118215803
196,196_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,2,1,1283,10,5,0.9989999999999999991118215803
197,197_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,39,5000,153,0.001000000000000000020816681712,20,0.9989999999999999991118215803
198,198_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,4,5000,1831,0.001000000000000000020816681712,20,0.9989999999999999991118215803
199,199_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,9,5000,1265,10,11,0.9989999999999999991118215803
200,200_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,4,5000,2400,10,20,0.001000000000000000020816681712
201,201_0,COMPLETED,BoTorch,GenerationStep_1,0.619999999999999995559107901499,2,1,2177,10,5,0.9989999999999999991118215803
202,202_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,9,5000,1701,10,20,0.001000000000000000020816681712
203,203_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,2,2690,5000,10,1,0.001000000000000000020816681712
204,204_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,3,1,363,10,7,0.9989999999999999991118215803
205,205_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,38,3243,94,10,10,0.9989999999999999991118215803
206,206_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,19,5000,416,10,12,0.9989999999999999991118215803
207,207_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,6,5000,1204,0.001000000000000000020816681712,20,0.9989999999999999991118215803
208,208_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,3,5000,4734,10,1,0.9989999999999999991118215803
209,209_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,7,5000,2151,10,17,0.001000000000000000020816681712
210,210_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,23,3096,324,10,5,0.751929411459826724239974282682
211,211_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,6,5000,4020,10,19,0.001000000000000000020816681712
212,212_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,4,5000,2021,10,13,0.9989999999999999991118215803
213,213_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,7,5000,3905,10,20,0.001000000000000000020816681712
214,214_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,499,5000,741,10,17,0.9989999999999999991118215803
215,215_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,12,2852,351,10,3,0.9989999999999999991118215803
216,216_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,3,772,3389,4.688031202139906206127761834068,10,0.001000000000000000020816681712
217,217_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,4,5000,3076,10,20,0.001000000000000000020816681712
218,218_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,6,3319,3939,10,20,0.001000000000000000020816681712
219,219_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,5,2530,4048,10,20,0.001000000000000000020816681712
220,220_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,62,3764,124,10,20,0.628633443953452553110139433556
221,221_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,4,5000,3789,10,1,0.9989999999999999991118215803
222,222_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,2,1,2431,10,1,0.001000000000000000020816681712
223,223_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,3,2887,3367,0.001000000000000000020816681712,13,0.001000000000000000020816681712
224,224_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,2,2850,4109,10,1,0.001000000000000000020816681712
225,225_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,5,5000,4070,10,20,0.9989999999999999991118215803
226,226_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,6,5000,3821,10,20,0.865597619125430539632759519009
227,227_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,4,5000,4070,10,12,0.001000000000000000020816681712
228,228_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,51,4965,155,7.434874648367184590824763290584,1,0.9989999999999999991118215803
229,229_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,45,3282,103,9.730597639996600989320540975314,1,0.001000000000000000020816681712
230,230_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,4,5000,2949,10,1,0.001000000000000000020816681712
231,231_0,COMPLETED,BoTorch,GenerationStep_1,0.650000000000000022204460492503,4,5000,2043,0.001000000000000000020816681712,8,0.9989999999999999991118215803
232,232_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,3,5000,3153,10,20,0.959879516593710846450449025724
233,233_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,4,5000,2621,10,1,0.9989999999999999991118215803
234,234_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,4,5000,2920,10,20,0.001000000000000000020816681712
235,235_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,3,5000,3092,10,8,0.9989999999999999991118215803
236,236_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,2,1,3403,10,20,0.001000000000000000020816681712
237,237_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,9,3695,664,0.001000000000000000020816681712,2,0.001000000000000000020816681712
238,238_0,COMPLETED,BoTorch,GenerationStep_1,0.660000000000000031086244689504,4,1,4048,10,20,0.001000000000000000020816681712
239,239_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,2,497,2448,0.001000000000000000020816681712,1,0.493029689135264459487473232002
240,240_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,5,2743,3821,10,20,0.001000000000000000020816681712
241,241_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,48,3605,104,0.001000000000000000020816681712,1,0.001000000000000000020816681712
242,242_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,5,2804,3949,10,20,0.9989999999999999991118215803
243,243_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,8,5000,935,0.001000000000000000020816681712,20,0.001000000000000000020816681712
244,244_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,5,5000,1555,0.001000000000000000020816681712,20,0.379514692210152937423828234387
245,245_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,10,1,1664,10,17,0.001000000000000000020816681712
246,246_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,4,5000,2237,0.001000000000000000020816681712,18,0.9989999999999999991118215803
247,247_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,7,1,33,10,6,0.9989999999999999991118215803
248,248_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,5,5000,1548,0.001000000000000000020816681712,1,0.9989999999999999991118215803
249,249_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,6,5000,1533,0.001000000000000000020816681712,20,0.001000000000000000020816681712
250,250_0,COMPLETED,BoTorch,GenerationStep_1,0.630000000000000004440892098501,2,1,2555,10,1,0.9989999999999999991118215803
251,251_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,4,3539,1554,0.001000000000000000020816681712,20,0.781966169970413904621864276123
252,252_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,3,3923,3755,10,20,0.001000000000000000020816681712
253,253_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,312,2549,304,10,12,0.001000000000000000020816681712
254,254_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,3,1,52,10,6,0.9989999999999999991118215803
255,255_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,5,1511,3838,10,20,0.001000000000000000020816681712
256,256_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,3,5000,3926,0.001000000000000000020816681712,13,0.9989999999999999991118215803
257,257_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,2,1,3162,10,1,0.001000000000000000020816681712
258,258_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,3,1322,1684,0.001000000000000000020816681712,20,0.001000000000000000020816681712
259,259_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,2,1,1708,10,8,0.001000000000000000020816681712
260,260_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,2,1,1364,10,1,0.001000000000000000020816681712
261,261_0,COMPLETED,BoTorch,GenerationStep_1,0.640000000000000013322676295502,4,2274,3820,10,20,0.680607056223083484169933399244
262,262_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,3,1795,3759,10,20,0.9989999999999999991118215803
263,263_0,COMPLETED,BoTorch,GenerationStep_1,0.650000000000000022204460492503,3,1,1774,10,20,0.001000000000000000020816681712
264,264_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,2,245,1591,7.258732981560813257715381041635,20,0.9989999999999999991118215803
265,265_0,COMPLETED,BoTorch,GenerationStep_1,0.640000000000000013322676295502,2,1,4568,0.001000000000000000020816681712,1,0.001000000000000000020816681712
266,266_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,23,5000,930,10,16,0.001000000000000000020816681712
267,267_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,15,5000,565,0.001000000000000000020816681712,2,0.9989999999999999991118215803
268,268_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,3,3353,3796,0.001000000000000000020816681712,20,0.001000000000000000020816681712
269,269_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,2,1,3627,0.001000000000000000020816681712,20,0.9989999999999999991118215803
270,270_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,19,4853,312,10,1,0.324107845528441240734451866956
271,271_0,COMPLETED,BoTorch,GenerationStep_1,0.75,2386,791,1,10,20,0.9989999999999999991118215803
272,272_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,4596,1848,1,10,1,0.9989999999999999991118215803
273,273_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,8,5000,735,10,1,0.001000000000000000020816681712
274,274_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,22,1,13,10,20,0.9989999999999999991118215803
275,275_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,3,5000,2788,0.001000000000000000020816681712,20,0.001000000000000000020816681712
276,276_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,67,217,34,10,20,0.997342226009621635185453669692
277,277_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,18,5000,335,0.001000000000000000020816681712,1,0.036815009015031534278517000303
278,278_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,4971,1348,1,0.001000000000000000020816681712,20,0.9989999999999999991118215803
279,279_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,10,4928,631,10,1,0.310479712580486455486550312344
280,280_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,17,4908,358,10,1,0.48468617535697983145226430679
281,281_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,8,5000,759,0.001000000000000000020816681712,1,0.001000000000000000020816681712
282,282_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,1193,5000,468,10,20,0.713048423636191586183485924266
283,283_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,49,4792,123,10,1,0.574778725787663757884615733929
284,284_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,153,5000,320,0.001000000000000000020816681712,20,0.001000000000000000020816681712
285,285_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,1586,559,1,10,1,0.9989999999999999991118215803
286,286_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,11,5000,657,0.001000000000000000020816681712,20,0.001000000000000000020816681712
287,287_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,3,5000,3467,0.001000000000000000020816681712,1,0.9989999999999999991118215803
288,288_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,31,5000,202,10,1,0.041771049228403481223814708301
289,289_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,350,4964,328,10,20,0.535972939947676918492902586877
290,290_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,5851,1975,1,10,20,0.9989999999999999991118215803
291,291_0,COMPLETED,BoTorch,GenerationStep_1,0.810000000000000053290705182008,39,1,1,10,1,0.9989999999999999991118215803
292,292_0,COMPLETED,BoTorch,GenerationStep_1,0.75,12,84,48,10,20,0.729200166445189368324975021096
293,293_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,9,5000,706,0.001000000000000000020816681712,20,0.383369379065453708133048849049
294,294_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,4745,1333,1,10,20,0.9989999999999999991118215803
295,295_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,6,5000,1386,0.001000000000000000020816681712,1,0.614093313713399369113687953359
296,296_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,21,5000,295,10,1,0.001000000000000000020816681712
297,297_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,2,1,5000,10,20,0.750692936862546345011537596292
298,298_0,COMPLETED,BoTorch,GenerationStep_1,0.810000000000000053290705182008,328,1,1,10,20,0.9989999999999999991118215803
299,299_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,2272,2749,1,10,20,0.9989999999999999991118215803
300,300_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,6,1,58,10,20,0.526205523606941949488202681096
301,301_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,11,55,44,10,20,0.9989999999999999991118215803
302,302_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,52,4927,120,10,1,0.294210468070871755674744463249
303,303_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,79,694,27,10,1,0.821331474805523376048199679644
304,304_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,8,5000,813,0.001000000000000000020816681712,20,0.001000000000000000020816681712
305,305_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,6,1,1500,10,20,0.001000000000000000020816681712
306,306_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,2,1,4572,10,20,0.9989999999999999991118215803
307,307_0,COMPLETED,BoTorch,GenerationStep_1,0.810000000000000053290705182008,32,1,1,0.001000000000000000020816681712,1,0.9989999999999999991118215803
308,308_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,45,5000,132,10,20,0.571829070582599130467826853419
309,309_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,13,5000,445,0.001000000000000000020816681712,20,0.001000000000000000020816681712
310,310_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,13,5000,457,0.001000000000000000020816681712,1,0.9989999999999999991118215803
311,311_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,3,5000,3452,10,1,0.001000000000000000020816681712
312,312_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,2,1,4853,0.001000000000000000020816681712,1,0.9989999999999999991118215803
313,313_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,53,5000,108,10,1,0.001000000000000000020816681712
314,314_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,5,69,59,10,1,0.544298329667322722258404610329
315,315_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,6,5000,1183,10,1,0.065111813925307876482762026171
316,316_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,17,5000,355,10,1,0.9989999999999999991118215803
317,317_0,COMPLETED,BoTorch,GenerationStep_1,0.75,3338,1307,1,10,1,0.9989999999999999991118215803
318,318_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,2,1,3403,10,20,0.9989999999999999991118215803
319,319_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,19,1248,317,0.001000000000000000020816681712,20,0.001000000000000000020816681712
320,320_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,19,5000,301,0.001000000000000000020816681712,1,0.508224399172210627995127651957
321,321_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,40,5000,150,10,20,0.001000000000000000020816681712
322,322_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,15,5000,410,10,1,0.001000000000000000020816681712
323,323_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,12,5000,490,0.001000000000000000020816681712,1,0.282821587358941917145216393692
324,324_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,27,1,22,0.001000000000000000020816681712,20,0.8780895479983349405372905494
325,325_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,6,2,68,10,20,0.371622995797189159539186675829
326,326_0,COMPLETED,BoTorch,GenerationStep_1,0.810000000000000053290705182008,555,1,1,0.001000000000000000020816681712,20,0.9989999999999999991118215803
327,327_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,9,1,4788,10,20,0.9989999999999999991118215803
328,328_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,907,232,1,10,20,0.737454734779045772974370720476
329,329_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,3,1,18,10,1,0.9989999999999999991118215803
330,330_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,2182,600,1,0.001000000000000000020816681712,20,0.9989999999999999991118215803
331,331_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,13,3404,1290,10,20,0.9989999999999999991118215803
332,332_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,10,5000,1295,10,20,0.631208425811755846623896104575
333,333_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,2,1,39,10,1,0.9989999999999999991118215803
334,334_0,COMPLETED,BoTorch,GenerationStep_1,0.640000000000000013322676295502,3,5000,3543,0.001000000000000000020816681712,20,0.9989999999999999991118215803
335,335_0,COMPLETED,BoTorch,GenerationStep_1,0.640000000000000013322676295502,2,1,4455,0.001000000000000000020816681712,1,0.9989999999999999991118215803
336,336_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,2,1,2832,0.001000000000000000020816681712,1,0.001000000000000000020816681712
337,337_0,COMPLETED,BoTorch,GenerationStep_1,0.660000000000000031086244689504,2,1,4945,0.001000000000000000020816681712,1,0.001000000000000000020816681712
338,338_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,1003,5000,604,10,20,0.9989999999999999991118215803
339,339_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,7,5000,1136,10,1,0.9989999999999999991118215803
340,340_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,4,1,13,0.001000000000000000020816681712,1,0.9989999999999999991118215803
341,341_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,16,1917,350,0.001000000000000000020816681712,20,0.9989999999999999991118215803
342,342_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,3,5000,4105,0.001000000000000000020816681712,1,0.9989999999999999991118215803
343,343_0,COMPLETED,BoTorch,GenerationStep_1,0.75,2389,898,1,0.001000000000000000020816681712,1,0.9989999999999999991118215803
344,344_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,18,5000,351,0.001000000000000000020816681712,20,0.9989999999999999991118215803
345,345_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,10,5000,582,10,1,0.001000000000000000020816681712
346,346_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,12,5000,559,0.001000000000000000020816681712,1,0.001000000000000000020816681712
347,347_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,4,3011,1360,10,1,0.9989999999999999991118215803
348,348_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,2,1,30,0.001000000000000000020816681712,1,0.9989999999999999991118215803
349,349_0,COMPLETED,BoTorch,GenerationStep_1,0.640000000000000013322676295502,2,1,4661,10,1,0.9989999999999999991118215803
350,350_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,3,1,21,0.001000000000000000020816681712,1,0.9989999999999999991118215803
351,351_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,3,5000,5000,10,1,0.001000000000000000020816681712
352,352_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,2,1,5000,10,20,0.001000000000000000020816681712
353,353_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,6,5000,1162,10,1,0.70191396969361197211156877529
354,354_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,16,5000,1645,10,20,0.9989999999999999991118215803
355,355_0,COMPLETED,BoTorch,GenerationStep_1,0.640000000000000013322676295502,2,1,4726,0.001000000000000000020816681712,1,0.9989999999999999991118215803
356,356_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,15,5000,1047,10,20,0.9989999999999999991118215803
357,357_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,27,5000,224,0.001000000000000000020816681712,1,0.001000000000000000020816681712
358,358_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,10,5000,630,10,1,0.9989999999999999991118215803
359,359_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,3,1643,2869,0.001000000000000000020816681712,1,0.001000000000000000020816681712
360,360_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,48,5000,123,10,20,0.9989999999999999991118215803
361,361_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,6,1,74,0.001000000000000000020816681712,20,0.9989999999999999991118215803
362,362_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,256,4534,28,0.001000000000000000020816681712,1,0.9989999999999999991118215803
363,363_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,6,1,67,10,20,0.9989999999999999991118215803
364,364_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,483,5000,348,10,20,0.001000000000000000020816681712
365,365_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,64,5000,100,10,20,0.9989999999999999991118215803
366,366_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,71,4951,93,0.001000000000000000020816681712,20,0.9989999999999999991118215803
367,367_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,7,1,50,10,20,0.9989999999999999991118215803
368,368_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,1053,2130,1,0.001000000000000000020816681712,20,0.9989999999999999991118215803
369,369_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,15,3611,349,0.001000000000000000020816681712,1,0.001000000000000000020816681712
370,370_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,21,1,23,10,20,0.9989999999999999991118215803
371,371_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,41,4,33,10,20,0.9989999999999999991118215803
372,372_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,58,2930,55,0.001000000000000000020816681712,20,0.9989999999999999991118215803
373,373_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,8,5000,794,0.001000000000000000020816681712,1,0.9989999999999999991118215803
374,374_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,42,5000,145,0.001000000000000000020816681712,1,0.9989999999999999991118215803
375,375_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,43,3965,147,10,20,0.9989999999999999991118215803
376,376_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,8,5000,858,0.001000000000000000020816681712,1,0.9989999999999999991118215803
377,377_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,57,5000,124,0.001000000000000000020816681712,20,0.9989999999999999991118215803
378,378_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,16,5000,899,10,20,0.9989999999999999991118215803
379,379_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,2,1,70,10,1,0.9989999999999999991118215803
380,380_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,51,5000,125,10,1,0.9989999999999999991118215803
381,381_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,5,1,87,10,20,0.9989999999999999991118215803
382,382_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,162,4884,42,0.001000000000000000020816681712,20,0.652229103029153156612096609024
383,383_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,2,1,59,10,1,0.9989999999999999991118215803
384,384_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,110,5000,380,0.001000000000000000020816681712,20,0.001000000000000000020816681712
385,385_0,COMPLETED,BoTorch,GenerationStep_1,0.75,1235,375,1,10,20,0.9989999999999999991118215803
386,386_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,31,5000,178,0.001000000000000000020816681712,1,0.9989999999999999991118215803
387,387_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,18,5000,385,0.001000000000000000020816681712,1,0.001000000000000000020816681712
388,388_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,51,1,12,0.001000000000000000020816681712,20,0.9989999999999999991118215803
389,389_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,63,5000,104,0.001000000000000000020816681712,20,0.001000000000000000020816681712
390,390_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,19,3664,313,0.001000000000000000020816681712,20,0.537757348633142728822065237182
391,391_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,4,2426,753,0.001000000000000000020816681712,20,0.001000000000000000020816681712
392,392_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,1660,2581,1,0.001000000000000000020816681712,1,0.9989999999999999991118215803
393,393_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,54,5000,108,10,1,0.9989999999999999991118215803
394,394_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,45,4212,128,0.001000000000000000020816681712,1,0.653947647460837444555181718897
395,395_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,44,5000,339,0.001000000000000000020816681712,20,0.389993087749901434779786768559
396,396_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,60,5000,95,0.001000000000000000020816681712,1,0.001000000000000000020816681712
397,397_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,6,5000,1125,0.001000000000000000020816681712,1,0.001000000000000000020816681712
398,398_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,2,1,298,10,1,0.001000000000000000020816681712
399,399_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,379,4758,20,10,1,0.9989999999999999991118215803
400,400_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,55,5000,129,0.001000000000000000020816681712,20,0.603269904114436261721721166396
401,401_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,8,3248,494,10,1,0.9989999999999999991118215803
402,402_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,5,1,9,10,1,0.9989999999999999991118215803
403,403_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,59,5000,262,0.001000000000000000020816681712,20,0.001000000000000000020816681712
404,404_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,2,1,1525,0.001000000000000000020816681712,1,0.001000000000000000020816681712
405,405_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,2,1,5000,0.001000000000000000020816681712,1,0.9989999999999999991118215803
406,406_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,68,5000,118,0.001000000000000000020816681712,1,0.552642418235704591111812078452
407,407_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,4,1,21,0.001000000000000000020816681712,1,0.591806268175156580113593918213
408,408_0,COMPLETED,BoTorch,GenerationStep_1,0.619999999999999995559107901499,2,1,3128,0.001000000000000000020816681712,1,0.9989999999999999991118215803
409,409_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,29,3044,127,0.001000000000000000020816681712,1,0.9989999999999999991118215803
410,410_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,39,1,8,10,20,0.9989999999999999991118215803
411,411_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,45,5000,129,10,1,0.744294579166857594998418790055
412,412_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,15,3358,302,10,1,0.001000000000000000020816681712
413,413_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,833,501,2,10,1,0.9989999999999999991118215803
414,414_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,3,5000,3279,0.001000000000000000020816681712,20,0.9989999999999999991118215803
415,415_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,9,2919,333,0.001000000000000000020816681712,1,0.9989999999999999991118215803
416,416_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,7,5000,967,10,1,0.001000000000000000020816681712
417,417_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,5,5000,1832,10,20,0.001000000000000000020816681712
418,418_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,311,5000,261,10,20,0.001000000000000000020816681712
419,419_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,19,4535,302,10,1,0.9989999999999999991118215803
420,420_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,6117,5000,1,0.001000000000000000020816681712,1,0.9989999999999999991118215803
421,421_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,57,3529,91,10,20,0.379869534478735393356885197136
422,422_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,42,4373,140,10,14,0.001000000000000000020816681712
423,423_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,146,5000,43,0.001000000000000000020816681712,1,0.9989999999999999991118215803
424,424_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,58,3932,111,0.001000000000000000020816681712,20,0.001000000000000000020816681712
425,425_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,77,5000,77,0.001000000000000000020816681712,1,0.9989999999999999991118215803
426,426_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,249,4480,322,10,10,0.001000000000000000020816681712
427,427_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,144,5000,289,10,10,0.001000000000000000020816681712
428,428_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,66,4498,90,0.001000000000000000020816681712,1,0.9989999999999999991118215803
429,429_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,65,4015,96,10,20,0.610641175041206074602939679608
430,430_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,54,4438,115,0.001000000000000000020816681712,20,0.406247287637847120933543010324
431,431_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,48,3217,77,0.001000000000000000020816681712,20,0.748587045121917316059523272997
432,432_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,14,3973,428,10,1,0.508145961518002953205552785221
433,433_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,79,4665,74,10,1,0.9989999999999999991118215803
434,434_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,43,4123,142,0.001000000000000000020816681712,20,0.001000000000000000020816681712
435,435_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,238,2872,12,10,20,0.9989999999999999991118215803
436,436_0,COMPLETED,BoTorch,GenerationStep_1,0.75,2724,3015,1,10,1,0.9989999999999999991118215803
437,437_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,58,4145,106,10,1,0.9989999999999999991118215803
438,438_0,COMPLETED,BoTorch,GenerationStep_1,0.75,2736,2855,1,0.001000000000000000020816681712,20,0.9989999999999999991118215803
439,439_0,COMPLETED,BoTorch,GenerationStep_1,0.760000000000000008881784197001,5716,5000,1,10,1,0.9989999999999999991118215803
440,440_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,24,5000,330,0.001000000000000000020816681712,10,0.001000000000000000020816681712
441,441_0,COMPLETED,BoTorch,GenerationStep_1,0.810000000000000053290705182008,32,1,1,10,1,0.68382688226986376722749128021
442,442_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,51,5000,614,0.001000000000000000020816681712,11,0.001000000000000000020816681712
443,443_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,308,4917,25,10,1,0.9989999999999999991118215803
444,444_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,30,3461,327,10,20,0.001000000000000000020816681712
445,445_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,12,3142,408,10,20,0.9989999999999999991118215803
446,446_0,COMPLETED,BoTorch,GenerationStep_1,0.739999999999999991118215802999,56,3893,103,0.001000000000000000020816681712,20,0.398515044119732209093598385152
447,447_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,45,3294,89,0.001000000000000000020816681712,20,0.60850328822462373956625469873
448,448_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,154,2943,23,10,20,0.9989999999999999991118215803
449,449_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,3,2892,1531,10,1,0.001000000000000000020816681712
450,450_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,4,5000,2108,0.001000000000000000020816681712,20,0.49502739334053147413072792915
451,451_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,2,1,1589,0.001000000000000000020816681712,20,0.001000000000000000020816681712
452,452_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,37,1,4187,10,20,0.9989999999999999991118215803
453,453_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,2,1,4332,0.001000000000000000020816681712,20,0.001000000000000000020816681712
454,454_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,4,5000,2016,10,1,0.122659812476311566586950618785
455,455_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,3,1,279,0.001000000000000000020816681712,20,0.9989999999999999991118215803
456,456_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,3,5000,4630,10,20,0.9989999999999999991118215803
457,457_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,3,4882,3402,10,1,0.68712820760523307672684723002
458,458_0,COMPLETED,BoTorch,GenerationStep_1,0.619999999999999995559107901499,3,5000,4570,0.001000000000000000020816681712,1,0.9989999999999999991118215803
459,459_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,1,1,2907,10,1,0.9989999999999999991118215803
460,460_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,7,5000,994,0.001000000000000000020816681712,1,0.9989999999999999991118215803
461,461_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,3,5000,2731,10,1,0.001000000000000000020816681712
462,462_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,3,2330,1041,0.001000000000000000020816681712,20,0.9989999999999999991118215803
463,463_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,2,1,49,10,1,0.001000000000000000020816681712
464,464_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,3,5000,2501,0.001000000000000000020816681712,1,0.001000000000000000020816681712
465,465_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,3,1664,2305,0.001000000000000000020816681712,20,0.001000000000000000020816681712
466,466_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,2,1,3007,0.001000000000000000020816681712,1,0.001000000000000000020816681712
467,467_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,8,4926,787,0.001000000000000000020816681712,1,0.579928974447770695377357696998
468,468_0,COMPLETED,BoTorch,GenerationStep_1,0.660000000000000031086244689504,2,1,4922,10,20,0.9989999999999999991118215803
469,469_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,3,4652,3647,0.001000000000000000020816681712,1,0.001000000000000000020816681712
470,470_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,3,5000,3342,10,1,0.544521993908610224544020184112
471,471_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,4,5000,2849,0.001000000000000000020816681712,20,0.459898420131524154896851541707
472,472_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,5,4960,1661,0.001000000000000000020816681712,1,0.479550643227101058840844416409
473,473_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,1,1,735,10,1,0.001000000000000000020816681712
474,474_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,2,1,131,10,1,0.001000000000000000020816681712
475,475_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,2,471,1609,0.001000000000000000020816681712,1,0.512815672247756149104702672048
476,476_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,3,3069,2362,10,1,0.9989999999999999991118215803
477,477_0,COMPLETED,BoTorch,GenerationStep_1,0.75,34,157,15,10,1,0.708495654541757891031750205002
478,478_0,COMPLETED,BoTorch,GenerationStep_1,0.640000000000000013322676295502,4,5000,2556,0.001000000000000000020816681712,1,0.001000000000000000020816681712
479,479_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,4,5000,1913,10,1,0.36967625831732991992240044965
480,480_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,3,5000,4853,10,1,0.9989999999999999991118215803
481,481_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,3,5000,3712,10,1,0.9989999999999999991118215803
482,482_0,COMPLETED,BoTorch,GenerationStep_1,0.660000000000000031086244689504,3,2205,452,0.001000000000000000020816681712,1,0.001000000000000000020816681712
483,483_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,2,1,1407,0.001000000000000000020816681712,1,0.001000000000000000020816681712
484,484_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,8,1,45,0.001000000000000000020816681712,20,0.47325975342876747120612890285
485,485_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,6,5000,1259,0.001000000000000000020816681712,1,0.618848468925940031759580506332
486,486_0,COMPLETED,BoTorch,GenerationStep_1,0.729999999999999982236431605997,3,5000,3011,0.001000000000000000020816681712,1,0.001000000000000000020816681712
487,487_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,27,5000,4870,10,20,0.001000000000000000020816681712
488,488_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,4,5000,2391,0.001000000000000000020816681712,1,0.9989999999999999991118215803
489,489_0,COMPLETED,BoTorch,GenerationStep_1,0.660000000000000031086244689504,16,1,3528,10,20,0.001000000000000000020816681712
490,490_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,11,5000,4802,10,20,0.9989999999999999991118215803
491,491_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,2,1,4011,0.001000000000000000020816681712,1,0.9989999999999999991118215803
492,492_0,COMPLETED,BoTorch,GenerationStep_1,0.709999999999999964472863211995,6,3701,993,0.001000000000000000020816681712,20,0.001000000000000000020816681712
493,493_0,COMPLETED,BoTorch,GenerationStep_1,0.75,10,105,35,10,1,0.459702317922291325835715269932
494,494_0,COMPLETED,BoTorch,GenerationStep_1,0.700000000000000066613381477509,5,4196,1307,0.001000000000000000020816681712,1,0.001000000000000000020816681712
495,495_0,COMPLETED,BoTorch,GenerationStep_1,0.660000000000000031086244689504,3,5000,4798,0.001000000000000000020816681712,1,0.001000000000000000020816681712
496,496_0,COMPLETED,BoTorch,GenerationStep_1,0.690000000000000057731597280508,7,2120,419,10,20,0.001000000000000000020816681712
497,497_0,COMPLETED,BoTorch,GenerationStep_1,0.670000000000000039968028886506,3,5000,3913,0.001000000000000000020816681712,1,0.001000000000000000020816681712
498,498_0,COMPLETED,BoTorch,GenerationStep_1,0.719999999999999973354647408996,12,4552,504,0.001000000000000000020816681712,1,0.671565545696383714435739875626
499,499_0,COMPLETED,BoTorch,GenerationStep_1,0.680000000000000048849813083507,3,5000,3691,10,20,0.001000000000000000020816681712
500,500_0,COMPLETED,BoTorch,GenerationStep_1,0.660000000000000031086244689504,6,4154,4135,10,20,0.9989999999999999991118215803
501,501_0,COMPLETED,Sobol,SOBOL,0.670000000000000039968028886506,5,2179,1989,6.339154988110066391016061970731,15,0.352086401164531714869099232601
502,502_0,COMPLETED,Sobol,SOBOL,0.670000000000000039968028886506,3,4346,3767,1.599037038854323355963060748763,2,0.508519689962267928962091900758
503,503_0,COMPLETED,Sobol,SOBOL,0.719999999999999973354647408996,25,3144,692,7.999197697264142981055101699894,18,0.869680724795907744706369157939
504,504_0,COMPLETED,Sobol,SOBOL,0.709999999999999964472863211995,4,351,2627,2.751298817995004419856286403956,6,0.028082407308742403373447160675
505,505_0,COMPLETED,Sobol,SOBOL,0.729999999999999982236431605997,23,929,164,0.879464920552447515511573783442,8,0.184992928236722947721304421975
506,506_0,COMPLETED,Sobol,SOBOL,0.709999999999999964472863211995,4,3097,3385,6.126140797570348794920391810592,16,0.964215541193261693742044826649
507,507_0,COMPLETED,Sobol,SOBOL,0.709999999999999964472863211995,6,4395,1543,4.726855416050181446507849614136,5,0.671276746211573516198711786274
508,508_0,COMPLETED,Sobol,SOBOL,0.619999999999999995559107901499,5,1602,4609,9.465750577237457719093072228134,12,0.452470112781971689486226750887
509,509_0,COMPLETED,Sobol,SOBOL,0.689999999999999946709294817992,17,1446,1107,4.252041721758433645561581215588,18,0.585175745114684064951404707244
510,510_0,COMPLETED,Sobol,SOBOL,0.650000000000000022204460492503,5,4903,3081,9.003164298015645883310753561091,9,0.304969444179907456238254326308
511,511_0,COMPLETED,Sobol,SOBOL,0.709999999999999964472863211995,4,2607,2462,0.092191714056767529172908837154,11,0.067339671744033699485321164957
512,512_0,COMPLETED,Sobol,SOBOL,0.670000000000000039968028886506,4,1025,4280,5.351056862986647288948915957008,4,0.785161170955747333977114976733
513,513_0,COMPLETED,Sobol,SOBOL,0.699999999999999955591079014994,3,197,1665,8.473990234022959810999964247458,1,0.877752062806859578714124836551
514,514_0,COMPLETED,Sobol,SOBOL,0.709999999999999964472863211995,3,3654,4691,3.213906850736588438621765817516,14,0.222303412824869150998807754149
515,515_0,COMPLETED,Sobol,SOBOL,0.719999999999999973354647408996,38,3858,383,7.126444798426703641780477482826,8,0.391709993641823517318556469036
516,516_0,COMPLETED,Sobol,SOBOL,0.660000000000000031086244689504,23,2276,3566,2.374103987812996141570920372033,20,0.734294397113844699021001360961
517,517_0,COMPLETED,Sobol,SOBOL,0.680000000000000048849813083507,7,2361,615,9.1234677623445161742665732163,4,0.060721655867993828969986225275
518,518_0,COMPLETED,Sobol,SOBOL,0.709999999999999964472863211995,6,3942,3641,3.873127646467648510508752224268,13,0.840875119226053402421428017988
519,519_0,COMPLETED,Sobol,SOBOL,0.719999999999999973354647408996,10,3587,1755,5.275914785933681017127128143329,9,0.545027724390849455105012566491
520,520_0,COMPLETED,Sobol,SOBOL,0.699999999999999955591079014994,2,130,4937,0.533355534884147330920711738145,16,0.32720900276675818352245528331
521,521_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,586,5000,732,10,20,0.245634936326524389027525785423
522,522_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,48,3204,99,10,1,0.511834643775753383998505796626
523,523_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,90,4703,91,10,1,0.703182209900971022520366204844
524,524_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.75,1140,2400,1,0.001000000000000000020816681712,1,0.87239483130999662119364757018
525,525_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.75,9,19,20,10,1,0.743013895005972369034452640335
526,526_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,2,1,36,0.001000000000000000020816681712,1,0.654063620888167496225662489451
527,527_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.660000000000000031086244689504,47,2164,411,0.001000000000000000020816681712,20,0.9989999999999999991118215803
528,528_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,3,1,51,0.001000000000000000020816681712,1,0.9989999999999999991118215803
529,529_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,69,4856,101,0.001000000000000000020816681712,1,0.212369043718389410857483312611
530,530_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,10,5000,657,0.001000000000000000020816681712,1,0.574242193265003142421676329832
531,531_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,6,17,25,10,1,0.679590873412631801819827614963
532,532_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.75,15,5000,389,0.001000000000000000020816681712,1,0.9989999999999999991118215803
533,533_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,28,2769,109,10,1,0.9989999999999999991118215803
534,534_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.75,1268,353,1,0.001000000000000000020816681712,1,0.9989999999999999991118215803
535,535_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,49,5000,306,10,20,0.922439141435058673756941516331
536,536_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,6,1,13,10,1,0.9989999999999999991118215803
537,537_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,21,1758,267,10,1,0.001000000000000000020816681712
538,538_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,212,4860,42,10,20,0.9989999999999999991118215803
539,539_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.760000000000000008881784197001,2538,888,1,10,1,0.9989999999999999991118215803
540,540_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,60,4876,103,10,1,0.573173764211009517666184365225
541,541_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,24,5000,268,10,1,0.417222937999819243337640273239
542,542_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,54,4431,126,0.001000000000000000020816681712,1,0.9989999999999999991118215803
543,543_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,95,4147,85,10,1,0.001000000000000000020816681712
544,544_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,8,1359,789,10,1,0.001000000000000000020816681712
545,545_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,12,5000,665,10,1,0.001000000000000000020816681712
546,546_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,854,2293,1,10,1,0.9989999999999999991118215803
547,547_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.689999999999999946709294817992,82,1,305,10,20,0.9989999999999999991118215803
548,548_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,2,1,49,0.001000000000000000020816681712,1,0.465272569699275162502516423046
549,549_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,1265,5000,963,10,20,0.9989999999999999991118215803
550,550_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,6,5000,1436,0.001000000000000000020816681712,20,0.001000000000000000020816681712
551,551_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.760000000000000008881784197001,5041,1463,1,10,20,0.79232441330972536164267694403
552,552_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,22,4041,348,0.001000000000000000020816681712,1,0.9989999999999999991118215803
553,553_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.619999999999999995559107901499,5,5000,4908,10,20,0.9989999999999999991118215803
554,554_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,15,3624,398,10,1,0.001000000000000000020816681712
555,555_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,9,5000,842,0.001000000000000000020816681712,1,0.001000000000000000020816681712
556,556_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.810000000000000053290705182008,39,1,1,0.001000000000000000020816681712,1,0.833089458393135862124267987383
557,557_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,13,3115,272,0.001000000000000000020816681712,1,0.001000000000000000020816681712
558,558_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.699999999999999955591079014994,196,1,251,10,20,0.001000000000000000020816681712
559,559_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,13,1,7,10,1,0.655204694743940607715160240332
560,560_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.660000000000000031086244689504,2,1,2366,10,20,0.001000000000000000020816681712
561,561_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,16,2428,124,0.001000000000000000020816681712,1,0.001000000000000000020816681712
562,562_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,90,4686,95,10,1,0.001000000000000000020816681712
563,563_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.689999999999999946709294817992,6,1261,1349,0.001000000000000000020816681712,20,0.477971208118471047043840371771
564,564_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,22,827,148,10,1,0.001000000000000000020816681712
565,565_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.660000000000000031086244689504,2,2168,2974,10,20,0.001000000000000000020816681712
566,566_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,28,2914,112,10,19,0.001000000000000000020816681712
567,567_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,15,753,210,10,1,0.001000000000000000020816681712
568,568_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,48,4660,132,10,11,0.9989999999999999991118215803
569,569_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,11,768,247,0.001000000000000000020816681712,1,0.9989999999999999991118215803
570,570_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.660000000000000031086244689504,4,4159,2330,0.001000000000000000020816681712,1,0.001000000000000000020816681712
571,571_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,12,3891,572,0.001000000000000000020816681712,1,0.609563190669008103661496988934
572,572_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.660000000000000031086244689504,4,633,1462,10,1,0.176956774151419360396886304443
573,573_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,2,2027,601,0.001000000000000000020816681712,20,0.9989999999999999991118215803
574,574_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,38,1962,181,0.001000000000000000020816681712,1,0.001000000000000000020816681712
575,575_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,22,5000,398,10,1,0.483924614518907558746718677867
576,576_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.699999999999999955591079014994,5,2428,470,0.001000000000000000020816681712,1,0.9989999999999999991118215803
577,577_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,24,3006,141,0.001000000000000000020816681712,1,0.001000000000000000020816681712
578,578_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,17,620,131,0.001000000000000000020816681712,1,0.001000000000000000020816681712
579,579_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,542,1,1,10,1,0.434691910990370689038542195703
580,580_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.699999999999999955591079014994,3,5000,4693,0.001000000000000000020816681712,20,0.9989999999999999991118215803
581,581_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,13,2786,206,0.001000000000000000020816681712,1,0.82459947590846516263241028355
582,582_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.680000000000000048849813083507,6,1114,761,0.001000000000000000020816681712,20,0.001000000000000000020816681712
583,583_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,28,3262,145,0.001000000000000000020816681712,20,0.340978332306642428761733754072
584,584_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,249,2411,340,10,20,0.306529417826031269633801912278
585,585_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.689999999999999946709294817992,7,5000,1601,10,1,0.001000000000000000020816681712
586,586_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.699999999999999955591079014994,3,1699,3383,0.001000000000000000020816681712,1,0.9989999999999999991118215803
587,587_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.75,27,2798,88,0.001000000000000000020816681712,1,0.001000000000000000020816681712
588,588_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.650000000000000022204460492503,2,938,4019,0.001000000000000000020816681712,1,0.9989999999999999991118215803
589,589_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.689999999999999946709294817992,6,4397,2124,0.001000000000000000020816681712,20,0.489555788275771841533412498393
590,590_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,29,1658,299,0.001000000000000000020816681712,1,0.814747126481145889087542855123
591,591_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,1874,508,1,0.001000000000000000020816681712,9,0.889151595706708208766144707624
592,592_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,27,1325,167,0.001000000000000000020816681712,1,0.001000000000000000020816681712
593,593_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,9,676,331,0.001000000000000000020816681712,1,0.9989999999999999991118215803
594,594_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,1743,2645,1,0.001000000000000000020816681712,1,0.84160322933948139567661428373
595,595_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,24,2784,100,0.001000000000000000020816681712,1,0.317238452579041707579676767637
596,596_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,54,4629,117,0.001000000000000000020816681712,1,0.801362576583848018607625363074
597,597_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,54,4359,292,10,20,0.9989999999999999991118215803
598,598_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.689999999999999946709294817992,4,2407,749,0.001000000000000000020816681712,1,0.267898607587085668679804939529
599,599_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,27,4247,314,0.001000000000000000020816681712,1,0.9989999999999999991118215803
600,600_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,19,4552,328,0.001000000000000000020816681712,1,0.301035903296336115886333573144
601,601_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,18,4465,381,0.001000000000000000020816681712,1,0.9989999999999999991118215803
602,602_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,81,5000,110,0.001000000000000000020816681712,1,0.9989999999999999991118215803
603,603_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,128,5000,82,10,1,0.001000000000000000020816681712
604,604_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,27,3855,256,0.001000000000000000020816681712,20,0.001000000000000000020816681712
605,605_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,45,3143,96,0.001000000000000000020816681712,20,0.001000000000000000020816681712
606,606_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,65,4498,104,0.001000000000000000020816681712,1,0.001000000000000000020816681712
607,607_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,20,2476,119,10,1,0.306376112390076227320889756811
608,608_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.660000000000000031086244689504,5,5000,4055,0.001000000000000000020816681712,1,0.001000000000000000020816681712
609,609_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,7,3481,1045,10,1,0.9989999999999999991118215803
610,610_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,15,4079,562,10,20,0.555283005892674208503478894272
611,611_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,21,1376,238,10,1,0.778259612273463408094187343522
612,612_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,20,5000,1192,10,20,0.001000000000000000020816681712
613,613_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,22,2977,153,0.001000000000000000020816681712,20,0.9989999999999999991118215803
614,614_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,10,2657,198,10,1,0.9989999999999999991118215803
615,615_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,3,810,2375,0.001000000000000000020816681712,20,0.9989999999999999991118215803
616,616_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,32,1173,160,10,20,0.001000000000000000020816681712
617,617_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,6,5000,1740,10,1,0.9989999999999999991118215803
618,618_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,53,4554,144,0.001000000000000000020816681712,20,0.9989999999999999991118215803
619,619_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,7,4485,1127,0.001000000000000000020816681712,20,0.9989999999999999991118215803
620,620_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,62,4181,112,10,5,0.001000000000000000020816681712
621,621_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.650000000000000022204460492503,3,3753,5000,0.001000000000000000020816681712,20,0.001000000000000000020816681712
622,622_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.699999999999999955591079014994,13,3905,1238,10,20,0.001000000000000000020816681712
623,623_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,5,1768,1791,10,20,0.9989999999999999991118215803
624,624_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,7,157,159,0.001000000000000000020816681712,20,0.001000000000000000020816681712
625,625_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,11,4040,562,10,1,0.9989999999999999991118215803
626,626_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,24,1252,206,10,1,0.001000000000000000020816681712
627,627_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,21,3646,251,10,1,0.9989999999999999991118215803
628,628_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,11,3131,578,10,20,0.898966143345196089242676862341
629,629_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.689999999999999946709294817992,10,3461,824,0.001000000000000000020816681712,1,0.001000000000000000020816681712
630,630_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,29,2850,119,10,1,0.001000000000000000020816681712
631,631_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,27,4209,302,10,1,0.001000000000000000020816681712
632,632_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.650000000000000022204460492503,3,2735,1835,10,20,0.9989999999999999991118215803
633,633_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,21,587,97,0.001000000000000000020816681712,1,0.001000000000000000020816681712
634,634_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.650000000000000022204460492503,3,3227,2737,0.001000000000000000020816681712,20,0.001000000000000000020816681712
635,635_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.699999999999999955591079014994,4,5000,2749,10,1,0.399549027042126081443740304167
636,636_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,4,5000,2811,0.001000000000000000020816681712,1,0.9989999999999999991118215803
637,637_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,28,1953,256,10,1,0.9989999999999999991118215803
638,638_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,23,4601,447,0.001000000000000000020816681712,6,0.001000000000000000020816681712
639,639_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,26,2724,94,0.001000000000000000020816681712,20,0.001000000000000000020816681712
640,640_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.660000000000000031086244689504,4,1100,2397,10,1,0.9989999999999999991118215803
641,641_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,65,4710,123,10,1,0.9989999999999999991118215803
642,642_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.660000000000000031086244689504,3,2003,193,10,1,0.066506047225541042866581165072
643,643_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,15,4133,444,10,1,0.9989999999999999991118215803
644,644_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,25,3993,324,0.001000000000000000020816681712,20,0.9989999999999999991118215803
645,645_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,14,3466,359,10,1,0.9989999999999999991118215803
646,646_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,65,4936,95,0.001000000000000000020816681712,1,0.740938988071501491994297339261
647,647_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,33,2991,100,10,20,0.708250873695595473122921248432
648,648_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,98,4963,99,0.001000000000000000020816681712,1,0.535274927770195918519391398149
649,649_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,30,4195,252,0.001000000000000000020816681712,1,0.001000000000000000020816681712
650,650_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,65,4739,119,10,20,0.718101548461065108952539048914
651,651_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,44,2969,82,0.001000000000000000020816681712,1,0.9989999999999999991118215803
652,652_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,2356,2637,1,0.001000000000000000020816681712,20,0.837597901368810404676423786441
653,653_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,1864,2642,1,10,1,0.9989999999999999991118215803
654,654_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,14,4719,461,10,1,0.9989999999999999991118215803
655,655_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,81,4750,95,10,1,0.332820391595666120743146620953
656,656_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,5,2301,327,10,1,0.702284497640657590089574568992
657,657_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,58,4827,120,0.001000000000000000020816681712,1,0.9989999999999999991118215803
658,658_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,11,4433,574,10,1,0.379181975211485000620825758233
659,659_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,19,3748,280,0.001000000000000000020816681712,1,0.541517016357464964215751024312
660,660_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,26,3814,275,10,1,0.001000000000000000020816681712
661,661_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,16,1026,275,0.001000000000000000020816681712,1,0.001000000000000000020816681712
662,662_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,78,4700,91,0.001000000000000000020816681712,20,0.001000000000000000020816681712
663,663_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,12,4354,573,0.001000000000000000020816681712,20,0.9989999999999999991118215803
664,664_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,13,5000,463,10,1,0.497019975702735095079987104327
665,665_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,23,4552,273,0.001000000000000000020816681712,20,0.768544828625439824243414932425
666,666_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,49,4630,130,10,20,0.9989999999999999991118215803
667,667_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,47,4306,127,0.001000000000000000020816681712,1,0.312113596243715984979161248702
668,668_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,33,3269,128,0.001000000000000000020816681712,20,0.001000000000000000020816681712
669,669_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,14,4569,408,10,1,0.001000000000000000020816681712
670,670_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,14,4584,415,0.001000000000000000020816681712,1,0.300457206894607808944641647031
671,671_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,28,2922,103,10,1,0.598808355859835828027826210018
672,672_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,25,1966,244,0.001000000000000000020816681712,20,0.9989999999999999991118215803
673,673_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,24,3530,274,0.001000000000000000020816681712,20,0.9989999999999999991118215803
674,674_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,14,509,182,0.001000000000000000020816681712,1,0.001000000000000000020816681712
675,675_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,10,4571,743,10,1,0.9989999999999999991118215803
676,676_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,1219,4491,679,10,20,0.9989999999999999991118215803
677,677_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,8,2651,296,10,1,0.9989999999999999991118215803
678,678_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.699999999999999955591079014994,11,3964,760,0.001000000000000000020816681712,20,0.9989999999999999991118215803
679,679_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.680000000000000048849813083507,2,1176,5000,10,1,0.9989999999999999991118215803
680,680_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,46,3835,151,10,1,0.9989999999999999991118215803
681,681_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,36,3040,105,0.001000000000000000020816681712,1,0.63331442458999631650584660747
682,682_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,36,4021,187,0.001000000000000000020816681712,20,0.9989999999999999991118215803
683,683_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,32,2982,129,10,20,0.558450464044279781816726426769
684,684_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,40,3148,92,10,20,0.001000000000000000020816681712
685,685_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,321,1,340,10,20,0.001000000000000000020816681712
686,686_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,35,3174,189,0.001000000000000000020816681712,20,0.9989999999999999991118215803
687,687_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,41,1920,212,0.001000000000000000020816681712,20,0.001000000000000000020816681712
688,688_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,25,4417,515,10,20,0.9989999999999999991118215803
689,689_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.699999999999999955591079014994,13,3627,665,0.001000000000000000020816681712,20,0.001000000000000000020816681712
690,690_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,6,4013,1073,10,1,0.181381220827376454796109328527
691,691_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.670000000000000039968028886506,4,5000,2730,0.001000000000000000020816681712,1,0.9989999999999999991118215803
692,692_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,15,4393,495,0.001000000000000000020816681712,1,0.001000000000000000020816681712
693,693_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,234,4429,813,10,20,0.001000000000000000020816681712
694,694_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.699999999999999955591079014994,6,4870,1329,10,1,0.298351141975666256378474372468
695,695_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,10,4495,640,0.001000000000000000020816681712,20,0.401580952597170415252492148284
696,696_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,72,4983,100,10,1,0.448722694738025285055016411206
697,697_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,19,4133,364,10,1,0.001000000000000000020816681712
698,698_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.660000000000000031086244689504,2,2078,1467,0.001000000000000000020816681712,1,0.001000000000000000020816681712
699,699_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,15,4410,590,0.001000000000000000020816681712,1,0.870171527359448915284190206876
700,700_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,8,3348,597,0.001000000000000000020816681712,1,0.9989999999999999991118215803
701,701_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,52,3701,118,10,20,0.001000000000000000020816681712
702,702_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,32,2806,83,10,1,0.001000000000000000020816681712
703,703_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,16,2646,178,10,19,0.001000000000000000020816681712
704,704_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.75,2267,2636,1,4.921976815304446972731966525316,7,0.9989999999999999991118215803
705,705_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,61,4467,105,10,20,0.001000000000000000020816681712
706,706_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,19,4371,328,0.001000000000000000020816681712,20,0.344346372391821253788890544456
707,707_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.680000000000000048849813083507,3,2639,1019,0.001000000000000000020816681712,1,0.001000000000000000020816681712
708,708_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,40,4021,155,10,1,0.512448908516001222501756728889
709,709_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,124,4625,342,0.001000000000000000020816681712,20,0.001000000000000000020816681712
710,710_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,19,4122,341,0.001000000000000000020816681712,20,0.001000000000000000020816681712
711,711_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,22,3430,476,10,15,0.571862652029844542589387401677
712,712_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,16,2912,200,10,1,0.299831029075891930535391338708
713,713_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,12,2970,245,0.001000000000000000020816681712,1,0.9989999999999999991118215803
714,714_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,17,3468,342,0.001000000000000000020816681712,1,0.583546579005764454173288413585
715,715_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.699999999999999955591079014994,3,2900,1236,10,1,0.001000000000000000020816681712
716,716_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.660000000000000031086244689504,4,591,1217,0.001000000000000000020816681712,20,0.9989999999999999991118215803
717,717_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,28,3081,138,10,20,0.9989999999999999991118215803
718,718_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.680000000000000048849813083507,7,4452,1168,0.001000000000000000020816681712,20,0.001000000000000000020816681712
719,719_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,19,4174,330,10,1,0.60111839789288656898946783258
720,720_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,11,756,254,0.001000000000000000020816681712,1,0.646657403882320069854472421866
721,721_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,13,4857,548,10,1,0.433787173300875905646023511508
722,722_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,11,4256,686,0.001000000000000000020816681712,1,0.322861775014304908104634250776
723,723_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,87,5000,94,10,1,0.9989999999999999991118215803
724,724_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,38,3045,100,0.001000000000000000020816681712,20,0.313685111955037676523261325201
725,725_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,13,5000,499,10,1,0.001000000000000000020816681712
726,726_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,30,2938,111,10,20,0.203936735715402300828102966079
727,727_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,28,3112,122,10,1,0.24452129227070557027090558222
728,728_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,9,2392,155,0.001000000000000000020816681712,1,0.001000000000000000020816681712
729,729_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.680000000000000048849813083507,4,5000,2940,0.001000000000000000020816681712,1,0.9989999999999999991118215803
730,730_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.660000000000000031086244689504,2,1,1581,10,1,0.001000000000000000020816681712
731,731_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,89,4747,85,0.001000000000000000020816681712,1,0.001000000000000000020816681712
732,732_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,75,4518,111,10,1,0.554330860559730909109532603907
733,733_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,37,3721,143,10,20,0.373391704001361346421106190974
734,734_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,15,5000,399,0.001000000000000000020816681712,1,0.704850887822567662155393009016
735,735_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.680000000000000048849813083507,4,1,2523,10,20,0.001000000000000000020816681712
736,736_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,35,3633,217,10,20,0.9989999999999999991118215803
737,737_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,32,1300,142,0.001000000000000000020816681712,1,0.001000000000000000020816681712
738,738_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,22,789,121,10,20,0.001000000000000000020816681712
739,739_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,25,3394,175,10,1,0.9989999999999999991118215803
740,740_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,87,5000,84,0.001000000000000000020816681712,20,0.001000000000000000020816681712
741,741_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,13,5000,562,10,1,0.699408648939845778436108503229
742,742_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.699999999999999955591079014994,9,4904,844,10,1,0.518198819678064914739934465615
743,743_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,44,3221,92,0.001000000000000000020816681712,1,0.416289831274359201085388804131
744,744_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,14,4311,455,0.001000000000000000020816681712,1,0.001000000000000000020816681712
745,745_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,42,3819,146,0.001000000000000000020816681712,20,0.760232300414082518003056065936
746,746_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,142,2619,237,0.001000000000000000020816681712,20,0.871299359665128614338414081431
747,747_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,38,3733,145,10,20,0.001000000000000000020816681712
748,748_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,61,2956,230,10,20,0.9989999999999999991118215803
749,749_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,83,4378,114,0.001000000000000000020816681712,20,0.001000000000000000020816681712
750,750_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,19,1178,253,0.001000000000000000020816681712,20,0.9989999999999999991118215803
751,751_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,55,1764,131,10,1,0.001000000000000000020816681712
752,752_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,50,3150,74,10,1,0.001000000000000000020816681712
753,753_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,34,3503,129,10,1,0.001000000000000000020816681712
754,754_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,28,3369,153,0.001000000000000000020816681712,1,0.9989999999999999991118215803
755,755_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,46,4409,129,10,1,0.9989999999999999991118215803
756,756_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,49,4182,129,0.001000000000000000020816681712,1,0.001000000000000000020816681712
757,757_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,30,1216,181,0.001000000000000000020816681712,16,0.001000000000000000020816681712
758,758_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,15,4000,404,10,1,0.80381453551418768910252765636
759,759_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,5,1,24,10,1,0.9989999999999999991118215803
760,760_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.689999999999999946709294817992,5,5000,1274,10,1,0.001000000000000000020816681712
761,761_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,42,1851,193,0.001000000000000000020816681712,1,0.501014092058657434236579319986
762,762_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,12,2421,115,10,1,0.001000000000000000020816681712
763,763_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,54,4916,116,0.001000000000000000020816681712,9,0.9989999999999999991118215803
764,764_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,80,4560,112,10,20,0.430548858944595602693539149186
765,765_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.630000000000000004440892098501,3,3544,3336,10,1,0.9989999999999999991118215803
766,766_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,60,4803,109,0.001000000000000000020816681712,1,0.721383144694819233855298534763
767,767_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,15,4322,512,0.001000000000000000020816681712,20,0.484864940369024721711355141451
768,768_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,10,2500,180,10,1,0.001000000000000000020816681712
769,769_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,23,5000,282,10,1,0.9989999999999999991118215803
770,770_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.680000000000000048849813083507,2,2085,1730,10,1,0.9989999999999999991118215803
771,771_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,63,5000,102,0.001000000000000000020816681712,8,0.6689841333411876700409948171
772,772_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,69,4951,94,10,10,0.001000000000000000020816681712
773,773_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,28,5000,365,10,1,0.202313529667489194752150183376
774,774_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,74,4844,86,10,20,0.405525821871942471208427605234
775,775_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,27,4337,242,0.001000000000000000020816681712,1,0.9989999999999999991118215803
776,776_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,25,4642,379,0.001000000000000000020816681712,1,0.650655401607157068966102997365
777,777_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.699999999999999955591079014994,127,241,270,10,20,0.244930271577782687764113234152
778,778_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,39,3157,106,0.001000000000000000020816681712,20,0.9989999999999999991118215803
779,779_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,4,1,15,10,1,0.9989999999999999991118215803
780,780_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,23,4445,1393,10,20,0.628040210117312369675346417353
781,781_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,17,1255,256,10,1,0.9989999999999999991118215803
782,782_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.609999999999999986677323704498,2,1,1445,0.001000000000000000020816681712,20,0.001000000000000000020816681712
783,783_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,50,4525,132,10,20,0.703990613204510840006378202816
784,784_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,141,2754,24,10,1,0.9989999999999999991118215803
785,785_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,75,2789,38,10,1,0.9989999999999999991118215803
786,786_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,173,2700,13,10,1,0.9989999999999999991118215803
787,787_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,49,2825,51,10,1,0.9989999999999999991118215803
788,788_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.760000000000000008881784197001,3201,2999,1,0.001000000000000000020816681712,1,0.9989999999999999991118215803
789,789_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,100,2746,28,0.001000000000000000020816681712,1,0.9989999999999999991118215803
790,790_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,53,2829,80,10,1,0.9989999999999999991118215803
791,791_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.75,3534,3082,1,10,20,0.9989999999999999991118215803
792,792_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,173,5000,64,10,1,0.9989999999999999991118215803
793,793_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,299,2839,27,0.001000000000000000020816681712,20,0.9989999999999999991118215803
794,794_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,639,2761,1,10,1,0.001000000000000000020816681712
795,795_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.699999999999999955591079014994,10,5000,4734,10,20,0.001000000000000000020816681712
796,796_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,107,5000,78,10,20,0.9989999999999999991118215803
797,797_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,35,2875,96,10,1,0.9989999999999999991118215803
798,798_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.760000000000000008881784197001,4456,3390,1,10,20,0.9989999999999999991118215803
799,799_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,131,5000,62,10,20,0.9989999999999999991118215803
800,800_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,293,5000,36,0.001000000000000000020816681712,20,0.9989999999999999991118215803
801,801_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,173,5000,65,0.001000000000000000020816681712,20,0.9989999999999999991118215803
802,802_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,48,2883,69,10,20,0.9989999999999999991118215803
803,803_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,331,2663,7,10,1,0.9989999999999999991118215803
804,804_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,3,431,3941,0.001000000000000000020816681712,1,0.001000000000000000020816681712
805,805_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,91,2800,47,0.001000000000000000020816681712,1,0.9989999999999999991118215803
806,806_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,583,200,1,10,1,0.9989999999999999991118215803
807,807_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.689999999999999946709294817992,17,3942,1640,10,20,0.324149023957811810436879795816
808,808_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.689999999999999946709294817992,2,1,3929,0.001000000000000000020816681712,1,0.001000000000000000020816681712
809,809_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,86,2892,38,10,20,0.9989999999999999991118215803
810,810_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.810000000000000053290705182008,131,1,1,10,7,0.845880908435667766553933688556
811,811_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,60,5000,109,0.001000000000000000020816681712,20,0.956603391153051263451345676003
812,812_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,4,3736,4773,10,1,0.9989999999999999991118215803
813,813_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,4,4109,2856,0.001000000000000000020816681712,1,0.001000000000000000020816681712
814,814_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,57,2780,68,10,1,0.9989999999999999991118215803
815,815_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.670000000000000039968028886506,3,2631,4671,0.001000000000000000020816681712,20,0.9989999999999999991118215803
816,816_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.670000000000000039968028886506,2,2524,3315,0.001000000000000000020816681712,20,0.489114074826769995585351580303
817,817_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,624,2657,5,10,20,0.9989999999999999991118215803
818,818_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,6,5000,1405,0.001000000000000000020816681712,20,0.598335188031162812372087955737
819,819_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,78,1909,96,10,20,0.9989999999999999991118215803
820,820_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.75,1700,5000,4,10,20,0.9989999999999999991118215803
821,821_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,19,403,86,10,10,0.001000000000000000020816681712
822,822_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,15,2512,110,0.001000000000000000020816681712,10,0.001000000000000000020816681712
823,823_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,117,5000,556,10,10,0.001000000000000000020816681712
824,824_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,6,5000,1355,10,11,0.9989999999999999991118215803
825,825_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.689999999999999946709294817992,5,5000,1725,0.001000000000000000020816681712,10,0.001000000000000000020816681712
826,826_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,4,1,75,0.001000000000000000020816681712,11,0.001000000000000000020816681712
827,827_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.689999999999999946709294817992,5,5000,2007,10,20,0.001000000000000000020816681712
828,828_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.699999999999999955591079014994,8,5000,1161,0.001000000000000000020816681712,11,0.9989999999999999991118215803
829,829_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,8,5000,930,0.001000000000000000020816681712,1,0.9989999999999999991118215803
830,830_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.660000000000000031086244689504,3,2338,3952,10,10,0.001000000000000000020816681712
831,831_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,4,5000,2892,0.001000000000000000020816681712,10,0.001000000000000000020816681712
832,832_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,4,1,82,0.001000000000000000020816681712,12,0.9989999999999999991118215803
833,833_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,11,4987,1224,10,11,0.366253154210592180017869168296
834,834_0,RUNNING,BoTorch,BOTORCH_MODULAR,,,3772,1,10,1,0.9989999999999999991118215803
835,835_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,2,1,3181,0.001000000000000000020816681712,20,0.001000000000000000020816681712
836,836_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.689999999999999946709294817992,2,1,1005,10,1,0.9989999999999999991118215803
837,837_0,RUNNING,BoTorch,BOTORCH_MODULAR,,,5000,57,0.001000000000000000020816681712,1,0.9989999999999999991118215803</pre>
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<h1><img class='invert_icon' src='i/table.svg' style='height: 1em' />&nbsp;Args Overview</h1>
<h2>Arguments Overview:                                                                              </h2><table cellspacing="0" cellpadding="5"><thead><tr><th> Key</th><th>Value                                                                                                                           </th></tr></thead><tbody><tr><td> config_yaml</td><td>None                                                                                                                            </td></tr><tr><td> config_toml</td><td>None                                                                                                                            </td></tr><tr><td> config_json</td><td>None                                                                                                                            </td></tr><tr><td> num_random_steps</td><td>20                                                                                                                              </td></tr><tr><td> max_eval</td><td>50000                                                                                                                           </td></tr><tr><td> run_program</td><td>None                                                                                                                            </td></tr><tr><td> experiment_name</td><td>None                                                                                                                            </td></tr><tr><td> mem_gb</td><td>1                                                                                                                               </td></tr><tr><td> parameter</td><td>None                                                                                                                            </td></tr><tr><td> continue_previous_job</td><td>/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_Electricity_HoeffdingTreeClassifier_ACCURACY-RUNTIME/0/ </td></tr><tr><td> experiment_constraints</td><td>None                                                                                                                            </td></tr><tr><td> run_dir</td><td>runs                                                                                                                            </td></tr><tr><td> seed</td><td>None                                                                                                                            </td></tr><tr><td> decimalrounding</td><td>4                                                                                                                               </td></tr><tr><td> enforce_sequential_optimization</td><td>False                                                                                                                           </td></tr><tr><td> verbose_tqdm</td><td>False                                                                                                                           </td></tr><tr><td> model</td><td>None                                                                                                                            </td></tr><tr><td> gridsearch</td><td>False                                                                                                                           </td></tr><tr><td> occ</td><td>False                                                                                                                           </td></tr><tr><td> show_sixel_scatter</td><td>False                                                                                                                           </td></tr><tr><td> show_sixel_general</td><td>False                                                                                                                           </td></tr><tr><td> show_sixel_trial_index_result</td><td>False                                                                                                                           </td></tr><tr><td> follow</td><td>False                                                                                                                           </td></tr><tr><td> send_anonymized_usage_stats</td><td>False                                                                                                                           </td></tr><tr><td> ui_url</td><td>None                                                                                                                            </td></tr><tr><td> root_venv_dir</td><td>/home/s4122485                                                                                                                  </td></tr><tr><td> exclude</td><td>None                                                                                                                            </td></tr><tr><td> main_process_gb</td><td>8                                                                                                                               </td></tr><tr><td> pareto_front_confidence</td><td>1                                                                                                                               </td></tr><tr><td> max_nr_of_zero_results</td><td>10                                                                                                                              </td></tr><tr><td> abbreviate_job_names</td><td>False                                                                                                                           </td></tr><tr><td> orchestrator_file</td><td>None                                                                                                                            </td></tr><tr><td> checkout_to_latest_tested_version</td><td>False                                                                                                                           </td></tr><tr><td> live_share</td><td>False                                                                                                                           </td></tr><tr><td> disable_tqdm</td><td>False                                                                                                                           </td></tr><tr><td> workdir</td><td>False                                                                                                                           </td></tr><tr><td> occ_type</td><td>euclid                                                                                                                          </td></tr><tr><td> result_names</td><td>[&#039;RESULT=min&#039;]                                                                                                                  </td></tr><tr><td> minkowski_p</td><td>2                                                                                                                               </td></tr><tr><td> signed_weighted_euclidean_weights</td><td></td></tr><tr><td> generation_strategy</td><td>None                                                                                                                            </td></tr><tr><td> generate_all_jobs_at_once</td><td>False                                                                                                                           </td></tr><tr><td> revert_to_random_when_seemingly_exhausted</td><td>True                                                                                                                            </td></tr><tr><td> load_data_from_existing_jobs</td><td>[]                                                                                                                              </td></tr><tr><td> n_estimators_randomforest</td><td>100                                                                                                                             </td></tr><tr><td> external_generator</td><td>None                                                                                                                            </td></tr><tr><td> username</td><td>None                                                                                                                            </td></tr><tr><td> max_failed_jobs</td><td>None                                                                                                                            </td></tr><tr><td> num_parallel_jobs</td><td>20                                                                                                                              </td></tr><tr><td> worker_timeout</td><td>120                                                                                                                             </td></tr><tr><td> slurm_use_srun</td><td>False                                                                                                                           </td></tr><tr><td> time</td><td></td></tr><tr><td> partition</td><td></td></tr><tr><td> reservation</td><td>None                                                                                                                            </td></tr><tr><td> force_local_execution</td><td>False                                                                                                                           </td></tr><tr><td> slurm_signal_delay_s</td><td>0                                                                                                                               </td></tr><tr><td> nodes_per_job</td><td>1                                                                                                                               </td></tr><tr><td> cpus_per_task</td><td>1                                                                                                                               </td></tr><tr><td> account</td><td>None                                                                                                                            </td></tr><tr><td> gpus</td><td>0                                                                                                                               </td></tr><tr><td> run_mode</td><td>local                                                                                                                           </td></tr><tr><td> verbose</td><td>False                                                                                                                           </td></tr><tr><td> verbose_break_run_search_table</td><td>False                                                                                                                           </td></tr><tr><td> debug</td><td>False                                                                                                                           </td></tr><tr><td> no_sleep</td><td>False                                                                                                                           </td></tr><tr><td> tests</td><td>False                                                                                                                           </td></tr><tr><td> show_worker_percentage_table_at_end</td><td>False                                                                                                                           </td></tr><tr><td> auto_exclude_defective_hosts</td><td>False                                                                                                                           </td></tr><tr><td> run_tests_that_fail_on_taurus</td><td>False                                                                                                                           </td></tr><tr><td> raise_in_eval</td><td>False                                                                                                                           </td></tr><tr><td> show_ram_every_n_seconds</td><td>False                                                                                                                           </td></tr></tbody></table>
<h1><img class='invert_icon' src='i/plot.svg' style='height: 1em' />&nbsp;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")'><img src='i/clipboard.svg' style='height: 1em'> Copy raw data to clipboard</button>
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<pre id="pre_tab_worker_usage">1745405554.9346569,20,0,0
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1745604832.5938933,20,1,5
1745604849.2918274,20,1,5
1745604866.2224352,20,1,5
1745604884.5199935,20,1,5
1745604901.3650603,20,1,5
1745604918.3501656,20,1,5
1745604935.300173,20,1,5
1745604952.249277,20,1,5
1745604969.529422,20,1,5
1745604988.0824556,20,1,5
1745605005.333832,20,1,5
1745605022.776534,20,1,5
1745605040.044138,20,1,5
1745605057.0563266,20,1,5
1745605074.1895633,20,1,5
1745605092.4399033,20,1,5
1745605109.5332012,20,1,5
1745605126.1819274,20,1,5
1745605143.2884872,20,1,5
1745605160.555429,20,1,5
1745605177.7425194,20,1,5
1745605194.9856148,20,1,5
1745605213.586285,20,1,5
1745605230.8720584,20,1,5
1745605248.0794926,20,1,5
1745605265.327508,20,1,5
1745605282.490549,20,1,5
1745605299.6418378,20,1,5
1745605316.7240741,20,1,5
1745605333.9475086,20,1,5
1745605351.3255157,20,1,5
1745605368.514389,20,1,5
1745605387.7931526,20,1,5
1745605404.781488,20,1,5
1745605422.0525763,20,1,5
1745605439.088019,20,1,5
1745605455.748657,20,1,5
1745605472.592266,20,1,5
1745605489.6034248,20,1,5
1745605506.5783894,20,1,5
1745605523.7408476,20,1,5
1745605541.107751,20,1,5
1745605558.4668179,20,1,5
1745605575.6434417,20,1,5
1745605592.8487847,20,1,5
1745605609.9748704,20,1,5
1745605628.581509,20,1,5
1745605645.5514624,20,1,5
1745605662.4718134,20,1,5
1745605679.4326968,20,1,5
1745605696.545702,20,1,5
1745605714.0561795,20,1,5
1745605731.4627962,20,1,5
1745605748.768053,20,1,5
1745605766.053501,20,1,5
1745605783.4528675,20,1,5
1745605800.8538516,20,1,5
1745605818.119869,20,1,5
1745605835.4004765,20,1,5
1745605852.7443664,20,1,5
1745605870.0740366,20,1,5
1745605887.3736255,20,1,5
1745605904.8205419,20,1,5
1745605922.2887442,20,1,5
1745605939.7699723,20,1,5
1745605957.295885,20,1,5
1745605974.9298782,20,1,5
1745605992.4730928,20,1,5
1745606010.0807345,20,1,5
1745606027.5752559,20,1,5
1745606045.0739648,20,1,5
1745606062.3857174,20,1,5
1745606079.5301402,20,1,5
1745606096.6863241,20,1,5
1745606113.572757,20,1,5
1745606130.4949667,20,1,5
1745606147.4910753,20,1,5
1745606164.6579869,20,1,5
1745606181.8458633,20,1,5
1745606199.2068894,20,1,5
1745606216.5467687,20,1,5
1745606233.6394956,20,1,5
1745606250.784903,20,1,5
1745606271.372683,20,1,5
1745606288.6264427,20,1,5
1745606306.1368089,20,1,5
1745606323.516576,20,1,5
1745606341.072866,20,1,5
1745606358.4732814,20,1,5
1745606375.925816,20,1,5
1745606393.428797,20,1,5
1745606411.0133405,20,1,5
1745606428.5763361,20,1,5
1745606445.946444,20,1,5
1745606463.5650911,20,1,5
1745606479.1951709,20,1,5
1745606496.7278557,20,1,5
1745606514.2746882,20,1,5
1745606531.7750428,20,1,5
1745606549.4619026,20,1,5
1745606566.958948,20,1,5
1745606584.8045852,20,1,5
1745606602.4585702,20,1,5
1745606619.9711244,20,1,5
1745606625.549862,20,1,5
1745606639.5506496,20,0,0
1745606658.9021418,20,0,0
1745607329.7095013,20,0,0
1745607329.9650452,20,0,0
1745607331.4901998,20,1,5
1745607344.7061882,20,1,5
1745607895.7645364,20,1,5
1745607896.1155968,20,1,5
1745607897.578759,20,2,10
1745607898.2141175,20,2,10
1745607917.9087818,20,1,5
1745607918.007284,20,1,5
1745608646.6389682,20,1,5
1745608647.0319042,20,1,5
1745608648.502837,20,2,10
1745608649.1559954,20,2,10
1745608670.2122319,20,1,5
1745608670.414766,20,1,5
1745610424.9133594,20,1,5
1745610425.2743397,20,1,5
1745610427.0671203,20,2,10
1745610427.69074,20,2,10
1745610446.6407757,20,1,5
1745610446.7297728,20,1,5
1745611059.0997748,20,1,5
1745611059.4487944,20,1,5
1745611061.0762691,20,2,10
1745611061.719206,20,2,10
1745611082.6328769,20,1,5
1745611082.8739214,20,1,5
1745611706.4928644,20,1,5
1745611707.0158713,20,1,5
1745611708.4869192,20,2,10
1745611709.0833564,20,2,10
1745611727.4557817,20,1,5
1745611727.8896105,20,1,5
1745613589.7828243,20,1,5
1745613590.128069,20,1,5
1745613591.5675592,20,2,10
1745613592.212217,20,2,10
1745613612.957692,20,1,5
1745613613.1488874,20,1,5
1745615262.494417,20,1,5
1745615263.260843,20,1,5
1745615265.0661805,20,2,10
1745615265.6864476,20,2,10
1745615286.6538868,20,1,5
1745615286.882278,20,1,5
1745615916.3503287,20,1,5
1745615916.5797627,20,1,5
1745615918.0719697,20,2,10
1745615918.6623814,20,2,10
1745615937.296647,20,1,5
1745615937.6059134,20,1,5
1745617481.3400497,20,1,5
1745617481.9544268,20,1,5
1745617483.3758984,20,2,10
1745617483.9840627,20,2,10
1745617503.0667849,20,1,5
1745617503.260829,20,1,5
1745618890.611493,20,1,5
1745618891.0107865,20,1,5
1745618892.444642,20,2,10
1745618893.05072,20,2,10
1745618911.6257153,20,1,5
1745618911.879643,20,1,5
1745620568.3174617,20,1,5
1745620568.9191113,20,1,5
1745620570.3540702,20,2,10
1745620570.9480686,20,2,10
1745620589.3502438,20,1,5
1745620589.8248103,20,1,5
1745622359.7962086,20,1,5
1745622360.1521063,20,1,5
1745622362.074689,20,2,10
1745622362.6921222,20,2,10
1745622381.588911,20,1,5
1745622381.8675988,20,1,5
1745623147.8942788,20,1,5
1745623149.2729585,20,1,5
1745623151.046506,20,2,10
1745623151.6782756,20,2,10
1745623170.4635773,20,1,5
1745623170.8903322,20,1,5
1745625082.8406038,20,1,5
1745625083.1621556,20,1,5
1745625084.6438117,20,2,10
1745625085.2188163,20,2,10
1745625103.2842314,20,1,5
1745625103.5339563,20,1,5
1745626905.9541614,20,1,5
1745626906.2935712,20,1,5
1745626908.0627356,20,2,10
1745626908.653515,20,2,10
1745626927.1996331,20,1,5
1745626927.3868928,20,1,5
1745627638.6323175,20,1,5
1745627638.8666382,20,1,5
1745627640.3100414,20,2,10
1745627640.9113636,20,2,10
1745627660.2427206,20,1,5
1745627660.4434175,20,1,5
1745629591.385515,20,1,5
1745629591.9961963,20,1,5
1745629593.4426868,20,2,10
1745629594.0478067,20,2,10
1745629613.8964477,20,1,5
1745629614.0989423,20,1,5
1745630426.499666,20,1,5
1745630427.0161016,20,1,5
1745630428.467163,20,2,10
1745630429.0921292,20,2,10
1745630448.582061,20,1,5
1745630448.883157,20,1,5
1745631210.8306327,20,1,5
1745631211.178447,20,1,5
1745631212.6576881,20,2,10
1745631213.2362635,20,2,10
1745631233.0449529,20,1,5
1745631233.28483,20,1,5
</pre><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("pre_tab_worker_usage")'><img src='i/clipboard.svg' style='height: 1em'> Copy raw data to clipboard</button>
<button onclick='download_as_file("pre_tab_worker_usage", "worker_usage.csv")'><img src='i/download.svg' style='height: 1em'> Download &raquo;worker_usage.csv&laquo; as file</button>

<h1><img class='invert_icon' src='i/cpu.svg' style='height: 1em' />&nbsp;CPU/RAM-Usage (main)</h1>
<div class='invert_in_dark_mode' id='mainWorkerCPURAM'></div><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("pre_tab_main_worker_cpu_ram")'><img src='i/clipboard.svg' style='height: 1em'> Copy raw data to clipboard</button>
<button onclick='download_as_file("pre_tab_main_worker_cpu_ram", "cpu_ram_usage.csv")'><img src='i/download.svg' style='height: 1em'> Download &raquo;cpu_ram_usage.csv&laquo; as file</button>
<pre id="pre_tab_main_worker_cpu_ram">timestamp,ram_usage_mb,cpu_usage_percent
1745405554,633.96484375,34.9
1745405554,633.96875,42.6
1745405554,633.96875,42.4
1745405554,633.96875,44.7
1745405554,633.96875,33.3
1745405554,633.96875,45.5
1745405554,633.96875,42.6
1745406104,683.34375,44.6
1745406104,683.34375,35.0
1745406104,683.34375,42.0
1745406104,683.34375,48.8
1745416073,924.0703125,42.2
1745416073,924.0703125,44.2
1745416073,924.0703125,44.2
1745416073,924.0703125,43.2
1745428529,968.9609375,37.5
1745428529,968.9609375,34.7
1745428529,968.9609375,33.1
1745428529,968.9609375,34.0
1745439158,980.9921875,42.2
1745439158,980.9921875,43.1
1745439158,980.9921875,42.9
1745439158,980.9921875,45.0
1745449944,1057.578125,40.8
1745449944,1057.578125,38.0
1745449944,1057.578125,39.9
1745449944,1057.578125,25.8
1745462646,1016.5703125,41.4
1745462646,1016.5703125,44.6
1745462646,1016.5703125,43.7
1745462646,1016.5703125,43.7
1745476633,1030.59375,42.8
1745476633,1030.59375,36.9
1745476633,1030.59375,37.8
1745476633,1030.59375,23.7
1745489592,1063.625,40.1
1745489592,1063.625,39.3
1745489592,1063.625,40.7
1745489592,1063.625,45.6
1745504911,1135.8046875,36.1
1745504911,1135.8046875,31.8
1745504911,1135.8046875,33.3
1745504911,1135.8046875,29.9
1745520226,1158.01171875,37.3
1745520227,1158.01171875,36.0
1745520227,1158.01171875,35.2
1745520227,1158.01171875,35.3
1745535616,1170.546875,37.6
1745535616,1170.546875,39.8
1745535616,1170.546875,38.1
1745535616,1170.546875,43.3
1745551038,1186.0234375,36.7
1745551038,1186.0234375,37.5
1745551038,1186.0234375,38.1
1745551038,1186.0234375,33.3
1745569523,1195.8828125,37.3
1745569523,1195.8828125,39.8
1745569523,1195.8828125,39.9
1745569523,1195.8828125,37.3
1745588579,1220.015625,37.6
1745588579,1220.015625,37.1
1745588579,1220.015625,36.5
1745588579,1220.015625,34.6
1745603313,1275.97265625,36.8
1745603313,1275.97265625,38.8
1745603313,1275.97265625,38.2
1745603313,1275.97265625,44.2
1745631246,1300.24609375,37.3
1745631246,1300.24609375,37.7
1745631246,1300.24609375,36.5
1745631246,1300.24609375,35.3
</pre><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("pre_tab_main_worker_cpu_ram")'><img src='i/clipboard.svg' style='height: 1em'> Copy raw data to clipboard</button>
<button onclick='download_as_file("pre_tab_main_worker_cpu_ram", "cpu_ram_usage.csv")'><img src='i/download.svg' style='height: 1em'> Download &raquo;cpu_ram_usage.csv&laquo; as file</button>

<h1><img class='invert_icon' src='i/plot.svg' style='height: 1em' />&nbsp;Param-Distrib by Status</h1>
<div class='invert_in_dark_mode' id='parameter_by_status_distribution'></div>
<h1><img class='invert_icon' src='i/insights.svg' style='height: 1em' />&nbsp;Insights</h1>
<h2>Visualization for result: <code>ACCURACY</code> (goal: <b>maximize</b>)</h2><p>Best value: <b>0.81</b><br />
Achieved at:<br />
- <code>RUNTIME</code> = 86<br />
- <code>recent_samples_size</code> = 1<br />
- <code>n_samples</code> = 1<br />
- <code>const</code> = 8.1288447053914<br />
- <code>max_depth</code> = 5<br />
- <code>threshold</code> = 0.94976250175943</p><div class="result_parameter_visualization" data-resname="ACCURACY"></div><h2>Visualization for result: <code>RUNTIME</code> (goal: <b>minimize</b>)</h2><p>Best value: <b>1</b><br />
Achieved at:<br />
- <code>ACCURACY</code> = 0.67<br />
- <code>recent_samples_size</code> = 1<br />
- <code>n_samples</code> = 2907<br />
- <code>const</code> = 10<br />
- <code>max_depth</code> = 1<br />
- <code>threshold</code> = 0.999</p><div class="result_parameter_visualization" data-resname="RUNTIME"></div><h2>Parameter statistics</h2><table border='1' cellpadding='5' cellspacing='0'><thead><tr><th>Parameter</th><th>Min</th><th>Max</th><th>Mean</th><th>Std Dev</th><th>Count</th></tr></thead><tbody><tr><td>generation_method</td><td colspan='5' style='text-align:center;'>No numerical statistics available</td></tr><tr><td>ACCURACY</td><td>0.6</td><td>0.81</td><td>0.7153</td><td>0.0298</td><td>833</td></tr><tr><td>RUNTIME</td><td>1</td><td>7136</td><td>363.1273</td><td>1195.6615</td><td>833</td></tr><tr><td>recent_samples_size</td><td>1</td><td>5000</td><td>3076.8258</td><td>1854.6821</td><td>838</td></tr><tr><td>n_samples</td><td>1</td><td>5000</td><td>1104.6671</td><td>1451.1636</td><td>838</td></tr><tr><td>const</td><td>0.001</td><td>10</td><td>5.4243</td><td>4.7303</td><td>838</td></tr><tr><td>max_depth</td><td>1</td><td>20</td><td>9.5692</td><td>8.3694</td><td>838</td></tr><tr><td>threshold</td><td>0.001</td><td>0.999</td><td>0.5628</td><td>0.4286</td><td>838</td></tr></tbody></table>
<h1><img class='invert_icon' src='i/plot.svg' style='height: 1em' />&nbsp;Parallel Plot</h1>
<input type="checkbox" id="enable_slurm_id_if_exists" onchange="createParallelPlot(tab_results_csv_json, tab_results_headers_json, result_names, special_col_names, true)" /> Show SLURM-Job-ID (if it exists)<br><div class="invert_in_dark_mode" id="parallel-plot"></div>
<h1><img class='invert_icon' src='i/scatter.svg' style='height: 1em' />&nbsp;Scatter-2D</h1>
<div class='invert_in_dark_mode' id='plotScatter2d'></div>
<h1><img class='invert_icon' src='i/scatter.svg' style='height: 1em' />&nbsp;Scatter-3D</h1>
<div class='invert_in_dark_mode' id='plotScatter3d'></div>
<h1><img class='invert_icon' src='i/plot.svg' style='height: 1em' />&nbsp;Job Status Distribution</h1>
<div class="invert_in_dark_mode" id="plotJobStatusDistribution"></div>
<h1><img class='invert_icon' src='i/plot.svg' style='height: 1em' />&nbsp;Boxplots</h1>
<div class="invert_in_dark_mode" id="plotBoxplot"></div>
<h1><img class='invert_icon' src='i/violin.svg' style='height: 1em' />&nbsp;Violin</h1>
<div class="invert_in_dark_mode" id="plotViolin"></div>
<h1><img class='invert_icon' src='i/plot.svg' style='height: 1em' />&nbsp;Histogram</h1>
<div class="invert_in_dark_mode" id="plotHistogram"></div>
<h1><img class='invert_icon' src='i/plot.svg' style='height: 1em' />&nbsp;Heatmap</h1>
<div class="invert_in_dark_mode" id="plotHeatmap"></div><br>
    <h1>Correlation Heatmap Explanation</h1>

    <p>
        This is a heatmap that visualizes the correlation between numerical columns in a dataset. The values represented in the heatmap show the strength and direction of relationships between different variables.
    </p>

    <h2>How It Works</h2>
    <p>
        The heatmap uses a matrix to represent correlations between each pair of numerical columns. The calculation behind this is based on the concept of "correlation," which measures how strongly two variables are related. A correlation can be positive, negative, or zero:
    </p>
    <ul>
        <li><strong>Positive correlation</strong>: Both variables increase or decrease together (e.g., if the temperature rises, ice cream sales increase).</li>
        <li><strong>Negative correlation</strong>: As one variable increases, the other decreases (e.g., as the price of a product rises, the demand for it decreases).</li>
        <li><strong>Zero correlation</strong>: There is no relationship between the two variables (e.g., height and shoe size might show zero correlation in some contexts).</li>
    </ul>

    <h2>Color Scale: Yellow to Purple (Viridis)</h2>
    <p>
        The heatmap uses a color scale called "Viridis," which ranges from yellow to purple. Here's what the colors represent:
    </p>
    <ul>
        <li><strong>Yellow (brightest)</strong>: A strong positive correlation (close to +1). This indicates that as one variable increases, the other increases in a very predictable manner.</li>
        <li><strong>Green</strong>: A moderate positive correlation. Variables are still positively related, but the relationship is not as strong.</li>
        <li><strong>Blue</strong>: A weak or near-zero correlation. There is a small or no discernible relationship between the variables.</li>
        <li><strong>Purple (darkest)</strong>: A strong negative correlation (close to -1). This indicates that as one variable increases, the other decreases in a very predictable manner.</li>
    </ul>

    <h2>What the Heatmap Shows</h2>
    <p>
        In the heatmap, each cell represents the correlation between two numerical columns. The color of the cell is determined by the correlation coefficient: from yellow for strong positive correlations, through green and blue for weaker correlations, to purple for strong negative correlations.
    </p>

<h1><img class='invert_icon' src='i/scatter.svg' style='height: 1em' />&nbsp;Result-Pairs</h1>
<div class="invert_in_dark_mode" id="plotResultPairs"></div>
<h1><img class='invert_icon' src='i/evolution.svg' style='height: 1em' />&nbsp;Evolution</h1>
<div class="invert_in_dark_mode" id="plotResultEvolution"></div>
	</body>
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