Experiment overview:

Experiment parameters:

Number of evaluations

Result names and types

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trial_index,arm_name,trial_status,generation_method,generation_node,ACCURACY,RUNTIME,recent_samples_size,batch_size,divergence,detect_batch,statistic,significance,subsets,feature_id
0,0_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,246.000000000000000000000000000000,2032,973,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.670107585072517442092987494107,76,25
1,1_0,COMPLETED,Sobol,GenerationStep_0,0.100000000000000005551115123126,178.000000000000000000000000000000,4751,2960,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.223488174019381397039651915293,46,25
2,2_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,180.000000000000000000000000000000,3490,2376,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.490903230674564816649052545472,55,25
3,3_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,158.000000000000000000000000000000,751,4373,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.933123707715421968345026471070,23,25
4,4_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,167.000000000000000000000000000000,82,1626,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.589890163851901849767500607413,65,25
5,5_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,173.000000000000000000000000000000,2831,4795,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.023392168471589685346812004241,7,25
6,6_0,COMPLETED,Sobol,GenerationStep_0,0.100000000000000005551115123126,312.000000000000000000000000000000,4092,535,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.254504572529345773901354732516,92,25
7,7_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,181.000000000000000000000000000000,1362,3694,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.826346605591475991126060307579,37,25
8,8_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,165.000000000000000000000000000000,1785,2064,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.993259560670703645079981924937,75,25
9,9_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,178.000000000000000000000000000000,4056,4061,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.422880077421665168113662502947,5,25
10,10_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,345.000000000000000000000000000000,2778,661,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.159117679318413141054122661444,95,25
11,11_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,167.000000000000000000000000000000,527,2648,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.727078112976625612340342286188,28,25
12,12_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,170.000000000000000000000000000000,1108,222,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.757956561043858556558916461654,86,25
13,13_0,COMPLETED,Sobol,GenerationStep_0,0.100000000000000005551115123126,148.000000000000000000000000000000,3369,3381,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.315249065589159715994327370936,44,25
14,14_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,161.000000000000000000000000000000,4647,1314,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.079508471580222256358538857057,60,25
15,15_0,COMPLETED,Sobol,GenerationStep_0,0.100000000000000005551115123126,160.000000000000000000000000000000,2367,4483,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.525641004567965919314076472801,14,25
16,16_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,206.000000000000000000000000000000,2334,1450,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.368865946847945436193327850560,48,25
17,17_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,166.000000000000000000000000000000,4448,4619,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.799881862513720953700158133870,81,25
18,18_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,159.000000000000000000000000000000,3168,46,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.532480383409187241205984264525,22,25
19,19_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,188.000000000000000000000000000000,1073,3205,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.105836275467649107429046750894,51,25
20,20_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,188.000000000000000000000000000000,404,797,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.386711010523140441552669699377,13,25
21,21_0,COMPLETED,Sobol,GenerationStep_0,0.100000000000000005551115123126,156.000000000000000000000000000000,2509,2785,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.937602157954126602668054601963,67,25
22,22_0,COMPLETED,Sobol,GenerationStep_0,0.100000000000000005551115123126,167.000000000000000000000000000000,3789,1888,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.706506662631407378327708102006,33,25
23,23_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,187.000000000000000000000000000000,1665,3885,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.150237660048529508838299761919,91,25
24,24_0,COMPLETED,Sobol,GenerationStep_0,0.100000000000000005551115123126,197.000000000000000000000000000000,1483,358,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.045730172665789721453410976437,2,25
25,25_0,COMPLETED,Sobol,GenerationStep_0,0.100000000000000005551115123126,159.000000000000000000000000000000,4359,3517,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.600536588257178705063665802300,70,25
26,26_0,COMPLETED,Sobol,GenerationStep_0,0.100000000000000005551115123126,167.000000000000000000000000000000,3100,1763,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.864282107368111618406203433551,29,25
27,27_0,COMPLETED,Sobol,GenerationStep_0,0.100000000000000005551115123126,175.000000000000000000000000000000,205,4932,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.311928499352186916482310152787,99,25
28,28_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,182.000000000000000000000000000000,786,2200,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.218658882400020959657638286444,39,25
29,29_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,183.000000000000000000000000000000,3691,4197,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.645789986448362496318509329285,84,25
30,30_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,162.000000000000000000000000000000,4125,3950,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.103482496414467092793465496925,27,25
31,31_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,159.000000000000000000000000000000,19,3511,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.295024713957104334216552388170,25,25
32,32_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,176.000000000000000000000000000000,2217,4444,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.050272832737935653490968235246,45,25
33,33_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,268.000000000000000000000000000000,3523,2793,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.257095693764328392383333721227,1,25
34,34_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,191.000000000000000000000000000000,597,1185,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,60,25
35,35_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,191.000000000000000000000000000000,3978,885,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.215266585143749300534921076178,39,25
36,36_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,292.000000000000000000000000000000,3412,3450,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,1,25
37,37_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,256.000000000000000000000000000000,1,1,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,1,25
38,38_0,FAILED,BoTorch,GenerationStep_1,,,4112,1,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,1,25
39,39_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,150.000000000000000000000000000000,3160,4213,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,49,25
40,40_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,185.000000000000000000000000000000,2846,3374,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,100,25
41,41_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,144.000000000000000000000000000000,1944,5000,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,44,25
42,42_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,162.000000000000000000000000000000,5000,5000,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,1,25
43,43_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,171.000000000000000000000000000000,2392,2469,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,100,25
44,44_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,164.000000000000000000000000000000,183,611,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,49,25
45,45_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,158.000000000000000000000000000000,3092,2962,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.333121735335604185479496663902,21,25
46,46_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,182.000000000000000000000000000000,873,909,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.536170184311933528675808702246,52,25
47,47_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,158.000000000000000000000000000000,121,4746,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.209524693498227360111130224141,48,25
48,48_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,153.000000000000000000000000000000,1456,4114,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,18,25
49,49_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,136.000000000000000000000000000000,533,5000,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,30,25
50,50_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,266.000000000000000000000000000000,5000,3482,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,1,25
51,51_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,150.000000000000000000000000000000,3475,3991,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,26,25
52,52_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,316.000000000000000000000000000000,226,3597,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,1,25
53,53_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,246.000000000000000000000000000000,751,1,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,46,25
54,54_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,208.000000000000000000000000000000,1,1026,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,1,25
55,55_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,265.000000000000000000000000000000,1,2899,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.333116985101935714208565286754,1,25
56,56_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,173.000000000000000000000000000000,1907,2867,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.567093166797052683492097457929,100,25
57,57_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,202.000000000000000000000000000000,870,52,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,1,25
58,58_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,187.000000000000000000000000000000,4007,5000,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,48,25
59,59_0,FAILED,BoTorch,GenerationStep_1,,,668,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,1,25
60,60_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,163.000000000000000000000000000000,1562,4316,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,54,25
61,61_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,155.000000000000000000000000000000,4393,3898,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,52,25
62,62_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,162.000000000000000000000000000000,4788,4706,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.003489735922205241310661838483,24,25
63,63_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,172.000000000000000000000000000000,885,1208,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,57,25
64,64_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,178.000000000000000000000000000000,1203,1599,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.956874109158280305997834602749,45,25
65,65_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,177.000000000000000000000000000000,3856,1058,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.094947771233474184682243901534,55,25
66,66_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,168.000000000000000000000000000000,1066,4079,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,63,25
67,67_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,151.000000000000000000000000000000,4541,4157,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,36,25
68,68_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,167.000000000000000000000000000000,4586,1814,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.466340315431842400428763539821,20,25
69,69_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,175.000000000000000000000000000000,1021,972,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,68,25
70,70_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,173.000000000000000000000000000000,4311,4395,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,53,25
71,71_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,149.000000000000000000000000000000,4779,4769,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.601766075497445429576259812166,21,25
72,72_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,167.000000000000000000000000000000,703,4331,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,64,25
73,73_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,152.000000000000000000000000000000,1678,2478,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,83,25
74,74_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,167.000000000000000000000000000000,804,2176,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,17,25
75,75_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,168.000000000000000000000000000000,4670,2425,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.466155162871799366719471890974,27,25
76,76_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,163.000000000000000000000000000000,614,4660,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,14,25
77,77_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,186.000000000000000000000000000000,3879,1673,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.898356359558590389369214790349,52,25
78,78_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,182.000000000000000000000000000000,1430,1956,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,66,25
79,79_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,161.000000000000000000000000000000,1619,4843,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.191178291970295871626817074684,60,25
80,80_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,172.000000000000000000000000000000,727,1397,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.010610146094010560607889814833,75,25
81,81_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,162.000000000000000000000000000000,4479,4386,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,19,25
82,82_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,178.000000000000000000000000000000,2358,4491,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,64,25
83,83_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,175.000000000000000000000000000000,4396,1001,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,23,25
84,84_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,178.000000000000000000000000000000,4563,951,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.094058928302647962227389655254,50,25
85,85_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,172.000000000000000000000000000000,1691,614,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,51,25
86,86_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,191.000000000000000000000000000000,4889,3065,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.938815560939274873497595308436,23,25
87,87_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,147.000000000000000000000000000000,4633,3178,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,43,25
88,88_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,182.000000000000000000000000000000,1331,2432,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,79,25
89,89_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,166.000000000000000000000000000000,81,1813,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,77,25
90,90_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,182.000000000000000000000000000000,960,4965,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.925830202133979041079214766796,19,25
91,91_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,164.000000000000000000000000000000,344,1899,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.254206794555207782337902244763,21,25
92,92_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,170.000000000000000000000000000000,82,3048,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,22,25
93,93_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,175.000000000000000000000000000000,1,4333,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,99,25
94,94_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,162.000000000000000000000000000000,1063,382,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,20,25
95,95_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,184.000000000000000000000000000000,521,4067,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,75,25
96,96_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,198.000000000000000000000000000000,1,4134,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,99,25
97,97_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,159.000000000000000000000000000000,2564,3624,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.902442681317450756672826628346,21,25
98,98_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,165.000000000000000000000000000000,809,4642,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.940014911281453979796651765355,16,25
99,99_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,173.000000000000000000000000000000,4116,4794,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.750477717298692947878180348198,100,25
100,100_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,183.000000000000000000000000000000,797,221,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.964900877171947612964686413761,74,25
101,101_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,168.000000000000000000000000000000,3330,4818,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.739787978415867963910557136842,100,25
102,102_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,154.000000000000000000000000000000,4845,4664,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.257017495122564498810646682614,23,25
103,103_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,171.000000000000000000000000000000,4007,4656,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.732182289227484517368793603964,74,25
104,104_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,178.000000000000000000000000000000,85,4439,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,73,25
105,105_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,164.000000000000000000000000000000,4380,1310,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.122802080472957764190056195730,19,25
106,106_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,197.000000000000000000000000000000,1,5000,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,100,25
107,107_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,147.000000000000000000000000000000,328,4834,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.933226507619265399640084979183,20,25
108,108_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,182.000000000000000000000000000000,4234,3807,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,71,25
109,109_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,220.000000000000000000000000000000,5000,5000,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,100,25
110,110_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,188.000000000000000000000000000000,1,3938,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,74,25
111,111_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,147.000000000000000000000000000000,715,1307,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,23,25
112,112_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,169.000000000000000000000000000000,2568,796,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.602234909273098417692438033555,74,25
113,113_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,154.000000000000000000000000000000,3691,4833,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.182927071865035706377256019550,19,25
114,114_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,144.000000000000000000000000000000,936,4213,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.998862696871666622122631906677,19,25
115,115_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,177.000000000000000000000000000000,1,4021,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,80,25
116,116_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,206.000000000000000000000000000000,4049,5000,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.778881545150762577556236010423,100,25
117,117_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,176.000000000000000000000000000000,47,3753,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.981459704316696601722469495144,20,25
118,118_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,149.000000000000000000000000000000,1,2986,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,29,25
119,119_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,170.000000000000000000000000000000,596,459,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,20,25
120,120_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,159.000000000000000000000000000000,1131,4143,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,35,25
121,121_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,162.000000000000000000000000000000,5000,2141,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,77,25
122,122_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,172.000000000000000000000000000000,1367,4850,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,37,25
123,123_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,169.000000000000000000000000000000,1,1336,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,26,25
124,124_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,172.000000000000000000000000000000,1,4125,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,79,25
125,125_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,165.000000000000000000000000000000,4955,2634,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,71,25
126,126_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,161.000000000000000000000000000000,3452,3264,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,32,25
127,127_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,147.000000000000000000000000000000,3288,2293,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,28,25
128,128_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,168.000000000000000000000000000000,1,4613,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.602867301683098211206868199952,36,25
129,129_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,161.000000000000000000000000000000,1,5000,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,37,25
130,130_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,173.000000000000000000000000000000,2305,1987,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,82,25
131,131_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,168.000000000000000000000000000000,4676,4825,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,36,25
132,132_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,167.000000000000000000000000000000,1139,927,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.434555968096149325408106278701,20,25
133,133_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,165.000000000000000000000000000000,78,3692,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.863839777653022666825677333691,35,25
134,134_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,175.000000000000000000000000000000,265,4011,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,36,25
135,135_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,179.000000000000000000000000000000,1,1904,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,30,25
136,136_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,159.000000000000000000000000000000,4716,5000,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,76,25
137,137_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,162.000000000000000000000000000000,1,1937,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,30,25
138,138_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,172.000000000000000000000000000000,4125,3011,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,88,25
139,139_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,149.000000000000000000000000000000,1,3467,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,36,25
140,140_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,164.000000000000000000000000000000,481,522,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.859511345665886383748954813200,18,25
141,141_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,172.000000000000000000000000000000,4412,4513,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,38,25
142,142_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,181.000000000000000000000000000000,5000,5000,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,11,25
143,143_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,163.000000000000000000000000000000,1,3942,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,71,25
144,144_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,180.000000000000000000000000000000,1,5000,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,50,25
145,145_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,172.000000000000000000000000000000,1,1907,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,86,25
146,146_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,161.000000000000000000000000000000,712,4457,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.504779593681710214703173278394,31,25
147,147_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,152.000000000000000000000000000000,2909,2404,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,28,25
148,148_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,169.000000000000000000000000000000,76,1552,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.507956804584632770627194986446,88,25
149,149_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,247.000000000000000000000000000000,4105,1,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,17,25
150,150_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,171.000000000000000000000000000000,1209,3672,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.432643130086026617142636041535,27,25
151,151_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,150.000000000000000000000000000000,4470,3939,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.553200691786827736251552778413,24,25
152,152_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,148.000000000000000000000000000000,4606,4963,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.024206495740357932694442055777,31,25
153,153_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,182.000000000000000000000000000000,2516,3439,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.370182153413035786027052154168,28,25
154,154_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,144.000000000000000000000000000000,4615,4940,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.666460591273171476522918510454,25,25
155,155_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,156.000000000000000000000000000000,107,1214,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.617126273711456341253267510183,23,25
156,156_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,168.000000000000000000000000000000,3912,5000,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,100,25
157,157_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,156.000000000000000000000000000000,4199,3203,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,22,25
158,158_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,193.000000000000000000000000000000,2197,4914,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.463946126054125773663372456213,21,25
159,159_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,167.000000000000000000000000000000,2199,4832,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.200513910555775581867621326637,87,25
160,160_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,159.000000000000000000000000000000,337,2112,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,33,25
161,161_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,164.000000000000000000000000000000,1200,5000,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,100,25
162,162_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,181.000000000000000000000000000000,4460,5000,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,96,25
163,163_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,144.000000000000000000000000000000,4787,4185,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.165999591995936696120494957540,33,25
164,164_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,144.000000000000000000000000000000,4700,4199,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.842862108443538371460590497009,25,25
165,165_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,159.000000000000000000000000000000,785,623,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,25,25
166,166_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,149.000000000000000000000000000000,4623,4944,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,28,25
167,167_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,188.000000000000000000000000000000,24,4656,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.409110121904068479992133688938,18,25
168,168_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,179.000000000000000000000000000000,4728,5000,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,1,25
169,169_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,168.000000000000000000000000000000,4428,4894,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.432990612798112017856055899756,71,25
170,170_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,169.000000000000000000000000000000,2232,5000,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.057245482976993576629265447764,85,25
171,171_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,168.000000000000000000000000000000,2729,4078,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.517823863181286814239001614624,28,25
172,172_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,211.000000000000000000000000000000,4001,5000,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,85,25
173,173_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,176.000000000000000000000000000000,742,705,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.464705604705690611400115130891,68,25
174,174_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,156.000000000000000000000000000000,421,2439,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,21,25
175,175_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,174.000000000000000000000000000000,1,5000,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,95,25
176,176_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,178.000000000000000000000000000000,2906,1021,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,28,25
177,177_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,175.000000000000000000000000000000,633,5000,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,91,25
178,178_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,157.000000000000000000000000000000,1,2917,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.891219556286128034017224308627,21,25
179,179_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,152.000000000000000000000000000000,118,3982,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.797839613820967685775542577176,71,25
180,180_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,176.000000000000000000000000000000,151,4015,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.384313475226658263217416333646,84,25
181,181_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,159.000000000000000000000000000000,1680,392,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,61,25
182,182_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,178.000000000000000000000000000000,4950,3708,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.532028046673946430900059567648,81,25
183,183_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,158.000000000000000000000000000000,2663,2678,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,72,25
184,184_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,168.000000000000000000000000000000,1026,4802,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.720059438432725351653118650574,56,25
185,185_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,155.000000000000000000000000000000,464,657,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,64,25
186,186_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,173.000000000000000000000000000000,4979,4490,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.624253039710641388637668569572,77,25
187,187_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,165.000000000000000000000000000000,4213,4161,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.203838854302110905614142666309,100,25
188,188_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,171.000000000000000000000000000000,341,4542,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.410051725629308583265242305060,67,25
189,189_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,166.000000000000000000000000000000,3599,4981,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.438302650829938744703184738682,86,25
190,190_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,162.000000000000000000000000000000,545,4995,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.286237834397163437571975919127,82,25
191,191_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,160.000000000000000000000000000000,337,3877,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.351852739290410998496128058832,98,25
192,192_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,201.000000000000000000000000000000,4543,5000,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,1,25
193,193_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,154.000000000000000000000000000000,4908,2773,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,84,25
194,194_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,169.000000000000000000000000000000,2578,4960,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.613912183194944560682415612973,75,25
195,195_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,168.000000000000000000000000000000,1926,4016,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.964244401184866095633196891868,1,25
196,196_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,156.000000000000000000000000000000,2310,536,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,44,25
197,197_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,162.000000000000000000000000000000,1074,5000,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,42,25
198,198_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,158.000000000000000000000000000000,49,1639,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,25,25
199,199_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,159.000000000000000000000000000000,55,5000,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.438300019741893420732736785794,1,25
200,200_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,162.000000000000000000000000000000,1662,3309,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,86,25
201,201_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,158.000000000000000000000000000000,2226,3753,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.441789082012099487695166999401,100,25
202,202_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,160.000000000000000000000000000000,578,5000,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.778745386396359484670881556667,51,25
203,203_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,178.000000000000000000000000000000,2658,2251,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,20,25
204,204_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,250.000000000000000000000000000000,5000,1,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,63,25
205,205_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,165.000000000000000000000000000000,282,668,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.551039150465345350937695911853,27,25
206,206_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,172.000000000000000000000000000000,521,4000,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.261869710345817574559390550348,83,25
207,207_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,163.000000000000000000000000000000,2034,2365,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,61,25
208,208_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,176.000000000000000000000000000000,2181,400,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.530188935663614802074050658121,24,25
209,209_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,148.000000000000000000000000000000,3579,1301,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,100,25
210,210_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,162.000000000000000000000000000000,1,1297,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,58,25
211,211_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,163.000000000000000000000000000000,1,879,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,48,25
212,212_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,163.000000000000000000000000000000,3680,1928,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,99,25
213,213_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,172.000000000000000000000000000000,995,3133,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,100,25
214,214_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,171.000000000000000000000000000000,323,3354,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.173092786510225971063903216418,100,25
215,215_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,148.000000000000000000000000000000,5000,1623,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,93,25
216,216_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,158.000000000000000000000000000000,1,28,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,100,25
217,217_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,151.000000000000000000000000000000,687,1746,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,68,25
218,218_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,147.000000000000000000000000000000,1,2795,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,100,25
219,219_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,163.000000000000000000000000000000,1092,1774,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.843914292796544285302218213474,100,25
220,220_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,183.000000000000000000000000000000,5000,333,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,100,25
221,221_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,166.000000000000000000000000000000,2678,5000,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.492837654999773444597366278686,61,25
222,222_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,162.000000000000000000000000000000,4188,5000,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,65,25
223,223_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,160.000000000000000000000000000000,171,904,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,100,25
224,224_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,167.000000000000000000000000000000,811,130,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,33,25
225,225_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,171.000000000000000000000000000000,4794,2630,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,93,25
226,226_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,172.000000000000000000000000000000,4515,1220,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,98,25
227,227_0,FAILED,BoTorch,GenerationStep_1,,,4,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,41,25
228,228_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,155.000000000000000000000000000000,4934,3465,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,100,25
229,229_0,COMPLETED,BoTorch,GenerationStep_1,0.119999999999999995559107901499,176.000000000000000000000000000000,1,4871,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,27,25
230,230_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,159.000000000000000000000000000000,2906,3980,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,27,25
231,231_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,174.000000000000000000000000000000,1,4649,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,1,25
232,232_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,160.000000000000000000000000000000,4631,3961,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,38,25
233,233_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,185.000000000000000000000000000000,438,5000,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.613646157455354557264115555881,1,25
234,234_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,151.000000000000000000000000000000,1,1530,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,52,25
235,235_0,FAILED,BoTorch,GenerationStep_1,,,2783,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,17,25
236,236_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,146.000000000000000000000000000000,1,1888,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,100,25
237,237_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,160.000000000000000000000000000000,109,1852,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.656988487280723898464884769055,21,25
238,238_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,163.000000000000000000000000000000,1,5000,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,15,25
239,239_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,169.000000000000000000000000000000,1,3678,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,100,25
240,240_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,164.000000000000000000000000000000,1,1026,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,92,25
241,241_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,179.000000000000000000000000000000,1587,5000,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,55,25
242,242_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,175.000000000000000000000000000000,4359,4766,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,52,25
243,243_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,154.000000000000000000000000000000,1,712,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,100,25
244,244_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,154.000000000000000000000000000000,1,3897,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,100,25
245,245_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,151.000000000000000000000000000000,4673,1284,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,27,25
246,246_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,179.000000000000000000000000000000,1,3950,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,12,25
247,247_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,166.000000000000000000000000000000,1,4682,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,20,25
248,248_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,166.000000000000000000000000000000,5000,5000,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,61,25
249,249_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,168.000000000000000000000000000000,2783,1295,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,33,25
250,250_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,148.000000000000000000000000000000,4103,1251,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,30,25
251,251_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,158.000000000000000000000000000000,605,4416,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,12,25
252,252_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,176.000000000000000000000000000000,1978,5000,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,41,25
253,253_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,162.000000000000000000000000000000,5000,5000,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,40,25
254,254_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,165.000000000000000000000000000000,5000,5000,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,44,25
255,255_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,166.000000000000000000000000000000,1,4203,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,20,25
256,256_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,153.000000000000000000000000000000,5000,2900,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,31,25
257,257_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,161.000000000000000000000000000000,2850,1062,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,94,25
258,258_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,172.000000000000000000000000000000,585,5000,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,60,25
259,259_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,173.000000000000000000000000000000,2905,673,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,21,25
260,260_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,161.000000000000000000000000000000,5000,3513,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,75,25
261,261_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,181.000000000000000000000000000000,5000,5000,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,26,25
262,262_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,161.000000000000000000000000000000,287,4440,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,50,25
263,263_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,167.000000000000000000000000000000,5000,4190,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,53,25
264,264_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,168.000000000000000000000000000000,3030,4136,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,47,25
265,265_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,188.000000000000000000000000000000,1,909,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,100,25
266,266_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,175.000000000000000000000000000000,4227,4989,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.628296524094222763601180758997,58,25
267,267_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,161.000000000000000000000000000000,3961,4961,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.641356436373760385727393895650,55,25
268,268_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,163.000000000000000000000000000000,206,5000,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.371429348298845107834154077864,100,25
269,269_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,176.000000000000000000000000000000,4653,5000,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,61,25
270,270_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,179.000000000000000000000000000000,426,1360,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.143445624160254331380670578255,70,25
271,271_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,167.000000000000000000000000000000,5000,353,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,100,25
272,272_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,159.000000000000000000000000000000,3624,3234,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,28,25
273,273_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,153.000000000000000000000000000000,4955,1361,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,21,25
274,274_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,176.000000000000000000000000000000,265,3097,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,35,25
275,275_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,149.000000000000000000000000000000,2516,5000,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,24,25
276,276_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,164.000000000000000000000000000000,1,4027,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,100,25
277,277_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,199.000000000000000000000000000000,3274,2805,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,77,25
278,278_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,190.000000000000000000000000000000,1263,5000,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.929617650776776938137402339635,73,25
279,279_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,173.000000000000000000000000000000,1157,2958,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,62,25
280,280_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,154.000000000000000000000000000000,674,4335,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,31,25
281,281_0,FAILED,BoTorch,GenerationStep_1,,,1495,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,24,25
282,282_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,156.000000000000000000000000000000,4992,4777,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,74,25
283,283_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,167.000000000000000000000000000000,4929,1364,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,24,25
284,284_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,163.000000000000000000000000000000,2957,5000,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.593471271779253517486552027549,56,25
285,285_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,186.000000000000000000000000000000,4174,2867,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,73,25
286,286_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,165.000000000000000000000000000000,432,1367,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,31,25
287,287_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,183.000000000000000000000000000000,1,3558,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,100,25
288,288_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,1164.000000000000000000000000000000,1,1,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,28,25
289,289_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,158.000000000000000000000000000000,3536,661,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,24,25
290,290_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,168.000000000000000000000000000000,4316,3939,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.542980406313094743353531157481,57,25
291,291_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,194.000000000000000000000000000000,842,151,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,36,25
292,292_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.723337542880256312294307008415,31,25
293,293_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,166.000000000000000000000000000000,4580,3149,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,1,25
294,294_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,152.000000000000000000000000000000,4429,2985,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,29,25
295,295_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,272.000000000000000000000000000000,61,31,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,35,25
296,296_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,175.000000000000000000000000000000,3668,407,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,38,25
297,297_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,182.000000000000000000000000000000,3652,1867,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,26,25
298,298_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,152.000000000000000000000000000000,2085,5000,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,29,25
299,299_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,182.000000000000000000000000000000,917,195,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.385874291994510287828745731531,8,25
300,300_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,167.000000000000000000000000000000,4652,462,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.247344377057235553785119464010,15,25
301,301_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,168.000000000000000000000000000000,3351,667,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.490892099778257984254992152273,36,25
302,302_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,201.000000000000000000000000000000,1,2218,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,1,25
303,303_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,233.000000000000000000000000000000,1134,1106,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.913164544378584963624234660529,93,25
304,304_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,161.000000000000000000000000000000,5000,517,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,8,25
305,305_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,197.000000000000000000000000000000,3569,243,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.661258043578607290768900384137,50,25
306,306_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,171.000000000000000000000000000000,4974,696,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.301530939231251404741840360657,37,25
307,307_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,196.000000000000000000000000000000,3987,412,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.543708621970852346017011313961,1,25
308,308_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,162.000000000000000000000000000000,1,2948,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,60,25
309,309_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,207.000000000000000000000000000000,2920,812,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.955961895642333914224764157552,66,25
310,310_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,268.000000000000000000000000000000,5000,932,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,1,25
311,311_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,169.000000000000000000000000000000,2890,1087,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.455345875448971038057521809606,20,25
312,312_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,184.000000000000000000000000000000,5000,207,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.440208373172518929727914382966,41,25
313,313_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,165.000000000000000000000000000000,4516,668,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,31,25
314,314_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,161.000000000000000000000000000000,4851,10,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.716892033802374650797162303206,66,25
315,315_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,246.000000000000000000000000000000,1,1623,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,100,25
316,316_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,225.000000000000000000000000000000,5000,3587,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,1,25
317,317_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,211.000000000000000000000000000000,5000,587,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.434652732490832249823142774403,1,25
318,318_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,268.000000000000000000000000000000,5000,659,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.296808226833867816463197186749,1,25
319,319_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,203.000000000000000000000000000000,5000,138,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.147883750816170056463505488864,2,25
320,320_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,243.000000000000000000000000000000,269,1,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.569936472742659572254808608704,100,25
321,321_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,200.000000000000000000000000000000,642,1531,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.721796341756688497603988707851,74,25
322,322_0,RUNNING,BoTorch,GenerationStep_1,,,5000,1,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.832734446011483053773361007188,83,25
323,323_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,401.000000000000000000000000000000,764,600,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,100,25
324,324_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,196.000000000000000000000000000000,5000,4079,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.803829100998839196634548898146,100,25
325,325_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,207.000000000000000000000000000000,156,1846,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,68,25
326,326_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,167.000000000000000000000000000000,5000,594,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.446332051571011578783299000861,20,25
327,327_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,174.000000000000000000000000000000,4893,4337,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.348849923590979438259296330216,1,25
328,328_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,244.000000000000000000000000000000,4699,1,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.322855188433874396025657915743,100,25
329,329_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,1570.000000000000000000000000000000,5000,1,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,31,25
330,330_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,167.000000000000000000000000000000,1185,1018,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.012932205019385974165135877456,7,25
331,331_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,174.000000000000000000000000000000,1320,913,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.015414413932158992429077848385,26,25
332,332_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,251.000000000000000000000000000000,1032,1202,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,1,25
333,333_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,206.000000000000000000000000000000,1327,780,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.131641567666801378999608118647,1,25
334,334_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,160.000000000000000000000000000000,1045,1229,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,45,25
335,335_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,198.000000000000000000000000000000,1284,558,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.138210966592687917176007772468,40,25
336,336_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,216.000000000000000000000000000000,1336,879,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,1,25
337,337_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,212.000000000000000000000000000000,1546,456,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,1,25
338,338_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,162.000000000000000000000000000000,1232,963,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,58,25
339,339_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,213.000000000000000000000000000000,4009,4083,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,100,25
340,340_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,190.000000000000000000000000000000,1530,714,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.005399085796964481036297467398,45,25
341,341_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,205.000000000000000000000000000000,1289,889,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,1,25
342,342_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,247.000000000000000000000000000000,1930,1,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.517467779511990189078574076120,80,25
343,343_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,211.000000000000000000000000000000,1087,1221,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,1,25
344,344_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,194.000000000000000000000000000000,3998,1577,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.915573227508305276245437198668,1,25
345,345_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,303.000000000000000000000000000000,1622,1636,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,1,25
346,346_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,211.000000000000000000000000000000,1044,1308,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.144689324319884710101646874136,1,25
347,347_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,196.000000000000000000000000000000,1275,815,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.117066489569364953760022274309,57,25
348,348_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,282.000000000000000000000000000000,2061,1,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,4,25
349,349_0,FAILED,BoTorch,GenerationStep_1,,,3416,1,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,100,25
350,350_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,216.000000000000000000000000000000,2053,4050,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,100,25
351,351_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,171.000000000000000000000000000000,4693,2005,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,100,25
352,352_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,186.000000000000000000000000000000,4669,1696,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.815245592038954858260524360958,79,25
353,353_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,202.000000000000000000000000000000,890,4317,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,1,25
354,354_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,171.000000000000000000000000000000,2961,4698,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.935660738091772192781547801133,1,25
355,355_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,181.000000000000000000000000000000,1038,989,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.136181079525958897979975859016,33,25
356,356_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,221.000000000000000000000000000000,2133,4195,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.745979368852484392427015791327,100,25
357,357_0,FAILED,BoTorch,GenerationStep_1,,,3488,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,1,25
358,358_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,3137.000000000000000000000000000000,2504,1,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,39,25
359,359_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,262.000000000000000000000000000000,2546,1753,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,1,25
360,360_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,207.000000000000000000000000000000,1875,208,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.106239504518715430214648165475,1,25
361,361_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,203.000000000000000000000000000000,1982,1332,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.314446224728111012325371120824,1,25
362,362_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,206.000000000000000000000000000000,1881,488,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,1,25
363,363_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,272.000000000000000000000000000000,3371,506,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,1,25
364,364_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,254.000000000000000000000000000000,1879,9,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.270234962760957764249525325795,28,25
365,365_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,214.000000000000000000000000000000,2248,2136,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.610084622247039520814837487706,100,25
366,366_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,249.000000000000000000000000000000,1867,1,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,1,25
367,367_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,200.000000000000000000000000000000,1853,1029,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.127458626441503991566506215349,1,25
368,368_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,202.000000000000000000000000000000,1923,1424,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,1,25
369,369_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,183.000000000000000000000000000000,1879,709,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.250030272477203496794828652128,36,25
370,370_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,207.000000000000000000000000000000,2386,1619,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.698335188364988868059413107403,1,25
371,371_0,FAILED,BoTorch,GenerationStep_1,,,3487,1,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,1,25
372,372_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,223.000000000000000000000000000000,2116,2517,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.155149798694846463575913730892,1,25
373,373_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,267.000000000000000000000000000000,3991,838,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,1,25
374,374_0,FAILED,BoTorch,GenerationStep_1,,,4219,1,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.765007859824111124957823903969,1,25
375,375_0,FAILED,BoTorch,GenerationStep_1,,,3691,1,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,91,25
376,376_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,239.000000000000000000000000000000,2035,1613,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.480737888570965887780062075763,100,25
377,377_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,213.000000000000000000000000000000,1899,775,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.459659345703515909153935581344,1,25
378,378_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,173.000000000000000000000000000000,1509,4489,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,67,25
379,379_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,171.000000000000000000000000000000,2574,5000,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,82,25
380,380_0,FAILED,BoTorch,GenerationStep_1,,,4127,1,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,100,25
381,381_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,325.000000000000000000000000000000,1844,1,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.609136786333944080240598850651,1,25
382,382_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,173.000000000000000000000000000000,3090,4557,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,100,25
383,383_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,1301.000000000000000000000000000000,4140,85,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.933105489287526568276120997325,88,25
384,384_0,FAILED,BoTorch,GenerationStep_1,,,1377,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,100,25
385,385_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,266.000000000000000000000000000000,3929,154,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.681098475747072718000652002956,1,25
386,386_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,214.000000000000000000000000000000,3439,353,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.343527877076413301615787077026,4,25
387,387_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,248.000000000000000000000000000000,2228,1485,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.741532952518698329491542153846,100,25
388,388_0,FAILED,BoTorch,GenerationStep_1,,,4369,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,1,25
389,389_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,169.000000000000000000000000000000,2049,706,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.801263922969548958441521335772,34,25
390,390_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,210.000000000000000000000000000000,3758,435,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.528355725566471257081957446644,54,25
391,391_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,199.000000000000000000000000000000,297,1899,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,1,25
392,392_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,212.000000000000000000000000000000,2880,2188,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.486429946089650233620460539896,1,25
393,393_0,FAILED,BoTorch,GenerationStep_1,,,1291,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,1,25
394,394_0,FAILED,BoTorch,GenerationStep_1,,,3682,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.637242071752991967592549826804,100,25
395,395_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,189.000000000000000000000000000000,3620,43,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.779998524686435934505368550163,24,25
396,396_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,206.000000000000000000000000000000,494,74,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.774196562957898293255709631921,1,25
397,397_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,283.000000000000000000000000000000,3807,43,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.422805966163716850925169410402,43,25
398,398_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,268.000000000000000000000000000000,3770,727,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.477184413124626727320531927035,1,25
399,399_0,FAILED,BoTorch,GenerationStep_1,,,387,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,60,25
400,400_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,161.000000000000000000000000000000,2590,4409,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.026184771363501644497739917483,65,25
401,401_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,271.000000000000000000000000000000,3812,525,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.416958825526664966787393495906,1,25
402,402_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,166.000000000000000000000000000000,3610,21,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.580617295154744028629067997826,65,25
403,403_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,205.000000000000000000000000000000,3045,2636,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.417252158429571862185980535287,1,25
404,404_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,170.000000000000000000000000000000,2948,774,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.528791586544473668496380014403,100,25
405,405_0,FAILED,BoTorch,GenerationStep_1,,,1553,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,100,25
406,406_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,241.000000000000000000000000000000,3255,1,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,100,25
407,407_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,163.000000000000000000000000000000,3391,125,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.039161055407632379410376444184,44,25
408,408_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,267.000000000000000000000000000000,3640,517,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.792429430086777020214583444613,1,25
409,409_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,169.000000000000000000000000000000,3121,3359,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.438931774119498019359753016033,36,25
410,410_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,238.000000000000000000000000000000,1418,102,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.692311796909405807731729964871,36,25
411,411_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,196.000000000000000000000000000000,4734,4219,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.519467378914756139351993624587,1,25
412,412_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,169.000000000000000000000000000000,3288,4368,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.457388308380446306777855625114,100,25
413,413_0,FAILED,BoTorch,GenerationStep_1,,,1221,1,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,1,25
414,414_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,206.000000000000000000000000000000,3416,4663,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.170364060751760054701620106243,100,25
415,415_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,177.000000000000000000000000000000,1655,4614,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.443257578970954746466759388568,41,25
416,416_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,202.000000000000000000000000000000,2940,3525,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.479010826323223337652734699077,1,25
417,417_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,283.000000000000000000000000000000,1208,747,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.735088170006104602016705484857,1,25
418,418_0,FAILED,BoTorch,GenerationStep_1,,,166,1,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,57,25
419,419_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,279.000000000000000000000000000000,3758,18,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.506224772414589851976529644162,1,25
420,420_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,238.000000000000000000000000000000,418,323,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,64,25
421,421_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,189.000000000000000000000000000000,2863,4506,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,100,25
422,422_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,250.000000000000000000000000000000,1692,3586,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,100,25
423,423_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,222.000000000000000000000000000000,2315,666,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,44,25
424,424_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,200.000000000000000000000000000000,2620,4578,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.818861875458588572840312735934,36,25
425,425_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,293.000000000000000000000000000000,4822,1266,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,1,25
426,426_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,244.000000000000000000000000000000,4084,293,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,73,25
427,427_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,190.000000000000000000000000000000,2577,221,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,34,25
428,428_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,157.000000000000000000000000000000,4858,1123,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,21,25
429,429_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,197.000000000000000000000000000000,2881,4269,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,62,25
430,430_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,222.000000000000000000000000000000,4795,421,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,40,25
431,431_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,162.000000000000000000000000000000,2829,220,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.656174438689502981247869684012,64,25
432,432_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,177.000000000000000000000000000000,1072,4755,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,58,25
433,433_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,267.000000000000000000000000000000,4309,1242,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.353306517041787004895780910374,1,25
434,434_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,201.000000000000000000000000000000,40,3875,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.464082716004398265763342124046,1,25
435,435_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,160.000000000000000000000000000000,318,4420,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.263815770913058800228867539772,100,25
436,436_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,256.000000000000000000000000000000,510,416,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.320464021982252211806496688951,25,25
437,437_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,210.000000000000000000000000000000,2090,3135,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.278615762748492146183565409956,1,25
438,438_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,266.000000000000000000000000000000,180,2183,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,1,25
439,439_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,200.000000000000000000000000000000,4560,318,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,33,25
440,440_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,171.000000000000000000000000000000,31,596,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.562203554552934248178530651785,71,25
441,441_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,172.000000000000000000000000000000,1807,4349,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.246513779050833936601350160345,36,25
442,442_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,192.000000000000000000000000000000,1836,3626,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.390199849604466020291937411457,100,25
443,443_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,195.000000000000000000000000000000,4369,711,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.376257676993542899968048232040,45,25
444,444_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,215.000000000000000000000000000000,812,3389,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,100,25
445,445_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,163.000000000000000000000000000000,2557,3839,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.295517791837619281380966640427,1,25
446,446_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,166.000000000000000000000000000000,367,532,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.252842970575296366320117158466,100,25
447,447_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,363.000000000000000000000000000000,4545,1113,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,100,25
448,448_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,233.000000000000000000000000000000,4128,3647,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,100,25
449,449_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,176.000000000000000000000000000000,3812,4712,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,100,25
450,450_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,229.000000000000000000000000000000,3120,488,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.561376764967602359668319422781,48,25
451,451_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,232.000000000000000000000000000000,4914,2008,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.943742951781810890388157986308,1,25
452,452_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,207.000000000000000000000000000000,1293,4144,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.570789554437399426767285604001,100,25
453,453_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,196.000000000000000000000000000000,3347,4583,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.298039142153652070188485367908,62,25
454,454_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,202.000000000000000000000000000000,4948,1863,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.725045928301556341644129588531,1,25
455,455_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,264.000000000000000000000000000000,2010,232,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,1,25
456,456_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,260.000000000000000000000000000000,1308,1,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,1,25
457,457_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,321.000000000000000000000000000000,2054,1273,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,1,25
458,458_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,166.000000000000000000000000000000,3438,5000,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,60,25
459,459_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,244.000000000000000000000000000000,3045,1,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,72,25
460,460_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,202.000000000000000000000000000000,3173,962,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.186484602056419396243214237074,1,25
461,461_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,180.000000000000000000000000000000,3651,4871,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,52,25
462,462_0,FAILED,BoTorch,GenerationStep_1,,,2518,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,90,25
463,463_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,249.000000000000000000000000000000,2034,1,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,66,25
464,464_0,FAILED,BoTorch,GenerationStep_1,,,707,1,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,1,25
465,465_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,649.000000000000000000000000000000,3245,45,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.758481435134582437918027153501,63,25
466,466_0,FAILED,BoTorch,GenerationStep_1,,,427,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,89,25
467,467_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,210.000000000000000000000000000000,3065,302,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.626930194162442222527431567869,1,25
468,468_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,192.000000000000000000000000000000,396,702,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.738483330678875060648636008409,18,25
469,469_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,194.000000000000000000000000000000,2473,74,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,95,25
470,470_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,163.000000000000000000000000000000,2293,5000,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,51,25
471,471_0,FAILED,BoTorch,GenerationStep_1,,,2304,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,39,25
472,472_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,173.000000000000000000000000000000,1302,5000,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.430073708150368327896018172396,69,25
473,473_0,FAILED,BoTorch,GenerationStep_1,,,1765,1,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,65,25
474,474_0,FAILED,BoTorch,GenerationStep_1,,,3295,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,100,25
475,475_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,208.000000000000000000000000000000,1255,4263,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.307874714667338122975337455500,1,25
476,476_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,179.000000000000000000000000000000,467,4794,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.541148149064331951407780252339,56,25
477,477_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,167.000000000000000000000000000000,3520,4295,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,100,25
478,478_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,181.000000000000000000000000000000,1642,566,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,100,25
479,479_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,184.000000000000000000000000000000,434,4447,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.256551467520271969657841282242,100,25
480,480_0,COMPLETED,Sobol,SOBOL,0.110000000000000000555111512313,232.000000000000000000000000000000,4470,3863,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.568587420940399157487377124198,94,25
481,481_0,COMPLETED,Sobol,SOBOL,0.100000000000000005551115123126,275.000000000000000000000000000000,350,1193,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.288193865431472684424107910672,49,25
482,482_0,COMPLETED,Sobol,SOBOL,0.100000000000000005551115123126,224.000000000000000000000000000000,1438,2534,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.005175765106454491629173197964,51,25
483,483_0,COMPLETED,Sobol,SOBOL,0.100000000000000005551115123126,244.000000000000000000000000000000,3685,2373,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.847669251957908320704859761463,10,25
484,484_0,COMPLETED,Sobol,SOBOL,0.100000000000000005551115123126,211.000000000000000000000000000000,2517,3136,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.629304999629035632935369903862,65,25
485,485_0,COMPLETED,Sobol,SOBOL,0.110000000000000000555111512313,199.000000000000000000000000000000,2304,1725,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.473071187803521753245661329856,20,25
486,486_0,COMPLETED,Sobol,SOBOL,0.110000000000000000555111512313,218.000000000000000000000000000000,891,4472,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.194686448944732554133807411745,79,25
487,487_0,COMPLETED,Sobol,SOBOL,0.110000000000000000555111512313,235.000000000000000000000000000000,4232,552,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.911565582675859298333875813114,37,25
488,488_0,COMPLETED,Sobol,SOBOL,0.100000000000000005551115123126,228.000000000000000000000000000000,3969,2966,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.769208437506109454773195466259,73,25
489,489_0,COMPLETED,Sobol,SOBOL,0.110000000000000000555111512313,229.000000000000000000000000000000,1214,2171,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.114824077699333434998685277151,19,25
490,490_0,COMPLETED,Sobol,SOBOL,0.110000000000000000555111512313,229.000000000000000000000000000000,2000,4134,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.334498279251158214808725688272,84,25
491,491_0,COMPLETED,Sobol,SOBOL,0.110000000000000000555111512313,213.000000000000000000000000000000,2878,848,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.553470517344772816592524122825,27,25
492,492_0,COMPLETED,Sobol,SOBOL,0.100000000000000005551115123126,274.000000000000000000000000000000,3422,4738,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.958840798802673810463659265224,94,25
493,493_0,COMPLETED,Sobol,SOBOL,0.110000000000000000555111512313,252.000000000000000000000000000000,1760,203,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.178598730958998197504428162574,40,25
494,494_0,COMPLETED,Sobol,SOBOL,0.100000000000000005551115123126,234.000000000000000000000000000000,47,3572,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.395581175658851869059162709164,62,25
495,495_0,COMPLETED,Sobol,SOBOL,0.110000000000000000555111512313,295.000000000000000000000000000000,4831,1527,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.737982509914785644866697111866,4,25
496,496_0,COMPLETED,Sobol,SOBOL,0.110000000000000000555111512313,232.000000000000000000000000000000,4915,3709,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.136014410797506563044478866686,45,25
497,497_0,COMPLETED,Sobol,SOBOL,0.110000000000000000555111512313,245.000000000000000000000000000000,285,1350,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.978026630733162205544317657768,90,25
498,498_0,COMPLETED,Sobol,SOBOL,0.110000000000000000555111512313,237.000000000000000000000000000000,1698,4877,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.695527879156172312846706518030,13,25
499,499_0,COMPLETED,Sobol,SOBOL,0.110000000000000000555111512313,570.000000000000000000000000000000,3201,28,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.414653044648468471766733500772,54,25
500,500_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,1,25
501,501_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,302.000000000000000000000000000000,22,1008,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,44,25
502,502_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,246.000000000000000000000000000000,334,598,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.558225362864634089277160455822,100,25
503,503_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,305.000000000000000000000000000000,497,3889,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.318969811712510042944757060468,1,25
504,504_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,256.000000000000000000000000000000,4632,274,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,22,25
505,505_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,236.000000000000000000000000000000,996,3623,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.444527716181782717175252628294,1,25
506,506_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,421.000000000000000000000000000000,1136,1,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.949638093018795537147980212467,51,25
507,507_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,228.000000000000000000000000000000,4798,4056,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.446681838351661808506065654001,29,25
508,508_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,210.000000000000000000000000000000,1006,4486,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,1,25
509,509_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,176.000000000000000000000000000000,1387,4303,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.242748234590536848820363502455,45,25
510,510_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,235.000000000000000000000000000000,2801,4217,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,25,25
511,511_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,199.000000000000000000000000000000,4709,1314,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.186299878830038873056551551599,45,25
512,512_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,260.000000000000000000000000000000,712,4617,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,47,25
513,513_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,261.000000000000000000000000000000,3137,3628,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.591531042765077508249760285253,65,25
514,514_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,238.000000000000000000000000000000,2853,4250,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,52,25
515,515_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,248.000000000000000000000000000000,132,346,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,77,25
516,516_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,298.000000000000000000000000000000,886,258,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,57,25
517,517_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,402.000000000000000000000000000000,3804,643,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,74,25
518,518_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,243.000000000000000000000000000000,851,3891,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,50,25
519,519_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,356.000000000000000000000000000000,1356,1,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,1,25
520,520_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.100000000000000005551115123126,229.000000000000000000000000000000,422,2570,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.164697644332714776549408952633,31,25
521,521_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,388.000000000000000000000000000000,434,2527,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.113181777465687430361818144320,4,25
522,522_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,234.000000000000000000000000000000,60,4387,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.611790645430995594367118428636,22,25
523,523_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,322.000000000000000000000000000000,3259,4569,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.735195455422403831846622779267,100,25
524,524_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,251.000000000000000000000000000000,2126,3940,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,44,25
525,525_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,286.000000000000000000000000000000,1982,4691,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,1,25
526,526_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,235.000000000000000000000000000000,961,4059,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.684211789341599985192488020402,1,25
527,527_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,275.000000000000000000000000000000,4060,3251,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.330377661934819821798470229623,1,25
528,528_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,262.000000000000000000000000000000,4,4587,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,43,25
529,529_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,268.000000000000000000000000000000,2049,4242,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.653807936792050070629045421811,59,25
530,530_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,247.000000000000000000000000000000,1749,3540,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.427464207771481030651017363198,1,25
531,531_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,174.000000000000000000000000000000,3788,210,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,29,25
532,532_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,360.000000000000000000000000000000,2572,2324,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,100,25
533,533_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,325.000000000000000000000000000000,3596,3085,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,100,25
534,534_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,411.000000000000000000000000000000,5000,1849,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,1,25
535,535_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,187.000000000000000000000000000000,3643,4043,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,66,25
536,536_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,227.000000000000000000000000000000,2761,227,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,90,25
537,537_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,245.000000000000000000000000000000,170,4836,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,29,25
538,538_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,303.000000000000000000000000000000,3474,3935,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,100,25
539,539_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,252.000000000000000000000000000000,3262,3894,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,1,25
540,540_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,321.000000000000000000000000000000,4945,2848,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.487983487036425078731127769061,1,25
541,541_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,235.000000000000000000000000000000,4861,688,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,70,25
542,542_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,277.000000000000000000000000000000,2453,3400,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.506992999583983028344391641440,1,25
543,543_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,246.000000000000000000000000000000,4432,4976,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.269338980529308880118577462781,26,25
544,544_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.100000000000000005551115123126,293.000000000000000000000000000000,2513,945,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,39,25
545,545_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,196.000000000000000000000000000000,2712,3907,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,100,25
546,546_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,264.000000000000000000000000000000,923,4834,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.537436401671924968148630341602,82,25
547,547_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4639,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.723639473958450962776112191932,1,25
548,548_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,291.000000000000000000000000000000,2350,4546,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,1,25
549,549_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,253.000000000000000000000000000000,3657,4259,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.148792952062735628349088301547,80,25
550,550_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1022,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.713628445002457700852005473280,1,25
551,551_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,269.000000000000000000000000000000,4181,1158,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,1,25
552,552_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,197.000000000000000000000000000000,617,3294,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.432900275344055840420764980081,1,25
553,553_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,280.000000000000000000000000000000,1436,4562,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,72,25
554,554_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,245.000000000000000000000000000000,864,4250,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.094556772260360605342199846746,1,25
555,555_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,231.000000000000000000000000000000,2426,394,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.664158417931471567463574956491,77,25
556,556_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,332.000000000000000000000000000000,1960,3615,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,100,25
557,557_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,235.000000000000000000000000000000,413,4170,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,28,25
558,558_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,249.000000000000000000000000000000,3955,237,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.438355603493796153191652820169,45,25
559,559_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,201.000000000000000000000000000000,4575,3824,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.130579296807009859193726697413,24,25
560,560_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.100000000000000005551115123126,231.000000000000000000000000000000,3211,2878,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.569669314440646945563173630944,1,25
561,561_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,1,25
562,562_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,224.000000000000000000000000000000,1965,4505,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,1,25
563,561_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,1,25
564,564_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,246.000000000000000000000000000000,2791,3928,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.745003105818614730360138764809,43,25
565,565_0,RUNNING,BoTorch,BOTORCH_MODULAR,,,5000,1,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,100,25
566,566_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,270.000000000000000000000000000000,4684,902,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.188456004993952264126022555502,88,25
567,567_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,167.000000000000000000000000000000,4405,4850,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,1,25
568,568_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,308.000000000000000000000000000000,2680,1318,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.355707798032781241648336845174,40,25
569,569_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,251.000000000000000000000000000000,1242,3667,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.354216904199870119551718516959,38,25
570,570_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,275.000000000000000000000000000000,2159,967,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,9,25
571,571_0,FAILED,BoTorch,BOTORCH_MODULAR,,,2662,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,1,25
572,572_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,272.000000000000000000000000000000,3756,3661,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,1,25
573,573_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,277.000000000000000000000000000000,3749,408,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,38,25
574,574_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,256.000000000000000000000000000000,4853,3876,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,19,25
575,575_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,314.000000000000000000000000000000,1273,4874,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,71,25
576,576_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,226.000000000000000000000000000000,824,4760,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,82,25
577,577_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,312.000000000000000000000000000000,78,4103,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,1,25
578,578_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,312.000000000000000000000000000000,395,3320,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.716589876220009025509227740258,100,25
579,579_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,240.000000000000000000000000000000,3835,4375,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.006884260712372454980856328888,100,25
580,580_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,258.000000000000000000000000000000,1044,4261,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,65,25
581,581_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,485.000000000000000000000000000000,760,1201,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.421655438000955173905026640568,100,25
582,582_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.100000000000000005551115123126,244.000000000000000000000000000000,4218,1852,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,100,25
583,583_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,298.000000000000000000000000000000,1843,1211,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,70,25
584,584_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,257.000000000000000000000000000000,3390,3601,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,68,25
585,585_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1370,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.617234658705579475324043414730,1,25
586,586_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,233.000000000000000000000000000000,3091,4051,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,100,25
587,587_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,324.000000000000000000000000000000,5000,5000,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,1,25
588,588_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,251.000000000000000000000000000000,208,1041,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.480357341856725073014899862756,44,25
589,589_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4264,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,1,25
590,590_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,274.000000000000000000000000000000,3142,3451,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,65,25
591,591_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,236.000000000000000000000000000000,2583,199,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,100,25
592,592_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,260.000000000000000000000000000000,191,4000,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,100,25
593,593_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,323.000000000000000000000000000000,4993,4560,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,100,25
594,594_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,239.000000000000000000000000000000,3889,4010,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,76,25
595,595_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,201.000000000000000000000000000000,948,525,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.402023364291021034766515640513,32,25
596,596_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,224.000000000000000000000000000000,3819,222,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,1,25
597,597_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,256.000000000000000000000000000000,4300,1094,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.450857019376496748197524766510,100,25
598,598_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3702,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.473132416159768587338163570166,1,25
599,599_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,239.000000000000000000000000000000,2601,3845,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,73,25
600,600_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,308.000000000000000000000000000000,3650,2258,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.512648226352792169002725586324,1,25
601,601_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1718,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,1,25
602,602_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,253.000000000000000000000000000000,282,148,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.331853195202929773799382928701,73,25
603,603_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,249.000000000000000000000000000000,3123,171,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,72,25
604,604_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,276.000000000000000000000000000000,1,4794,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,1,25
605,605_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,216.000000000000000000000000000000,1332,1489,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.683542567803650413793548068497,100,25
606,606_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,681.000000000000000000000000000000,2106,781,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,100,25
607,607_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,266.000000000000000000000000000000,195,3845,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,87,25
608,608_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,359.000000000000000000000000000000,1780,4323,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,100,25
609,609_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,1,25
610,610_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,296.000000000000000000000000000000,1807,1622,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.279119837526944525318839396277,1,25
611,611_0,FAILED,BoTorch,BOTORCH_MODULAR,,,822,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.419441909528645462401641452743,1,25
612,612_0,FAILED,BoTorch,BOTORCH_MODULAR,,,2208,1,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,100,25
613,613_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,247.000000000000000000000000000000,1351,4212,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,29,25
614,614_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,288.000000000000000000000000000000,3181,422,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,50,25
615,615_0,FAILED,BoTorch,BOTORCH_MODULAR,,,616,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.746574320106507927086170184339,1,25
616,616_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.100000000000000005551115123126,242.000000000000000000000000000000,1,1804,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.740726896947487056799275251251,100,25
617,617_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.100000000000000005551115123126,251.000000000000000000000000000000,502,2010,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.697670084552463709570702121709,40,25
618,618_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,237.000000000000000000000000000000,4673,1629,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,52,25
619,561_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,1,25
620,561_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,1,25
621,621_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.100000000000000005551115123126,189.000000000000000000000000000000,231,838,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.940581827373391687885373357858,78,25
622,622_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,254.000000000000000000000000000000,3507,4366,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,38,25
623,609_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,1,25
624,624_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,267.000000000000000000000000000000,5000,4239,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,100,25
625,625_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,269.000000000000000000000000000000,3644,5000,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,100,25
626,561_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,1,25
627,627_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,252.000000000000000000000000000000,495,4549,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,70,25
628,628_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,175.000000000000000000000000000000,3433,4010,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,1,25
629,629_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,267.000000000000000000000000000000,4957,4796,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.815524207845276905004539003130,32,25
630,630_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,226.000000000000000000000000000000,1005,4515,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,27,25
631,631_0,FAILED,BoTorch,BOTORCH_MODULAR,,,868,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.942371749071947095721668574697,1,25
632,632_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,234.000000000000000000000000000000,4273,4741,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.588651453848575201277526502963,1,25
633,633_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,319.000000000000000000000000000000,4925,3807,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,100,25
634,634_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,288.000000000000000000000000000000,2546,1162,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,33,25
635,635_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,230.000000000000000000000000000000,1179,639,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,1,25
636,636_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,223.000000000000000000000000000000,2105,3390,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,41,25
637,637_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4009,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,1,25
638,638_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,241.000000000000000000000000000000,4938,3134,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,39,25
639,639_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,285.000000000000000000000000000000,4537,4470,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,97,25
640,640_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,209.000000000000000000000000000000,1741,4429,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.347596805431886923809514655659,39,25
641,500_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,1,25
642,642_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.100000000000000005551115123126,251.000000000000000000000000000000,1272,2967,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,34,25
643,643_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,227.000000000000000000000000000000,2491,3305,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,31,25
644,644_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,230.000000000000000000000000000000,1336,788,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.186718652510031418723102092372,1,25
645,645_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.100000000000000005551115123126,201.000000000000000000000000000000,4087,2152,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,1,25
646,646_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,273.000000000000000000000000000000,4264,3597,str\(\'H\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,100,25
647,647_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,209.000000000000000000000000000000,529,3728,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,100,25
648,648_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.100000000000000005551115123126,270.000000000000000000000000000000,2192,1983,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,60,25
649,649_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,251.000000000000000000000000000000,4635,1305,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,43,25
650,650_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,256.000000000000000000000000000000,4537,1092,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.051550465683067349387247446657,1,25
651,651_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,248.000000000000000000000000000000,3086,3453,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,100,25
652,652_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,230.000000000000000000000000000000,4854,2721,str\(\'KL\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,39,25
653,653_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.100000000000000005551115123126,226.000000000000000000000000000000,1079,1557,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.064768959365835113151099733386,1,25
654,654_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,228.000000000000000000000000000000,2849,1458,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,44,25
655,655_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,184.000000000000000000000000000000,2502,3347,str\(\'H\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,71,25
656,656_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,255.000000000000000000000000000000,1372,3016,str\(\'H\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,1,25
657,657_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,249.000000000000000000000000000000,4959,2201,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,59,25
658,658_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,231.000000000000000000000000000000,4158,1945,str\(\'H\'\),2.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,60,25
659,659_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,236.000000000000000000000000000000,3354,1351,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,73,25
660,660_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,224.000000000000000000000000000000,3552,3573,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.571641189404822669395400680514,28,25
661,661_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,222.000000000000000000000000000000,2123,3898,str\(\'KL\'\),3.000000000000000000000000000000,str\(\'stdev\'\),0.001000000000000000020816681712,24,25
662,662_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,280.000000000000000000000000000000,1,3708,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.998999999999999999111821580300,1,25
663,663_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.119999999999999995559107901499,225.000000000000000000000000000000,1295,4848,str\(\'H\'\),2.000000000000000000000000000000,str\(\'tstat\'\),0.952289383452741167168653646513,14,25
664,664_0,FAILED,BoTorch,BOTORCH_MODULAR,,,2394,1,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,1,25
665,665_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4745,1,str\(\'H\'\),1.000000000000000000000000000000,str\(\'stdev\'\),0.998999999999999999111821580300,23,25
666,666_0,RUNNING,BoTorch,BOTORCH_MODULAR,,,3155,653,str\(\'KL\'\),1.000000000000000000000000000000,str\(\'tstat\'\),0.001000000000000000020816681712,29,25

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start_time,end_time,run_time,program_string,recent_samples_size,batch_size,divergence,detect_batch,statistic,significance,subsets,feature_id,ACCURACY,RUNTIME,exit_code,signal,hostname,OO_Info_runtime,OO_Info_peak_memory,OO_Info_mean_memory,OO_Info_lpd,OO_Info_portion_req_label,OO_Info_SLURM_JOB_ID
1744999019,1744999267,248,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4470 feature_id 25 batch_size 3863 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.5685874209403992 subsets 94,4470,3863,str\(\'KL\'\),3,str\(\'stdev\'\),0.5685874209403992,94,25,0.11,232,0,None,i7175,232,688.68359375,688.4812199519231,-1,0.19254828660436138,4548074
1744999091,1744999334,243,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1438 feature_id 25 batch_size 2534 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.005175765106454492 subsets 51,1438,2534,str\(\'KL\'\),2,str\(\'tstat\'\),0.005175765106454492,51,25,0.1,224,0,None,i7170,224,689.51953125,689.11640625,-1,0.06315264797507789,4548138
1744999060,1744999348,288,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 350 feature_id 25 batch_size 1193 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.2881938654314727 subsets 49,350,1193,str\(\'H\'\),2,str\(\'tstat\'\),0.2881938654314727,49,25,0.1,275,0,None,i7175,275,687.81640625,687.7829427083333,-1,0.22299065420560749,4548106
1744999140,1744999396,256,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3685 feature_id 25 batch_size 2373 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.8476692519579083 subsets 10,3685,2373,str\(\'H\'\),1,str\(\'stdev\'\),0.8476692519579083,10,25,0.1,244,0,None,i7173,244,688.2421875,688.2184606481482,-1,0.17742056074766355,4548180
1744999181,1744999407,226,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2517 feature_id 25 batch_size 3136 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.6293049996290356 subsets 65,2517,3136,str\(\'H\'\),1,str\(\'stdev\'\),0.6293049996290356,65,25,0.1,211,0,None,i7169,211,688.46484375,688.23388671875,-1,0.03907788161993769,4548221
1744999239,1744999451,212,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2304 feature_id 25 batch_size 1725 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.47307118780352175 subsets 20,2304,1725,str\(\'KL\'\),3,str\(\'tstat\'\),0.47307118780352175,20,25,0.11,199,0,None,i7171,199,688.30859375,688.2633167613636,-1,0.17196261682242991,4548267
1744999283,1744999522,239,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 891 feature_id 25 batch_size 4472 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.19468644894473255 subsets 79,891,4472,str\(\'H\'\),2,str\(\'tstat\'\),0.19468644894473255,79,25,0.11,218,0,None,i7168,218,687.453125,687.2556966145834,-1,0.16717757009345793,4548322
1744999289,1744999548,259,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3969 feature_id 25 batch_size 2966 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.7692084375061095 subsets 73,3969,2966,str\(\'H\'\),3,str\(\'tstat\'\),0.7692084375061095,73,25,0.1,228,0,None,i7167,228,688.91015625,688.8753125,-1,0.2956760124610592,4548425
1744999285,1744999552,267,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4232 feature_id 25 batch_size 552 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.9115655826758593 subsets 37,4232,552,str\(\'KL\'\),3,str\(\'stdev\'\),0.9115655826758593,37,25,0.11,235,0,None,i7167,235,687.06640625,687.046875,-1,0.21323364485981308,4548369
1744999300,1744999587,287,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2878 feature_id 25 batch_size 848 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.5534705173447728 subsets 27,2878,848,str\(\'KL\'\),2,str\(\'tstat\'\),0.5534705173447728,27,25,0.11,213,0,None,i7165,213,688.10546875,683.28515625,-1,0.2641744548286604,4548594
1744999301,1744999588,287,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3422 feature_id 25 batch_size 4738 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.9588407988026738 subsets 94,3422,4738,str\(\'KL\'\),1,str\(\'tstat\'\),0.9588407988026738,94,25,0.1,274,0,None,i7177,274,688.84375,688.5514322916666,-1,0.23616199376947042,4548655
1744999304,1744999591,287,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2000 feature_id 25 batch_size 4134 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.3344982792511582 subsets 84,2000,4134,str\(\'H\'\),3,str\(\'stdev\'\),0.3344982792511582,84,25,0.11,229,0,None,i7166,229,688.0078125,686.7753125,-1,0.2575700934579439,4548541
1744999304,1744999596,292,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1214 feature_id 25 batch_size 2171 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.11482407769933343 subsets 19,1214,2171,str\(\'KL\'\),1,str\(\'stdev\'\),0.11482407769933343,19,25,0.11,229,0,None,i7166,229,687.56640625,686.36234375,-1,0.16231775700934578,4548480
1744999360,1744999628,268,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1760 feature_id 25 batch_size 203 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.1785987309589982 subsets 40,1760,203,str\(\'H\'\),3,str\(\'stdev\'\),0.1785987309589982,40,25,0.11,252,0,None,i7172,252,687.48828125,687.4617745535714,-1,0.20742679127725858,4548712
1744999421,1744999670,249,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 47 feature_id 25 batch_size 3572 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.39558117565885187 subsets 62,47,3572,str\(\'KL\'\),1,str\(\'stdev\'\),0.39558117565885187,62,25,0.1,234,0,None,i7170,234,689.41796875,689.3915264423077,-1,0.13353271028037383,4548776
1744999500,1744999807,307,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4831 feature_id 25 batch_size 1527 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.7379825099147856 subsets 4,4831,1527,str\(\'H\'\),2,str\(\'tstat\'\),0.7379825099147856,4,25,0.11,295,0,None,i7170,295,688.34375,688.30859375,-1,0.47570093457943924,4548840
1744999560,1744999807,247,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4915 feature_id 25 batch_size 3709 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.13601441079750656 subsets 45,4915,3709,str\(\'KL\'\),2,str\(\'stdev\'\),0.13601441079750656,45,25,0.11,232,0,None,i7170,232,687.953125,687.7244591346154,-1,0.18487227414330218,4548893
1744999587,1744999853,266,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1698 feature_id 25 batch_size 4877 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.6955278791561723 subsets 13,1698,4877,str\(\'KL\'\),1,str\(\'tstat\'\),0.6955278791561723,13,25,0.11,237,0,None,i7168,237,689.32421875,689.2853064903846,-1,0.30386292834890966,4548973
1744999586,1744999859,273,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 285 feature_id 25 batch_size 1350 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.9780266307331622 subsets 90,285,1350,str\(\'H\'\),3,str\(\'tstat\'\),0.9780266307331622,90,25,0.11,245,0,None,i7168,245,688.59375,688.5636574074074,-1,0.2523364485981308,4548940
1744999602,1745000187,585,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3201 feature_id 25 batch_size 28 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.41465304464846847 subsets 54,3201,28,str\(\'H\'\),2,str\(\'stdev\'\),0.41465304464846847,54,25,0.11,570,0,None,i7172,570,688.0234375,688.0094014830509,-1,0.15142679127725855,4549024
1745000564,1745000577,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 25 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 1,1,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,1,25,None,None,1,None,i7180,,,,,,4549978
1745000941,1745001256,315,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 22 feature_id 25 batch_size 1008 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 44,22,1008,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,44,25,0.11,302,0,None,i7172,302,688.3671875,688.3527462121212,-1,0.40194392523364486,4550405
1745001222,1745001481,259,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 334 feature_id 25 batch_size 598 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.5582253628646341 subsets 100,334,598,str\(\'H\'\),3,str\(\'stdev\'\),0.5582253628646341,100,25,0.11,246,0,None,i7169,246,688.35546875,688.3337673611111,-1,0.260809968847352,4550840
1745001603,1745001925,322,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 497 feature_id 25 batch_size 3889 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.31896981171251004 subsets 1,497,3889,str\(\'KL\'\),2,str\(\'stdev\'\),0.31896981171251004,1,25,0.11,305,0,None,i7168,305,687.34765625,687.3128551136364,-1,0.4597009345794393,4551361
1745001882,1745002154,272,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4632 feature_id 25 batch_size 274 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 22,4632,274,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,22,25,0.11,256,0,None,i7166,256,689.5078125,689.4845145089286,-1,0.33801869158878506,4551759
1745002182,1745002443,261,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 996 feature_id 25 batch_size 3623 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.4445277161817827 subsets 1,996,3623,str\(\'H\'\),3,str\(\'stdev\'\),0.4445277161817827,1,25,0.11,236,0,None,i7185,236,664.53125,581.5162259615385,-1,0.18058566978193147,4552060
1745002562,1745002999,437,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1136 feature_id 25 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.9496380930187955 subsets 51,1136,1,str\(\'H\'\),3,str\(\'stdev\'\),0.9496380930187955,51,25,0.11,421,0,None,i7180,421,694.51953125,690.8795138888889,-1,0.23804361370716512,4552322
1745002881,1745003126,245,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4798 feature_id 25 batch_size 4056 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.4466818383516618 subsets 29,4798,4056,str\(\'H\'\),2,str\(\'stdev\'\),0.4466818383516618,29,25,0.11,228,0,None,i7172,228,687.875,687.83671875,-1,0.3032523364485981,4552526
1745003185,1745003412,227,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1006 feature_id 25 batch_size 4486 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 1,1006,4486,str\(\'H\'\),3,str\(\'tstat\'\),0.001,1,25,0.11,210,0,None,i7168,210,688.7734375,688.5061141304348,-1,0.16770093457943924,4552798
1745003541,1745003730,189,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1387 feature_id 25 batch_size 4303 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.24274823459053685 subsets 45,1387,4303,str\(\'KL\'\),2,str\(\'stdev\'\),0.24274823459053685,45,25,0.11,176,0,None,i7169,176,687.5859375,687.537890625,-1,0.2680996884735202,4553127
1745003952,1745004200,248,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2801 feature_id 25 batch_size 4217 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 25,2801,4217,str\(\'H\'\),3,str\(\'stdev\'\),0.999,25,25,0.11,235,0,None,i7170,235,689.22265625,689.1841947115385,-1,0.26274143302180686,4553450
1745004302,1745004515,213,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4709 feature_id 25 batch_size 1314 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.18629987883003887 subsets 45,4709,1314,str\(\'H\'\),1,str\(\'stdev\'\),0.18629987883003887,45,25,0.11,199,0,None,i7167,199,688.34375,668.109375,-1,0.4093457943925234,4553786
1745004683,1745004958,275,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 712 feature_id 25 batch_size 4617 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 47,712,4617,str\(\'H\'\),2,str\(\'tstat\'\),0.999,47,25,0.11,260,0,None,i7167,260,688.44140625,688.3844866071429,-1,0.28766355140186917,4554184
1745004983,1745005257,274,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3137 feature_id 25 batch_size 3628 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.5915310427650775 subsets 65,3137,3628,str\(\'H\'\),2,str\(\'tstat\'\),0.5915310427650775,65,25,0.11,261,0,None,i7167,261,688.79296875,688.7487877155172,-1,0.2260436137071651,4554558
1745005363,1745005617,254,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2853 feature_id 25 batch_size 4250 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 52,2853,4250,str\(\'KL\'\),3,str\(\'stdev\'\),0.999,52,25,0.11,238,0,None,i7170,238,687.7421875,687.7109375,-1,0.2118380062305296,4554867
1745005725,1745005988,263,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 132 feature_id 25 batch_size 346 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 77,132,346,str\(\'H\'\),3,str\(\'tstat\'\),0.001,77,25,0.11,248,0,None,i7173,248,687.44921875,686.9382233796297,-1,0.15952647975077883,4555192
1745006054,1745006369,315,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 886 feature_id 25 batch_size 258 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 57,886,258,str\(\'H\'\),2,str\(\'tstat\'\),0.999,57,25,0.11,298,0,None,i7166,298,687.7421875,686.9560546875,-1,0.24433644859813083,4555503
1745006472,1745006890,418,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3804 feature_id 25 batch_size 643 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 74,3804,643,str\(\'H\'\),1,str\(\'tstat\'\),0.999,74,25,0.11,402,0,None,i7169,402,686.28515625,686.2369186046511,-1,0.4326728971962617,4555842
1745006785,1745007050,265,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 851 feature_id 25 batch_size 3891 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 50,851,3891,str\(\'KL\'\),3,str\(\'stdev\'\),0.001,50,25,0.11,243,0,None,i7169,243,687.46484375,687.4419849537037,-1,0.2909158878504673,4556122
1745007164,1745007532,368,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1356 feature_id 25 batch_size 1 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 1,1356,1,str\(\'H\'\),3,str\(\'stdev\'\),0.999,1,25,0.11,356,0,None,i7173,356,694.2265625,690.5430715460526,-1,0.23804361370716512,4556459
1745007922,1745008163,241,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 422 feature_id 25 batch_size 2570 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.16469764433271478 subsets 31,422,2570,str\(\'KL\'\),1,str\(\'stdev\'\),0.16469764433271478,31,25,0.1,229,0,None,i7167,229,688.01171875,687.989375,-1,0.19926479750778817,4557160
1745008244,1745008650,406,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 434 feature_id 25 batch_size 2527 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.11318177746568743 subsets 4,434,2527,str\(\'KL\'\),1,str\(\'stdev\'\),0.11318177746568743,4,25,0.11,388,0,None,i7185,388,653.95703125,577.2063643292682,-1,0.8882741433021807,4557483
1745008635,1745008884,249,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 60 feature_id 25 batch_size 4387 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.6117906454309956 subsets 22,60,4387,str\(\'KL\'\),2,str\(\'stdev\'\),0.6117906454309956,22,25,0.11,234,0,None,i7173,234,688.41796875,688.0850360576923,-1,0.164,4557869
1745008935,1745009275,340,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3259 feature_id 25 batch_size 4569 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.7351954554224038 subsets 100,3259,4569,str\(\'H\'\),2,str\(\'stdev\'\),0.7351954554224038,100,25,0.11,322,0,None,i7185,322,657.1015625,577.2345982142857,-1,0.2846728971962617,4558129
1745009361,1745009631,270,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2126 feature_id 25 batch_size 3940 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 44,2126,3940,str\(\'H\'\),3,str\(\'stdev\'\),0.001,44,25,0.11,251,0,None,i7173,251,688.453125,688.4231305803571,-1,0.24548286604361372,4558479
1745009686,1745009986,300,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1982 feature_id 25 batch_size 4691 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 1,1982,4691,str\(\'KL\'\),2,str\(\'stdev\'\),0.999,1,25,0.11,286,0,None,i7170,286,689.04296875,689.000504032258,-1,0.501183800623053,4558769
1745010104,1745010358,254,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 961 feature_id 25 batch_size 4059 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.6842117893416 subsets 1,961,4059,str\(\'KL\'\),3,str\(\'stdev\'\),0.6842117893416,1,25,0.11,235,0,None,i7185,235,661.6953125,575.3954326923077,-1,0.2528971962616822,4559083
1745010465,1745010764,299,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4060 feature_id 25 batch_size 3251 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.3303776619348198 subsets 1,4060,3251,str\(\'H\'\),2,str\(\'stdev\'\),0.3303776619348198,1,25,0.11,275,0,None,i7185,275,644.09765625,581.3408854166667,-1,0.46122118380062305,4559419
1745010844,1745011120,276,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4 feature_id 25 batch_size 4587 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 43,4,4587,str\(\'H\'\),3,str\(\'stdev\'\),0.001,43,25,0.11,262,0,None,i7180,262,688.05859375,688.0297683189655,-1,0.28579439252336447,4559758
1745011165,1745011446,281,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2049 feature_id 25 batch_size 4242 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.6538079367920501 subsets 59,2049,4242,str\(\'H\'\),2,str\(\'tstat\'\),0.6538079367920501,59,25,0.11,268,0,None,i7168,268,688.40234375,688.3500808189655,-1,0.3171588785046729,4560062
1745011515,1745011777,262,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1749 feature_id 25 batch_size 3540 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.42746420777148103 subsets 1,1749,3540,str\(\'KL\'\),3,str\(\'tstat\'\),0.42746420777148103,1,25,0.11,247,0,None,i7170,247,687.90234375,687.8629918981482,-1,0.2646728971962617,4560401
1745011946,1745012140,194,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3788 feature_id 25 batch_size 210 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 29,3788,210,str\(\'H\'\),1,str\(\'stdev\'\),0.999,29,25,0.11,174,0,None,i7166,174,688.9453125,677.358984375,-1,0.23551401869158878,4560791
1745012285,1745012659,374,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2572 feature_id 25 batch_size 2324 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 100,2572,2324,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,100,25,0.11,360,0,None,i7180,360,688.83203125,686.4194078947369,-1,0.289595015576324,4561080
1745012716,1745013057,341,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3596 feature_id 25 batch_size 3085 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 100,3596,3085,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,100,25,0.11,325,0,None,i7180,325,688.49609375,688.4483258928572,-1,0.26909657320872277,4561418
1745013105,1745013537,432,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 25 batch_size 1849 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 1,5000,1849,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,1,25,0.11,411,0,None,i7185,411,602.78125,580.4369673295455,-1,0.9658317757009346,4561749
1745013504,1745013701,197,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3643 feature_id 25 batch_size 4043 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 66,3643,4043,str\(\'KL\'\),2,str\(\'stdev\'\),0.001,66,25,0.11,187,0,None,i7168,187,688.00390625,687.9553571428571,-1,0.3022803738317757,4562079
1745013856,1745014098,242,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2761 feature_id 25 batch_size 227 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 90,2761,227,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,90,25,0.11,227,0,None,i7170,227,688.31640625,688.2828125,-1,0.10466043613707166,4562371
1745014186,1745014447,261,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 170 feature_id 25 batch_size 4836 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 29,170,4836,str\(\'KL\'\),3,str\(\'stdev\'\),0.999,29,25,0.11,245,0,None,i7169,245,688.67578125,688.6440972222222,-1,0.2410467289719626,4562671
1745014607,1745014930,323,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3474 feature_id 25 batch_size 3935 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 100,3474,3935,str\(\'H\'\),2,str\(\'stdev\'\),0.999,100,25,0.11,303,0,None,i7173,303,687.7265625,687.494081439394,-1,0.19613707165109034,4562997
1745015046,1745015313,267,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3262 feature_id 25 batch_size 3894 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 1,3262,3894,str\(\'H\'\),3,str\(\'stdev\'\),0.001,1,25,0.11,252,0,None,i7169,252,687.49609375,687.4743303571429,-1,0.29114018691588783,4563378
1745015806,1745016140,334,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4945 feature_id 25 batch_size 2848 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.4879834870364251 subsets 1,4945,2848,str\(\'H\'\),2,str\(\'tstat\'\),0.4879834870364251,1,25,0.11,321,0,None,i7170,321,688.75,688.7185267857143,-1,0.47193769470404984,4564024
1745016227,1745016473,246,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4861 feature_id 25 batch_size 688 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 70,4861,688,str\(\'KL\'\),3,str\(\'stdev\'\),0.001,70,25,0.11,235,0,None,i7168,235,687.96875,687.9484675480769,-1,0.24862305295950154,4564355
1745016685,1745016976,291,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2453 feature_id 25 batch_size 3400 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.506992999583983 subsets 1,2453,3400,str\(\'KL\'\),2,str\(\'tstat\'\),0.506992999583983,1,25,0.11,277,0,None,i7169,277,688.23046875,688.1915364583333,-1,0.48350155763239877,4564698
1745017086,1745017362,276,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4432 feature_id 25 batch_size 4976 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.2693389805293089 subsets 26,4432,4976,str\(\'H\'\),2,str\(\'stdev\'\),0.2693389805293089,26,25,0.11,246,0,None,i7185,246,656.6484375,584.1127025462963,-1,0.24802492211838006,4564988
1745017522,1745017827,305,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2513 feature_id 25 batch_size 945 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 39,2513,945,str\(\'H\'\),1,str\(\'tstat\'\),0.999,39,25,0.1,293,0,None,i7169,293,687.62890625,687.6060791015625,-1,0.47102803738317756,4565344
1745017888,1745018098,210,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2712 feature_id 25 batch_size 3907 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 100,2712,3907,str\(\'KL\'\),2,str\(\'stdev\'\),0.001,100,25,0.11,196,0,None,i7168,196,687.86328125,687.5516690340909,-1,0.19474143302180685,4565673
1745018358,1745018638,280,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 923 feature_id 25 batch_size 4834 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.537436401671925 subsets 82,923,4834,str\(\'KL\'\),2,str\(\'stdev\'\),0.537436401671925,82,25,0.11,264,0,None,i7168,264,688.72265625,688.668911637931,-1,0.24094704049844237,4566066
1745018898,1745018911,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4639 feature_id 25 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.723639473958451 subsets 1,4639,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.723639473958451,1,25,None,None,1,None,i7168,,,,,,4566518
1745019289,1745019602,313,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2350 feature_id 25 batch_size 4546 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 1,2350,4546,str\(\'H\'\),2,str\(\'tstat\'\),0.999,1,25,0.11,291,0,None,i7185,291,683.1328125,593.64306640625,-1,0.48492211838006233,4566797
1745019628,1745019910,282,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3657 feature_id 25 batch_size 4259 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.14879295206273563 subsets 80,3657,4259,str\(\'KL\'\),3,str\(\'stdev\'\),0.14879295206273563,80,25,0.11,253,0,None,i7185,253,602.51953125,571.7716238839286,-1,0.21228660436137073,4567052
1745020068,1745020081,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1022 feature_id 25 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.7136284450024577 subsets 1,1022,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.7136284450024577,1,25,None,None,1,None,i7173,,,,,,4567373
1745020489,1745020778,289,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4181 feature_id 25 batch_size 1158 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 1,4181,1158,str\(\'KL\'\),3,str\(\'stdev\'\),0.001,1,25,0.11,269,0,None,i7185,269,683.63671875,627.633755387931,-1,0.2741682242990654,4567695
1745020877,1745021089,212,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 617 feature_id 25 batch_size 3294 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.43290027534405584 subsets 1,617,3294,str\(\'H\'\),3,str\(\'tstat\'\),0.43290027534405584,1,25,0.11,197,0,None,i7168,197,687.8828125,687.4083806818181,-1,0.20523364485981307,4568014
1745021289,1745021582,293,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1436 feature_id 25 batch_size 4562 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 72,1436,4562,str\(\'KL\'\),2,str\(\'stdev\'\),0.001,72,25,0.11,280,0,None,i7169,280,689.31640625,689.268359375,-1,0.2842367601246106,4568354
1745021792,1745022051,259,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 864 feature_id 25 batch_size 4250 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.0945567722603606 subsets 1,864,4250,str\(\'H\'\),3,str\(\'tstat\'\),0.0945567722603606,1,25,0.11,245,0,None,i7169,245,688.265625,688.2216435185185,-1,0.2118380062305296,4568748
1745022290,1745022538,248,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2426 feature_id 25 batch_size 394 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.6641584179314716 subsets 77,2426,394,str\(\'KL\'\),3,str\(\'tstat\'\),0.6641584179314716,77,25,0.11,231,0,None,i7173,231,688.16796875,688.1352163461538,-1,0.21566355140186916,4569110
1745022739,1745023086,347,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1960 feature_id 25 batch_size 3615 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 100,1960,3615,str\(\'H\'\),2,str\(\'stdev\'\),0.001,100,25,0.11,332,0,None,i7173,332,687.55078125,687.5215928819445,-1,0.3153271028037383,4569424
1745023189,1745023437,248,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 413 feature_id 25 batch_size 4170 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 28,413,4170,str\(\'KL\'\),2,str\(\'stdev\'\),0.001,28,25,0.11,235,0,None,i7173,235,689.37890625,689.3230168269231,-1,0.25981308411214954,4569762
1745023709,1745023970,261,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3955 feature_id 25 batch_size 237 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.43835560349379615 subsets 45,3955,237,str\(\'KL\'\),3,str\(\'stdev\'\),0.43835560349379615,45,25,0.11,249,0,None,i7170,249,686.0234375,685.9991319444445,-1,0.21558878504672896,4570187
1745024249,1745024461,212,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4575 feature_id 25 batch_size 3824 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.13057929680700986 subsets 24,4575,3824,str\(\'H\'\),2,str\(\'stdev\'\),0.13057929680700986,24,25,0.11,201,0,None,i7168,201,689.453125,689.4055706521739,-1,0.28590654205607474,4570671
1745024870,1745025117,247,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3211 feature_id 25 batch_size 2878 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.569669314440647 subsets 1,3211,2878,str\(\'KL\'\),3,str\(\'stdev\'\),0.569669314440647,1,25,0.1,231,0,None,i7169,231,689.38671875,689.3566706730769,-1,0.17931464174454828,4571153
1745025350,1745025364,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 25 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 1,1,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,1,25,None,None,1,None,i7185,,,,,,4571480
1745025731,1745025971,240,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1965 feature_id 25 batch_size 4505 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 1,1965,4505,str\(\'KL\'\),3,str\(\'stdev\'\),0.999,1,25,0.11,224,0,None,i7170,224,688.453125,688.215,-1,0.16841121495327102,4571744
1745026101,1745026115,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 25 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 1,1,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,1,25,None,None,1,None,i7180,,,,,,4571987
1745026611,1745026874,263,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2791 feature_id 25 batch_size 3928 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.7450031058186147 subsets 43,2791,3928,str\(\'KL\'\),2,str\(\'stdev\'\),0.7450031058186147,43,25,0.11,246,0,None,i7180,246,688.359375,688.1273148148148,-1,0.19578816199376947,4572344
1745027519,1745027802,283,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4684 feature_id 25 batch_size 902 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.18845600499395226 subsets 88,4684,902,str\(\'H\'\),3,str\(\'stdev\'\),0.18845600499395226,88,25,0.11,270,0,None,i7180,270,688.6640625,688.6364493534483,-1,0.2585171339563863,4573043
1745027999,1745028207,208,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4405 feature_id 25 batch_size 4850 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 1,4405,4850,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,1,25,0.11,167,0,None,i7167,167,659.91796875,620.9907483552631,-1,0.24174454828660435,4573429
1745028411,1745028735,324,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2680 feature_id 25 batch_size 1318 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.35570779803278124 subsets 40,2680,1318,str\(\'KL\'\),1,str\(\'stdev\'\),0.35570779803278124,40,25,0.11,308,0,None,i7185,308,687.89453125,687.8791429924242,-1,0.34489719626168225,4573731
1745028831,1745029094,263,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1242 feature_id 25 batch_size 3667 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.3542169041998701 subsets 38,1242,3667,str\(\'H\'\),3,str\(\'stdev\'\),0.3542169041998701,38,25,0.11,251,0,None,i7185,251,687.57421875,687.361328125,-1,0.22847352024922118,4574036
1745029271,1745029557,286,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2159 feature_id 25 batch_size 967 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 9,2159,967,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,9,25,0.11,275,0,None,i7170,275,687.37890625,687.3576822916667,-1,0.4337943925233645,4574366
1745029672,1745029685,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2662 feature_id 25 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 1,2662,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,1,25,None,None,1,None,i7185,,,,,,4574647
1745030051,1745030335,284,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3756 feature_id 25 batch_size 3661 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 1,3756,3661,str\(\'H\'\),2,str\(\'stdev\'\),0.001,1,25,0.11,272,0,None,i7169,272,687.83984375,687.8079427083334,-1,0.47690965732087226,4574939
1745030512,1745030800,288,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3749 feature_id 25 batch_size 408 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 38,3749,408,str\(\'H\'\),2,str\(\'stdev\'\),0.001,38,25,0.11,277,0,None,i7185,277,687.66015625,687.6295572916666,-1,0.2598006230529595,4575253
1745031082,1745031351,269,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4853 feature_id 25 batch_size 3876 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 19,4853,3876,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,19,25,0.11,256,0,None,i7173,256,687.5546875,687.5209263392857,-1,0.2897943925233645,4575653
1745031533,1745031864,331,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1273 feature_id 25 batch_size 4874 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 71,1273,4874,str\(\'H\'\),2,str\(\'tstat\'\),0.999,71,25,0.11,314,0,None,i7180,314,688.6484375,688.6007582720588,-1,0.3036760124610592,4575978
1745031921,1745032159,238,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 824 feature_id 25 batch_size 4760 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 82,824,4760,str\(\'KL\'\),3,str\(\'stdev\'\),0.001,82,25,0.11,226,0,None,i7169,226,688.3359375,688.30109375,-1,0.29657320872274145,4576263
1745032333,1745032661,328,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 78 feature_id 25 batch_size 4103 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 1,78,4103,str\(\'H\'\),2,str\(\'stdev\'\),0.999,1,25,0.11,312,0,None,i7173,312,687.94921875,687.9176240808823,-1,0.4863676012461059,4576552
1745032762,1745033087,325,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 395 feature_id 25 batch_size 3320 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.716589876220009 subsets 100,395,3320,str\(\'H\'\),2,str\(\'tstat\'\),0.716589876220009,100,25,0.11,312,0,None,i7170,312,688.29296875,688.2550551470588,-1,0.24822429906542057,4576860
1745033293,1745033550,257,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3835 feature_id 25 batch_size 4375 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.006884260712372455 subsets 100,3835,4375,str\(\'H\'\),3,str\(\'tstat\'\),0.006884260712372455,100,25,0.11,240,0,None,i7185,240,688.7578125,688.4710036057693,-1,0.16355140186915887,4577195
1745034013,1745034282,269,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1044 feature_id 25 batch_size 4261 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 65,1044,4261,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,65,25,0.11,258,0,None,i7180,258,687.8359375,687.7755301339286,-1,0.21238629283489097,4577664
1745034413,1745034912,499,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 760 feature_id 25 batch_size 1201 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.4216554380009552 subsets 100,760,1201,str\(\'H\'\),1,str\(\'stdev\'\),0.4216554380009552,100,25,0.11,485,0,None,i7170,485,688.9765625,688.964231004902,-1,0.35917757009345797,4577945
1745034852,1745035110,258,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4218 feature_id 25 batch_size 1852 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 100,4218,1852,str\(\'H\'\),2,str\(\'tstat\'\),0.999,100,25,0.1,244,0,None,i7169,244,687.9453125,687.9089988425926,-1,0.25385669781931464,4578243
1745035334,1745035647,313,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1843 feature_id 25 batch_size 1211 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 70,1843,1211,str\(\'H\'\),1,str\(\'stdev\'\),0.001,70,25,0.11,298,0,None,i7169,298,688.5703125,688.5526123046875,-1,0.4225295950155763,4578602
1745035823,1745036091,268,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3390 feature_id 25 batch_size 3601 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 68,3390,3601,str\(\'KL\'\),3,str\(\'stdev\'\),0.001,68,25,0.11,257,0,None,i7173,257,687.57421875,687.5505022321429,-1,0.31410591900311524,4578922
1745036275,1745036288,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1370 feature_id 25 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.6172346587055795 subsets 1,1370,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.6172346587055795,1,25,None,None,1,None,i7180,,,,,,4579217
1745036778,1745037024,246,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3091 feature_id 25 batch_size 4051 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 100,3091,4051,str\(\'KL\'\),3,str\(\'stdev\'\),0.001,100,25,0.11,233,0,None,i7170,233,687.609375,687.5857872596154,-1,0.3028785046728972,4579537
1745037274,1745037611,337,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 25 batch_size 5000 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 1,5000,5000,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,1,25,0.11,324,0,None,i7180,324,688.953125,688.6274553571428,-1,0.47353271028037386,4579835
1745037744,1745038006,262,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 208 feature_id 25 batch_size 1041 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.4803573418567251 subsets 44,208,1041,str\(\'KL\'\),3,str\(\'stdev\'\),0.4803573418567251,44,25,0.11,251,0,None,i7185,251,687.46875,687.4467075892857,-1,0.26047352024922116,4580118
1745038224,1745038237,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4264 feature_id 25 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 1,4264,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,1,25,None,None,1,None,i7173,,,,,,4580431
1745038764,1745039052,288,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3142 feature_id 25 batch_size 3451 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 65,3142,3451,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,65,25,0.11,274,0,None,i7173,274,687.73828125,687.69375,-1,0.30102180685358254,4580805
1745039184,1745039431,247,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2583 feature_id 25 batch_size 199 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 100,2583,199,str\(\'H\'\),3,str\(\'stdev\'\),0.001,100,25,0.11,236,0,None,i7170,236,688.07421875,688.0389122596154,-1,0.22306542056074766,4581095
1745039665,1745039940,275,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 191 feature_id 25 batch_size 4000 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 100,191,4000,str\(\'H\'\),1,str\(\'tstat\'\),0.999,100,25,0.11,260,0,None,i7185,260,689.78515625,689.4916294642857,-1,0.14953271028037382,4581397
1745040156,1745040493,337,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4993 feature_id 25 batch_size 4560 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 100,4993,4560,str\(\'KL\'\),2,str\(\'stdev\'\),0.999,100,25,0.11,323,0,None,i7180,323,688.6875,688.6449776785714,-1,0.2841121495327103,4581681
1745040655,1745040906,251,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3889 feature_id 25 batch_size 4010 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 76,3889,4010,str\(\'H\'\),2,str\(\'stdev\'\),0.001,76,25,0.11,239,0,None,i7173,239,687.75,687.7068810096154,-1,0.2998130841121495,4581968
1745041094,1745041310,216,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 948 feature_id 25 batch_size 525 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.40202336429102103 subsets 32,948,525,str\(\'H\'\),1,str\(\'stdev\'\),0.40202336429102103,32,25,0.11,201,0,None,i7169,201,688.9375,688.91796875,-1,0.3663551401869159,4582219
1745041615,1745041849,234,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3819 feature_id 25 batch_size 222 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 1,3819,222,str\(\'KL\'\),3,str\(\'stdev\'\),0.999,1,25,0.11,224,0,None,i7185,224,688.40625,688.38421875,-1,0.1604485981308411,4582534
1745042035,1745042304,269,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4300 feature_id 25 batch_size 1094 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.45085701937649675 subsets 100,4300,1094,str\(\'KL\'\),3,str\(\'tstat\'\),0.45085701937649675,100,25,0.11,256,0,None,i7180,256,687.5703125,687.5408761160714,-1,0.2181183800623053,4582813
1745042495,1745042509,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3702 feature_id 25 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.4731324161597686 subsets 1,3702,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.4731324161597686,1,25,None,None,1,None,i7185,,,,,,4583064
1745043115,1745043369,254,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2601 feature_id 25 batch_size 3845 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 73,2601,3845,str\(\'H\'\),2,str\(\'stdev\'\),0.999,73,25,0.11,239,0,None,i7173,239,688.29296875,688.0665564903846,-1,0.19165109034267913,4583449
1745043925,1745044247,322,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3650 feature_id 25 batch_size 2258 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.5126482263527922 subsets 1,3650,2258,str\(\'KL\'\),2,str\(\'tstat\'\),0.5126482263527922,1,25,0.11,308,0,None,i7173,308,689.203125,684.609375,-1,0.4815576323987539,4583941
1745044481,1745044495,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1718 feature_id 25 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 1,1718,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,1,25,None,None,1,None,i7185,,,,,,4584367
1745045036,1745045305,269,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 282 feature_id 25 batch_size 148 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.3318531952029298 subsets 73,282,148,str\(\'KL\'\),3,str\(\'stdev\'\),0.3318531952029298,73,25,0.11,253,0,None,i7180,253,688.30859375,688.2808314732143,-1,0.21299688473520248,4584793
1745045546,1745045815,269,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3123 feature_id 25 batch_size 171 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 72,3123,171,str\(\'KL\'\),3,str\(\'stdev\'\),0.999,72,25,0.11,249,0,None,i7185,249,637.07421875,577.332175925926,-1,0.16473520249221185,4585102
1745046117,1745046419,302,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 25 batch_size 4794 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 1,1,4794,str\(\'H\'\),3,str\(\'stdev\'\),0.001,1,25,0.11,276,0,None,i7173,276,603.65234375,571.35390625,-1,0.2986915887850467,4585411
1745046595,1745046832,237,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1332 feature_id 25 batch_size 1489 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.6835425678036504 subsets 100,1332,1489,str\(\'KL\'\),3,str\(\'tstat\'\),0.6835425678036504,100,25,0.11,216,0,None,i7170,216,652.09375,581.6053059895834,-1,0.22265420560747665,4585696
1745047277,1745047983,706,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2106 feature_id 25 batch_size 781 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 100,2106,781,str\(\'H\'\),1,str\(\'stdev\'\),0.001,100,25,0.11,681,0,None,i7173,681,613.34765625,580.0309198943662,-1,0.4422305295950156,4586059
1745047767,1745048044,277,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 195 feature_id 25 batch_size 3845 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 87,195,3845,str\(\'H\'\),3,str\(\'stdev\'\),0.001,87,25,0.11,266,0,None,i7180,266,687.05078125,687.0153556034483,-1,0.2874766355140187,4586335
1745048197,1745048581,384,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1780 feature_id 25 batch_size 4323 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 100,1780,4323,str\(\'H\'\),2,str\(\'tstat\'\),0.999,100,25,0.11,359,0,None,i7173,359,622.9921875,578.0998149671053,-1,0.2693457943925234,4586577
1745048717,1745048743,26,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 25 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 1,1,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,1,25,None,None,1,None,i7170,,,,,,4586876
1745049237,1745049546,309,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1807 feature_id 25 batch_size 1622 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.2791198375269445 subsets 1,1807,1622,str\(\'KL\'\),2,str\(\'tstat\'\),0.2791198375269445,1,25,0.11,296,0,None,i7180,296,688.75,688.71728515625,-1,0.48508411214953273,4587180
1745049747,1745049761,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 822 feature_id 25 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.41944190952864546 subsets 1,822,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.41944190952864546,1,25,None,None,1,None,i7180,,,,,,4587471
1745050769,1745051030,261,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1351 feature_id 25 batch_size 4212 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 29,1351,4212,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,29,25,0.11,247,0,None,i7173,247,646.40234375,603.5844907407408,-1,0.26242990654205606,4588046
1745051398,1745051701,303,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3181 feature_id 25 batch_size 422 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 50,3181,422,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,50,25,0.11,288,0,None,i7180,288,688.08984375,688.058341733871,-1,0.252411214953271,4588372
1745051939,1745051959,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 616 feature_id 25 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.7465743201065079 subsets 1,616,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.7465743201065079,1,25,None,None,1,None,i7173,,,,,,4588675
1745052568,1745052829,261,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 25 batch_size 1804 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.7407268969474871 subsets 100,1,1804,str\(\'H\'\),3,str\(\'tstat\'\),0.7407268969474871,100,25,0.1,242,0,None,i7185,242,648.4375,597.5426793981482,-1,0.2023177570093458,4588990
1745053168,1745053436,268,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 502 feature_id 25 batch_size 2010 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.6976700845524637 subsets 40,502,2010,str\(\'KL\'\),2,str\(\'tstat\'\),0.6976700845524637,40,25,0.1,251,0,None,i7173,251,660.12890625,583.1939174107143,-1,0.22542056074766356,4589329
1745053765,1745054019,254,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4673 feature_id 25 batch_size 1629 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 52,4673,1629,str\(\'H\'\),1,str\(\'stdev\'\),0.001,52,25,0.11,237,0,None,i7170,237,647.765625,585.4692007211538,-1,0.40598130841121494,4589641
1745054369,1745054389,20,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 25 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 1,1,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,1,25,None,None,1,None,i7185,,,,,,4589973
1745055038,1745055052,14,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 25 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 1,1,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,1,25,None,None,1,None,i7173,,,,,,4590342
1745055478,1745055682,204,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 231 feature_id 25 batch_size 838 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.9405818273733917 subsets 78,231,838,str\(\'KL\'\),3,str\(\'stdev\'\),0.9405818273733917,78,25,0.1,189,0,None,i7183,189,688.60546875,688.57421875,-1,0.1670778816199377,4590571
1745056169,1745056437,268,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3507 feature_id 25 batch_size 4366 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 38,3507,4366,str\(\'KL\'\),3,str\(\'stdev\'\),0.001,38,25,0.11,254,0,None,i7185,254,679.296875,617.4282924107143,-1,0.2720249221183801,4590966
1745056719,1745056732,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 25 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 1,1,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.001,1,25,None,None,1,None,i7183,,,,,,4591260
1745057339,1745057626,287,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 25 batch_size 4239 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.001 subsets 100,5000,4239,str\(\'KL\'\),2,str\(\'tstat\'\),0.001,100,25,0.11,267,0,None,i7185,267,677.32421875,596.9300915948276,-1,0.21128971962616822,4591568
1745057779,1745058066,287,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3644 feature_id 25 batch_size 5000 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 100,3644,5000,str\(\'KL\'\),2,str\(\'stdev\'\),0.001,100,25,0.11,269,0,None,i7183,269,688.890625,688.6593480603449,-1,0.24922118380062305,4591800
1745058460,1745058473,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 25 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 1,1,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,1,25,None,None,1,None,i7183,,,,,,4592177
1745058990,1745059258,268,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 495 feature_id 25 batch_size 4549 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 70,495,4549,str\(\'KL\'\),3,str\(\'stdev\'\),0.999,70,25,0.11,252,0,None,i7185,252,681.9609375,600.60546875,-1,0.22674143302180685,4592461
1745059469,1745059659,190,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3433 feature_id 25 batch_size 4010 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 1,3433,4010,str\(\'KL\'\),3,str\(\'tstat\'\),0.001,1,25,0.11,175,0,None,i7173,175,594.6015625,583.85625,-1,0.14990654205607476,4592721
1745060041,1745060322,281,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4957 feature_id 25 batch_size 4796 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.8155242078452769 subsets 32,4957,4796,str\(\'KL\'\),2,str\(\'stdev\'\),0.8155242078452769,32,25,0.11,267,0,None,i7180,267,688.24609375,688.1950431034483,-1,0.29881619937694703,4593023
1745060646,1745060887,241,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1005 feature_id 25 batch_size 4515 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 27,1005,4515,str\(\'H\'\),3,str\(\'stdev\'\),0.999,27,25,0.11,226,0,None,i7183,226,688.3046875,688.02296875,-1,0.16878504672897196,4593345
1745061200,1745061213,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 868 feature_id 25 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.9423717490719471 subsets 1,868,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.9423717490719471,1,25,None,None,1,None,i7183,,,,,,4593648
1745061800,1745062049,249,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4273 feature_id 25 batch_size 4741 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.5886514538485752 subsets 1,4273,4741,str\(\'KL\'\),3,str\(\'stdev\'\),0.5886514538485752,1,25,0.11,234,0,None,i7185,234,685.046875,651.6231971153846,-1,0.17723364485981308,4593980
1745062407,1745062740,333,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4925 feature_id 25 batch_size 3807 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 100,4925,3807,str\(\'KL\'\),2,str\(\'tstat\'\),0.999,100,25,0.11,319,0,None,i7185,319,676.11328125,582.9241727941177,-1,0.33207476635514016,4594297
1745062921,1745063220,299,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2546 feature_id 25 batch_size 1162 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 33,2546,1162,str\(\'H\'\),1,str\(\'stdev\'\),0.001,33,25,0.11,288,0,None,i7183,288,688.8671875,688.8501764112904,-1,0.46335202492211836,4594575
1745063580,1745063829,249,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1179 feature_id 25 batch_size 639 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 1,1179,639,str\(\'H\'\),3,str\(\'stdev\'\),0.999,1,25,0.11,230,0,None,i7185,230,684.14453125,594.751875,-1,0.1433271028037383,4594904
1745064301,1745064542,241,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2105 feature_id 25 batch_size 3390 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 41,2105,3390,str\(\'KL\'\),3,str\(\'stdev\'\),0.999,41,25,0.11,223,0,None,i7185,223,636.078125,582.45515625,-1,0.12672897196261682,4595284
1745064841,1745064854,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4009 feature_id 25 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 1,4009,1,str\(\'KL\'\),1,str\(\'stdev\'\),0.999,1,25,None,None,1,None,i7183,,,,,,4595576
1745065401,1745065662,261,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4938 feature_id 25 batch_size 3134 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 39,4938,3134,str\(\'H\'\),2,str\(\'tstat\'\),0.999,39,25,0.11,241,0,None,i7185,241,651.63671875,581.7760416666666,-1,0.27337071651090344,4595870
1745066121,1745066428,307,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4537 feature_id 25 batch_size 4470 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 97,4537,4470,str\(\'H\'\),1,str\(\'tstat\'\),0.999,97,25,0.11,285,0,None,i7185,285,647.51171875,582.7486139112904,-1,0.27850467289719627,4596246
1745067081,1745067301,220,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1741 feature_id 25 batch_size 4429 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.3475968054318869 subsets 39,1741,4429,str\(\'H\'\),2,str\(\'stdev\'\),0.3475968054318869,39,25,0.11,209,0,None,i7183,209,688.02734375,685.1428328804348,-1,0.2207601246105919,4596744
1745067561,1745067574,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 25 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 1,1,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,1,25,None,None,1,None,i7183,,,,,,4596982
1745068172,1745068439,267,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1272 feature_id 25 batch_size 2967 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 34,1272,2967,str\(\'KL\'\),2,str\(\'stdev\'\),0.001,34,25,0.1,251,0,None,i7185,251,686.76953125,619.7914341517857,-1,0.29577570093457944,4597294
1745068713,1745068958,245,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2491 feature_id 25 batch_size 3305 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 31,2491,3305,str\(\'H\'\),3,str\(\'stdev\'\),0.001,31,25,0.11,227,0,None,i7183,227,636.62109375,588.4446875,-1,0.3294704049844237,4597569
1745069301,1745069546,245,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1336 feature_id 25 batch_size 788 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.18671865251003142 subsets 1,1336,788,str\(\'KL\'\),3,str\(\'stdev\'\),0.18671865251003142,1,25,0.11,230,0,None,i7180,230,687.5,687.4777644230769,-1,0.27494080996884734,4597870
1745070122,1745070343,221,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4087 feature_id 25 batch_size 2152 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 1,4087,2152,str\(\'H\'\),3,str\(\'tstat\'\),0.001,1,25,0.1,201,0,None,i7183,201,649.984375,583.9510869565217,-1,0.08044859813084113,4598279
1745070742,1745071036,294,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4264 feature_id 25 batch_size 3597 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 100,4264,3597,str\(\'H\'\),1,str\(\'tstat\'\),0.999,100,25,0.11,273,0,None,i7183,273,674.48828125,576.9149739583333,-1,0.17928971962616821,4598578
1745071402,1745071627,225,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 529 feature_id 25 batch_size 3728 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.999 subsets 100,529,3728,str\(\'KL\'\),1,str\(\'tstat\'\),0.999,100,25,0.11,209,0,None,i7180,209,686.5859375,686.2547554347826,-1,0.1393644859813084,4598898
1745072183,1745072475,292,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2192 feature_id 25 batch_size 1983 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.001 subsets 60,2192,1983,str\(\'H\'\),1,str\(\'stdev\'\),0.001,60,25,0.1,270,0,None,i7183,270,630.44140625,571.5238415948276,-1,0.2965233644859813,4599315
1745072823,1745073091,268,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4635 feature_id 25 batch_size 1305 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.001 subsets 43,4635,1305,str\(\'KL\'\),2,str\(\'stdev\'\),0.001,43,25,0.11,251,0,None,i7185,251,653.26953125,595.396484375,-1,0.24392523364485982,4599641
1745073443,1745073717,274,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4537 feature_id 25 batch_size 1092 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.05155046568306735 subsets 1,4537,1092,str\(\'H\'\),3,str\(\'stdev\'\),0.05155046568306735,1,25,0.11,256,0,None,i7185,256,669.91796875,580.1591796875,-1,0.27445482866043613,4599951
1745074284,1745074545,261,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3086 feature_id 25 batch_size 3453 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.999 subsets 100,3086,3453,str\(\'H\'\),3,str\(\'stdev\'\),0.999,100,25,0.11,248,0,None,i7185,248,667.94921875,591.0632233796297,-1,0.21514018691588785,4600361
1745074984,1745075231,247,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4854 feature_id 25 batch_size 2721 divergence str\(\'KL\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 39,4854,2721,str\(\'KL\'\),2,str\(\'stdev\'\),0.999,39,25,0.11,230,0,None,i7185,230,616.6640625,588.5043569711538,-1,0.2034392523364486,4600701
1745075743,1745075984,241,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1079 feature_id 25 batch_size 1557 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.06476895936583511 subsets 1,1079,1557,str\(\'H\'\),3,str\(\'stdev\'\),0.06476895936583511,1,25,0.1,226,0,None,i7185,226,625.59375,584.47984375,-1,0.23282242990654206,4601056
1745076343,1745076588,245,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2849 feature_id 25 batch_size 1458 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 44,2849,1458,str\(\'KL\'\),3,str\(\'stdev\'\),0.001,44,25,0.11,228,0,None,i7183,228,633.01171875,578.801875,-1,0.2543551401869159,4601330
1745077043,1745077241,198,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2502 feature_id 25 batch_size 3347 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.001 subsets 71,2502,3347,str\(\'H\'\),3,str\(\'tstat\'\),0.001,71,25,0.11,184,0,None,i7180,184,689.0546875,689.0128348214286,-1,0.12512149532710282,4601677
1745077684,1745077958,274,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1372 feature_id 25 batch_size 3016 divergence str\(\'H\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 1,1372,3016,str\(\'H\'\),3,str\(\'stdev\'\),0.001,1,25,0.11,255,0,None,i7183,255,654.2265625,575.6748046875,-1,0.26307788161993767,4601975
1745078315,1745078582,267,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4959 feature_id 25 batch_size 2201 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 59,4959,2201,str\(\'H\'\),2,str\(\'tstat\'\),0.999,59,25,0.11,249,0,None,i7185,249,688.10546875,688.0188078703703,-1,0.3016947040498442,4602284
1745079394,1745079636,242,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4158 feature_id 25 batch_size 1945 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'stdev\'\) significance 0.999 subsets 60,4158,1945,str\(\'H\'\),2,str\(\'stdev\'\),0.999,60,25,0.11,231,0,None,i7185,231,688.74609375,688.5262920673077,-1,0.14542056074766355,4602775
1745080127,1745080373,246,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3354 feature_id 25 batch_size 1351 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'tstat\'\) significance 0.999 subsets 73,3354,1351,str\(\'KL\'\),3,str\(\'tstat\'\),0.999,73,25,0.11,236,0,None,i7183,236,683.4609375,683.1956129807693,-1,0.2693582554517134,4603122
1745080992,1745081231,239,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3552 feature_id 25 batch_size 3573 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.5716411894048227 subsets 28,3552,3573,str\(\'H\'\),2,str\(\'tstat\'\),0.5716411894048227,28,25,0.11,224,0,None,i7183,224,687.96875,687.91078125,-1,0.26714018691588787,4603514
1745081649,1745081884,235,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2123 feature_id 25 batch_size 3898 divergence str\(\'KL\'\) detect_batch 3 statistic str\(\'stdev\'\) significance 0.001 subsets 24,2123,3898,str\(\'KL\'\),3,str\(\'stdev\'\),0.001,24,25,0.11,222,0,None,i7185,222,688.8359375,688.600625,-1,0.1457196261682243,4603808
1745082433,1745082731,298,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 25 batch_size 3708 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.999 subsets 1,1,3708,str\(\'H\'\),2,str\(\'tstat\'\),0.999,1,25,0.11,280,0,None,i7183,280,688.6328125,688.5971354166667,-1,0.4833520249221184,4604132
1745083059,1745083297,238,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1295 feature_id 25 batch_size 4848 divergence str\(\'H\'\) detect_batch 2 statistic str\(\'tstat\'\) significance 0.9522893834527412 subsets 14,1295,4848,str\(\'H\'\),2,str\(\'tstat\'\),0.9522893834527412,14,25,0.12,225,0,None,i7183,225,689.09765625,689.0334375,-1,0.30205607476635515,4604405
1745083832,1745083845,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2394 feature_id 25 batch_size 1 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 1,2394,1,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,1,25,None,None,1,None,i7183,,,,,,4604733
1745084334,1745084347,13,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4745 feature_id 25 batch_size 1 divergence str\(\'H\'\) detect_batch 1 statistic str\(\'stdev\'\) significance 0.999 subsets 23,4745,1,str\(\'H\'\),1,str\(\'stdev\'\),0.999,23,25,None,None,1,None,i7183,,,,,,4604853
1745084894,1745085149,255,module load GCCcore/10.3.0 Python && source /data/horse/ws/s4122485-compPerfDD/benchmark/venv/bin/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3155 feature_id 25 batch_size 653 divergence str\(\'KL\'\) detect_batch 1 statistic str\(\'tstat\'\) significance 0.001 subsets 29,3155,653,str\(\'KL\'\),1,str\(\'tstat\'\),0.001,29,25,0.1,241,0,None,i7185,241,688.66015625,688.6355613425926,-1,0.18715264797507788,4604947

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/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4549978/4549978_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4566518/4566518_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4567373/4567373_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4571480/4571480_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4571987/4571987_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4574647/4574647_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4579217/4579217_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4580431/4580431_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4583064/4583064_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4584367/4584367_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4586876/4586876_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4587471/4587471_0_log.err not found


⚠ Job 4587754 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4587754/4587754_0_result.pkl
has not produced any output (state: TIMEOUT)
No error stream produced. Look at stdout: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4587754/4587754_0_log.out
----------------------------------------
submitit INFO (2025-04-19 10:10:54,152) - Starting with JobEnvironment(job_id=4587754, hostname=i7170, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-04-19 10:10:54,164) - Loading pickle: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4587754/4587754_submitted.pkl
slurmstepd: error: *** JOB 4587754 ON i7170 CANCELLED AT 2025-04-19T10:41:16 DUE TO TIME LIMIT ***



/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4587754/4587754_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4588675/4588675_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4589973/4589973_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4590342/4590342_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4591260/4591260_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4592177/4592177_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4593648/4593648_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4595576/4595576_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4596982/4596982_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4604733/4604733_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4604853/4604853_0_log.err not found

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1744998970.9520757,20,0,0
1744998981.7354088,20,0,0
1744998982.6058784,20,0,0
1744998982.8446982,20,0,0
1744998984.5605567,20,1,5
1744998990.61115,20,1,5
1744998991.4699695,20,1,5
1744998991.6728148,20,1,5
1744998993.099283,20,2,10
1744999001.9973948,20,2,10
1744999002.888163,20,2,10
1744999003.0928261,20,2,10
1744999004.450726,20,3,15
1744999015.8825645,20,3,15
1744999016.7402997,20,3,15
1744999016.9421299,20,3,15
1744999018.2932267,20,4,20
1744999033.164793,20,4,20
1744999034.0264122,20,4,20
1744999034.2218397,20,4,20
1744999035.8827643,20,5,25
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timestamp,ram_usage_mb,cpu_usage_percent
1744998970,646.27734375,21.6
1744998970,646.28125,22.9
1744998970,646.33203125,22.6
1744998970,646.33203125,25.5
1744998970,646.33203125,20.0
1744998971,646.33203125,23.0
1744998971,646.33203125,24.5
1744999658,708.50390625,31.9
1744999658,708.50390625,32.5
1744999659,708.50390625,25.7
1744999659,708.50390625,26.1
1745007163,956.96484375,8.9
1745007163,956.96484375,7.3
1745007164,956.96484375,7.2
1745007164,956.96484375,3.1
1745015042,968.09765625,7.1
1745015042,968.09765625,7.2
1745015042,968.09765625,7.1
1745015042,968.09765625,7.0
1745024256,1032.59765625,7.3
1745024256,1032.59765625,7.0
1745024256,1032.59765625,7.2
1745024256,1032.59765625,7.5
1745033287,1031.38671875,7.3
1745033287,1031.38671875,6.2
1745033287,1031.38671875,6.1
1745033287,1031.38671875,4.9
1745043126,1069.73046875,7.4
1745043126,1069.73046875,6.5
1745043126,1069.73046875,6.9
1745043126,1069.73046875,3.2
1745054372,1045.80859375,7.5
1745054372,1045.80859375,7.2
1745054372,1045.80859375,7.1
1745054372,1045.80859375,3.1
1745066122,1057.9375,7.4
1745066122,1057.9375,6.4
1745066122,1057.9375,6.5
1745066122,1057.9375,6.3
1745080135,1092.99609375,7.5
1745080135,1092.99609375,7.3
1745080135,1092.99609375,7.3
1745080135,1092.99609375,5.9

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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: 'IBM Plex Sans', 'Source Sans Pro', sans-serif;
				background-color: #fafafa;
				text-shadow: 0 0.05em 0.1em rgba(0,0,0,0.2);
				scroll-behavior: smooth;
				text-wrap: balance;
				text-rendering: optimizeLegibility;
				-webkit-font-smoothing: antialiased;
				-moz-osx-font-smoothing: grayscale;
				font-feature-settings: "ss02", "liga", "onum";
			}
			
			.marked_text {
				background-color: yellow;
			}
			
			.time_picker_container {
				font-variant: small-caps;
				width: 100%;
			}
			
			.time_picker_container > input {
				width: 50px;
			}
			
			#loader {
				display: grid;
				justify-content: center;
				align-items: center;
				height: 100%;
			}
			
			.no_linebreak {
				line-break: auto;
			}
			
			.dark_code_bg {
				background-color: #363636;
				color: white;
			}
			
			.code_bg {
				background-color: #C0C0C0;
			}
			
			#commands {
				line-break: anywhere;
			}
			
			.color_red {
				color: red;
			}
			
			.color_orange {
				color: orange;
			}
			
			table > tbody > tr:nth-child(odd) {
				background-color: #fafafa;
			}
			
			table > tbody > tr:nth-child(even) {
				background-color: #ddd;
			}
			
			table {
				border-collapse: collapse;
				margin: 0 0;
				min-width: 200px;
			}
			
			th {
				background-color: #4eae46;
				color: #ffffff;
				text-align: left;
				border: 0px;
			}
			
			.error_element {
				background-color: #e57373;
				border-radius: 10px;
				padding: 4px;
				display: none;
			}
			
			button {
				background-color: #4eae46;
				border: 1px solid #2A8387;
				border-radius: 4px;
				box-shadow: rgba(0, 0, 0, 0.12) 0 1px 1px;
				cursor: pointer;
				display: block;
				line-height: 100%;
				outline: 0;
				padding: 11px 15px 12px;
				text-align: center;
				transition: box-shadow .05s ease-in-out, opacity .05s ease-in-out;
				user-select: none;
				-webkit-user-select: none;
				touch-action: manipulation;
				font-family: 'IBM Plex Sans', 'Source Sans Pro', sans-serif;
			}
			
			button:hover {
				box-shadow: rgba(255, 255, 255, 0.3) 0 0 2px inset, rgba(0, 0, 0, 0.4) 0 1px 2px;
				text-decoration: none;
				transition-duration: .15s, .15s;
			}
			
			button:active {
				box-shadow: rgba(0, 0, 0, 0.15) 0 2px 4px inset, rgba(0, 0, 0, 0.4) 0 1px 1px;
			}
			
			button:disabled {
				cursor: not-allowed;
				opacity: .6;
			}
			
			button:disabled:active {
				pointer-events: none;
			}
			
			button:disabled:hover {
				box-shadow: none;
			}
			
			.half_width_td {
				vertical-align: baseline;
				width: 50%;
			}
			
			#scads_bar {
				width: 100%;
				margin: 0;
				padding: 0;
				user-select: none;
				user-drag: none;
				-webkit-user-drag: none;
				user-select: none;
				-moz-user-select: none;
				-webkit-user-select: none;
				-ms-user-select: none;
				display: -webkit-box;
			}
			
			.tab {
				display: inline-block;
				padding: 0px;
				margin: 0px;
				font-size: 16px;
				font-weight: bold;
				text-align: center;
				border-radius: 25px;
				text-decoration: none !important;
				transition: background-color 0.3s, color 0.3s;
				color: unset !important;
			}
			
			.tooltipster-base {
				border: 1px solid black;
				position: absolute;
				border-radius: 8px;
				padding: 2px;
				color: white;
				background-color: #61686f;
				width: 70%;
				min-width: 200px;
				pointer-events: none;
			}
			
			td {
				padding-top: 3px;
				padding-bottom: 3px;
			}
			
			.left_side {
				text-align: right;
			}
			
			.right_side {
				text-align: left;
			}
			
			.spinner {
				border: 8px solid rgba(0, 0, 0, 0.1);
				border-left: 8px solid #3498db;
				border-radius: 50%;
				width: 50px;
				height: 50px;
				animation: spin 1s linear infinite;
			}
			
			@keyframes spin {
				0% {
					transform: rotate(0deg);
				}
			
				100% {
					transform: rotate(360deg);
				}
			}
			
			#spinner-overlay {
				-webkit-text-stroke: 1px black;
				white !important;
				position: fixed;
				top: 0;
				left: 0;
				width: 100%;
				height: 100%;
				display: flex;
				justify-content: center;
				align-items: center;
				z-index: 9999;
			}
			
			#spinner-container {
				text-align: center;
				color: #fff;
				display: contents;
			}
			
			#spinner-text {
				font-size: 3vw;
				margin-left: 10px;
			}
			
			a, a:visited, a:active, a:hover, a:link {
				color: #007bff;
				text-decoration: none;
			}
			
			.copy-container {
				display: inline-block;
				position: relative;
				cursor: pointer;
				margin-left: 10px;
				color: blue;
			}
			
			.copy-container:hover {
				text-decoration: underline;
			}
			
			.clipboard-icon {
				position: absolute;
				top: 5px;
				right: 5px;
				font-size: 1.5em;
			}
			
			#main_tab {
				overflow: scroll;
				width: max-content;
			}
			
			.ui-tabs .ui-tabs-nav li {
				user-select: none;
			}
			
			.stacktrace_table {
				background-color: black !important;
				color: white !important;
			}
			
			#breadcrumb {
				user-select: none;
			}
			
			#statusBar {
				user-select: none;
			}
			
			.error_line {
				background-color: red !important;
				color: white !important;
			}
			
			.header_table {
				border: 0px !important;
				padding: 0px !important;
				width: revert !important;
				min-width: revert !important;
			}
			
			.img_auto_width {
				max-width: revert !important;
			}
			
			#main_dir_or_plot_view {
				display: inline-grid;
			}
			
			#refresh_button {
				width: 300px;
			}
			
			._share_link {
				color: black !important;
			}
			
			#footer_element {
				height: 30px;
				background-color: #f8f9fa;
				padding: 0px;
				text-align: center;
				border-top: 1px solid #dee2e6;
				width: 100%;
				box-sizing: border-box;
				position: fixed;
				bottom: 0;
				z-index: 2;
				margin-left: -9px;
				z-index: 99;
			}
			
			.switch {
				position: relative;
				display: inline-block;
				width: 50px;
				height: 26px;
			}
			
			.switch input {
				opacity: 0;
				width: 0;
				height: 0;
			}
			
			.slider {
				position: absolute;
				cursor: pointer;
				top: 0;
				left: 0;
				right: 0;
				bottom: 0;
				background-color: #ccc;
				transition: .4s;
				border-radius: 26px;
			}
			
			.slider:before {
				position: absolute;
				content: "";
				height: 20px;
				width: 20px;
				left: 3px;
				bottom: 3px;
				background-color: white;
				transition: .4s;
				border-radius: 50%;
			}
			
			input:checked + .slider {
				background-color: #444;
			}
			
			input:checked + .slider:before {
				transform: translateX(24px);
			}
			
			.mode-text {
				position: absolute;
				top: 5px;
				left: 65px;
				font-size: 14px;
				color: black;
				transition: .4s;
				width: 65px;
				display: block;
				font-size: 0.7rem;
				text-align: center;
			}
			
			input:checked + .slider .mode-text {
				content: "Dark Mode";
				color: white;
			}
			
			#mainContent {
				height: fit-content;
				min-height: 100%;
			}
			
			li {
				text-align: left;
			}
			
			#share_path {
				margin-bottom: 20px;
				margin-top: 20px;
			}
			
			#sortForm {
				margin-bottom: 20px;
			}
			
			.share_folder_buttons {
				margin-top: 10px;
				margin-bottom: 10px;
			}
			
			.nav_tab_button {
				margin: 10px;
			}
			
			.header_table {
				margin: 10px;
			}
			
			.no_border {
				border: unset !important;
			}
			
			.gui_table {
				padding: 5px !important;
			}
			
			.gui_parameter_row {
			}
			
			.gui_parameter_row_cell {
				border: unset !important;
			}
			
			.gui_param_table {
				width: 95%;
				margin: unset !important;
			}
			
			table td, table tr,
			.parameterRow table {
				padding: 2px !important;
			}
			
			.parameterRow table {
				margin: 0px;
				border: unset;
			}
			
			.parameterRow > td {
				border: 0px !important;
			}
			
			.parameter_config_table td, .parameter_config_table tr, #config_table th, #config_table td, #hidden_config_table th, #hidden_config_table td {
				border: 0px !important;
			}
			
			.green_text {
				color: green;
			}
			
			.remove_parameter {
				white-space: pre;
			}
			
			select {
				appearance: none;
				-webkit-appearance: none;
				-moz-appearance: none;
				background-color: #fff;
				color: #222;
				padding: 5px 30px 5px 5px;
				border: 1px solid #555;
				border-radius: 5px;
				cursor: pointer;
				outline: none;
				transition: all 0.3s ease;
				background:
					url("data:image/svg+xml;charset=UTF-8,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 10 6'%3E%3Cpath fill='%23888' d='M0 0l5 6 5-6z'/%3E%3C/svg%3E")
					no-repeat right 10px center,
				linear-gradient(180deg, #fff, #ecebe5 86%, #d8d0c4);
				background-size: 12px, auto;
			}
			
			select:hover {
				border-color: #888;
			}
			
			select:focus {
				border-color: #4caf50;
				box-shadow: 0 0 5px rgba(76, 175, 80, 0.5);
			}
			
			select::-ms-expand {
				display: none;
			}
			
			input, textarea {
				border-radius: 5px;
			}
			
			#search {
				width: 200px;
				max-width: 70%;
				background-image: url(images/search.svg);
				background-repeat: no-repeat;
				background-size: auto 40px;
				height: 40px;
				line-height: 40px;
				padding-left: 40px;
				box-sizing: border-box;
			}
			
			input[type="checkbox"] {
				appearance: none;
				-webkit-appearance: none;
				-moz-appearance: none;
				width: 25px;
				height: 25px;
				border: 2px solid #3498db;
				border-radius: 5px;
				background-color: #fff;
				position: relative;
				cursor: pointer;
				transition: all 0.3s ease;
				width: 25px !important;
			}
			
			input[type="checkbox"]:checked {
				background-color: #3498db;
				border-color: #2980b9;
			}
			
			input[type="checkbox"]:checked::before {
				content: '✔';
				position: absolute;
				left: 4px;
				top: 2px;
				color: #fff;
			}
			
			input[type="checkbox"]:hover {
				border-color: #2980b9;
				background-color: #3caffc;
			}
			
			.toc {
				margin-bottom: 20px;
			}
			
			.toc li {
				margin-bottom: 5px;
			}
			
			.toc a {
				text-decoration: none;
				color: #007bff;
			}
			
			.toc a:hover {
				text-decoration: underline;
			}
			
			.table-container {
				width: 100%;
				overflow-x: auto;
			}
			
			.section-header {
				background-color: #1d6f9a !important;
				color: white;
			}
			
			.warning {
				color: red;
			}
			
			.li_list a {
				text-decoration: none;
			}
			
			.gridjs-td {
				white-space: nowrap;
			}
			
			th, td {
				border: 1px solid gray !important;
			}
			
			.no_border {
				border: 0px !important;
			}
			
			.no_break {
			
			}
			
			img {
				user-select: none;
				pointer-events: none;
			}
			
			#config_table, #hidden_config_table {
				user-select: none;
			}
			
			.copy_clipboard_button {
				margin-bottom: 10px;
			}
			
			.badge_table {
				background-color: unset !important;
			}
			
			.make_markable {
				user-select: text;
			}
			
			.header-container {
				display: flex;
				flex-wrap: wrap;
				align-items: center;
				justify-content: space-between;
				gap: 1rem;
				padding: 10px;
				background: var(--header-bg, #fff);
				border-bottom: 1px solid #ccc;
			}
			
			.header-logo-group {
				display: flex;
				gap: 1rem;
				align-items: center;
				flex: 1 1 auto;
				min-width: 200px;
			}
			
			.logo-img {
				max-height: 45px;
				height: auto;
				width: auto;
				object-fit: contain;
				pointer-events: unset;
			}
			
			.header-badges {
				flex-direction: column;
				gap: 5px;
				align-items: flex-start;
				flex: 0 1 auto;
				margin-top: auto;
				margin-bottom: auto;
			}
			
			.badge-img {
				height: auto;
				max-width: 130px;
				margin-top: 3px;
			}
			
			.header-tabs {
				margin-top: 10px;
				display: flex;
				flex-wrap: wrap;
				gap: 10px;
				flex: 2 1 100%;
				justify-content: center;
			}
			
			.nav-tab {
				display: inline-block;
				text-decoration: none;
				padding: 8px 16px;
				border-radius: 20px;
				background: linear-gradient(to right, #4a90e2, #357ABD);
				color: white;
				font-weight: bold;
				white-space: nowrap;
				transition: background 0.2s ease-in-out, transform 0.2s;
				box-shadow: 0 2px 4px rgba(0,0,0,0.2);
			}
			
			.nav-tab:hover {
				background: linear-gradient(to right, #5aa0f2, #4a90e2);
				transform: translateY(-2px);
			}
			
			.current-tag {
				padding-left: 10px;
				font-size: 0.9rem;
				color: #666;
			}
			
			.header-theme-toggle {
				flex: 1 1 auto;
				align-items: center;
				margin-top: 20px;
				min-width: 120px;
			}
			
			.switch {
				position: relative;
				display: inline-block;
				width: 60px;
				height: 30px;
			}
			
			.switch input {
				display: none;
			}
			
			.slider {
				position: absolute;
				top: 0; left: 0; right: 0; bottom: 0;
				background-color: #ccc;
				border-radius: 34px;
				cursor: pointer;
			}
			
			.slider::before {
				content: "";
				position: absolute;
				height: 24px;
				width: 24px;
				left: 3px;
				bottom: 3px;
				background-color: white;
				transition: .4s;
				border-radius: 50%;
			}
			
			input:checked + .slider {
				background-color: #2196F3;
			}
			
			input:checked + .slider::before {
				transform: translateX(30px);
			}
			
			@media (max-width: 768px) {
				.header-logo-group,
				.header-badges,
				.header-theme-toggle {
					justify-content: center;
					flex: 1 1 100%;
					text-align: center;
					width: inherit;
				}
			
				.logo-img {
					max-height: 50px;
					pointer-events: unset;
				}
			
				.badge-img {
					max-width: 100px;
				}
			
				.hide_on_mobile {
					display: none;
				}
			
				.nav-tab {
					font-size: 0.9rem;
					padding: 6px 12px;
				}
			
				.header_button {
					white-space: pre;
					font-size: 2em;
				}
			}
			
			.header_button {
				white-space: pre;
				margin-top: 20px;
				margin: 5px;
			}
			
			.line_break_anywhere {
				line-break: anywhere;
			}
			
			.responsive-container {
				display: flex;
				flex-wrap: wrap;
				justify-content: space-between;
				gap: 20px;
			}
			
			.responsive-container .half {
				flex: 1 1 48%;
				box-sizing: border-box;
				min-width: 500px;
			}
			
			.config-section table {
				width: 100%;
				border-collapse: collapse;
			}
			
			@media (max-width: 768px) {
				.responsive-container .half {
					flex: 1 1 100%;
				}
			}
			
			@keyframes spin {
				0% {
					transform: rotate(0deg);
				}
			
				100% {
					transform: rotate(360deg);
				}
			}
			
			.rotate {
				animation: spin 2s linear infinite;
				display: inline-block;
			}
			
			input::placeholder {
				font-family: 'IBM Plex Sans', 'Source Sans Pro', sans-serif;
			}
			
			.gridjs-th-content {
				overflow: visible !important;
			}
			
			.error_text {
				color: red;
			}
			
			h1, h2, h3, h4, h5, h6 {
				margin-top: 1em;
				font-weight: bold;
				color: #333;
				border-left: 5px solid #ccc;
				padding-left: 0.5em;
			}
			
			.no_cursive {
				font-style: normal;	
			}
			
			.caveat {
				background-color: #fff8b3;
				border: 1px solid #f2d600;
				padding: 1em 1em 1em 70px;
				position: relative;
				font-family: sans-serif;
				color: #665500;
				margin: 1em 0;
				border-radius: 4px;
			}
			
			.caveat h1, .caveat h2, .caveat h3, .caveat h4 {
				margin-top: 0;
				margin-bottom: 0.5em;
				font-weight: bold;
			}
			
			.caveat::before {
				content: "⚠️";
				font-size: 50px;
				line-height: 1;
				position: absolute;
				left: 10px;
				top: 50%;
				transform: translateY(-50%);
				pointer-events: none;
				user-select: none;
			}
			
			.caveat.warning::before { content: "⚠️"; }
			.caveat.stop::before { content: "🛑"; }
			.caveat.exclamation::before { content: "❗"; }
			.caveat.alarm::before { content: "🚨"; }
			.caveat.tip::before { content: "💡"; }
			
			.tutorial_icon {
				display: inline-block;
				font-size: 1.3em;
				line-height: 1;
				vertical-align: middle;
				transform: translateY(-10%);
				padding: 0.2em 0;
			}
			
			.highlight {
				background-color: yellow;
				font-weight: bold;
			}
			
			#searchResults li {
				opacity: 0;
				transform: translateY(8px);
				animation: fadeInUp 0.3s ease-out forwards;
				animation-delay: 0.05s;
				list-style: none;
				margin-bottom: 5px;
			}
			
			@keyframes fadeInUp {
				to {
					opacity: 1;
					transform: translateY(0);
				}
			}
			
			.search_headline {
				font-weight: bold;
				margin-top: 1em;
				margin-bottom: 0.3em;
				color: #444;
			}
			
			.search_share_path {
				color: black;
				display: block ruby;
				margin-top: 20px;
			}
			
			@media print {
				#scads_bar {
					display: none !important;
				}
			}
			

			/*! XP.css v0.2.6 - https: //botoxparty.github.io/XP.css/ */
			body{
				color: #222
			}
			
			.surface{
				background: #ece9d8
			}
			
			u{
				text-decoration: none;
				border-bottom: .5px solid #222
			}
			
			a{
				color: #00f
			}
			
			a: focus{
				outline: 1px dotted #00f
			}
			
			code,code *{
				font-family: monospace
			}
			
			pre{
				display: block;
				padding: 12px 8px;
				background-color: #000;
				color: silver;
				font-size: 1rem;
				margin: 0;
				overflow: scroll;
			}
			
			summary: focus{
				outline: 1px dotted #000
			}
			
			: :-webkit-scrollbar{
				width: 16px
			}
			
			: :-webkit-scrollbar: horizontal{
				height: 17px
			}
			
			: :-webkit-scrollbar-track{
				background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='2' height='2' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M1 0H0v1h1v1h1V1H1V0z' fill='silver'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 0H1v1H0v1h1V1h1V0z' fill='%23fff'/%3E%3C/svg%3E")
			}
			
			: :-webkit-scrollbar-thumb{
				background-color: #dfdfdf;
				box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #fff,inset -2px -2px grey,inset 2px 2px #dfdfdf
			}
			
			: :-webkit-scrollbar-button: horizontal: end: increment,: :-webkit-scrollbar-button: horizontal: start: decrement,: :-webkit-scrollbar-button: vertical: end: increment,: :-webkit-scrollbar-button: vertical: start: decrement{
				display: block
			}
			
			: :-webkit-scrollbar-button: vertical: start{
				background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 6H7v1H6v1H5v1H4v1h7V9h-1V8H9V7H8V6z' fill='%23000'/%3E%3C/svg%3E")
			}
			
			: :-webkit-scrollbar-button: vertical: end{
				background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 6H4v1h1v1h1v1h1v1h1V9h1V8h1V7h1V6z' fill='%23000'/%3E%3C/svg%3E")
			}
			
			: :-webkit-scrollbar-button: horizontal: start{
				width: 16px;
				background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 4H8v1H7v1H6v1H5v1h1v1h1v1h1v1h1V4z' fill='%23000'/%3E%3C/svg%3E")
			}
			
			: :-webkit-scrollbar-button: horizontal: end{
				width: 16px;
				background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M7 4H6v7h1v-1h1V9h1V8h1V7H9V6H8V5H7V4z' fill='%23000'/%3E%3C/svg%3E")
			}
			
			button{
				border: none;
				background: #ece9d8;
				box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #fff,inset -2px -2px grey,inset 2px 2px #dfdfdf;
				border-radius: 0;
				min-width: 75px;
				min-height: 23px;
				padding: 0 12px
			}
			
			button: not(: disabled).active,button: not(: disabled): active{
				box-shadow: inset -1px -1px #fff,inset 1px 1px #0a0a0a,inset -2px -2px #dfdfdf,inset 2px 2px grey
			}
			
			button.focused,button: focus{
				outline: 1px dotted #000;
				outline-offset: -4px
			}
			
			label{
				display: inline-flex;
				align-items: center
			}
			
			textarea{
				padding: 3px 4px;
				border: none;
				background-color: #fff;
				box-sizing: border-box;
				-webkit-appearance: none;
				-moz-appearance: none;
				appearance: none;
				border-radius: 0
			}
			
			textarea: focus{
				outline: none
			}
			
			select: focus option{
				color: #000;
				background-color: #fff
			}
			
			.vertical-bar{
				width: 4px;
				height: 20px;
				background: silver;
				box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #fff,inset -2px -2px grey,inset 2px 2px #dfdfdf
			}
			
			&: disabled,&: disabled+label{
				color: grey;
				text-shadow: 1px 1px 0 #fff
			}
			
			input[type=radio]+label{
				line-height: 13px;
				position: relative;
				margin-left: 19px
			}
			
			input[type=radio]+label: before{
				content: "";
				position: absolute;
				top: 0;
				left: -19px;
				display: inline-block;
				width: 13px;
				height: 13px;
				margin-right: 6px;
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='12' height='12' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 0H4v1H2v1H1v2H0v4h1v2h1V8H1V4h1V2h2V1h4v1h2V1H8V0z' fill='gray'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 1H4v1H2v2H1v4h1v1h1V8H2V4h1V3h1V2h4v1h2V2H8V1z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 3h1v1H9V3zm1 5V4h1v4h-1zm-2 2V9h1V8h1v2H8zm-4 0v1h4v-1H4zm0 0V9H2v1h2z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 2h-1v2h1v4h-1v2H8v1H4v-1H2v1h2v1h4v-1h2v-1h1V8h1V4h-1V2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M4 2h4v1h1v1h1v4H9v1H8v1H4V9H3V8H2V4h1V3h1V2z' fill='%23fff'/%3E%3C/svg%3E")
			}
			
			input[type=radio]: active+label: before{
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='12' height='12' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 0H4v1H2v1H1v2H0v4h1v2h1V8H1V4h1V2h2V1h4v1h2V1H8V0z' fill='gray'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 1H4v1H2v2H1v4h1v1h1V8H2V4h1V3h1V2h4v1h2V2H8V1z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 3h1v1H9V3zm1 5V4h1v4h-1zm-2 2V9h1V8h1v2H8zm-4 0v1h4v-1H4zm0 0V9H2v1h2z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 2h-1v2h1v4h-1v2H8v1H4v-1H2v1h2v1h4v-1h2v-1h1V8h1V4h-1V2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M4 2h4v1h1v1h1v4H9v1H8v1H4V9H3V8H2V4h1V3h1V2z' fill='silver'/%3E%3C/svg%3E")
			}
			
			input[type=radio]: checked+label: after{
				content: "";
				display: block;
				width: 5px;
				height: 5px;
				top: 5px;
				left: -14px;
				position: absolute;
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='4' height='4' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M3 0H1v1H0v2h1v1h2V3h1V1H3V0z' fill='%23000'/%3E%3C/svg%3E")
			}
			
			input[type=radio][disabled]+label: before{
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='12' height='12' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 0H4v1H2v1H1v2H0v4h1v2h1V8H1V4h1V2h2V1h4v1h2V1H8V0z' fill='gray'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 1H4v1H2v2H1v4h1v1h1V8H2V4h1V3h1V2h4v1h2V2H8V1z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 3h1v1H9V3zm1 5V4h1v4h-1zm-2 2V9h1V8h1v2H8zm-4 0v1h4v-1H4zm0 0V9H2v1h2z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 2h-1v2h1v4h-1v2H8v1H4v-1H2v1h2v1h4v-1h2v-1h1V8h1V4h-1V2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M4 2h4v1h1v1h1v4H9v1H8v1H4V9H3V8H2V4h1V3h1V2z' fill='silver'/%3E%3C/svg%3E")
			}
			
			input[type=radio][disabled]: checked+label: after{
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='4' height='4' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M3 0H1v1H0v2h1v1h2V3h1V1H3V0z' fill='gray'/%3E%3C/svg%3E")
			}
			
			input[type=email],input[type=password]{
				padding: 3px 4px;
				border: 1px solid #7f9db9;
				background-color: #fff;
				box-sizing: border-box;
				-webkit-appearance: none;
				-moz-appearance: none;
				appearance: none;
				border-radius: 0;
				height: 21px;
				line-height: 2
			}
			
			input[type=email]: focus,input[type=password]: focus{
				outline: none
			}
			
			input[type=range]{
				-webkit-appearance: none;
				width: 100%;
				background: transparent
			}
			
			input[type=range]: focus{
				outline: none
			}
			
			input[type=range]: :-webkit-slider-thumb{
				-webkit-appearance: none;
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v16h2v2h2v2h1v-1H3v-2H1V1h9V0z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M1 1v15h1v1h1v1h1v1h2v-1h1v-1h1v-1h1V1z' fill='%23C0C7C8'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v15H8v2H6v2H5v-1h2v-2h2z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v16H9v2H7v2H5v1h1v-2h2v-2h2z' fill='%23000'/%3E%3C/svg%3E")
			}
			
			input[type=range]: :-moz-range-thumb{
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v16h2v2h2v2h1v-1H3v-2H1V1h9V0z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M1 1v15h1v1h1v1h1v1h2v-1h1v-1h1v-1h1V1z' fill='%23C0C7C8'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v15H8v2H6v2H5v-1h2v-2h2z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v16H9v2H7v2H5v1h1v-2h2v-2h2z' fill='%23000'/%3E%3C/svg%3E")
			}
			
			input[type=range]: :-webkit-slider-runnable-track{
				background: #000;
				border-right: 1px solid grey;
				border-bottom: 1px solid grey;
				box-shadow: 1px 0 0 #fff,1px 1px 0 #fff,0 1px 0 #fff,-1px 0 0 #a9a9a9,-1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,-1px 1px 0 #fff,1px -1px #a9a9a9
			}
			
			input[type=range]: :-moz-range-track{
				background: #000;
				border-right: 1px solid grey;
				border-bottom: 1px solid grey;
				box-shadow: 1px 0 0 #fff,1px 1px 0 #fff,0 1px 0 #fff,-1px 0 0 #a9a9a9,-1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,-1px 1px 0 #fff,1px -1px #a9a9a9
			}
			
			input[type=range].has-box-indicator: :-webkit-slider-thumb{
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v20h1V1h9V0z' fill='%23fff'/%3E%3Cpath fill='%23C0C7C8' d='M1 1h8v18H1z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v19H1v-1h8z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v21H0v-1h10z' fill='%23000'/%3E%3C/svg%3E")
			}
			
			input[type=range].has-box-indicator: :-moz-range-thumb{
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v20h1V1h9V0z' fill='%23fff'/%3E%3Cpath fill='%23C0C7C8' d='M1 1h8v18H1z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v19H1v-1h8z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v21H0v-1h10z' fill='%23000'/%3E%3C/svg%3E")
			}
			
			.is-vertical{
				display: inline-block;
				width: 4px;
				height: 150px;
				transform: translateY(50%)
			}
			
			.is-vertical>input[type=range]{
				width: 150px;
				height: 4px;
				margin: 0 16px 0 10px;
				transform-origin: left;
				transform: rotate(270deg) translateX(calc(-50% + 8px))
			}
			
			.is-vertical>input[type=range]: :-webkit-slider-runnable-track{
				border-left: 1px solid grey;
				border-bottom: 1px solid grey;
				box-shadow: -1px 0 0 #fff,-1px 1px 0 #fff,0 1px 0 #fff,1px 0 0 #a9a9a9,1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,1px 1px 0 #fff,-1px -1px #a9a9a9
			}
			
			.is-vertical>input[type=range]: :-moz-range-track{
				border-left: 1px solid grey;
				border-bottom: 1px solid grey;
				box-shadow: -1px 0 0 #fff,-1px 1px 0 #fff,0 1px 0 #fff,1px 0 0 #a9a9a9,1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,1px 1px 0 #fff,-1px -1px #a9a9a9
			}
			
			.is-vertical>input[type=range]: :-webkit-slider-thumb{
				transform: translateY(-8px) scaleX(-1)
			}
			
			.is-vertical>input[type=range]: :-moz-range-thumb{
				transform: translateY(2px) scaleX(-1)
			}
			
			.is-vertical>input[type=range].has-box-indicator: :-webkit-slider-thumb{
				transform: translateY(-10px) scaleX(-1)
			}
			
			.is-vertical>input[type=range].has-box-indicator: :-moz-range-thumb{
				transform: translateY(0) scaleX(-1)
			}
			
			.window{
				font-size: 11px;
				box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #dfdfdf,inset -2px -2px grey,inset 2px 2px #fff;
				background: #ece9d8;
				padding: 3px
			}
			
			.window fieldset{
				margin-bottom: 9px
			}
			
			.title-bar{
				background: #000;
				padding: 3px 2px 3px 3px;
				display: flex;
				justify-content: space-between;
				align-items: center
			}
			
			.title-bar-text{
				font-weight: 700;
				color: #fff;
				letter-spacing: 0;
				margin-right: 24px
			}
			
			.title-bar-controls button{
				padding: 0;
				display: block;
				min-width: 16px;
				min-height: 14px
			}
			
			.title-bar-controls button: focus{
				outline: none
			}
			
			.window-body{
				margin: 8px
			}
			
			.window-body pre{
				margin: -8px
			}
			
			.status-bar{
				margin: 0 1px;
				display: flex;
				gap: 1px
			}
			
			.status-bar-field{
				box-shadow: inset -1px -1px #dfdfdf,inset 1px 1px grey;
				flex-grow: 1;
				padding: 2px 3px;
				margin: 0
			}
			
			ul.tree-view{
				display: block;
				background: #fff;
				padding: 6px;
				margin: 0
			}
			
			ul.tree-view li{
				list-style-type: none;
				margin-top: 3px
			}
			
			ul.tree-view a{
				text-decoration: none;
				color: #000
			}
			
			ul.tree-view a: focus{
				background-color: #2267cb;
				color: #fff
			}
			
			ul.tree-view ul{
				margin-top: 3px;
				margin-left: 16px;
				padding-left: 16px;
				border-left: 1px dotted grey
			}
			
			ul.tree-view ul>li{
				position: relative
			}
			
			ul.tree-view ul>li: before{
				content: "";
				display: block;
				position: absolute;
				left: -16px;
				top: 6px;
				width: 12px;
				border-bottom: 1px dotted grey
			}
			
			ul.tree-view ul>li: last-child: after{
				content: "";
				display: block;
				position: absolute;
				left: -20px;
				top: 7px;
				bottom: 0;
				width: 8px;
				background: #fff
			}
			
			ul.tree-view ul details>summary: before{
				margin-left: -22px;
				position: relative;
				z-index: 1
			}
			
			ul.tree-view details{
				margin-top: 0
			}
			
			ul.tree-view details>summary: before{
				text-align: center;
				display: block;
				float: left;
				content: "+";
				border: 1px solid grey;
				width: 8px;
				height: 9px;
				line-height: 9px;
				margin-right: 5px;
				padding-left: 1px;
				background-color: #fff
			}
			
			ul.tree-view details[open] summary{
				margin-bottom: 0
			}
			
			ul.tree-view details[open]>summary: before{
				content: "-"
			}
			
			fieldset{
				border-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='5' height='5' fill='gray' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0h5v5H0V2h2v1h1V2H0' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0h4v4H0V1h1v2h2V1H0'/%3E%3C/svg%3E") 2;
				padding: 10px;
				padding-block-start: 8px;
				margin: 0
			}
			
			legend{
				background: #ece9d8
			}
			
			menu[role=tablist]{
				position: relative;
				margin: 0 0 -2px;
				text-indent: 0;
				list-style-type: none;
				display: flex;
				padding-left: 3px
			}
			
			menu[role=tablist] button{
				z-index: 1;
				display: block;
				color: #222;
				text-decoration: none;
				min-width: unset
			}
			
			menu[role=tablist] button[aria-selected=true]{
				padding-bottom: 2px;margin-top: -2px;background-color: #ece9d8;position: relative;z-index: 8;margin-left: -3px;margin-bottom: 1px
			}
			
			menu[role=tablist] button: focus{
				outline: 1px dotted #222;outline-offset: -4px
			}
			
			menu[role=tablist].justified button{
				flex-grow: 1;text-align: center
			}
			
			[role=tabpanel]{
				padding: 14px;clear: both;background: linear-gradient(180deg,#fcfcfe,#f4f3ee);border: 1px solid #919b9c;position: relative;z-index: 2;margin-bottom: 9px
			}
			
			: :-webkit-scrollbar{
				width: 17px
			}
			
			: :-webkit-scrollbar-corner{
				background: #dfdfdf
			}
			
			: :-webkit-scrollbar-track: vertical{
				background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 17 1' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eeede5' d='M0 0h1m15 0h1'/%3E%3Cpath stroke='%23f3f1ec' d='M1 0h1'/%3E%3Cpath stroke='%23f4f1ec' d='M2 0h1'/%3E%3Cpath stroke='%23f4f3ee' d='M3 0h1'/%3E%3Cpath stroke='%23f5f4ef' d='M4 0h1'/%3E%3Cpath stroke='%23f6f5f0' d='M5 0h1'/%3E%3Cpath stroke='%23f7f7f3' d='M6 0h1'/%3E%3Cpath stroke='%23f9f8f4' d='M7 0h1'/%3E%3Cpath stroke='%23f9f9f7' d='M8 0h1'/%3E%3Cpath stroke='%23fbfbf8' d='M9 0h1'/%3E%3Cpath stroke='%23fbfbf9' d='M10 0h2'/%3E%3Cpath stroke='%23fdfdfa' d='M12 0h1'/%3E%3Cpath stroke='%23fefefb' d='M13 0h3'/%3E%3C/svg%3E")
			}
			
			: :-webkit-scrollbar-track: horizontal{
				background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 1 17' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eeede5' d='M0 0h1M0 16h1'/%3E%3Cpath stroke='%23f3f1ec' d='M0 1h1'/%3E%3Cpath stroke='%23f4f1ec' d='M0 2h1'/%3E%3Cpath stroke='%23f4f3ee' d='M0 3h1'/%3E%3Cpath stroke='%23f5f4ef' d='M0 4h1'/%3E%3Cpath stroke='%23f6f5f0' d='M0 5h1'/%3E%3Cpath stroke='%23f7f7f3' d='M0 6h1'/%3E%3Cpath stroke='%23f9f8f4' d='M0 7h1'/%3E%3Cpath stroke='%23f9f9f7' d='M0 8h1'/%3E%3Cpath stroke='%23fbfbf8' d='M0 9h1'/%3E%3Cpath stroke='%23fbfbf9' d='M0 10h1m-1 1h1'/%3E%3Cpath stroke='%23fdfdfa' d='M0 12h1'/%3E%3Cpath stroke='%23fefefb' d='M0 13h1m-1 1h1m-1 1h1'/%3E%3C/svg%3E")
			}
			
			: :-webkit-scrollbar-thumb{
				background-position: 50%;
				background-repeat: no-repeat;
				background-color: #c8d6fb;
				background-size: 7px;
				border: 1px solid #fff;
				border-radius: 2px;
				box-shadow: inset -3px 0 #bad1fc,inset 1px 1px #b7caf5
			}
			
			: :-webkit-scrollbar-thumb: vertical{
				background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 7 8' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eef4fe' d='M0 0h6M0 2h6M0 4h6M0 6h6'/%3E%3Cpath stroke='%23bad1fc' d='M6 0h1M6 2h1M6 4h1'/%3E%3Cpath stroke='%23c8d6fb' d='M0 1h1M0 3h1M0 5h1M0 7h1'/%3E%3Cpath stroke='%238cb0f8' d='M1 1h6M1 3h6M1 5h6M1 7h6'/%3E%3Cpath stroke='%23bad3fc' d='M6 6h1'/%3E%3C/svg%3E")
			}
			
			: :-webkit-scrollbar-thumb: horizontal{
				background-size: 8px;background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 8 7' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eef4fe' d='M0 0h1m1 0h1m1 0h1m1 0h1M0 1h1m1 0h1m1 0h1m1 0h1M0 2h1m1 0h1m1 0h1m1 0h1M0 3h1m1 0h1m1 0h1m1 0h1M0 4h1m1 0h1m1 0h1m1 0h1M0 5h1m1 0h1m1 0h1m1 0h1'/%3E%3Cpath stroke='%23c8d6fb' d='M1 0h1m1 0h1m1 0h1m1 0h1'/%3E%3Cpath stroke='%238cb0f8' d='M1 1h1m1 0h1m1 0h1m1 0h1M1 2h1m1 0h1m1 0h1m1 0h1M1 3h1m1 0h1m1 0h1m1 0h1M1 4h1m1 0h1m1 0h1m1 0h1M1 5h1m1 0h1m1 0h1m1 0h1M1 6h1m1 0h1m1 0h1m1 0h1'/%3E%3Cpath stroke='%23bad1fc' d='M0 6h1m1 0h1'/%3E%3Cpath stroke='%23bad3fc' d='M4 6h1m1 0h1'/%3E%3C/svg%3E")
			}
			
			: :-webkit-scrollbar-button: vertical: start{
				height: 17px;
				background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 17 17' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eeede5' d='M0 0h1m15 0h1M0 1h1M0 2h1M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m15 0h1M0 16h1m15 0h1'/%3E%3Cpath stroke='%23fdfdfa' d='M1 0h1'/%3E%3Cpath stroke='%23fff' d='M2 0h14M1 1h1m13 0h1M1 2h1m13 0h1M1 3h1m13 0h1M1 4h1m13 0h1M1 5h1m13 0h1M1 6h1m13 0h1M1 7h1m13 0h1M1 8h1m13 0h1M1 9h1m13 0h1M1 10h1m13 0h1M1 11h1m13 0h1M1 12h1m13 0h1M1 13h1m13 0h1M1 14h1m13 0h1M2 15h13'/%3E%3Cpath stroke='%23e6eefc' d='M2 1h1'/%3E%3Cpath stroke='%23d0dffc' d='M3 1h1M2 2h1'/%3E%3Cpath stroke='%23cad8f9' d='M4 1h1M2 3h1'/%3E%3Cpath stroke='%23c4d2f7' d='M5 1h1'/%3E%3Cpath stroke='%23c0d0f7' d='M6 1h1'/%3E%3Cpath stroke='%23bdcef7' d='M7 1h1M2 6h1'/%3E%3Cpath stroke='%23bbcdf5' d='M8 1h1'/%3E%3Cpath stroke='%23b8cbf6' d='M9 1h1M2 7h1'/%3E%3Cpath stroke='%23b7caf5' d='M10 1h1M2 8h1'/%3E%3Cpath stroke='%23b5c8f7' d='M11 1h1'/%3E%3Cpath stroke='%23b3c7f5' d='M12 1h1'/%3E%3Cpath stroke='%23afc5f4' d='M13 1h1'/%3E%3Cpath stroke='%23dce6f9' d='M14 1h1'/%3E%3Cpath stroke='%23dfe2e1' d='M16 1h1'/%3E%3Cpath stroke='%23e1eafe' d='M3 2h1'/%3E%3Cpath stroke='%23dae6fe' d='M4 2h1M3 3h1'/%3E%3Cpath stroke='%23d4e1fc' d='M5 2h1M3 4h1'/%3E%3Cpath stroke='%23d1e0fd' d='M6 2h1M4 4h1'/%3E%3Cpath stroke='%23d0ddfc' d='M7 2h1M3 5h1'/%3E%3Cpath stroke='%23cedbfd' d='M8 2h1M6 3h1'/%3E%3Cpath stroke='%23cad9fd' d='M9 2h1M7 3h1M5 5h1'/%3E%3Cpath stroke='%23c8d8fb' d='M10 2h1'/%3E%3Cpath stroke='%23c5d6fc' d='M11 2h1m-8 8h1m1 0h1'/%3E%3Cpath stroke='%23c2d3fc' d='M12 2h1m-2 1h1m-9 7h1m0 1h1'/%3E%3Cpath stroke='%23bccefa' d='M13 2h1m-1 2h1m-9 9h2'/%3E%3Cpath stroke='%23b9c9f3' d='M14 2h1M5 14h3'/%3E%3Cpath stroke='%23cfd7dd' d='M16 2h1'/%3E%3Cpath stroke='%23d8e3fc' d='M4 3h1'/%3E%3Cpath stroke='%23d1defd' d='M5 3h1'/%3E%3Cpath stroke='%23c9d8fc' d='M8 3h1M6 4h2M5 6h2M3 7h1'/%3E%3Cpath stroke='%23c5d5fc' d='M9 3h1M3 9h1m3 0h1'/%3E%3Cpath stroke='%23c5d3fc' d='M10 3h1'/%3E%3Cpath stroke='%23bed0fc' d='M12 3h1M9 4h1m-7 7h1m0 1h1'/%3E%3Cpath stroke='%23bccdfa' d='M13 3h1'/%3E%3Cpath stroke='%23baccf4' d='M14 3h1'/%3E%3Cpath stroke='%23bdcbda' d='M16 3h1'/%3E%3Cpath stroke='%23c4d4f7' d='M2 4h1'/%3E%3Cpath stroke='%23cddbfc' d='M5 4h1M3 6h1'/%3E%3Cpath stroke='%23c8d5fb' d='M8 4h1'/%3E%3Cpath stroke='%23bbcefd' d='M10 4h3M9 5h1'/%3E%3Cpath stroke='%23bcccf3' d='M14 4h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b1c2d5' d='M16 4h1'/%3E%3Cpath stroke='%23bed0f8' d='M2 5h1'/%3E%3Cpath stroke='%23ceddfd' d='M4 5h1'/%3E%3Cpath stroke='%23c8d6fb' d='M6 5h2M3 8h2'/%3E%3Cpath stroke='%234d6185' d='M8 5h1M7 6h3M6 7h5M5 8h3m1 0h3M4 9h3m3 0h3m-8 1h1m5 0h1'/%3E%3Cpath stroke='%23bacdfc' d='M10 5h1m1 0h2M3 12h1'/%3E%3Cpath stroke='%23b9cdfb' d='M11 5h1m-2 1h1m1 0h2m-1 1h1'/%3E%3Cpath stroke='%23a8bbd4' d='M16 5h1'/%3E%3Cpath stroke='%23cddafc' d='M4 6h1'/%3E%3Cpath stroke='%23b7cdfc' d='M11 6h1m0 1h1'/%3E%3Cpath stroke='%23a4b8d3' d='M16 6h1'/%3E%3Cpath stroke='%23cad8fd' d='M4 7h2'/%3E%3Cpath stroke='%23b6cefb' d='M11 7h1m0 1h1'/%3E%3Cpath stroke='%23bacbf4' d='M14 7h1'/%3E%3Cpath stroke='%23a0b5d3' d='M16 7h1m-1 1h1m-1 5h1'/%3E%3Cpath stroke='%23c1d3fb' d='M8 8h1'/%3E%3Cpath stroke='%23b6cdfb' d='M13 8h1m-5 5h1'/%3E%3Cpath stroke='%23b9cbf3' d='M14 8h1'/%3E%3Cpath stroke='%23b4c8f6' d='M2 9h1'/%3E%3Cpath stroke='%23c2d5fc' d='M8 9h1m-1 1h1m-3 1h2'/%3E%3Cpath stroke='%23bdd3fb' d='M9 9h1m-2 3h1'/%3E%3Cpath stroke='%23b5cdfa' d='M13 9h1'/%3E%3Cpath stroke='%23b5c9f3' d='M14 9h1'/%3E%3Cpath stroke='%239fb5d2' d='M16 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b1c7f6' d='M2 10h1'/%3E%3Cpath stroke='%23c3d5fd' d='M7 10h1'/%3E%3Cpath stroke='%23bad4fc' d='M9 10h1m-1 1h1'/%3E%3Cpath stroke='%23b2cffb' d='M10 10h1m1 0h1m-2 2h1'/%3E%3Cpath stroke='%23b1cbfa' d='M13 10h1'/%3E%3Cpath stroke='%23b3c8f5' d='M14 10h1m-6 4h2'/%3E%3Cpath stroke='%23adc3f6' d='M2 11h1'/%3E%3Cpath stroke='%23c3d3fd' d='M5 11h1'/%3E%3Cpath stroke='%23c1d5fb' d='M8 11h1'/%3E%3Cpath stroke='%23b7d3fc' d='M10 11h1m-2 1h1'/%3E%3Cpath stroke='%23b3d1fc' d='M11 11h1'/%3E%3Cpath stroke='%23afcefb' d='M12 11h1'/%3E%3Cpath stroke='%23aecafa' d='M13 11h1'/%3E%3Cpath stroke='%23b1c8f3' d='M14 11h1'/%3E%3Cpath stroke='%23acc2f5' d='M2 12h1'/%3E%3Cpath stroke='%23c1d2fb' d='M5 12h1'/%3E%3Cpath stroke='%23bed1fc' d='M6 12h2'/%3E%3Cpath stroke='%23b6d1fb' d='M10 12h1'/%3E%3Cpath stroke='%23afccfb' d='M12 12h1'/%3E%3Cpath stroke='%23adc9f9' d='M13 12h1m-2 1h1'/%3E%3Cpath stroke='%23b1c5f3' d='M14 12h1'/%3E%3Cpath stroke='%23aac0f3' d='M2 13h1'/%3E%3Cpath stroke='%23b7cbf9' d='M3 13h1'/%3E%3Cpath stroke='%23b9cefb' d='M4 13h1'/%3E%3Cpath stroke='%23bbcef9' d='M7 13h1'/%3E%3Cpath stroke='%23b9cffb' d='M8 13h1'/%3E%3Cpath stroke='%23b2cdfb' d='M10 13h1'/%3E%3Cpath stroke='%23b0cbf9' d='M11 13h1'/%3E%3Cpath stroke='%23aec8f7' d='M13 13h1'/%3E%3Cpath stroke='%23b0c5f2' d='M14 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			: :-webkit-scrollbar-button: vertical: end{
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			}
			
			: :-webkit-scrollbar-button: horizontal: start{
				width: 17px;
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15h1'/%3E%3Cpath stroke='%23aec4e5' d='M15 15h1'/%3E%3Cpath stroke='%23edf1f3' d='M0 16h1'/%3E%3Cpath stroke='%23aac0e1' d='M1 16h1'/%3E%3Cpath stroke='%2394b1d9' d='M2 16h1'/%3E%3Cpath stroke='%2388a7d8' d='M3 16h1'/%3E%3Cpath stroke='%2383a4d3' d='M4 16h1'/%3E%3Cpath stroke='%237da0d4' d='M5 16h1m4 0h3'/%3E%3Cpath stroke='%237e9fd2' d='M6 16h1'/%3E%3Cpath stroke='%237c9fd3' d='M7 16h3'/%3E%3Cpath stroke='%2382a4d6' d='M13 16h1'/%3E%3Cpath stroke='%2394b0dd' d='M14 16h1'/%3E%3Cpath stroke='%23ecf2f7' d='M15 16h1'/%3E%3C/svg%3E")
			}
			
			: :-webkit-scrollbar-button: horizontal: end{
				width: 17px;
				background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 17 17' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eeede5' d='M0 0h17m-1 1h1m-1 14h1m-1 1h1'/%3E%3Cpath stroke='%23fdfdfa' d='M0 1h1'/%3E%3Cpath stroke='%23fff' d='M1 1h15M0 2h1m14 0h1M0 3h1m14 0h1M0 4h1m14 0h1M0 5h1m14 0h1M0 6h1m14 0h1M0 7h1m14 0h1M0 8h1m14 0h1M0 9h1m14 0h1M0 10h1m14 0h1M0 11h1m14 0h1M0 12h1m14 0h1M0 13h1m14 0h1M0 14h1m14 0h1M1 15h14'/%3E%3Cpath stroke='%23e6eefc' d='M1 2h1'/%3E%3Cpath stroke='%23d0dffc' d='M2 2h1M1 3h1'/%3E%3Cpath stroke='%23cad8f9' d='M3 2h1M1 4h1'/%3E%3Cpath stroke='%23c4d2f7' d='M4 2h1'/%3E%3Cpath stroke='%23c0d0f7' d='M5 2h1'/%3E%3Cpath stroke='%23bdcef7' d='M6 2h1M1 7h1'/%3E%3Cpath stroke='%23bbcdf5' d='M7 2h2'/%3E%3Cpath stroke='%23b8cbf6' d='M9 2h1M1 8h1'/%3E%3Cpath stroke='%23b7caf5' d='M10 2h1'/%3E%3Cpath stroke='%23b5c8f7' d='M11 2h1'/%3E%3Cpath stroke='%23b3c7f5' d='M12 2h1'/%3E%3Cpath stroke='%23afc5f4' d='M13 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			}
			
			.window{
				box-shadow: inset -1px -1px #00138c,inset 1px 1px #0831d9,inset -2px -2px #001ea0,inset 2px 2px #166aee,inset -3px -3px #003bda,inset 3px 3px #0855dd;
				border-top-left-radius: 8px;
				border-top-right-radius: 8px;
				padding: 0 0 3px;
				-webkit-font-smoothing: antialiased
			}
			
			.title-bar{
				background: linear-gradient(180deg,#0997ff,#0053ee 8%,#0050ee 40%,#06f 88%,#06f 93%,#005bff 95%,#003dd7 96%,#003dd7);
				padding: 3px 5px 3px 3px;
				border-top: 1px solid #0831d9;
				border-left: 1px solid #0831d9;
				border-right: 1px solid #001ea0;
				border-top-left-radius: 8px;
				border-top-right-radius: 7px;
				font-size: 13px;
				text-shadow: 1px 1px #0f1089;
				height: 21px
			}
			
			.title-bar-text{
				padding-left: 3px
			}
			
			.title-bar-controls{
				display: flex
			}
			
			.title-bar-controls button{
				min-width: 21px;
				min-height: 21px;
				margin-left: 2px;
				background-repeat: no-repeat;
				background-position: 50%;
				box-shadow: none;
				background-color: #0050ee;
				transition: background .1s;
				border: none
			}
			
			.title-bar-controls button: active,.title-bar-controls button: focus,.title-bar-controls button: hover{
				box-shadow: none!important
			}
			
			.title-bar-controls button[aria-label=Minimize]{
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stroke='%239e3217' d='M2 10h1'/%3E%3Cpath stroke='%23b4381a' d='M3 10h1'/%3E%3Cpath stroke='%23df9a87' d='M10 10h1m-2 1h1m-2 2h1'/%3E%3Cpath stroke='%23c6441f' d='M13 10h1m3 0h1m-8 3h1m-1 3h1'/%3E%3Cpath stroke='%23c74520' d='M14 10h2m-6 4h1m-1 1h1m7 2h1m-7 1h1m4 0h1'/%3E%3Cpath stroke='%23c7451f' d='M16 10h1m1 2h1'/%3E%3Cpath stroke='%237b2711' d='M1 11h1'/%3E%3Cpath stroke='%23a13217' d='M2 11h1'/%3E%3Cpath stroke='%23b7391a' d='M3 11h1'/%3E%3Cpath stroke='%23e09b88' d='M11 11h1'/%3E%3Cpath stroke='%23e29d89' d='M12 11h1'/%3E%3Cpath stroke='%23c94621' d='M13 11h1m-3 2h1'/%3E%3Cpath stroke='%23ca4721' d='M14 11h1m2 1h1m-7 2h1m-1 1h1m0 2h1m2 1h1'/%3E%3Cpath stroke='%23ca4821' d='M15 11h1m1 6h1'/%3E%3Cpath stroke='%23c94620' d='M16 11h1m1 3h1m-8 2h1m6 0h1'/%3E%3Cpath stroke='%23c84620' d='M17 11h1m0 2h1'/%3E%3Cpath stroke='%23a53418' d='M2 12h1'/%3E%3Cpath stroke='%23b83a1b' d='M3 12h1'/%3E%3Cpath stroke='%23e19d89' d='M11 12h1'/%3E%3Cpath stroke='%23e39e89' d='M12 12h1'/%3E%3Cpath stroke='%23e0947c' d='M13 12h1'/%3E%3Cpath stroke='%23cc4a22' d='M14 12h1m-3 2h1m4 0h1m-6 1h1'/%3E%3Cpath stroke='%23cd4a22' d='M15 12h1m0 1h1m0 2h1m-5 1h1m1 1h1'/%3E%3Cpath stroke='%23cb4922' d='M16 12h1m0 1h1m-5 4h1'/%3E%3Cpath stroke='%23c3411e' d='M19 12h1m-1 1h1m-1 4h1m-8 2h2m3 0h1'/%3E%3Cpath stroke='%23a93618' d='M2 13h1'/%3E%3Cpath stroke='%23dd9987' d='M7 13h1m-2 2h1'/%3E%3Cpath stroke='%23e39f8a' d='M12 13h1'/%3E%3Cpath stroke='%23e59f8b' d='M13 13h1'/%3E%3Cpath stroke='%23e5a08b' d='M14 13h1m-2 1h1'/%3E%3Cpath stroke='%23ce4c23' d='M15 13h1m0 3h1'/%3E%3Cpath stroke='%23882b13' d='M1 14h1'/%3E%3Cpath stroke='%23e6a08b' d='M14 14h1'/%3E%3Cpath stroke='%23e6a18b' d='M15 14h1m-2 1h1'/%3E%3Cpath stroke='%23ce4b23' d='M16 14h1m-4 1h1'/%3E%3Cpath stroke='%238b2c14' d='M1 15h1m-1 1h1'/%3E%3Cpath stroke='%23ac3619' d='M2 15h1'/%3E%3Cpath stroke='%23d76b48' d='M15 15h1'/%3E%3Cpath stroke='%23cf4c23' d='M16 15h1m-2 1h1'/%3E%3Cpath stroke='%23c94721' d='M18 15h1m-3 3h1'/%3E%3Cpath stroke='%23bb3c1b' d='M3 16h1'/%3E%3Cpath stroke='%23bf3e1d' d='M6 16h1'/%3E%3Cpath stroke='%23cb4821' d='M12 16h1'/%3E%3Cpath stroke='%23cd4b23' d='M14 16h1'/%3E%3Cpath stroke='%23cc4922' d='M17 16h1m-4 1h1m1 0h1'/%3E%3Cpath stroke='%238d2d14' d='M1 17h1'/%3E%3Cpath stroke='%23bc3c1b' d='M3 17h1m-1 1h1'/%3E%3Cpath stroke='%23c84520' d='M11 17h1m1 1h1'/%3E%3Cpath stroke='%23ae3719' d='M2 18h1'/%3E%3Cpath stroke='%23c94720' d='M14 18h1'/%3E%3Cpath stroke='%23c95839' d='M19 18h1'/%3E%3Cpath stroke='%23a7bdf0' d='M0 19h1m0 1h1'/%3E%3Cpath stroke='%23ead7d3' d='M1 19h1'/%3E%3Cpath stroke='%23b34e35' d='M2 19h1'/%3E%3Cpath stroke='%23c03e1c' d='M8 19h1'/%3E%3Cpath stroke='%23c9583a' d='M18 19h1'/%3E%3Cpath stroke='%23f3dbd4' d='M19 19h1'/%3E%3Cpath stroke='%23a7bcef' d='M20 19h1m-2 1h1'/%3E%3C/svg%3E")
			}
			
			.status-bar{
				margin: 0 3px;
				box-shadow: inset 0 1px 2px grey;
				padding: 2px 1px;
				gap: 0
			}
			
			.status-bar-field{
				-webkit-font-smoothing: antialiased;
				box-shadow: none;
				padding: 1px 2px;
				border-right: 1px solid rgba(208,206,191,.75);
				border-left: 1px solid hsla(0,0%,100%,.75)
			}
			
			.status-bar-field: first-of-type{
				border-left: none
			}
			
			.status-bar-field: last-of-type{
				border-right: none
			}
			
			button{
				-webkit-font-smoothing: antialiased;
				box-sizing: border-box;
				border: 1px solid #003c74;
				background: linear-gradient(180deg,#fff,#ecebe5 86%,#d8d0c4);
				box-shadow: none;
				border-radius: 3px
			}
			
			button: not(: disabled).active,button: not(: disabled): active{
				box-shadow: none;
				background: linear-gradient(180deg,#cdcac3,#e3e3db 8%,#e5e5de 94%,#f2f2f1)
			}
			
			button: not(: disabled): hover{
				box-shadow: inset -1px 1px #fff0cf,inset 1px 2px #fdd889,inset -2px 2px #fbc761,inset 2px -2px #e5a01a
			}
			
			button.focused,button: focus{
				box-shadow: inset -1px 1px #cee7ff,inset 1px 2px #98b8ea,inset -2px 2px #bcd4f6,inset 1px -1px #89ade4,inset 2px -2px #89ade4
			}
			
			button: :-moz-focus-inner{
				border: 0
			}
			
			input,label,option,select,textarea{
				-webkit-font-smoothing: antialiased
			}
			
			input[type=radio]{
				appearance: none;
				-webkit-appearance: none;
				-moz-appearance: none;
				margin: 0;
				background: 0;
				position: fixed;
				opacity: 0;
				border: none
			}
			
			input[type=radio]+label{
				line-height: 16px
			}
			
			input[type=radio]+label: before{
				background: linear-gradient(135deg,#dcdcd7,#fff);
				border-radius: 50%;
				border: 1px solid #1d5281
			}
			
			input[type=radio]: not([disabled]): not(: active)+label: hover: before{
				box-shadow: inset -2px -2px #f8b636,inset 2px 2px #fedf9c
			}
			
			input[type=radio]: active+label: before{
				background: linear-gradient(135deg,#b0b0a7,#e3e1d2)
			}
			
			input[type=radio]: checked+label: after{
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 5 5' shape-rendering='crispEdges'%3E%3Cpath stroke='%23a9dca6' d='M1 0h1M0 1h1'/%3E%3Cpath stroke='%234dbf4a' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23a0d29e' d='M3 0h1M0 3h1'/%3E%3Cpath stroke='%2355d551' d='M1 1h1'/%3E%3Cpath stroke='%2343c33f' d='M2 1h1'/%3E%3Cpath stroke='%2329a826' d='M3 1h1'/%3E%3Cpath stroke='%239acc98' d='M4 1h1M1 4h1'/%3E%3Cpath stroke='%2342c33f' d='M1 2h1'/%3E%3Cpath stroke='%2338b935' d='M2 2h1'/%3E%3Cpath stroke='%2321a121' d='M3 2h1'/%3E%3Cpath stroke='%23269623' d='M4 2h1'/%3E%3Cpath stroke='%232aa827' d='M1 3h1'/%3E%3Cpath stroke='%2322a220' d='M2 3h1'/%3E%3Cpath stroke='%23139210' d='M3 3h1'/%3E%3Cpath stroke='%2398c897' d='M4 3h1'/%3E%3Cpath stroke='%23249624' d='M2 4h1'/%3E%3Cpath stroke='%2398c997' d='M3 4h1'/%3E%3C/svg%3E")
			}
			
			input[type=radio]: focus+label{
				outline: 1px dotted #000
			}
			
			input[type=radio][disabled]+label: before{
				border: 1px solid #cac8bb;
				background: #fff
			}
			
			input[type=radio][disabled]: checked+label: after{
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 5 5' shape-rendering='crispEdges'%3E%3Cpath stroke='%23e8e6da' d='M1 0h1M0 1h1'/%3E%3Cpath stroke='%23d2ceb5' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23e5e3d4' d='M3 0h1M0 3h1'/%3E%3Cpath stroke='%23d7d3bd' d='M1 1h1'/%3E%3Cpath stroke='%23d0ccb2' d='M2 1h1M1 2h1'/%3E%3Cpath stroke='%23c7c2a2' d='M3 1h1M1 3h1'/%3E%3Cpath stroke='%23e2dfd0' d='M4 1h1M1 4h1'/%3E%3Cpath stroke='%23cdc8ac' d='M2 2h1'/%3E%3Cpath stroke='%23c5bf9f' d='M3 2h1M2 3h1'/%3E%3Cpath stroke='%23c3bd9c' d='M4 2h1'/%3E%3Cpath stroke='%23bfb995' d='M3 3h1'/%3E%3Cpath stroke='%23e2dfcf' d='M4 3h1M3 4h1'/%3E%3Cpath stroke='%23c4be9d' d='M2 4h1'/%3E%3C/svg%3E")
			}
			
			input[type=email],input[type=password],textarea: :selection{
				background: #2267cb;
				color: #fff
			}
			
			input[type=range]: :-webkit-slider-thumb{
				height: 21px;
				width: 11px;
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 11 21' shape-rendering='crispEdges'%3E%3Cpath stroke='%23becbd3' d='M1 0h1M0 1h1'/%3E%3Cpath stroke='%23b6c5cd' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23b5c4cd' d='M3 0h5M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23afbfc8' d='M8 0h1M0 14h1'/%3E%3Cpath stroke='%239fb2be' d='M9 0h1M0 15h1'/%3E%3Cpath stroke='%23a6d1b1' d='M1 1h1'/%3E%3Cpath stroke='%236fd16e' d='M2 1h1M1 2h1'/%3E%3Cpath stroke='%2367ce65' d='M3 1h1M1 3h1'/%3E%3Cpath stroke='%2366ce64' d='M4 1h3'/%3E%3Cpath stroke='%2362cd61' d='M7 1h1'/%3E%3Cpath stroke='%2345c343' d='M8 1h1M7 2h1'/%3E%3Cpath stroke='%2363ac76' d='M9 1h1M2 16h1m0 1h1m0 1h1'/%3E%3Cpath stroke='%23879aa6' d='M10 1h1'/%3E%3Cpath stroke='%2363cd62' d='M2 2h1'/%3E%3Cpath stroke='%2349c547' d='M3 2h1M2 3h1'/%3E%3Cpath stroke='%2347c446' d='M4 2h3'/%3E%3Cpath stroke='%2321b71f' d='M8 2h1'/%3E%3Cpath stroke='%231da41c' d='M9 2h1'/%3E%3Cpath stroke='%237d8e99' d='M10 2h1'/%3E%3Cpath stroke='%2325b923' d='M3 3h1'/%3E%3Cpath stroke='%2321b81f' d='M4 3h4M2 15h1'/%3E%3Cpath stroke='%231ea71c' d='M8 3h1'/%3E%3Cpath stroke='%231b9619' d='M9 3h1'/%3E%3Cpath stroke='%23778892' d='M10 3h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f7f7f4' d='M1 4h1M1 5h1M1 6h1M1 7h1M1 8h1M1 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f5f5f2' d='M2 4h1M2 5h1M2 6h1M2 7h1M2 8h1M2 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f3f3ef' d='M3 4h5M3 5h5M3 6h5M3 7h5M3 8h5M3 9h5m-5 1h5m-5 1h5m-5 1h5m-5 1h4m-4 1h3m-2 1h1'/%3E%3Cpath stroke='%23dcdcd9' d='M8 4h1M8 5h1M8 6h1M8 7h1M8 8h1M8 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c3c3c0' d='M9 4h1M9 5h1M9 6h1M9 7h1M9 8h1M9 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f1f1ed' d='M7 13h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%23dbdbd8' d='M8 13h1'/%3E%3Cpath stroke='%23c4c4c1' d='M9 13h1'/%3E%3Cpath stroke='%234bc549' d='M1 14h1'/%3E%3Cpath stroke='%23f4f4f1' d='M2 14h1'/%3E%3Cpath stroke='%23e6e6e2' d='M7 14h1m-2 1h1'/%3E%3Cpath stroke='%23cececa' d='M8 14h1'/%3E%3Cpath stroke='%231a9319' d='M9 14h1'/%3E%3Cpath stroke='%23788993' d='M10 14h1'/%3E%3Cpath stroke='%2369b17b' d='M1 15h1'/%3E%3Cpath stroke='%23f2f2ee' d='M3 15h1m0 1h1'/%3E%3Cpath stroke='%23d0d0cc' d='M7 15h1m-2 1h1'/%3E%3Cpath stroke='%231a9118' d='M8 15h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%234c845a' d='M9 15h1'/%3E%3Cpath stroke='%2372838d' d='M10 15h1'/%3E%3Cpath stroke='%2391a6b2' d='M1 16h1m0 1h1m0 1h1m0 1h1'/%3E%3Cpath stroke='%2321b61f' d='M3 16h1m0 1h1'/%3E%3Cpath stroke='%23e7e7e3' d='M5 16h1'/%3E%3Cpath stroke='%234b8259' d='M8 16h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%236e7e88' d='M9 16h1m-2 1h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%23d7d7d4' d='M5 17h1'/%3E%3Cpath stroke='%231da21b' d='M5 18h1'/%3E%3Cpath stroke='%23589868' d='M5 19h1'/%3E%3Cpath stroke='%2380929e' d='M5 20h1'/%3E%3C/svg%3E");
				transform: translateY(-8px)
			}
			
			input[type=range]: :-moz-range-thumb{
				height: 21px;
				width: 11px;
				border: 0;
				border-radius: 0;
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 11 21' shape-rendering='crispEdges'%3E%3Cpath stroke='%23becbd3' d='M1 0h1M0 1h1'/%3E%3Cpath stroke='%23b6c5cd' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23b5c4cd' d='M3 0h5M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23afbfc8' d='M8 0h1M0 14h1'/%3E%3Cpath stroke='%239fb2be' d='M9 0h1M0 15h1'/%3E%3Cpath stroke='%23a6d1b1' d='M1 1h1'/%3E%3Cpath stroke='%236fd16e' d='M2 1h1M1 2h1'/%3E%3Cpath stroke='%2367ce65' d='M3 1h1M1 3h1'/%3E%3Cpath stroke='%2366ce64' d='M4 1h3'/%3E%3Cpath stroke='%2362cd61' d='M7 1h1'/%3E%3Cpath stroke='%2345c343' d='M8 1h1M7 2h1'/%3E%3Cpath stroke='%2363ac76' d='M9 1h1M2 16h1m0 1h1m0 1h1'/%3E%3Cpath stroke='%23879aa6' d='M10 1h1'/%3E%3Cpath stroke='%2363cd62' d='M2 2h1'/%3E%3Cpath stroke='%2349c547' d='M3 2h1M2 3h1'/%3E%3Cpath stroke='%2347c446' d='M4 2h3'/%3E%3Cpath stroke='%2321b71f' d='M8 2h1'/%3E%3Cpath stroke='%231da41c' d='M9 2h1'/%3E%3Cpath stroke='%237d8e99' d='M10 2h1'/%3E%3Cpath stroke='%2325b923' d='M3 3h1'/%3E%3Cpath stroke='%2321b81f' d='M4 3h4M2 15h1'/%3E%3Cpath stroke='%231ea71c' d='M8 3h1'/%3E%3Cpath stroke='%231b9619' d='M9 3h1'/%3E%3Cpath stroke='%23778892' d='M10 3h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f7f7f4' d='M1 4h1M1 5h1M1 6h1M1 7h1M1 8h1M1 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f5f5f2' d='M2 4h1M2 5h1M2 6h1M2 7h1M2 8h1M2 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f3f3ef' d='M3 4h5M3 5h5M3 6h5M3 7h5M3 8h5M3 9h5m-5 1h5m-5 1h5m-5 1h5m-5 1h4m-4 1h3m-2 1h1'/%3E%3Cpath stroke='%23dcdcd9' d='M8 4h1M8 5h1M8 6h1M8 7h1M8 8h1M8 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c3c3c0' d='M9 4h1M9 5h1M9 6h1M9 7h1M9 8h1M9 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f1f1ed' d='M7 13h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%23dbdbd8' d='M8 13h1'/%3E%3Cpath stroke='%23c4c4c1' d='M9 13h1'/%3E%3Cpath stroke='%234bc549' d='M1 14h1'/%3E%3Cpath stroke='%23f4f4f1' d='M2 14h1'/%3E%3Cpath stroke='%23e6e6e2' d='M7 14h1m-2 1h1'/%3E%3Cpath stroke='%23cececa' d='M8 14h1'/%3E%3Cpath stroke='%231a9319' d='M9 14h1'/%3E%3Cpath stroke='%23788993' d='M10 14h1'/%3E%3Cpath stroke='%2369b17b' d='M1 15h1'/%3E%3Cpath stroke='%23f2f2ee' d='M3 15h1m0 1h1'/%3E%3Cpath stroke='%23d0d0cc' d='M7 15h1m-2 1h1'/%3E%3Cpath stroke='%231a9118' d='M8 15h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%234c845a' d='M9 15h1'/%3E%3Cpath stroke='%2372838d' d='M10 15h1'/%3E%3Cpath stroke='%2391a6b2' d='M1 16h1m0 1h1m0 1h1m0 1h1'/%3E%3Cpath stroke='%2321b61f' d='M3 16h1m0 1h1'/%3E%3Cpath stroke='%23e7e7e3' d='M5 16h1'/%3E%3Cpath stroke='%234b8259' d='M8 16h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%236e7e88' d='M9 16h1m-2 1h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%23d7d7d4' d='M5 17h1'/%3E%3Cpath stroke='%231da21b' d='M5 18h1'/%3E%3Cpath stroke='%23589868' d='M5 19h1'/%3E%3Cpath stroke='%2380929e' d='M5 20h1'/%3E%3C/svg%3E");
				transform: translateY(2px)
			}
			
			input[type=range]: :-webkit-slider-runnable-track{
				width: 100%;
				height: 2px;
				box-sizing: border-box;
				background: #ecebe4;
				border-right: 1px solid #f3f2ea;
				border-bottom: 1px solid #f3f2ea;
				border-radius: 2px;
				box-shadow: 1px 0 0 #fff,1px 1px 0 #fff,0 1px 0 #fff,-1px 0 0 #9d9c99,-1px -1px 0 #9d9c99,0 -1px 0 #9d9c99,-1px 1px 0 #fff,1px -1px #9d9c99
			}
			
			input[type=range]: :-moz-range-track{
				width: 100%;
				height: 2px;
				box-sizing: border-box;
				background: #ecebe4;
				border-right: 1px solid #f3f2ea;
				border-bottom: 1px solid #f3f2ea;
				border-radius: 2px;
				box-shadow: 1px 0 0 #fff,1px 1px 0 #fff,0 1px 0 #fff,-1px 0 0 #9d9c99,-1px -1px 0 #9d9c99,0 -1px 0 #9d9c99,-1px 1px 0 #fff,1px -1px #9d9c99
			}
			
			input[type=range].has-box-indicator: :-webkit-slider-thumb{
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 11 22' shape-rendering='crispEdges'%3E%3Cpath stroke='%23f2f1e7' d='M0 0h1m9 0h1M0 21h1m9 0h1'/%3E%3Cpath stroke='%23879aa6' d='M1 0h1m8 20h1'/%3E%3Cpath stroke='%237d8e99' d='M2 0h1m7 19h1'/%3E%3Cpath stroke='%23778892' d='M3 0h5m2 3h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23788993' d='M8 0h1m1 2h1'/%3E%3Cpath stroke='%2372838d' d='M9 0h1m0 1h1'/%3E%3Cpath stroke='%239fb2be' d='M0 1h1m8 20h1'/%3E%3Cpath stroke='%2363af76' d='M1 1h1m7 19h1'/%3E%3Cpath stroke='%231eab1c' d='M2 1h1m6 18h1'/%3E%3Cpath stroke='%231c9d1a' d='M3 1h1'/%3E%3Cpath stroke='%231b9a1a' d='M4 1h3m1 0h1m0 1h1'/%3E%3Cpath stroke='%231b9b1a' d='M7 1h1'/%3E%3Cpath stroke='%234d875b' d='M9 1h1'/%3E%3Cpath stroke='%23afbfc8' d='M0 2h1m7 19h1'/%3E%3Cpath stroke='%2346ca44' d='M1 2h1m5 17h1m0 1h1'/%3E%3Cpath stroke='%2322be20' d='M2 2h1m5 17h1'/%3E%3Cpath stroke='%231faf1d' d='M3 2h1'/%3E%3Cpath stroke='%231fae1d' d='M4 2h3'/%3E%3Cpath stroke='%231fad1d' d='M7 2h1'/%3E%3Cpath stroke='%231da11b' d='M8 2h1'/%3E%3Cpath stroke='%23b5c4cd' d='M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m2 3h5'/%3E%3Cpath stroke='%23f7f7f4' d='M1 3h1M1 4h1M1 5h1M1 6h1M1 7h1M1 8h1M1 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f5f5f2' d='M2 3h1M2 4h1M2 5h1M2 6h1M2 7h1M2 8h1M2 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f3f3ef' d='M3 3h4M3 4h5M3 5h5M3 6h5M3 7h5M3 8h5M3 9h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5'/%3E%3Cpath stroke='%23f1f1ed' d='M7 3h1'/%3E%3Cpath stroke='%23dbdbd8' d='M8 3h1'/%3E%3Cpath stroke='%23c4c4c1' d='M9 3h1'/%3E%3Cpath stroke='%23ddddd9' d='M8 4h1M8 18h1'/%3E%3Cpath stroke='%23c6c6c3' d='M9 4h1M9 18h1'/%3E%3Cpath stroke='%23dcdcd9' d='M8 5h1M8 6h1M8 7h1M8 8h1M8 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c3c3c0' d='M9 5h1M9 6h1M9 7h1M9 8h1M9 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b6c5cd' d='M0 19h1m1 2h1'/%3E%3Cpath stroke='%2370d66f' d='M1 19h1m0 1h1'/%3E%3Cpath stroke='%2364d362' d='M2 19h1'/%3E%3Cpath stroke='%234acb48' d='M3 19h1'/%3E%3Cpath stroke='%2348cb46' d='M4 19h3'/%3E%3Cpath stroke='%23becbd3' d='M0 20h1m0 1h1'/%3E%3Cpath stroke='%23a6d2b1' d='M1 20h1'/%3E%3Cpath stroke='%2367d466' d='M3 20h1'/%3E%3Cpath stroke='%2366d465' d='M4 20h3'/%3E%3Cpath stroke='%2363d362' d='M7 20h1'/%3E%3C/svg%3E");transform: translateY(-10px)
			}
			
			input[type=range].has-box-indicator: :-moz-range-thumb{
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 11 22' shape-rendering='crispEdges'%3E%3Cpath stroke='%23f2f1e7' d='M0 0h1m9 0h1M0 21h1m9 0h1'/%3E%3Cpath stroke='%23879aa6' d='M1 0h1m8 20h1'/%3E%3Cpath stroke='%237d8e99' d='M2 0h1m7 19h1'/%3E%3Cpath stroke='%23778892' d='M3 0h5m2 3h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23788993' d='M8 0h1m1 2h1'/%3E%3Cpath stroke='%2372838d' d='M9 0h1m0 1h1'/%3E%3Cpath stroke='%239fb2be' d='M0 1h1m8 20h1'/%3E%3Cpath stroke='%2363af76' d='M1 1h1m7 19h1'/%3E%3Cpath stroke='%231eab1c' d='M2 1h1m6 18h1'/%3E%3Cpath stroke='%231c9d1a' d='M3 1h1'/%3E%3Cpath stroke='%231b9a1a' d='M4 1h3m1 0h1m0 1h1'/%3E%3Cpath stroke='%231b9b1a' d='M7 1h1'/%3E%3Cpath stroke='%234d875b' d='M9 1h1'/%3E%3Cpath stroke='%23afbfc8' d='M0 2h1m7 19h1'/%3E%3Cpath stroke='%2346ca44' d='M1 2h1m5 17h1m0 1h1'/%3E%3Cpath stroke='%2322be20' d='M2 2h1m5 17h1'/%3E%3Cpath stroke='%231faf1d' d='M3 2h1'/%3E%3Cpath stroke='%231fae1d' d='M4 2h3'/%3E%3Cpath stroke='%231fad1d' d='M7 2h1'/%3E%3Cpath stroke='%231da11b' d='M8 2h1'/%3E%3Cpath stroke='%23b5c4cd' d='M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m2 3h5'/%3E%3Cpath stroke='%23f7f7f4' d='M1 3h1M1 4h1M1 5h1M1 6h1M1 7h1M1 8h1M1 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f5f5f2' d='M2 3h1M2 4h1M2 5h1M2 6h1M2 7h1M2 8h1M2 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f3f3ef' d='M3 3h4M3 4h5M3 5h5M3 6h5M3 7h5M3 8h5M3 9h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5'/%3E%3Cpath stroke='%23f1f1ed' d='M7 3h1'/%3E%3Cpath stroke='%23dbdbd8' d='M8 3h1'/%3E%3Cpath stroke='%23c4c4c1' d='M9 3h1'/%3E%3Cpath stroke='%23ddddd9' d='M8 4h1M8 18h1'/%3E%3Cpath stroke='%23c6c6c3' d='M9 4h1M9 18h1'/%3E%3Cpath stroke='%23dcdcd9' d='M8 5h1M8 6h1M8 7h1M8 8h1M8 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c3c3c0' d='M9 5h1M9 6h1M9 7h1M9 8h1M9 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b6c5cd' d='M0 19h1m1 2h1'/%3E%3Cpath stroke='%2370d66f' d='M1 19h1m0 1h1'/%3E%3Cpath stroke='%2364d362' d='M2 19h1'/%3E%3Cpath stroke='%234acb48' d='M3 19h1'/%3E%3Cpath stroke='%2348cb46' d='M4 19h3'/%3E%3Cpath stroke='%23becbd3' d='M0 20h1m0 1h1'/%3E%3Cpath stroke='%23a6d2b1' d='M1 20h1'/%3E%3Cpath stroke='%2367d466' d='M3 20h1'/%3E%3Cpath stroke='%2366d465' d='M4 20h3'/%3E%3Cpath stroke='%2363d362' d='M7 20h1'/%3E%3C/svg%3E");transform: translateY(0)
			}
			
			.is-vertical>input[type=range]: :-webkit-slider-runnable-track{
				border-left: 1px solid #f3f2ea;
				border-right: 0;
				border-bottom: 1px solid #f3f2ea;
				box-shadow: -1px 0 0 #fff,-1px 1px 0 #fff,0 1px 0 #fff,1px 0 0 #9d9c99,1px -1px 0 #9d9c99,0 -1px 0 #9d9c99,1px 1px 0 #fff,-1px -1px #9d9c99
			}
			
			.is-vertical>input[type=range]: :-moz-range-track{
				border-left: 1px solid #f3f2ea;
				border-right: 0;
				border-bottom: 1px solid #f3f2ea;
				box-shadow: -1px 0 0 #fff,-1px 1px 0 #fff,0 1px 0 #fff,1px 0 0 #9d9c99,1px -1px 0 #9d9c99,0 -1px 0 #9d9c99,1px 1px 0 #fff,-1px -1px #9d9c99
			}
			
			fieldset{
				box-shadow: none;
				background: #fff;
				border: 1px solid #d0d0bf;
				border-radius: 4px;
				padding-top: 10px
			}
			
			legend{
				background: transparent;
				color: #0046d5
			}
			
			.field-row{
				display: flex;
				align-items: center
			}
			
			.field-row>*+*{
				margin-left: 6px
			}
			
			[class^=field-row]+[class^=field-row]{
				margin-top: 6px
			}
			
			.field-row-stacked{
				display: flex;
				flex-direction: column
			}
			
			.field-row-stacked *+*{
				margin-top: 6px
			}
			
			menu[role=tablist] button{
				background: linear-gradient(180deg,#fff,#fafaf9 26%,#f0f0ea 95%,#ecebe5);
				margin-left: -1px;
				margin-right: 2px;
				border-radius: 0;
				border-color: #91a7b4;
				border-top-right-radius: 3px;
				border-top-left-radius: 3px;
				padding: 0 12px 3px
			}
			
			menu[role=tablist] button: hover{
				box-shadow: unset;
				border-top: 1px solid #e68b2c;
				box-shadow: inset 0 2px #ffc73c
			}
			
			menu[role=tablist] button[aria-selected=true]{
				border-color: #919b9c;
				margin-right: -1px;
				border-bottom: 1px solid transparent;
				border-top: 1px solid #e68b2c;
				box-shadow: inset 0 2px #ffc73c
			}
			
			menu[role=tablist] button[aria-selected=true]: first-of-type: before{
				content: "";
				display: block;
				position: absolute;
				z-index: -1;
				top: 100%;
				left: -1px;
				height: 2px;
				width: 0;
				border-left: 1px solid #919b9c
			}
			
			[role=tabpanel]{
				box-shadow: inset 1px 1px #fcfcfe,inset -1px -1px #fcfcfe,1px 2px 2px 0 rgba(208,206,191,.75)
			}
			
			ul.tree-view{
				-webkit-font-smoothing: auto;
				border: 1px solid #7f9db9;
				padding: 2px 5px
			}
			
			@keyframes sliding{
				0%{
					transform: translateX(-30px)
				}
			
				to{
					transform: translateX(100%)
				}
			}
			
			progress{
				box-sizing: border-box;
				appearance: none;
				-webkit-appearance: none;
				-moz-appearance: none;
				height: 14px;
				border: 1px solid #686868;
				border-radius: 4px;
				padding: 1px 2px 1px 0;
				overflow: hidden;
				background-color: #fff;
				-webkit-box-shadow: inset 0 0 1px 0 #686868;
				-moz-box-shadow: inset 0 0 1px 0 #686868
			}
			
			progress,progress: not([value]){
				box-shadow: inset 0 0 1px 0 #686868
			}
			
			progress: not([value]){
				-moz-box-shadow: inset 0 0 1px 0 #686868;
				-webkit-box-shadow: inset 0 0 1px 0 #686868;
				height: 14px
			}
			
			progress[value]: :-webkit-progress-bar{
				background-color: transparent
			}
			
			progress[value]: :-webkit-progress-value{
				border-radius: 2px;
				background: repeating-linear-gradient(90deg,#fff 0,#fff 2px,transparent 0,transparent 10px),linear-gradient(180deg,#acedad 0,#7be47d 14%,#4cda50 28%,#2ed330 42%,#42d845 57%,#76e275 71%,#8fe791 85%,#fff)
			}
			
			progress[value]: :-moz-progress-bar{
				border-radius: 2px;
				background: repeating-linear-gradient(90deg,#fff 0,#fff 2px,transparent 0,transparent 10px),linear-gradient(180deg,#acedad 0,#7be47d 14%,#4cda50 28%,#2ed330 42%,#42d845 57%,#76e275 71%,#8fe791 85%,#fff)
			}
			
			progress: not([value]): :-webkit-progress-bar{
				width: 100%;
				background: repeating-linear-gradient(90deg,transparent 0,transparent 8px,#fff 0,#fff 10px,transparent 0,transparent 18px,#fff 0,#fff 20px,transparent 0,transparent 28px,#fff 0,#fff),linear-gradient(180deg,#acedad 0,#7be47d 14%,#4cda50 28%,#2ed330 42%,#42d845 57%,#76e275 71%,#8fe791 85%,#fff);
				animation: sliding 2s linear 0s infinite
			}
			
			progress: not([value]): :-webkit-progress-bar: not([value]){
				animation: sliding 2s linear 0s infinite;
				background: repeating-linear-gradient(90deg,transparent 0,transparent 8px,#fff 0,#fff 10px,transparent 0,transparent 18px,#fff 0,#fff 20px,transparent 0,transparent 28px,#fff 0,#fff),linear-gradient(180deg,#acedad 0,#7be47d 14%,#4cda50 28%,#2ed330 42%,#42d845 57%,#76e275 71%,#8fe791 85%,#fff)
			}
			
			progress: not([value]){
				position: relative
			}
			
			progress: not([value]): before{
				box-sizing: border-box;
				content: "";
				position: absolute;
				top: 0;
				left: 0;
				width: 100%;
				height: 100%;
				background-color: #fff;
				-webkit-box-shadow: inset 0 0 1px 0 #686868;
				-moz-box-shadow: inset 0 0 1px 0 #686868
			}
			
			progress: not([value]): before,progress: not([value]): before: not([value]){
				box-shadow: inset 0 0 1px 0 #686868
			}
			
			progress: not([value]): before: not([value]){
				-moz-box-shadow: inset 0 0 1px 0 #686868;
				-webkit-box-shadow: inset 0 0 1px 0 #686868
			}
			
			progress: not([value]): after{
				box-sizing: border-box;
				content: "";
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1214 feature_id 25 batch_size 2171 divergence str\\(\\'KL\\'\\) detect_batch 1 statistic str\\(\\'stdev\\'\\) significance 0.11482407769933343 subsets 19",
			        1214,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1760 feature_id 25 batch_size 203 divergence str\\(\\'H\\'\\) detect_batch 3 statistic str\\(\\'stdev\\'\\) significance 0.1785987309589982 subsets 40",
			        1760,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 47 feature_id 25 batch_size 3572 divergence str\\(\\'KL\\'\\) detect_batch 1 statistic str\\(\\'stdev\\'\\) significance 0.39558117565885187 subsets 62",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4831 feature_id 25 batch_size 1527 divergence str\\(\\'H\\'\\) detect_batch 2 statistic str\\(\\'tstat\\'\\) significance 0.7379825099147856 subsets 4",
			        4831,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4915 feature_id 25 batch_size 3709 divergence str\\(\\'KL\\'\\) detect_batch 2 statistic str\\(\\'stdev\\'\\) significance 0.13601441079750656 subsets 45",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1698 feature_id 25 batch_size 4877 divergence str\\(\\'KL\\'\\) detect_batch 1 statistic str\\(\\'tstat\\'\\) significance 0.6955278791561723 subsets 13",
			        1698,
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			        "str\\(\\'KL\\'\\)",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 285 feature_id 25 batch_size 1350 divergence str\\(\\'H\\'\\) detect_batch 3 statistic str\\(\\'tstat\\'\\) significance 0.9780266307331622 subsets 90",
			        285,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3201 feature_id 25 batch_size 28 divergence str\\(\\'H\\'\\) detect_batch 2 statistic str\\(\\'stdev\\'\\) significance 0.41465304464846847 subsets 54",
			        3201,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1 feature_id 25 batch_size 1 divergence str\\(\\'KL\\'\\) detect_batch 1 statistic str\\(\\'tstat\\'\\) significance 0.999 subsets 1",
			        1,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 22 feature_id 25 batch_size 1008 divergence str\\(\\'KL\\'\\) detect_batch 1 statistic str\\(\\'stdev\\'\\) significance 0.001 subsets 44",
			        22,
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			        "str\\(\\'KL\\'\\)",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 334 feature_id 25 batch_size 598 divergence str\\(\\'H\\'\\) detect_batch 3 statistic str\\(\\'stdev\\'\\) significance 0.5582253628646341 subsets 100",
			        334,
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			        "str\\(\\'H\\'\\)",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 497 feature_id 25 batch_size 3889 divergence str\\(\\'KL\\'\\) detect_batch 2 statistic str\\(\\'stdev\\'\\) significance 0.31896981171251004 subsets 1",
			        497,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4632 feature_id 25 batch_size 274 divergence str\\(\\'KL\\'\\) detect_batch 1 statistic str\\(\\'tstat\\'\\) significance 0.999 subsets 22",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 996 feature_id 25 batch_size 3623 divergence str\\(\\'H\\'\\) detect_batch 3 statistic str\\(\\'stdev\\'\\) significance 0.4445277161817827 subsets 1",
			        996,
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			    [
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1136 feature_id 25 batch_size 1 divergence str\\(\\'H\\'\\) detect_batch 3 statistic str\\(\\'stdev\\'\\) significance 0.9496380930187955 subsets 51",
			        1136,
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			        "str\\(\\'H\\'\\)",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4798 feature_id 25 batch_size 4056 divergence str\\(\\'H\\'\\) detect_batch 2 statistic str\\(\\'stdev\\'\\) significance 0.4466818383516618 subsets 29",
			        4798,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1006 feature_id 25 batch_size 4486 divergence str\\(\\'H\\'\\) detect_batch 3 statistic str\\(\\'tstat\\'\\) significance 0.001 subsets 1",
			        1006,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1387 feature_id 25 batch_size 4303 divergence str\\(\\'KL\\'\\) detect_batch 2 statistic str\\(\\'stdev\\'\\) significance 0.24274823459053685 subsets 45",
			        1387,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2801 feature_id 25 batch_size 4217 divergence str\\(\\'H\\'\\) detect_batch 3 statistic str\\(\\'stdev\\'\\) significance 0.999 subsets 25",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4709 feature_id 25 batch_size 1314 divergence str\\(\\'H\\'\\) detect_batch 1 statistic str\\(\\'stdev\\'\\) significance 0.18629987883003887 subsets 45",
			        4709,
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			    [
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 712 feature_id 25 batch_size 4617 divergence str\\(\\'H\\'\\) detect_batch 2 statistic str\\(\\'tstat\\'\\) significance 0.999 subsets 47",
			        712,
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			        "str\\(\\'H\\'\\)",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3137 feature_id 25 batch_size 3628 divergence str\\(\\'H\\'\\) detect_batch 2 statistic str\\(\\'tstat\\'\\) significance 0.5915310427650775 subsets 65",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2853 feature_id 25 batch_size 4250 divergence str\\(\\'KL\\'\\) detect_batch 3 statistic str\\(\\'stdev\\'\\) significance 0.999 subsets 52",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 132 feature_id 25 batch_size 346 divergence str\\(\\'H\\'\\) detect_batch 3 statistic str\\(\\'tstat\\'\\) significance 0.001 subsets 77",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 886 feature_id 25 batch_size 258 divergence str\\(\\'H\\'\\) detect_batch 2 statistic str\\(\\'tstat\\'\\) significance 0.999 subsets 57",
			        886,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3804 feature_id 25 batch_size 643 divergence str\\(\\'H\\'\\) detect_batch 1 statistic str\\(\\'tstat\\'\\) significance 0.999 subsets 74",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 851 feature_id 25 batch_size 3891 divergence str\\(\\'KL\\'\\) detect_batch 3 statistic str\\(\\'stdev\\'\\) significance 0.001 subsets 50",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1356 feature_id 25 batch_size 1 divergence str\\(\\'H\\'\\) detect_batch 3 statistic str\\(\\'stdev\\'\\) significance 0.999 subsets 1",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 422 feature_id 25 batch_size 2570 divergence str\\(\\'KL\\'\\) detect_batch 1 statistic str\\(\\'stdev\\'\\) significance 0.16469764433271478 subsets 31",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 434 feature_id 25 batch_size 2527 divergence str\\(\\'KL\\'\\) detect_batch 1 statistic str\\(\\'stdev\\'\\) significance 0.11318177746568743 subsets 4",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 60 feature_id 25 batch_size 4387 divergence str\\(\\'KL\\'\\) detect_batch 2 statistic str\\(\\'stdev\\'\\) significance 0.6117906454309956 subsets 22",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3259 feature_id 25 batch_size 4569 divergence str\\(\\'H\\'\\) detect_batch 2 statistic str\\(\\'stdev\\'\\) significance 0.7351954554224038 subsets 100",
			        3259,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2126 feature_id 25 batch_size 3940 divergence str\\(\\'H\\'\\) detect_batch 3 statistic str\\(\\'stdev\\'\\) significance 0.001 subsets 44",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1982 feature_id 25 batch_size 4691 divergence str\\(\\'KL\\'\\) detect_batch 2 statistic str\\(\\'stdev\\'\\) significance 0.999 subsets 1",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 961 feature_id 25 batch_size 4059 divergence str\\(\\'KL\\'\\) detect_batch 3 statistic str\\(\\'stdev\\'\\) significance 0.6842117893416 subsets 1",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4060 feature_id 25 batch_size 3251 divergence str\\(\\'H\\'\\) detect_batch 2 statistic str\\(\\'stdev\\'\\) significance 0.3303776619348198 subsets 1",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4 feature_id 25 batch_size 4587 divergence str\\(\\'H\\'\\) detect_batch 3 statistic str\\(\\'stdev\\'\\) significance 0.001 subsets 43",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2049 feature_id 25 batch_size 4242 divergence str\\(\\'H\\'\\) detect_batch 2 statistic str\\(\\'tstat\\'\\) significance 0.6538079367920501 subsets 59",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1749 feature_id 25 batch_size 3540 divergence str\\(\\'KL\\'\\) detect_batch 3 statistic str\\(\\'tstat\\'\\) significance 0.42746420777148103 subsets 1",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3788 feature_id 25 batch_size 210 divergence str\\(\\'H\\'\\) detect_batch 1 statistic str\\(\\'stdev\\'\\) significance 0.999 subsets 29",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2572 feature_id 25 batch_size 2324 divergence str\\(\\'KL\\'\\) detect_batch 2 statistic str\\(\\'tstat\\'\\) significance 0.999 subsets 100",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3596 feature_id 25 batch_size 3085 divergence str\\(\\'KL\\'\\) detect_batch 2 statistic str\\(\\'tstat\\'\\) significance 0.999 subsets 100",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 5000 feature_id 25 batch_size 1849 divergence str\\(\\'KL\\'\\) detect_batch 1 statistic str\\(\\'stdev\\'\\) significance 0.001 subsets 1",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2761 feature_id 25 batch_size 227 divergence str\\(\\'KL\\'\\) detect_batch 3 statistic str\\(\\'tstat\\'\\) significance 0.001 subsets 90",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3474 feature_id 25 batch_size 3935 divergence str\\(\\'H\\'\\) detect_batch 2 statistic str\\(\\'stdev\\'\\) significance 0.999 subsets 100",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3262 feature_id 25 batch_size 3894 divergence str\\(\\'H\\'\\) detect_batch 3 statistic str\\(\\'stdev\\'\\) significance 0.001 subsets 1",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4945 feature_id 25 batch_size 2848 divergence str\\(\\'H\\'\\) detect_batch 2 statistic str\\(\\'tstat\\'\\) significance 0.4879834870364251 subsets 1",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4861 feature_id 25 batch_size 688 divergence str\\(\\'KL\\'\\) detect_batch 3 statistic str\\(\\'stdev\\'\\) significance 0.001 subsets 70",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2453 feature_id 25 batch_size 3400 divergence str\\(\\'KL\\'\\) detect_batch 2 statistic str\\(\\'tstat\\'\\) significance 0.506992999583983 subsets 1",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4432 feature_id 25 batch_size 4976 divergence str\\(\\'H\\'\\) detect_batch 2 statistic str\\(\\'stdev\\'\\) significance 0.2693389805293089 subsets 26",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2513 feature_id 25 batch_size 945 divergence str\\(\\'H\\'\\) detect_batch 1 statistic str\\(\\'tstat\\'\\) significance 0.999 subsets 39",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 923 feature_id 25 batch_size 4834 divergence str\\(\\'KL\\'\\) detect_batch 2 statistic str\\(\\'stdev\\'\\) significance 0.537436401671925 subsets 82",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2350 feature_id 25 batch_size 4546 divergence str\\(\\'H\\'\\) detect_batch 2 statistic str\\(\\'tstat\\'\\) significance 0.999 subsets 1",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1022 feature_id 25 batch_size 1 divergence str\\(\\'KL\\'\\) detect_batch 1 statistic str\\(\\'stdev\\'\\) significance 0.7136284450024577 subsets 1",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 2426 feature_id 25 batch_size 394 divergence str\\(\\'KL\\'\\) detect_batch 3 statistic str\\(\\'tstat\\'\\) significance 0.6641584179314716 subsets 77",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 1960 feature_id 25 batch_size 3615 divergence str\\(\\'H\\'\\) detect_batch 2 statistic str\\(\\'stdev\\'\\) significance 0.001 subsets 100",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 413 feature_id 25 batch_size 4170 divergence str\\(\\'KL\\'\\) detect_batch 2 statistic str\\(\\'stdev\\'\\) significance 0.001 subsets 28",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 3955 feature_id 25 batch_size 237 divergence str\\(\\'KL\\'\\) detect_batch 3 statistic str\\(\\'stdev\\'\\) significance 0.43835560349379615 subsets 45",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python main.py 1 1 0 RialtoBridgeTimelapse 2000 HoeffdingTreeClassifier CDBD recent_samples_size 4684 feature_id 25 batch_size 902 divergence str\\(\\'H\\'\\) detect_batch 3 statistic str\\(\\'stdev\\'\\) significance 0.18845600499395226 subsets 88",
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			    ],
			    [
			        1744999658,
			        708.50390625,
			        32.5
			    ],
			    [
			        1744999659,
			        708.50390625,
			        25.7
			    ],
			    [
			        1744999659,
			        708.50390625,
			        26.1
			    ],
			    [
			        1745007163,
			        956.96484375,
			        8.9
			    ],
			    [
			        1745007163,
			        956.96484375,
			        7.3
			    ],
			    [
			        1745007164,
			        956.96484375,
			        7.2
			    ],
			    [
			        1745007164,
			        956.96484375,
			        3.1
			    ],
			    [
			        1745015042,
			        968.09765625,
			        7.1
			    ],
			    [
			        1745015042,
			        968.09765625,
			        7.2
			    ],
			    [
			        1745015042,
			        968.09765625,
			        7.1
			    ],
			    [
			        1745015042,
			        968.09765625,
			        7
			    ],
			    [
			        1745024256,
			        1032.59765625,
			        7.3
			    ],
			    [
			        1745024256,
			        1032.59765625,
			        7
			    ],
			    [
			        1745024256,
			        1032.59765625,
			        7.2
			    ],
			    [
			        1745024256,
			        1032.59765625,
			        7.5
			    ],
			    [
			        1745033287,
			        1031.38671875,
			        7.3
			    ],
			    [
			        1745033287,
			        1031.38671875,
			        6.2
			    ],
			    [
			        1745033287,
			        1031.38671875,
			        6.1
			    ],
			    [
			        1745033287,
			        1031.38671875,
			        4.9
			    ],
			    [
			        1745043126,
			        1069.73046875,
			        7.4
			    ],
			    [
			        1745043126,
			        1069.73046875,
			        6.5
			    ],
			    [
			        1745043126,
			        1069.73046875,
			        6.9
			    ],
			    [
			        1745043126,
			        1069.73046875,
			        3.2
			    ],
			    [
			        1745054372,
			        1045.80859375,
			        7.5
			    ],
			    [
			        1745054372,
			        1045.80859375,
			        7.2
			    ],
			    [
			        1745054372,
			        1045.80859375,
			        7.1
			    ],
			    [
			        1745054372,
			        1045.80859375,
			        3.1
			    ],
			    [
			        1745066122,
			        1057.9375,
			        7.4
			    ],
			    [
			        1745066122,
			        1057.9375,
			        6.4
			    ],
			    [
			        1745066122,
			        1057.9375,
			        6.5
			    ],
			    [
			        1745066122,
			        1057.9375,
			        6.3
			    ],
			    [
			        1745080135,
			        1092.99609375,
			        7.5
			    ],
			    [
			        1745080135,
			        1092.99609375,
			        7.3
			    ],
			    [
			        1745080135,
			        1092.99609375,
			        7.3
			    ],
			    [
			        1745080135,
			        1092.99609375,
			        5.9
			    ]
			];
			var tab_main_worker_cpu_ram_headers_json = [
			    "timestamp",
			    "ram_usage_mb",
			    "cpu_usage_percent"
			];
			
			"use strict";
			
			function add_default_layout_data (layout, no_height = 0) {
				layout["width"] = get_graph_width();
				if (!no_height) {
					layout["height"] = get_graph_height();
				}
				layout["paper_bgcolor"] = 'rgba(0,0,0,0)';
				layout["plot_bgcolor"] = 'rgba(0,0,0,0)';
			
				return layout;
			}
			
			function get_marker_size() {
				return 12;
			}
			
			function get_text_color() {
				return theme == "dark" ? "white" : "black";
			}
			
			function get_font_size() {
				return 14;
			}
			
			function get_graph_height() {
				return 800;
			}
			
			function get_font_data() {
				return {
					size: get_font_size(),
					color: get_text_color()
				}
			}
			
			function get_axis_title_data(name, axis_type = "") {
				if(axis_type) {
					return {
						text: name,
						type: axis_type,
						font: get_font_data()
					};
				}
			
				return {
					text: name,
					font: get_font_data()
				};
			}
			
			function get_graph_width() {
				var width = document.body.clientWidth || window.innerWidth || document.documentElement.clientWidth;
				return Math.max(800, Math.floor(width * 0.9));
			}
			
			function createTable(data, headers, table_name) {
				if (!$("#" + table_name).length) {
					console.error("#" + table_name + " not found");
					return;
				}
			
				new gridjs.Grid({
					columns: headers,
					data: data,
					search: true,
					sort: true,
					ellipsis: false
				}).render(document.getElementById(table_name));
			
				if (typeof apply_theme_based_on_system_preferences === 'function') {
					apply_theme_based_on_system_preferences();
				}
			
				colorize_table_entries();
			
				add_colorize_to_gridjs_table();
			}
			
			function download_as_file(id, filename) {
				var text = $("#" + id).text();
				var blob = new Blob([text], {
					type: "text/plain"
				});
				var link = document.createElement("a");
				link.href = URL.createObjectURL(blob);
				link.download = filename;
				document.body.appendChild(link);
				link.click();
				document.body.removeChild(link);
			}
			
			function copy_to_clipboard_from_id (id) {
				var text = $("#" + id).text();
			
				copy_to_clipboard(text);
			}
			
			function copy_to_clipboard(text) {
				if (!navigator.clipboard) {
					let textarea = document.createElement("textarea");
					textarea.value = text;
					document.body.appendChild(textarea);
					textarea.select();
					try {
						document.execCommand("copy");
					} catch (err) {
						console.error("Copy failed:", err);
					}
					document.body.removeChild(textarea);
					return;
				}
			
				navigator.clipboard.writeText(text).then(() => {
					console.log("Text copied to clipboard");
				}).catch(err => {
					console.error("Failed to copy text:", err);
				});
			}
			
			function filterNonEmptyRows(data) {
				var new_data = [];
				for (var row_idx = 0; row_idx <  data.length; row_idx++) {
					var line = data[row_idx];
			
					var line_has_empty_data = false;
			
					for (var col_idx = 0; col_idx < line.length; col_idx++) {
						var col_header_name = tab_results_headers_json[col_idx];
						var single_data_point = line[col_idx];
			
						if(single_data_point === "" && !special_col_names.includes(col_header_name)) {
							line_has_empty_data = true;
							continue;
						}
					}
			
					if(!line_has_empty_data) {
						new_data.push(line);
					}
				}
			
				return new_data;
			}
			
			function make_text_in_parallel_plot_nicer() {
				$(".parcoords g > g > text").each(function() {
					if (theme == "dark") {
						$(this)
							.css("text-shadow", "unset")
							.css("font-size", "0.9em")
							.css("fill", "white")
							.css("stroke", "black")
							.css("stroke-width", "2px")
							.css("paint-order", "stroke fill");
					} else {
						$(this)
							.css("text-shadow", "unset")
							.css("font-size", "0.9em")
							.css("fill", "black")
							.css("stroke", "unset")
							.css("stroke-width", "unset")
							.css("paint-order", "stroke fill");
					}
				});
			}
			
			function createParallelPlot(dataArray, headers, resultNames, ignoreColumns = []) {
				if ($("#parallel-plot").data("loaded") == "true") {
					return;
				}
			
				dataArray = filterNonEmptyRows(dataArray);
				const ignoreSet = new Set(ignoreColumns);
				const numericalCols = [];
				const categoricalCols = [];
				const categoryMappings = {};
			
				headers.forEach((header, colIndex) => {
					if (ignoreSet.has(header)) return;
			
					const values = dataArray.map(row => row[colIndex]);
					if (values.every(val => !isNaN(parseFloat(val)))) {
						numericalCols.push({ name: header, index: colIndex });
					} else {
						categoricalCols.push({ name: header, index: colIndex });
						const uniqueValues = [...new Set(values)];
						categoryMappings[header] = Object.fromEntries(uniqueValues.map((val, i) => [val, i]));
					}
				});
			
				const dimensions = [];
			
				numericalCols.forEach(col => {
					dimensions.push({
						label: col.name,
						values: dataArray.map(row => parseFloat(row[col.index])),
						range: [
							Math.min(...dataArray.map(row => parseFloat(row[col.index]))),
							Math.max(...dataArray.map(row => parseFloat(row[col.index])))
						]
					});
				});
			
				categoricalCols.forEach(col => {
					dimensions.push({
						label: col.name,
						values: dataArray.map(row => categoryMappings[col.name][row[col.index]]),
						tickvals: Object.values(categoryMappings[col.name]),
						ticktext: Object.keys(categoryMappings[col.name])
					});
				});
			
				let colorScale = null;
				let colorValues = null;
			
				if (resultNames.length > 1) {
					let selectBox = '<select id="result-select" style="margin-bottom: 10px;">';
					selectBox += '<option value="none">No color</option>';
					var k = 0;
					resultNames.forEach(resultName => {
						var minMax = result_min_max[k];
						if(minMax === undefined) {
							minMax = "min [automatically chosen]"
						}
						selectBox += `<option value="${resultName}">${resultName} (${minMax})</option>`;
						k = k + 1;
					});
					selectBox += '</select>';
					$("#parallel-plot").before(selectBox);
			
					$("#result-select").change(function() {
						const selectedResult = $(this).val();
						if (selectedResult === "none") {
							colorValues = null;
							colorScale = null;
						} else {
							const resultCol = numericalCols.find(col => col.name.toLowerCase() === selectedResult.toLowerCase());
							colorValues = dataArray.map(row => parseFloat(row[resultCol.index]));
			
							let minResult = Math.min(...colorValues);
							let maxResult = Math.max(...colorValues);
			
							var _result_min_max_idx = result_names.indexOf(selectedResult);
			
							let invertColor = false;
							if (result_min_max.length > _result_min_max_idx) {
								invertColor = result_min_max[_result_min_max_idx] === "max";
							}
			
							colorScale = invertColor
								? [[0, 'red'], [1, 'green']]
								: [[0, 'green'], [1, 'red']];
						}
						updatePlot();
					});
				} else {
					let invertColor = false;
					if (Object.keys(result_min_max).length == 1) {
						invertColor = result_min_max[0] === "max";
					}
			
					colorScale = invertColor
						? [[0, 'red'], [1, 'green']]
						: [[0, 'green'], [1, 'red']];
			
					const resultCol = numericalCols.find(col => col.name.toLowerCase() === resultNames[0].toLowerCase());
					colorValues = dataArray.map(row => parseFloat(row[resultCol.index]));
				}
			
				function updatePlot() {
					const trace = {
						type: 'parcoords',
						dimensions: dimensions,
						line: colorValues ? { color: colorValues, colorscale: colorScale } : {},
						unselected: {
							line: {
								color: get_text_color(),
								opacity: 0
							}
						},
					};
			
					dimensions.forEach(dim => {
						if (!dim.line) {
							dim.line = {};
						}
						if (!dim.line.color) {
							dim.line.color = 'rgba(169,169,169, 0.01)';
						}
					});
			
					Plotly.newPlot('parallel-plot', [trace], add_default_layout_data({}));
			
					make_text_in_parallel_plot_nicer();
				}
			
				updatePlot();
			
				$("#parallel-plot").data("loaded", "true");
			
				make_text_in_parallel_plot_nicer();
			}
			
			function plotWorkerUsage() {
				if($("#workerUsagePlot").data("loaded") == "true") {
					return;
				}
				var data = tab_worker_usage_csv_json;
				if (!Array.isArray(data) || data.length === 0) {
					console.error("Invalid or empty data provided.");
					return;
				}
			
				let timestamps = [];
				let desiredWorkers = [];
				let realWorkers = [];
			
				for (let i = 0; i < data.length; i++) {
					let entry = data[i];
			
					if (!Array.isArray(entry) || entry.length < 3) {
						console.warn("Skipping invalid entry:", entry);
						continue;
					}
			
					let unixTime = parseFloat(entry[0]);
					let desired = parseInt(entry[1], 10);
					let real = parseInt(entry[2], 10);
			
					if (isNaN(unixTime) || isNaN(desired) || isNaN(real)) {
						console.warn("Skipping invalid numerical values:", entry);
						continue;
					}
			
					timestamps.push(new Date(unixTime * 1000).toISOString());
					desiredWorkers.push(desired);
					realWorkers.push(real);
				}
			
				let trace1 = {
					x: timestamps,
					y: desiredWorkers,
					mode: 'lines+markers',
					name: 'Desired Workers',
					line: {
						color: 'blue'
					}
				};
			
				let trace2 = {
					x: timestamps,
					y: realWorkers,
					mode: 'lines+markers',
					name: 'Real Workers',
					line: {
						color: 'red'
					}
				};
			
				let layout = {
					title: "Worker Usage Over Time",
					xaxis: {
						title: get_axis_title_data("Time", "date")
					},
					yaxis: {
						title: get_axis_title_data("Number of Workers")
					},
					legend: {
						x: 0,
						y: 1
					}
				};
			
				Plotly.newPlot('workerUsagePlot', [trace1, trace2], add_default_layout_data(layout));
				$("#workerUsagePlot").data("loaded", "true");
			}
			
			function plotCPUAndRAMUsage() {
				if($("#mainWorkerCPURAM").data("loaded") == "true") {
					return;
				}
				var timestamps = tab_main_worker_cpu_ram_csv_json.map(row => new Date(row[0] * 1000));
				var ramUsage = tab_main_worker_cpu_ram_csv_json.map(row => row[1]);
				var cpuUsage = tab_main_worker_cpu_ram_csv_json.map(row => row[2]);
			
				var trace1 = {
					x: timestamps,
					y: cpuUsage,
					mode: 'lines+markers',
					marker: {
						size: get_marker_size(),
					},
					name: 'CPU Usage (%)',
					type: 'scatter',
					yaxis: 'y1'
				};
			
				var trace2 = {
					x: timestamps,
					y: ramUsage,
					mode: 'lines+markers',
					marker: {
						size: get_marker_size(),
					},
					name: 'RAM Usage (MB)',
					type: 'scatter',
					yaxis: 'y2'
				};
			
				var layout = {
					title: 'CPU and RAM Usage Over Time',
					xaxis: {
						title: get_axis_title_data("Timestamp", "date"),
						tickmode: 'array',
						tickvals: timestamps.filter((_, index) => index % Math.max(Math.floor(timestamps.length / 10), 1) === 0),
						ticktext: timestamps.filter((_, index) => index % Math.max(Math.floor(timestamps.length / 10), 1) === 0).map(t => t.toLocaleString()),
						tickangle: -45
					},
					yaxis: {
						title: get_axis_title_data("CPU Usage (%)"),
						rangemode: 'tozero'
					},
					yaxis2: {
						title: get_axis_title_data("RAM Usage (MB)"),
						overlaying: 'y',
						side: 'right',
						rangemode: 'tozero'
					},
					legend: {
						x: 0.1,
						y: 0.9
					}
				};
			
				var data = [trace1, trace2];
				Plotly.newPlot('mainWorkerCPURAM', data, add_default_layout_data(layout));
				$("#mainWorkerCPURAM").data("loaded", "true");
			}
			
			function plotScatter2d() {
				if ($("#plotScatter2d").data("loaded") == "true") {
					return;
				}
			
				var plotDiv = document.getElementById("plotScatter2d");
			
				var minInput = document.getElementById("minValue");
				var maxInput = document.getElementById("maxValue");
			
				if (!minInput || !maxInput) {
					minInput = document.createElement("input");
					minInput.id = "minValue";
					minInput.type = "number";
					minInput.placeholder = "Min Value";
					minInput.step = "any";
			
					maxInput = document.createElement("input");
					maxInput.id = "maxValue";
					maxInput.type = "number";
					maxInput.placeholder = "Max Value";
					maxInput.step = "any";
			
					var inputContainer = document.createElement("div");
					inputContainer.style.marginBottom = "10px";
					inputContainer.appendChild(minInput);
					inputContainer.appendChild(maxInput);
					plotDiv.appendChild(inputContainer);
				}
			
				var resultSelect = document.getElementById("resultSelect");
				if (result_names.length > 1 && !resultSelect) {
					resultSelect = document.createElement("select");
					resultSelect.id = "resultSelect";
					resultSelect.style.marginBottom = "10px";
			
					var sortedResults = [...result_names].sort();
					sortedResults.forEach(result => {
						var option = document.createElement("option");
						option.value = result;
						option.textContent = result;
						resultSelect.appendChild(option);
					});
			
					var selectContainer = document.createElement("div");
					selectContainer.style.marginBottom = "10px";
					selectContainer.appendChild(resultSelect);
					plotDiv.appendChild(selectContainer);
				}
			
				minInput.addEventListener("input", updatePlots);
				maxInput.addEventListener("input", updatePlots);
				if (resultSelect) {
					resultSelect.addEventListener("change", updatePlots);
				}
			
				updatePlots();
			
				async function updatePlots() {
					var minValue = parseFloat(minInput.value);
					var maxValue = parseFloat(maxInput.value);
					if (isNaN(minValue)) minValue = -Infinity;
					if (isNaN(maxValue)) maxValue = Infinity;
			
					while (plotDiv.children.length > 2) {
						plotDiv.removeChild(plotDiv.lastChild);
					}
			
					var selectedResult = resultSelect ? resultSelect.value : result_names[0];
			
					var resultIndex = tab_results_headers_json.findIndex(header =>
						header.toLowerCase() === selectedResult.toLowerCase()
					);
					var resultValues = tab_results_csv_json.map(row => row[resultIndex]);
			
					var minResult = Math.min(...resultValues.filter(value => value !== null && value !== ""));
					var maxResult = Math.max(...resultValues.filter(value => value !== null && value !== ""));
			
					if (minValue !== -Infinity) minResult = Math.max(minResult, minValue);
					if (maxValue !== Infinity) maxResult = Math.min(maxResult, maxValue);
			
					var invertColor = result_min_max[result_names.indexOf(selectedResult)] === "max";
			
					var numericColumns = tab_results_headers_json.filter(col =>
						!special_col_names.includes(col) && !result_names.includes(col) &&
						tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
					);
			
					if (numericColumns.length < 2) {
						console.error("Not enough columns for Scatter-Plots");
						return;
					}
			
					for (let i = 0; i < numericColumns.length; i++) {
						for (let j = i + 1; j < numericColumns.length; j++) {
							let xCol = numericColumns[i];
							let yCol = numericColumns[j];
			
							let xIndex = tab_results_headers_json.indexOf(xCol);
							let yIndex = tab_results_headers_json.indexOf(yCol);
			
							let data = tab_results_csv_json.map(row => ({
								x: parseFloat(row[xIndex]),
								y: parseFloat(row[yIndex]),
								result: row[resultIndex] !== "" ? parseFloat(row[resultIndex]) : null
							}));
			
							data = data.filter(d => d.result >= minResult && d.result <= maxResult);
			
							let layoutTitle = `${xCol} (x) vs ${yCol} (y), result: ${selectedResult}`;
							let layout = {
								title: layoutTitle,
								xaxis: {
									title: get_axis_title_data(xCol)
								},
								yaxis: {
									title: get_axis_title_data(yCol)
								},
								showlegend: false
							};
							let subDiv = document.createElement("div");
			
							let spinnerContainer = document.createElement("div");
							spinnerContainer.style.display = "flex";
							spinnerContainer.style.alignItems = "center";
							spinnerContainer.style.justifyContent = "center";
							spinnerContainer.style.width = layout.width + "px";
							spinnerContainer.style.height = layout.height + "px";
							spinnerContainer.style.position = "relative";
			
							let spinner = document.createElement("div");
							spinner.className = "spinner";
							spinner.style.width = "40px";
							spinner.style.height = "40px";
			
							let loadingText = document.createElement("span");
							loadingText.innerText = `Loading ${layoutTitle}`;
							loadingText.style.marginLeft = "10px";
			
							spinnerContainer.appendChild(spinner);
							spinnerContainer.appendChild(loadingText);
			
							plotDiv.appendChild(spinnerContainer);
			
							await new Promise(resolve => setTimeout(resolve, 50));
			
							let colors = data.map(d => {
								if (d.result === null) {
									return 'rgb(0, 0, 0)';
								} else {
									let norm = (d.result - minResult) / (maxResult - minResult);
									if (invertColor) {
										norm = 1 - norm;
									}
									return `rgb(${Math.round(255 * norm)}, ${Math.round(255 * (1 - norm))}, 0)`;
								}
							});
			
							let trace = {
								x: data.map(d => d.x),
								y: data.map(d => d.y),
								mode: 'markers',
								marker: {
									size: get_marker_size(),
									color: data.map(d => d.result !== null ? d.result : null),
									colorscale: invertColor ? [
										[0, 'red'],
										[1, 'green']
									] : [
										[0, 'green'],
										[1, 'red']
									],
									colorbar: {
										title: 'Result',
										tickvals: [minResult, maxResult],
										ticktext: [`${minResult}`, `${maxResult}`]
									},
									symbol: data.map(d => d.result === null ? 'x' : 'circle'),
								},
								text: data.map(d => d.result !== null ? `Result: ${d.result}` : 'No result'),
								type: 'scatter',
								showlegend: false
							};
			
							try {
								plotDiv.replaceChild(subDiv, spinnerContainer);
							} catch (err) {
								//
							}
							Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
						}
					}
				}
			
				$("#plotScatter2d").data("loaded", "true");
			}
			
			function plotScatter3d() {
				if ($("#plotScatter3d").data("loaded") == "true") {
					return;
				}
			
				var plotDiv = document.getElementById("plotScatter3d");
				if (!plotDiv) {
					console.error("Div element with id 'plotScatter3d' not found");
					return;
				}
				plotDiv.innerHTML = "";
			
				var minInput3d = document.getElementById("minValue3d");
				var maxInput3d = document.getElementById("maxValue3d");
			
				if (!minInput3d || !maxInput3d) {
					minInput3d = document.createElement("input");
					minInput3d.id = "minValue3d";
					minInput3d.type = "number";
					minInput3d.placeholder = "Min Value";
					minInput3d.step = "any";
			
					maxInput3d = document.createElement("input");
					maxInput3d.id = "maxValue3d";
					maxInput3d.type = "number";
					maxInput3d.placeholder = "Max Value";
					maxInput3d.step = "any";
			
					var inputContainer3d = document.createElement("div");
					inputContainer3d.style.marginBottom = "10px";
					inputContainer3d.appendChild(minInput3d);
					inputContainer3d.appendChild(maxInput3d);
					plotDiv.appendChild(inputContainer3d);
				}
			
				var select3d = document.getElementById("select3dScatter");
				if (result_names.length > 1 && !select3d) {
					if (!select3d) {
						select3d = document.createElement("select");
						select3d.id = "select3dScatter";
						select3d.style.marginBottom = "10px";
						select3d.innerHTML = result_names.map(name => `<option value="${name}">${name}</option>`).join("");
			
						select3d.addEventListener("change", updatePlots3d);
			
						plotDiv.appendChild(select3d);
					}
				}
			
				minInput3d.addEventListener("input", updatePlots3d);
				maxInput3d.addEventListener("input", updatePlots3d);
			
				updatePlots3d();
			
				async function updatePlots3d() {
					var selectedResult = select3d ? select3d.value : result_names[0];
					var minValue3d = parseFloat(minInput3d.value);
					var maxValue3d = parseFloat(maxInput3d.value);
			
					if (isNaN(minValue3d)) minValue3d = -Infinity;
					if (isNaN(maxValue3d)) maxValue3d = Infinity;
			
					while (plotDiv.children.length > 2) {
						plotDiv.removeChild(plotDiv.lastChild);
					}
			
					var resultIndex = tab_results_headers_json.findIndex(header =>
						header.toLowerCase() === selectedResult.toLowerCase()
					);
					var resultValues = tab_results_csv_json.map(row => row[resultIndex]);
			
					var minResult = Math.min(...resultValues.filter(value => value !== null && value !== ""));
					var maxResult = Math.max(...resultValues.filter(value => value !== null && value !== ""));
			
					if (minValue3d !== -Infinity) minResult = Math.max(minResult, minValue3d);
					if (maxValue3d !== Infinity) maxResult = Math.min(maxResult, maxValue3d);
			
					var invertColor = result_min_max[result_names.indexOf(selectedResult)] === "max";
			
					var numericColumns = tab_results_headers_json.filter(col =>
						!special_col_names.includes(col) && !result_names.includes(col) &&
						tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
					);
			
					if (numericColumns.length < 3) {
						console.error("Not enough columns for 3D scatter plots");
						return;
					}
			
					for (let i = 0; i < numericColumns.length; i++) {
						for (let j = i + 1; j < numericColumns.length; j++) {
							for (let k = j + 1; k < numericColumns.length; k++) {
								let xCol = numericColumns[i];
								let yCol = numericColumns[j];
								let zCol = numericColumns[k];
			
								let xIndex = tab_results_headers_json.indexOf(xCol);
								let yIndex = tab_results_headers_json.indexOf(yCol);
								let zIndex = tab_results_headers_json.indexOf(zCol);
			
								let data = tab_results_csv_json.map(row => ({
									x: parseFloat(row[xIndex]),
									y: parseFloat(row[yIndex]),
									z: parseFloat(row[zIndex]),
									result: row[resultIndex] !== "" ? parseFloat(row[resultIndex]) : null
								}));
			
								data = data.filter(d => d.result >= minResult && d.result <= maxResult);
			
								let layoutTitle = `${xCol} (x) vs ${yCol} (y) vs ${zCol} (z), result: ${selectedResult}`;
								let layout = {
									title: layoutTitle,
									scene: {
										xaxis: {
											title: get_axis_title_data(xCol)
										},
										yaxis: {
											title: get_axis_title_data(yCol)
										},
										zaxis: {
											title: get_axis_title_data(zCol)
										}
									},
									showlegend: false
								};
			
								let spinnerContainer = document.createElement("div");
								spinnerContainer.style.display = "flex";
								spinnerContainer.style.alignItems = "center";
								spinnerContainer.style.justifyContent = "center";
								spinnerContainer.style.width = layout.width + "px";
								spinnerContainer.style.height = layout.height + "px";
								spinnerContainer.style.position = "relative";
			
								let spinner = document.createElement("div");
								spinner.className = "spinner";
								spinner.style.width = "40px";
								spinner.style.height = "40px";
			
								let loadingText = document.createElement("span");
								loadingText.innerText = `Loading ${layoutTitle}`;
								loadingText.style.marginLeft = "10px";
			
								spinnerContainer.appendChild(spinner);
								spinnerContainer.appendChild(loadingText);
			
								plotDiv.appendChild(spinnerContainer);
			
								await new Promise(resolve => setTimeout(resolve, 50));
			
								let colors = data.map(d => {
									if (d.result === null) {
										return 'rgb(0, 0, 0)';
									} else {
										let norm = (d.result - minResult) / (maxResult - minResult);
										if (invertColor) {
											norm = 1 - norm;
										}
										return `rgb(${Math.round(255 * norm)}, ${Math.round(255 * (1 - norm))}, 0)`;
									}
								});
			
								let trace = {
									x: data.map(d => d.x),
									y: data.map(d => d.y),
									z: data.map(d => d.z),
									mode: 'markers',
									marker: {
										size: get_marker_size(),
										color: data.map(d => d.result !== null ? d.result : null),
										colorscale: invertColor ? [
											[0, 'red'],
											[1, 'green']
										] : [
											[0, 'green'],
											[1, 'red']
										],
										colorbar: {
											title: 'Result',
											tickvals: [minResult, maxResult],
											ticktext: [`${minResult}`, `${maxResult}`]
										},
									},
									text: data.map(d => d.result !== null ? `Result: ${d.result}` : 'No result'),
									type: 'scatter3d',
									showlegend: false
								};
			
								let subDiv = document.createElement("div");
								try {
									plotDiv.replaceChild(subDiv, spinnerContainer);
								} catch (err) {
									//
								}
								Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
							}
						}
					}
				}
			
				$("#plotScatter3d").data("loaded", "true");
			}
			
			async function plot_worker_cpu_ram() {
				if($("#worker_cpu_ram_pre").data("loaded") == "true") {
					return;
				}
			
				const logData = $("#worker_cpu_ram_pre").text();
				const regex = /^Unix-Timestamp: (\d+), Hostname: ([\w-]+), CPU: ([\d.]+)%, RAM: ([\d.]+) MB \/ ([\d.]+) MB$/;
			
				const hostData = {};
			
				logData.split("\n").forEach(line => {
					line = line.trim();
					const match = line.match(regex);
					if (match) {
						const timestamp = new Date(parseInt(match[1]) * 1000);
						const hostname = match[2];
						const cpu = parseFloat(match[3]);
						const ram = parseFloat(match[4]);
			
						if (!hostData[hostname]) {
							hostData[hostname] = { timestamps: [], cpuUsage: [], ramUsage: [] };
						}
			
						hostData[hostname].timestamps.push(timestamp);
						hostData[hostname].cpuUsage.push(cpu);
						hostData[hostname].ramUsage.push(ram);
					}
				});
			
				if (!Object.keys(hostData).length) {
					console.log("No valid data found");
					return;
				}
			
				const container = document.getElementById("cpuRamWorkerChartContainer");
				container.innerHTML = "";
			
				var i = 1;
			
				Object.entries(hostData).forEach(([hostname, { timestamps, cpuUsage, ramUsage }], index) => {
					const chartId = `workerChart_${index}`;
					const chartDiv = document.createElement("div");
					chartDiv.id = chartId;
					chartDiv.style.marginBottom = "40px";
					container.appendChild(chartDiv);
			
					const cpuTrace = {
						x: timestamps,
						y: cpuUsage,
						mode: "lines+markers",
						name: "CPU Usage (%)",
						yaxis: "y1",
						line: {
							color: "red"
						}
					};
			
					const ramTrace = {
						x: timestamps,
						y: ramUsage,
						mode: "lines+markers",
						name: "RAM Usage (MB)",
						yaxis: "y2",
						line: {
							color: "blue"
						}
					};
			
					const layout = {
						title: `Worker CPU and RAM Usage - ${hostname}`,
						xaxis: {
							title: get_axis_title_data("Timestamp", "date")
						},
						yaxis: {
							title: get_axis_title_data("CPU Usage (%)"),
							side: "left",
							color: "red"
						},
						yaxis2: {
							title: get_axis_title_data("RAM Usage (MB)"),
							side: "right",
							overlaying: "y",
							color: "blue"
						},
						showlegend: true
					};
			
					Plotly.newPlot(chartId, [cpuTrace, ramTrace], add_default_layout_data(layout));
					i++;
				});
			
				$("#plot_worker_cpu_ram_button").remove();
				$("#worker_cpu_ram_pre").data("loaded", "true");
			}
			
			function load_log_file(log_nr, filename) {
				var pre_id = `single_run_${log_nr}_pre`;
			
				if (!$("#" + pre_id).data("loaded")) {
					const params = new URLSearchParams(window.location.search);
			
					const user_id = params.get('user_id');
					const experiment_name = params.get('experiment_name');
					const run_nr = params.get('run_nr');
			
					var url = `get_log?user_id=${user_id}&experiment_name=${experiment_name}&run_nr=${run_nr}&filename=${filename}`;
			
					fetch(url)
						.then(response => response.json())
						.then(data => {
							if (data.data) {
								$("#" + pre_id).html(data.data);
								$("#" + pre_id).data("loaded", true);
							} else {
								log(`No 'data' key found in response.`);
							}
			
							$("#spinner_log_" + log_nr).remove();
						})
						.catch(error => {
							log(`Error loading log: ${error}`);
							$("#spinner_log_" + log_nr).remove();
						});
				}
			}
			
			function load_debug_log () {
				var pre_id = `here_debuglogs_go`;
			
				if (!$("#" + pre_id).data("loaded")) {
					const params = new URLSearchParams(window.location.search);
			
					const user_id = params.get('user_id');
					const experiment_name = params.get('experiment_name');
					const run_nr = params.get('run_nr');
			
					var url = `get_debug_log?user_id=${user_id}&experiment_name=${experiment_name}&run_nr=${run_nr}`;
			
					fetch(url)
						.then(response => response.json())
						.then(data => {
							$("#debug_log_spinner").remove();
			
							if (data.data) {
								try {
									$("#" + pre_id).html(data.data);
								} catch (err) {
									$("#" + pre_id).text(`Error loading data: ${err}`);
								}
			
								$("#" + pre_id).data("loaded", true);
			
								if (typeof apply_theme_based_on_system_preferences === 'function') {
									apply_theme_based_on_system_preferences();
								}
							} else {
								log(`No 'data' key found in response.`);
							}
						})
						.catch(error => {
							log(`Error loading log: ${error}`);
							$("#debug_log_spinner").remove();
						});
				}
			}
			
			function plotBoxplot() {
				if ($("#plotBoxplot").data("loaded") == "true") {
					return;
				}
				var numericColumns = tab_results_headers_json.filter(col =>
					!special_col_names.includes(col) && !result_names.includes(col) &&
					tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
				);
			
				if (numericColumns.length < 1) {
					console.error("Not enough numeric columns for Boxplot");
					return;
				}
			
				var resultIndex = tab_results_headers_json.findIndex(function(header) {
					return result_names.includes(header.toLowerCase());
				});
				var resultValues = tab_results_csv_json.map(row => row[resultIndex]);
				var minResult = Math.min(...resultValues.filter(value => value !== null && value !== ""));
				var maxResult = Math.max(...resultValues.filter(value => value !== null && value !== ""));
			
				var plotDiv = document.getElementById("plotBoxplot");
				plotDiv.innerHTML = "";
			
				let traces = numericColumns.map(col => {
					let index = tab_results_headers_json.indexOf(col);
					let data = tab_results_csv_json.map(row => parseFloat(row[index]));
			
					return {
						y: data,
						type: 'box',
						name: col,
						boxmean: 'sd',
						marker: {
							color: 'rgb(0, 255, 0)'
						},
					};
				});
			
				let layout = {
					title: 'Boxplot of Numerical Columns',
					xaxis: {
						title: get_axis_title_data("Columns")
					},
					yaxis: {
						title: get_axis_title_data("Value")
					},
					showlegend: false
				};
			
				Plotly.newPlot(plotDiv, traces, add_default_layout_data(layout));
				$("#plotBoxplot").data("loaded", "true");
			}
			
			function plotHeatmap() {
				if ($("#plotHeatmap").data("loaded") === "true") {
					return;
				}
			
				var numericColumns = tab_results_headers_json.filter(col => {
					if (special_col_names.includes(col) || result_names.includes(col)) {
						return false;
					}
					let index = tab_results_headers_json.indexOf(col);
					return tab_results_csv_json.every(row => {
						let value = parseFloat(row[index]);
						return !isNaN(value) && isFinite(value);
					});
				});
			
				if (numericColumns.length < 2) {
					console.error("Not enough valid numeric columns for Heatmap");
					return;
				}
			
				var columnData = numericColumns.map(col => {
					let index = tab_results_headers_json.indexOf(col);
					return tab_results_csv_json.map(row => parseFloat(row[index]));
				});
			
				var dataMatrix = numericColumns.map((_, i) =>
					numericColumns.map((_, j) => {
						let values = columnData[i].map((val, index) => (val + columnData[j][index]) / 2);
						return values.reduce((a, b) => a + b, 0) / values.length;
					})
				);
			
				var trace = {
					z: dataMatrix,
					x: numericColumns,
					y: numericColumns,
					colorscale: 'Viridis',
					type: 'heatmap'
				};
			
				var layout = {
					xaxis: {
						title: get_axis_title_data("Columns")
					},
					yaxis: {
						title: get_axis_title_data("Columns")
					},
					showlegend: false
				};
			
				var plotDiv = document.getElementById("plotHeatmap");
				plotDiv.innerHTML = "";
			
				Plotly.newPlot(plotDiv, [trace], add_default_layout_data(layout));
				$("#plotHeatmap").data("loaded", "true");
			}
			
			function plotHistogram() {
				if ($("#plotHistogram").data("loaded") == "true") {
					return;
				}
			
				var numericColumns = tab_results_headers_json.filter(col =>
					!special_col_names.includes(col) && !result_names.includes(col) &&
					tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
				);
			
				if (numericColumns.length < 1) {
					console.error("Not enough columns for Histogram");
					return;
				}
			
				var plotDiv = document.getElementById("plotHistogram");
				plotDiv.innerHTML = "";
			
				const colorPalette = ['#ff9999', '#66b3ff', '#99ff99', '#ffcc99', '#c2c2f0', '#ffb3e6'];
			
				let traces = numericColumns.map((col, index) => {
					let data = tab_results_csv_json.map(row => parseFloat(row[tab_results_headers_json.indexOf(col)]));
			
					return {
						x: data,
						type: 'histogram',
						name: col,
						opacity: 0.7,
						marker: {
							color: colorPalette[index % colorPalette.length]
						},
						autobinx: true
					};
				});
			
				let layout = {
					title: 'Histogram of Numerical Columns',
					xaxis: {
						title: get_axis_title_data("Value")
					},
					yaxis: {
						title: get_axis_title_data("Frequency")
					},
					showlegend: true,
					barmode: 'overlay'
				};
			
				Plotly.newPlot(plotDiv, traces, add_default_layout_data(layout));
				$("#plotHistogram").data("loaded", "true");
			}
			
			function plotViolin() {
				if ($("#plotViolin").data("loaded") == "true") {
					return;
				}
				var numericColumns = tab_results_headers_json.filter(col =>
					!special_col_names.includes(col) && !result_names.includes(col) &&
					tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
				);
			
				if (numericColumns.length < 1) {
					console.error("Not enough columns for Violin Plot");
					return;
				}
			
				var plotDiv = document.getElementById("plotViolin");
				plotDiv.innerHTML = "";
			
				let traces = numericColumns.map(col => {
					let index = tab_results_headers_json.indexOf(col);
					let data = tab_results_csv_json.map(row => parseFloat(row[index]));
			
					return {
						y: data,
						type: 'violin',
						name: col,
						box: {
							visible: true
						},
						line: {
							color: 'rgb(0, 255, 0)'
						},
						marker: {
							color: 'rgb(0, 255, 0)'
						},
						meanline: {
							visible: true
						},
					};
				});
			
				let layout = {
					title: 'Violin Plot of Numerical Columns',
					yaxis: {
						title: get_axis_title_data("Value")
					},
					xaxis: {
						title: get_axis_title_data("Columns")
					},
					showlegend: false
				};
			
				Plotly.newPlot(plotDiv, traces, add_default_layout_data(layout));
				$("#plotViolin").data("loaded", "true");
			}
			
			function plotExitCodesPieChart() {
				if ($("#plotExitCodesPieChart").data("loaded") == "true") {
					return;
				}
			
				var exitCodes = tab_job_infos_csv_json.map(row => row[tab_job_infos_headers_json.indexOf("exit_code")]);
			
				var exitCodeCounts = exitCodes.reduce(function(counts, exitCode) {
					counts[exitCode] = (counts[exitCode] || 0) + 1;
					return counts;
				}, {});
			
				var labels = Object.keys(exitCodeCounts);
				var values = Object.values(exitCodeCounts);
			
				var plotDiv = document.getElementById("plotExitCodesPieChart");
				plotDiv.innerHTML = "";
			
				var trace = {
					labels: labels,
					values: values,
					type: 'pie',
					hoverinfo: 'label+percent',
					textinfo: 'label+value',
					marker: {
						colors: ['#ff9999','#66b3ff','#99ff99','#ffcc99','#c2c2f0']
					}
				};
			
				var layout = {
					title: 'Exit Code Distribution',
					showlegend: true
				};
			
				Plotly.newPlot(plotDiv, [trace], add_default_layout_data(layout));
				$("#plotExitCodesPieChart").data("loaded", "true");
			}
			
			function plotResultEvolution() {
				if ($("#plotResultEvolution").data("loaded") == "true") {
					return;
				}
			
				result_names.forEach(resultName => {
					var relevantColumns = tab_results_headers_json.filter(col =>
						!special_col_names.includes(col) && !col.startsWith("OO_Info") && col.toLowerCase() !== resultName.toLowerCase()
					);
			
					var xColumnIndex = tab_results_headers_json.indexOf("trial_index");
					var resultIndex = tab_results_headers_json.indexOf(resultName);
			
					let data = tab_results_csv_json.map(row => ({
						x: row[xColumnIndex],
						y: parseFloat(row[resultIndex])
					}));
			
					data.sort((a, b) => a.x - b.x);
			
					let xData = data.map(item => item.x);
					let yData = data.map(item => item.y);
			
					let trace = {
						x: xData,
						y: yData,
						mode: 'lines+markers',
						name: resultName,
						line: {
							shape: 'linear'
						},
						marker: {
							size: get_marker_size()
						}
					};
			
					let layout = {
						title: `Evolution of ${resultName} over time`,
						xaxis: {
							title: get_axis_title_data("Trial-Index")
						},
						yaxis: {
							title: get_axis_title_data(resultName)
						},
						showlegend: true
					};
			
					let subDiv = document.createElement("div");
					document.getElementById("plotResultEvolution").appendChild(subDiv);
			
					Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
				});
			
				$("#plotResultEvolution").data("loaded", "true");
			}
			
			function plotResultPairs() {
				if ($("#plotResultPairs").data("loaded") == "true") {
					return;
				}
			
				var plotDiv = document.getElementById("plotResultPairs");
				plotDiv.innerHTML = "";
			
				for (let i = 0; i < result_names.length; i++) {
					for (let j = i + 1; j < result_names.length; j++) {
						let xName = result_names[i];
						let yName = result_names[j];
			
						let xIndex = tab_results_headers_json.indexOf(xName);
						let yIndex = tab_results_headers_json.indexOf(yName);
			
						let data = tab_results_csv_json
							.filter(row => row[xIndex] !== "" && row[yIndex] !== "")
							.map(row => ({
								x: parseFloat(row[xIndex]),
								y: parseFloat(row[yIndex]),
								status: row[tab_results_headers_json.indexOf("trial_status")]
							}));
			
						let colors = data.map(d => d.status === "COMPLETED" ? 'green' : (d.status === "FAILED" ? 'red' : 'gray'));
			
						let trace = {
							x: data.map(d => d.x),
							y: data.map(d => d.y),
							mode: 'markers',
							marker: {
								size: get_marker_size(),
								color: colors
							},
							text: data.map(d => `Status: ${d.status}`),
							type: 'scatter',
							showlegend: false
						};
			
						let layout = {
							xaxis: {
								title: get_axis_title_data(xName)
							},
							yaxis: {
								title: get_axis_title_data(yName)
							},
							showlegend: false
						};
			
						let subDiv = document.createElement("div");
						plotDiv.appendChild(subDiv);
			
						Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
					}
				}
			
				$("#plotResultPairs").data("loaded", "true");
			}
			
			function add_up_down_arrows_for_scrolling () {
				const upArrow = document.createElement('div');
				const downArrow = document.createElement('div');
			
				const style = document.createElement('style');
				style.innerHTML = `
					.scroll-arrow {
						position: fixed;
						right: 10px;
						z-index: 100;
						cursor: pointer;
						font-size: 25px;
						display: none;
						background-color: green;
						color: white;
						padding: 5px;
						outline: 2px solid white;
						box-shadow: 0 0 10px rgba(0, 0, 0, 0.5);
						transition: background-color 0.3s, transform 0.3s;
					}
					.scroll-arrow:hover {
						background-color: darkgreen;
						transform: scale(1.1);
					}
					#up-arrow {
						top: 10px;
					}
					#down-arrow {
						bottom: 10px;
					}
				`;
				document.head.appendChild(style);
			
				upArrow.id = "up-arrow";
				upArrow.classList.add("scroll-arrow");
				upArrow.classList.add("invert_in_dark_mode");
				upArrow.innerHTML = "&#8593;";
			
				downArrow.id = "down-arrow";
				downArrow.classList.add("scroll-arrow");
				downArrow.classList.add("invert_in_dark_mode");
				downArrow.innerHTML = "&#8595;";
			
				document.body.appendChild(upArrow);
				document.body.appendChild(downArrow);
			
				function checkScrollPosition() {
					const scrollPosition = window.scrollY;
					const pageHeight = document.documentElement.scrollHeight;
					const windowHeight = window.innerHeight;
			
					if (scrollPosition > 0) {
						upArrow.style.display = "block";
					} else {
						upArrow.style.display = "none";
					}
			
					if (scrollPosition + windowHeight < pageHeight) {
						downArrow.style.display = "block";
					} else {
						downArrow.style.display = "none";
					}
				}
			
				window.addEventListener("scroll", checkScrollPosition);
			
				upArrow.addEventListener("click", function () {
					window.scrollTo({ top: 0, behavior: 'smooth' });
				});
			
				downArrow.addEventListener("click", function () {
					window.scrollTo({ top: document.documentElement.scrollHeight, behavior: 'smooth' });
				});
			
				checkScrollPosition();
			
				if (typeof apply_theme_based_on_system_preferences === 'function') {
					apply_theme_based_on_system_preferences();
				}
			}
			
			function plotGPUUsage() {
				if ($("#tab_gpu_usage").data("loaded") === "true") {
					return;
				}
			
				Object.keys(gpu_usage).forEach(node => {
					const nodeData = gpu_usage[node];
			
					var timestamps = [];
					var gpuUtilizations = [];
					var temperatures = [];
			
					nodeData.forEach(entry => {
						try {
							var timestamp = new Date(entry[0]* 1000);
							var utilization = parseFloat(entry[1]);
							var temperature = parseFloat(entry[2]);
			
							if (!isNaN(timestamp) && !isNaN(utilization) && !isNaN(temperature)) {
								timestamps.push(timestamp);
								gpuUtilizations.push(utilization);
								temperatures.push(temperature);
							} else {
								console.warn("Invalid data point:", entry);
							}
						} catch (error) {
							console.error("Error processing GPU data entry:", error, entry);
						}
					});
			
					var trace1 = {
						x: timestamps,
						y: gpuUtilizations,
						mode: 'lines+markers',
						marker: {
							size: get_marker_size(),
						},
						name: 'GPU Utilization (%)',
						type: 'scatter',
						yaxis: 'y1'
					};
			
					var trace2 = {
						x: timestamps,
						y: temperatures,
						mode: 'lines+markers',
						marker: {
							size: get_marker_size(),
						},
						name: 'GPU Temperature (°C)',
						type: 'scatter',
						yaxis: 'y2'
					};
			
					var layout = {
						title: 'GPU Usage Over Time - ' + node,
						xaxis: {
							title: get_axis_title_data("Timestamp", "date"),
							tickmode: 'array',
							tickvals: timestamps.filter((_, index) => index % Math.max(Math.floor(timestamps.length / 10), 1) === 0),
							ticktext: timestamps.filter((_, index) => index % Math.max(Math.floor(timestamps.length / 10), 1) === 0).map(t => t.toLocaleString()),
							tickangle: -45
						},
						yaxis: {
							title: get_axis_title_data("GPU Utilization (%)"),
							overlaying: 'y',
							rangemode: 'tozero'
						},
						yaxis2: {
							title: get_axis_title_data("GPU Temperature (°C)"),
							overlaying: 'y',
							side: 'right',
							position: 0.85,
							rangemode: 'tozero'
						},
						legend: {
							x: 0.1,
							y: 0.9
						}
					};
			
					var divId = 'gpu_usage_plot_' + node;
			
					if (!document.getElementById(divId)) {
						var div = document.createElement('div');
						div.id = divId;
						div.className = 'gpu-usage-plot';
						document.getElementById('tab_gpu_usage').appendChild(div);
					}
			
					var plotData = [trace1, trace2];
			
					Plotly.newPlot(divId, plotData, add_default_layout_data(layout));
				});
			
				$("#tab_gpu_usage").data("loaded", "true");
			}
			
			function plotResultsDistributionByGenerationMethod() {
				if ("true" === $("#plotResultsDistributionByGenerationMethod").data("loaded")) {
					return;
				}
			
				var res_col = result_names[0];
				var gen_method_col = "generation_node";
			
				var data = {};
			
				tab_results_csv_json.forEach(row => {
					var gen_method = row[tab_results_headers_json.indexOf(gen_method_col)];
					var result = row[tab_results_headers_json.indexOf(res_col)];
			
					if (!data[gen_method]) {
						data[gen_method] = [];
					}
					data[gen_method].push(result);
				});
			
				var traces = Object.keys(data).map(method => {
					return {
						y: data[method],
						type: 'box',
						name: method,
						boxpoints: 'outliers',
						jitter: 0.5,
						pointpos: 0
					};
				});
			
				var layout = {
					title: 'Distribution of Results by Generation Method',
					yaxis: {
						title: get_axis_title_data(res_col)
					},
					xaxis: {
						title: get_axis_title_data("Generation Method")
					},
					boxmode: 'group'
				};
			
				Plotly.newPlot("plotResultsDistributionByGenerationMethod", traces, add_default_layout_data(layout));
				$("#plotResultsDistributionByGenerationMethod").data("loaded", "true");
			}
			
			function plotJobStatusDistribution() {
				if ($("#plotJobStatusDistribution").data("loaded") === "true") {
					return;
				}
			
				var status_col = "trial_status";
				var status_counts = {};
			
				tab_results_csv_json.forEach(row => {
					var status = row[tab_results_headers_json.indexOf(status_col)];
					if (status) {
						status_counts[status] = (status_counts[status] || 0) + 1;
					}
				});
			
				var statuses = Object.keys(status_counts);
				var counts = Object.values(status_counts);
			
				var colors = statuses.map((status, i) =>
					status === "FAILED" ? "#FF0000" : `hsl(${30 + ((i * 137) % 330)}, 70%, 50%)`
				);
			
				var trace = {
					x: statuses,
					y: counts,
					type: 'bar',
					marker: { color: colors }
				};
			
				var layout = {
					title: 'Distribution of Job Status',
					xaxis: { title: 'Trial Status' },
					yaxis: { title: 'Nr. of jobs' }
				};
			
				Plotly.newPlot("plotJobStatusDistribution", [trace], add_default_layout_data(layout));
				$("#plotJobStatusDistribution").data("loaded", "true");
			}
			
			function _colorize_table_entries_by_generation_method () {
				document.querySelectorAll('[data-column-id="generation_node"]').forEach(el => {
					let text = el.textContent.toLowerCase();
					let color = text.includes("manual") ? "green" :
						text.includes("sobol") ? "orange" :
						text.includes("saasbo") ? "pink" :
						text.includes("uniform") ? "lightblue" :
						text.includes("legacy_gpei") ? "sienna" :
						text.includes("bo_mixed") ? "aqua" :
						text.includes("randomforest") ? "darkseagreen" :
						text.includes("external_generator") ? "purple" :
						text.includes("botorch") ? "yellow" : "";
					if (color !== "") {
						el.style.backgroundColor = color;
					}
					el.classList.add("invert_in_dark_mode");
				});
			}
			
			function _colorize_table_entries_by_trial_status () {
				document.querySelectorAll('[data-column-id="trial_status"]').forEach(el => {
					let color = el.textContent.includes("COMPLETED") ? "lightgreen" :
						el.textContent.includes("RUNNING") ? "orange" :
						el.textContent.includes("FAILED") ? "red" :
						el.textContent.includes("ABANDONED") ? "yellow" : "";
					if (color) el.style.backgroundColor = color;
					el.classList.add("invert_in_dark_mode");
				});
			}
			
			function _colorize_table_entries_by_run_time() {
				let cells = [...document.querySelectorAll('[data-column-id="run_time"]')];
				if (cells.length === 0) return;
			
				let values = cells.map(el => parseFloat(el.textContent)).filter(v => !isNaN(v));
				if (values.length === 0) return;
			
				let min = Math.min(...values);
				let max = Math.max(...values);
				let range = max - min || 1;
			
				cells.forEach(el => {
					let value = parseFloat(el.textContent);
					if (isNaN(value)) return;
			
					let ratio = (value - min) / range;
					let red = Math.round(255 * ratio);
					let green = Math.round(255 * (1 - ratio));
			
					el.style.backgroundColor = `rgb(${red}, ${green}, 0)`;
					el.classList.add("invert_in_dark_mode");
				});
			}
			
			function _colorize_table_entries_by_results() {
				result_names.forEach((name, index) => {
					let minMax = result_min_max[index];
					let selector_query = `[data-column-id="${name}"]`;
					let cells = [...document.querySelectorAll(selector_query)];
					if (cells.length === 0) return;
			
					let values = cells.map(el => parseFloat(el.textContent)).filter(v => v > 0 && !isNaN(v));
					if (values.length === 0) return;
			
					let logValues = values.map(v => Math.log(v));
					let logMin = Math.min(...logValues);
					let logMax = Math.max(...logValues);
					let logRange = logMax - logMin || 1;
			
					cells.forEach(el => {
						let value = parseFloat(el.textContent);
						if (isNaN(value) || value <= 0) return;
			
						let logValue = Math.log(value);
						let ratio = (logValue - logMin) / logRange;
						if (minMax === "max") ratio = 1 - ratio;
			
						let red = Math.round(255 * ratio);
						let green = Math.round(255 * (1 - ratio));
			
						el.style.backgroundColor = `rgb(${red}, ${green}, 0)`;
						el.classList.add("invert_in_dark_mode");
					});
				});
			}
			
			function _colorize_table_entries_by_generation_node_or_hostname() {
				["hostname", "generation_node"].forEach(element => {
					let selector_query = '[data-column-id="' + element + '"]:not(.gridjs-th)';
					let cells = [...document.querySelectorAll(selector_query)];
					if (cells.length === 0) return;
			
					let uniqueValues = [...new Set(cells.map(el => el.textContent.trim()))];
					let colorMap = {};
			
					uniqueValues.forEach((value, index) => {
						let hue = Math.round((360 / uniqueValues.length) * index);
						colorMap[value] = `hsl(${hue}, 70%, 60%)`;
					});
			
					cells.forEach(el => {
						let value = el.textContent.trim();
						if (colorMap[value]) {
							el.style.backgroundColor = colorMap[value];
							el.classList.add("invert_in_dark_mode");
						}
					});
				});
			}
			
			function colorize_table_entries () {
				setTimeout(() => {
					if (typeof result_names !== "undefined" && Array.isArray(result_names) && result_names.length > 0) {
						_colorize_table_entries_by_trial_status();
						_colorize_table_entries_by_results();
						_colorize_table_entries_by_run_time();
						_colorize_table_entries_by_generation_method();
						_colorize_table_entries_by_generation_node_or_hostname();
						if (typeof apply_theme_based_on_system_preferences === 'function') {
							apply_theme_based_on_system_preferences();
						}
					}
				}, 300);
			}
			
			function add_colorize_to_gridjs_table () {
				let searchInput = document.querySelector(".gridjs-search-input");
				if (searchInput) {
					searchInput.addEventListener("input", colorize_table_entries);
				}
			}
			
			function updatePreWidths() {
				var width = window.innerWidth * 0.95;
				var pres = document.getElementsByTagName('pre');
				for (var i = 0; i < pres.length; i++) {
					pres[i].style.width = width + 'px';
				}
			}
			
			function demo_mode(nr_sec = 3) {
				let i = 0;
				let tabs = $('menu[role="tablist"] > button');
			
				setInterval(() => {
					tabs.attr('aria-selected', 'false').removeClass('active');
			
					let tab = tabs.eq(i % tabs.length);
					tab.attr('aria-selected', 'true').addClass('active');
			
					tab.trigger('click');
			
					i++;
				}, nr_sec * 1000);
			}
			
			function resizePlotlyCharts() {
				const plotlyElements = document.querySelectorAll('.js-plotly-plot');
			
				if (plotlyElements.length) {
					const windowWidth = window.innerWidth;
					const windowHeight = window.innerHeight;
			
					const newWidth = windowWidth * 0.9;
					const newHeight = windowHeight * 0.9;
			
					plotlyElements.forEach(function(element, index) {
						const layout = {
							width: newWidth,
							height: newHeight,
							plot_bgcolor: 'rgba(0, 0, 0, 0)',
							paper_bgcolor: 'rgba(0, 0, 0, 0)',
						};
			
						Plotly.relayout(element, layout)
					});
				}
			
				make_text_in_parallel_plot_nicer();
				apply_theme_based_on_system_preferences();
			}
			
			window.addEventListener('load', updatePreWidths);
			window.addEventListener('resize', updatePreWidths);
			
			$(document).ready(function() {
				colorize_table_entries();
			
				add_up_down_arrows_for_scrolling();
			
				add_colorize_to_gridjs_table();
			});
			
			window.addEventListener('resize', function() {
				resizePlotlyCharts();
			});
			
			"use strict";
			
			function get_row_by_index(idx) {
				if (!Object.keys(window).includes("tab_results_csv_json")) {
					error("tab_results_csv_json is not defined");
					return;
				}
			
				if (!Object.keys(window).includes("tab_results_headers_json")) {
					error("tab_results_headers_json is not defined");
					return;
				}
			
			
				var trial_index_col_idx = tab_results_headers_json.indexOf("trial_index");
			
				if(trial_index_col_idx == -1) {
					error(`"trial_index" could not be found in tab_results_headers_json. Cannot continue`);
			
					return null;
				}
			
				for (var i = 0; i < tab_results_csv_json.length; i++) {
					var row = tab_results_csv_json[i];
					var trial_index = row[trial_index_col_idx];
			
					if (trial_index == idx) {
						return row;
					}
				}
			
				return null;
			}
			
			function load_pareto_graph_from_idxs () {
				if (!Object.keys(window).includes("pareto_idxs")) {
					error("pareto_idxs is not defined");
					return;
				}
			
				if (!Object.keys(window).includes("tab_results_csv_json")) {
					error("tab_results_csv_json is not defined");
					return;
				}
			
				if (!Object.keys(window).includes("tab_results_headers_json")) {
					error("tab_results_headers_json is not defined");
					return;
				}
			
				if(pareto_idxs === null) {
					var err_msg = "pareto_idxs is null. Cannot plot or create tables from empty data. This can be caused by a defective <tt>pareto_idxs.json</tt> file. Please try reloading, or re-calculating the pareto-front and re-submitting if this problem persists.";
					$("#pareto_from_idxs_table").html(`<div class="caveat alarm">${err_msg}</div>`);
					return;	
				}
			
				var table = get_pareto_table_data_from_idx();
			
				var html_tables = createParetoTablesFromData(table);
			
				$("#pareto_from_idxs_table").html(html_tables);
			
				renderParetoFrontPlots(table);
			
				apply_theme_based_on_system_preferences();
			}
			
			function renderParetoFrontPlots(data) {
				try {
					let container = document.getElementById("pareto_front_idxs_plot_container");
					if (!container) {
						console.error("DIV with id 'pareto_front_idxs_plot_container' not found.");
						return;
					}
			
					container.innerHTML = "";
			
					if(data === undefined || data === null) {
						var err_msg = "There was an error getting the data for Pareto-Fronts. See the developer's console to see further details.";
						$("#pareto_from_idxs_table").html(`<div class="caveat alarm">${err_msg}</div>`);
						return;
					}
			
					Object.keys(data).forEach((key, idx) => {
						if (!key.startsWith("Pareto front for ")) return;
			
						let label = key.replace("Pareto front for ", "");
						let [xKey, yKey] = label.split("/");
			
						if (!xKey || !yKey) {
							console.warn("Could not extract two objectives from key:", key);
							return;
						}
			
						let entries = data[key];
						let x = [];
						let y = [];
						let hoverTexts = [];
			
						entries.forEach((entry) => {
							let results = entry.results || {};
							let values = entry.values || {};
			
							let xVal = (results[xKey] || [])[0];
							let yVal = (results[yKey] || [])[0];
			
							if (xVal === undefined || yVal === undefined) {
								console.warn("Missing values for", xKey, yKey, "in", entry);
								return;
							}
			
							x.push(xVal);
							y.push(yVal);
			
							let hoverInfo = [];
			
							if ("trial_index" in values) {
								hoverInfo.push(`<b>Trial Index:</b> ${values.trial_index[0]}`);
							}
			
							Object.keys(values)
								.filter(k => k !== "trial_index")
								.sort()
								.forEach(k => {
									hoverInfo.push(`<b>${k}:</b> ${values[k][0]}`);
								});
			
							Object.keys(results)
								.sort()
								.forEach(k => {
									hoverInfo.push(`<b>${k}:</b> ${results[k][0]}`);
								});
			
							hoverTexts.push(hoverInfo.join("<br>"));
						});
			
						let wrapper = document.createElement("div");
						wrapper.style.marginBottom = "30px";
			
						let titleEl = document.createElement("h3");
						titleEl.textContent = `Pareto Front: ${xKey} (${getMinMaxByResultName(xKey)}) vs ${yKey} (${getMinMaxByResultName(yKey)})`;
						wrapper.appendChild(titleEl);
			
						let divId = `pareto_plot_${idx}`;
						let plotDiv = document.createElement("div");
						plotDiv.id = divId;
						plotDiv.style.width = "100%";
						plotDiv.style.height = "400px";
			
						wrapper.appendChild(plotDiv);
						container.appendChild(wrapper);
			
						let trace = {
							x: x,
							y: y,
							text: hoverTexts,
							hoverinfo: "text",
							mode: "markers",
							type: "scatter",
							marker: {
								size: 8,
								color: 'rgb(31, 119, 180)',
								line: {
									width: 1,
									color: 'black'
								}
							},
							name: label
						};
			
						let layout = {
							xaxis: { title: { text: xKey } },
							yaxis: { title: { text: yKey } },
							margin: { t: 10, l: 60, r: 20, b: 50 },
							hovermode: "closest",
							showlegend: false
						};
			
						Plotly.newPlot(divId, [trace], add_default_layout_data(layout, 1));
					});
				} catch (e) {
					console.error("Error while rendering Pareto front plots:", e);
				}
			}
			
			function createParetoTablesFromData(data) {
				try {
					var container = document.createElement("div");
			
					var parsedData;
					try {
						parsedData = typeof data === "string" ? JSON.parse(data) : data;
					} catch (e) {
						console.error("JSON parsing failed:", e);
						return container;
					}
			
					for (var sectionTitle in parsedData) {
						if (!parsedData.hasOwnProperty(sectionTitle)) {
							continue;
						}
			
						var sectionData = parsedData[sectionTitle];
						var heading = document.createElement("h2");
						heading.textContent = sectionTitle;
						container.appendChild(heading);
			
						var table = document.createElement("table");
						table.style.borderCollapse = "collapse";
						table.style.marginBottom = "2em";
						table.style.width = "100%";
			
						var thead = document.createElement("thead");
						var headerRow = document.createElement("tr");
			
						var allValueKeys = new Set();
						var allResultKeys = new Set();
			
						sectionData.forEach(entry => {
							var values = entry.values || {};
							var results = entry.results || {};
			
							Object.keys(values).forEach(key => {
								allValueKeys.add(key);
							});
			
							Object.keys(results).forEach(key => {
								allResultKeys.add(key);
							});
						});
			
						var sortedValueKeys = Array.from(allValueKeys).sort();
						var sortedResultKeys = Array.from(allResultKeys).sort();
			
						if (sortedValueKeys.includes("trial_index")) {
							sortedValueKeys = sortedValueKeys.filter(k => k !== "trial_index");
							sortedValueKeys.unshift("trial_index");
						}
			
						var allColumns = [...sortedValueKeys, ...sortedResultKeys];
			
						allColumns.forEach(col => {
							var th = document.createElement("th");
							th.textContent = col;
							th.style.border = "1px solid black";
							th.style.padding = "4px";
							headerRow.appendChild(th);
						});
			
						thead.appendChild(headerRow);
						table.appendChild(thead);
			
						var tbody = document.createElement("tbody");
			
						sectionData.forEach(entry => {
							var tr = document.createElement("tr");
			
							allColumns.forEach(col => {
								var td = document.createElement("td");
								td.style.border = "1px solid black";
								td.style.padding = "4px";
			
								var value = null;
			
								if (col in entry.values) {
									value = entry.values[col];
								} else if (col in entry.results) {
									value = entry.results[col];
								}
			
								if (Array.isArray(value)) {
									td.textContent = value.join(", ");
								} else {
									td.textContent = value !== null && value !== undefined ? value : "";
								}
			
								tr.appendChild(td);
							});
			
							tbody.appendChild(tr);
						});
			
						table.appendChild(tbody);
						container.appendChild(table);
					}
			
					return container;
				} catch (err) {
					console.error("Unexpected error:", err);
					var errorDiv = document.createElement("div");
					errorDiv.textContent = "Error generating tables.";
					return errorDiv;
				}
			}
			
			function get_pareto_table_data_from_idx () {
				if (!Object.keys(window).includes("pareto_idxs")) {
					error("pareto_idxs is not defined");
					return;
				}
			
				if (!Object.keys(window).includes("tab_results_csv_json")) {
					error("tab_results_csv_json is not defined");
					return;
				}
			
				if (!Object.keys(window).includes("tab_results_headers_json")) {
					error("tab_results_headers_json is not defined");
					return;
				}
			
				var x_keys = Object.keys(pareto_idxs);
			
				var tables = {};
			
				for (var i = 0; i < x_keys.length; i++) {
					var x_key = x_keys[i];
					var y_keys = Object.keys(pareto_idxs[x_key]);
			
					for (var j = 0; j < y_keys.length; j++) {
						var y_key = y_keys[j];
			
						var indices = pareto_idxs[x_key][y_key];
			
						for (var k = 0; k < indices.length; k++) {
							var idx = indices[k];
							var row = get_row_by_index(idx);
			
							if(row === null) {
								error(`Error getting the row for index ${idx}`);
								return;
							}
			
							var row_dict = {
								"results": {},
								"values": {},
							};
			
							for (var l = 0; l < tab_results_headers_json.length; l++) {
								var header = tab_results_headers_json[l];
			
								if (!special_col_names.includes(header) || header == "trial_index") {
									var val = row[l];
			
									if (result_names.includes(header)) {
										if (!Object.keys(row_dict["results"]).includes(header)) {
											row_dict["results"][header] = [];
										}
			
										row_dict["results"][header].push(val);
									} else {
										if (!Object.keys(row_dict["values"]).includes(header)) {
											row_dict["values"][header] = [];
										}
										row_dict["values"][header].push(val);
									}
								}
								
							}
			
							var table_key = `Pareto front for ${x_key}/${y_key}`;
			
							if(!Object.keys(tables).includes(table_key)) {
								tables[table_key] = [];
							}
			
							tables[table_key].push(row_dict);
						}
			
					}
				}
			
				return tables;
			}
			
			function getMinMaxByResultName(resultName) {
				try {
					if (typeof resultName !== "string") {
						error("Parameter resultName must be a string");
						return;
					}
			
					if (!Array.isArray(result_names)) {
						error("Global variable result_names is not an array or undefined");
						return;
					}
					if (!Array.isArray(result_min_max)) {
						error("Global variable result_min_max is not an array or undefined");
						return;
					}
			
					if (result_names.length !== result_min_max.length) {
						error("Global arrays result_names and result_min_max must have the same length");
						return;
					}
			
					var index = result_names.indexOf(resultName);
					if (index === -1) {
						error("Result name '" + resultName + "' not found in result_names");
						return;
					}
			
					var minMaxValue = result_min_max[index];
			
					if (minMaxValue !== "min" && minMaxValue !== "max") {
						error("Value for result name '" + resultName + "' is invalid: expected 'min' or 'max'");
						return;
					}
			
					return minMaxValue;
			
				} catch (e) {
					error("Unexpected error: " + e.message);
				}
			}
			

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

				colorize_table_entries();
			});
		</script>

					<h1>&nbsp;Overview</h1>
			<h2>Experiment overview:         </h2><table cellspacing="0" cellpadding="5"><thead><tr><th> Setting</th><th>Value </th></tr></thead><tbody><tr><td> Max. nr. evaluations</td><td>953   </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>453   </td></tr></tbody></table><h2>Experiment parameters:                                                    </h2><table cellspacing="0" cellpadding="5"><thead><tr><th> Name</th><th>Type</th><th>Lower bound</th><th>Upper bound</th><th>Values</th><th>Type</th><th>Log Scale? </th></tr></thead><tbody><tr><td> recent_samples_size</td><td>int</td><td>1</td><td>5000</td><td></td><td>int</td><td>No         </td></tr><tr><td> feature_id</td><td>FixedParameter</td><td></td><td></td><td>25</td><td></td><td></td></tr><tr><td> batch_size</td><td>int</td><td>1</td><td>5000</td><td></td><td>int</td><td>No         </td></tr><tr><td> divergence</td><td>choice</td><td></td><td></td><td>str\(\&#039;H\&#039;\), str\(\&#039;KL\&#039;\)</td><td></td><td></td></tr><tr><td> detect_batch</td><td>choice</td><td></td><td></td><td>1, 2, 3</td><td></td><td></td></tr><tr><td> statistic</td><td>choice</td><td></td><td></td><td>str\(\&#039;stdev\&#039;\), str\(\&#039;tstat\&#039;\)</td><td></td><td></td></tr><tr><td> significance</td><td>float</td><td>0.001</td><td>0.999</td><td></td><td>float</td><td>No         </td></tr><tr><td> subsets</td><td>int</td><td>1</td><td>100</td><td></td><td>int</td><td>No         </td></tr></tbody></table><h2>Number of evaluations</h2>
			<table>
			<tbody>
			<tr>
			<th>Failed</th>
			<th>Succeeded</th>
			<th>Running</th>
			<th>Total</th>
			</tr>
			<tr>
			<td>49</td>
			<td>615</td>
			<td>3</td>
			<td>667</td>
			</tr>
			</tbody>
			</table>
			<h2>Result names and types</h2>
			<table>
			<tr><th>name</th><th>min/max</th></tr>
			<tr>
			<td>ACCURACY</td>
			<td>max</td>
			</tr>
			<tr>
			<td>RUNTIME</td>
			<td>min</td>
			</tr>
			</table>
			<br>
			<h2>Git-Version</h2>
			<tt>Commit: 2223ae6553abdd3e288f4b391080b763a7a48477
			</tt>
			<h1>&nbsp;Results</h1>
			<div id='tab_results_csv_table'></div>
			<button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("tab_results_csv_table_pre")'> Copy raw data to clipboard</button>
			<button onclick='download_as_file("tab_results_csv_table_pre", "results.csv")'> Download &raquo;results.csv&laquo; as file</button>
<pre id='tab_results_csv_table_pre'>trial_index,arm_name,trial_status,generation_method,generation_node,ACCURACY,RUNTIME,recent_samples_size,batch_size,divergence,detect_batch,statistic,significance,subsets,feature_id
0,0_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,246.000000000000000000000000000000,2032,973,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.670107585072517442092987494107,76,25
1,1_0,COMPLETED,Sobol,GenerationStep_0,0.100000000000000005551115123126,178.000000000000000000000000000000,4751,2960,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.223488174019381397039651915293,46,25
2,2_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,180.000000000000000000000000000000,3490,2376,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.490903230674564816649052545472,55,25
3,3_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,158.000000000000000000000000000000,751,4373,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.933123707715421968345026471070,23,25
4,4_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,167.000000000000000000000000000000,82,1626,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.589890163851901849767500607413,65,25
5,5_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,173.000000000000000000000000000000,2831,4795,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.023392168471589685346812004241,7,25
6,6_0,COMPLETED,Sobol,GenerationStep_0,0.100000000000000005551115123126,312.000000000000000000000000000000,4092,535,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.254504572529345773901354732516,92,25
7,7_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,181.000000000000000000000000000000,1362,3694,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.826346605591475991126060307579,37,25
8,8_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,165.000000000000000000000000000000,1785,2064,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.993259560670703645079981924937,75,25
9,9_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,178.000000000000000000000000000000,4056,4061,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.422880077421665168113662502947,5,25
10,10_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,345.000000000000000000000000000000,2778,661,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.159117679318413141054122661444,95,25
11,11_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,167.000000000000000000000000000000,527,2648,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.727078112976625612340342286188,28,25
12,12_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,170.000000000000000000000000000000,1108,222,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.757956561043858556558916461654,86,25
13,13_0,COMPLETED,Sobol,GenerationStep_0,0.100000000000000005551115123126,148.000000000000000000000000000000,3369,3381,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.315249065589159715994327370936,44,25
14,14_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,161.000000000000000000000000000000,4647,1314,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.079508471580222256358538857057,60,25
15,15_0,COMPLETED,Sobol,GenerationStep_0,0.100000000000000005551115123126,160.000000000000000000000000000000,2367,4483,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.525641004567965919314076472801,14,25
16,16_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,206.000000000000000000000000000000,2334,1450,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.368865946847945436193327850560,48,25
17,17_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,166.000000000000000000000000000000,4448,4619,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.799881862513720953700158133870,81,25
18,18_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,159.000000000000000000000000000000,3168,46,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.532480383409187241205984264525,22,25
19,19_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,188.000000000000000000000000000000,1073,3205,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.105836275467649107429046750894,51,25
20,20_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,188.000000000000000000000000000000,404,797,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.386711010523140441552669699377,13,25
21,21_0,COMPLETED,Sobol,GenerationStep_0,0.100000000000000005551115123126,156.000000000000000000000000000000,2509,2785,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.937602157954126602668054601963,67,25
22,22_0,COMPLETED,Sobol,GenerationStep_0,0.100000000000000005551115123126,167.000000000000000000000000000000,3789,1888,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.706506662631407378327708102006,33,25
23,23_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,187.000000000000000000000000000000,1665,3885,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.150237660048529508838299761919,91,25
24,24_0,COMPLETED,Sobol,GenerationStep_0,0.100000000000000005551115123126,197.000000000000000000000000000000,1483,358,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.045730172665789721453410976437,2,25
25,25_0,COMPLETED,Sobol,GenerationStep_0,0.100000000000000005551115123126,159.000000000000000000000000000000,4359,3517,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.600536588257178705063665802300,70,25
26,26_0,COMPLETED,Sobol,GenerationStep_0,0.100000000000000005551115123126,167.000000000000000000000000000000,3100,1763,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.864282107368111618406203433551,29,25
27,27_0,COMPLETED,Sobol,GenerationStep_0,0.100000000000000005551115123126,175.000000000000000000000000000000,205,4932,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.311928499352186916482310152787,99,25
28,28_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,182.000000000000000000000000000000,786,2200,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.218658882400020959657638286444,39,25
29,29_0,COMPLETED,Sobol,GenerationStep_0,0.110000000000000000555111512313,183.000000000000000000000000000000,3691,4197,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.645789986448362496318509329285,84,25
30,30_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,162.000000000000000000000000000000,4125,3950,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.103482496414467092793465496925,27,25
31,31_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,159.000000000000000000000000000000,19,3511,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.295024713957104334216552388170,25,25
32,32_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,176.000000000000000000000000000000,2217,4444,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.050272832737935653490968235246,45,25
33,33_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,268.000000000000000000000000000000,3523,2793,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.257095693764328392383333721227,1,25
34,34_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,191.000000000000000000000000000000,597,1185,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,60,25
35,35_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,191.000000000000000000000000000000,3978,885,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.215266585143749300534921076178,39,25
36,36_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,292.000000000000000000000000000000,3412,3450,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,25
37,37_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,256.000000000000000000000000000000,1,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,25
38,38_0,FAILED,BoTorch,GenerationStep_1,,,4112,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,25
39,39_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,150.000000000000000000000000000000,3160,4213,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,49,25
40,40_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,185.000000000000000000000000000000,2846,3374,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,25
41,41_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,144.000000000000000000000000000000,1944,5000,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,44,25
42,42_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,162.000000000000000000000000000000,5000,5000,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,25
43,43_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,171.000000000000000000000000000000,2392,2469,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,25
44,44_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,164.000000000000000000000000000000,183,611,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,49,25
45,45_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,158.000000000000000000000000000000,3092,2962,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.333121735335604185479496663902,21,25
46,46_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,182.000000000000000000000000000000,873,909,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.536170184311933528675808702246,52,25
47,47_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,158.000000000000000000000000000000,121,4746,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.209524693498227360111130224141,48,25
48,48_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,153.000000000000000000000000000000,1456,4114,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,18,25
49,49_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,136.000000000000000000000000000000,533,5000,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,30,25
50,50_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,266.000000000000000000000000000000,5000,3482,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,25
51,51_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,150.000000000000000000000000000000,3475,3991,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,26,25
52,52_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,316.000000000000000000000000000000,226,3597,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,25
53,53_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,246.000000000000000000000000000000,751,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,46,25
54,54_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,208.000000000000000000000000000000,1,1026,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,25
55,55_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,265.000000000000000000000000000000,1,2899,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.333116985101935714208565286754,1,25
56,56_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,173.000000000000000000000000000000,1907,2867,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.567093166797052683492097457929,100,25
57,57_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,202.000000000000000000000000000000,870,52,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,25
58,58_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,187.000000000000000000000000000000,4007,5000,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,48,25
59,59_0,FAILED,BoTorch,GenerationStep_1,,,668,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,25
60,60_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,163.000000000000000000000000000000,1562,4316,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,54,25
61,61_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,155.000000000000000000000000000000,4393,3898,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,52,25
62,62_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,162.000000000000000000000000000000,4788,4706,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.003489735922205241310661838483,24,25
63,63_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,172.000000000000000000000000000000,885,1208,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,57,25
64,64_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,178.000000000000000000000000000000,1203,1599,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.956874109158280305997834602749,45,25
65,65_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,177.000000000000000000000000000000,3856,1058,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.094947771233474184682243901534,55,25
66,66_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,168.000000000000000000000000000000,1066,4079,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,63,25
67,67_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,151.000000000000000000000000000000,4541,4157,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,36,25
68,68_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,167.000000000000000000000000000000,4586,1814,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.466340315431842400428763539821,20,25
69,69_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,175.000000000000000000000000000000,1021,972,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,68,25
70,70_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,173.000000000000000000000000000000,4311,4395,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,53,25
71,71_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,149.000000000000000000000000000000,4779,4769,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.601766075497445429576259812166,21,25
72,72_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,167.000000000000000000000000000000,703,4331,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,64,25
73,73_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,152.000000000000000000000000000000,1678,2478,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,83,25
74,74_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,167.000000000000000000000000000000,804,2176,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,17,25
75,75_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,168.000000000000000000000000000000,4670,2425,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.466155162871799366719471890974,27,25
76,76_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,163.000000000000000000000000000000,614,4660,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,14,25
77,77_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,186.000000000000000000000000000000,3879,1673,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.898356359558590389369214790349,52,25
78,78_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,182.000000000000000000000000000000,1430,1956,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,66,25
79,79_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,161.000000000000000000000000000000,1619,4843,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.191178291970295871626817074684,60,25
80,80_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,172.000000000000000000000000000000,727,1397,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.010610146094010560607889814833,75,25
81,81_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,162.000000000000000000000000000000,4479,4386,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,19,25
82,82_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,178.000000000000000000000000000000,2358,4491,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,64,25
83,83_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,175.000000000000000000000000000000,4396,1001,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,23,25
84,84_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,178.000000000000000000000000000000,4563,951,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.094058928302647962227389655254,50,25
85,85_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,172.000000000000000000000000000000,1691,614,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,51,25
86,86_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,191.000000000000000000000000000000,4889,3065,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.938815560939274873497595308436,23,25
87,87_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,147.000000000000000000000000000000,4633,3178,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,43,25
88,88_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,182.000000000000000000000000000000,1331,2432,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,79,25
89,89_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,166.000000000000000000000000000000,81,1813,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,77,25
90,90_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,182.000000000000000000000000000000,960,4965,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.925830202133979041079214766796,19,25
91,91_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,164.000000000000000000000000000000,344,1899,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.254206794555207782337902244763,21,25
92,92_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,170.000000000000000000000000000000,82,3048,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,22,25
93,93_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,175.000000000000000000000000000000,1,4333,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,99,25
94,94_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,162.000000000000000000000000000000,1063,382,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,20,25
95,95_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,184.000000000000000000000000000000,521,4067,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,75,25
96,96_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,198.000000000000000000000000000000,1,4134,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,99,25
97,97_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,159.000000000000000000000000000000,2564,3624,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.902442681317450756672826628346,21,25
98,98_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,165.000000000000000000000000000000,809,4642,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.940014911281453979796651765355,16,25
99,99_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,173.000000000000000000000000000000,4116,4794,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.750477717298692947878180348198,100,25
100,100_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,183.000000000000000000000000000000,797,221,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.964900877171947612964686413761,74,25
101,101_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,168.000000000000000000000000000000,3330,4818,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.739787978415867963910557136842,100,25
102,102_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,154.000000000000000000000000000000,4845,4664,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.257017495122564498810646682614,23,25
103,103_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,171.000000000000000000000000000000,4007,4656,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.732182289227484517368793603964,74,25
104,104_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,178.000000000000000000000000000000,85,4439,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,73,25
105,105_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,164.000000000000000000000000000000,4380,1310,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.122802080472957764190056195730,19,25
106,106_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,197.000000000000000000000000000000,1,5000,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,25
107,107_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,147.000000000000000000000000000000,328,4834,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.933226507619265399640084979183,20,25
108,108_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,182.000000000000000000000000000000,4234,3807,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,71,25
109,109_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,220.000000000000000000000000000000,5000,5000,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,100,25
110,110_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,188.000000000000000000000000000000,1,3938,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,74,25
111,111_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,147.000000000000000000000000000000,715,1307,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,23,25
112,112_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,169.000000000000000000000000000000,2568,796,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.602234909273098417692438033555,74,25
113,113_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,154.000000000000000000000000000000,3691,4833,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.182927071865035706377256019550,19,25
114,114_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,144.000000000000000000000000000000,936,4213,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998862696871666622122631906677,19,25
115,115_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,177.000000000000000000000000000000,1,4021,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,80,25
116,116_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,206.000000000000000000000000000000,4049,5000,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.778881545150762577556236010423,100,25
117,117_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,176.000000000000000000000000000000,47,3753,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.981459704316696601722469495144,20,25
118,118_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,149.000000000000000000000000000000,1,2986,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,29,25
119,119_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,170.000000000000000000000000000000,596,459,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,20,25
120,120_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,159.000000000000000000000000000000,1131,4143,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,35,25
121,121_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,162.000000000000000000000000000000,5000,2141,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,77,25
122,122_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,172.000000000000000000000000000000,1367,4850,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,37,25
123,123_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,169.000000000000000000000000000000,1,1336,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,26,25
124,124_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,172.000000000000000000000000000000,1,4125,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,79,25
125,125_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,165.000000000000000000000000000000,4955,2634,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,71,25
126,126_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,161.000000000000000000000000000000,3452,3264,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,32,25
127,127_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,147.000000000000000000000000000000,3288,2293,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,28,25
128,128_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,168.000000000000000000000000000000,1,4613,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.602867301683098211206868199952,36,25
129,129_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,161.000000000000000000000000000000,1,5000,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,37,25
130,130_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,173.000000000000000000000000000000,2305,1987,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,82,25
131,131_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,168.000000000000000000000000000000,4676,4825,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,36,25
132,132_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,167.000000000000000000000000000000,1139,927,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.434555968096149325408106278701,20,25
133,133_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,165.000000000000000000000000000000,78,3692,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.863839777653022666825677333691,35,25
134,134_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,175.000000000000000000000000000000,265,4011,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,36,25
135,135_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,179.000000000000000000000000000000,1,1904,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,30,25
136,136_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,159.000000000000000000000000000000,4716,5000,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,76,25
137,137_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,162.000000000000000000000000000000,1,1937,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,30,25
138,138_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,172.000000000000000000000000000000,4125,3011,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,88,25
139,139_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,149.000000000000000000000000000000,1,3467,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,36,25
140,140_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,164.000000000000000000000000000000,481,522,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.859511345665886383748954813200,18,25
141,141_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,172.000000000000000000000000000000,4412,4513,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,38,25
142,142_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,181.000000000000000000000000000000,5000,5000,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,11,25
143,143_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,163.000000000000000000000000000000,1,3942,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,71,25
144,144_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,180.000000000000000000000000000000,1,5000,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,50,25
145,145_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,172.000000000000000000000000000000,1,1907,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,86,25
146,146_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,161.000000000000000000000000000000,712,4457,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.504779593681710214703173278394,31,25
147,147_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,152.000000000000000000000000000000,2909,2404,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,28,25
148,148_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,169.000000000000000000000000000000,76,1552,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.507956804584632770627194986446,88,25
149,149_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,247.000000000000000000000000000000,4105,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,17,25
150,150_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,171.000000000000000000000000000000,1209,3672,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.432643130086026617142636041535,27,25
151,151_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,150.000000000000000000000000000000,4470,3939,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.553200691786827736251552778413,24,25
152,152_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,148.000000000000000000000000000000,4606,4963,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.024206495740357932694442055777,31,25
153,153_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,182.000000000000000000000000000000,2516,3439,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.370182153413035786027052154168,28,25
154,154_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,144.000000000000000000000000000000,4615,4940,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.666460591273171476522918510454,25,25
155,155_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,156.000000000000000000000000000000,107,1214,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.617126273711456341253267510183,23,25
156,156_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,168.000000000000000000000000000000,3912,5000,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,100,25
157,157_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,156.000000000000000000000000000000,4199,3203,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,22,25
158,158_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,193.000000000000000000000000000000,2197,4914,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.463946126054125773663372456213,21,25
159,159_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,167.000000000000000000000000000000,2199,4832,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.200513910555775581867621326637,87,25
160,160_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,159.000000000000000000000000000000,337,2112,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,33,25
161,161_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,164.000000000000000000000000000000,1200,5000,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,100,25
162,162_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,181.000000000000000000000000000000,4460,5000,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,96,25
163,163_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,144.000000000000000000000000000000,4787,4185,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.165999591995936696120494957540,33,25
164,164_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,144.000000000000000000000000000000,4700,4199,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.842862108443538371460590497009,25,25
165,165_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,159.000000000000000000000000000000,785,623,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,25,25
166,166_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,149.000000000000000000000000000000,4623,4944,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,28,25
167,167_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,188.000000000000000000000000000000,24,4656,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.409110121904068479992133688938,18,25
168,168_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,179.000000000000000000000000000000,4728,5000,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,25
169,169_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,168.000000000000000000000000000000,4428,4894,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.432990612798112017856055899756,71,25
170,170_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,169.000000000000000000000000000000,2232,5000,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.057245482976993576629265447764,85,25
171,171_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,168.000000000000000000000000000000,2729,4078,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.517823863181286814239001614624,28,25
172,172_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,211.000000000000000000000000000000,4001,5000,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,85,25
173,173_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,176.000000000000000000000000000000,742,705,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.464705604705690611400115130891,68,25
174,174_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,156.000000000000000000000000000000,421,2439,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,21,25
175,175_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,174.000000000000000000000000000000,1,5000,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,95,25
176,176_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,178.000000000000000000000000000000,2906,1021,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,28,25
177,177_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,175.000000000000000000000000000000,633,5000,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,91,25
178,178_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,157.000000000000000000000000000000,1,2917,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.891219556286128034017224308627,21,25
179,179_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,152.000000000000000000000000000000,118,3982,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.797839613820967685775542577176,71,25
180,180_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,176.000000000000000000000000000000,151,4015,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.384313475226658263217416333646,84,25
181,181_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,159.000000000000000000000000000000,1680,392,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,61,25
182,182_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,178.000000000000000000000000000000,4950,3708,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.532028046673946430900059567648,81,25
183,183_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,158.000000000000000000000000000000,2663,2678,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,72,25
184,184_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,168.000000000000000000000000000000,1026,4802,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.720059438432725351653118650574,56,25
185,185_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,155.000000000000000000000000000000,464,657,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,64,25
186,186_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,173.000000000000000000000000000000,4979,4490,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.624253039710641388637668569572,77,25
187,187_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,165.000000000000000000000000000000,4213,4161,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.203838854302110905614142666309,100,25
188,188_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,171.000000000000000000000000000000,341,4542,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.410051725629308583265242305060,67,25
189,189_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,166.000000000000000000000000000000,3599,4981,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.438302650829938744703184738682,86,25
190,190_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,162.000000000000000000000000000000,545,4995,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.286237834397163437571975919127,82,25
191,191_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,160.000000000000000000000000000000,337,3877,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.351852739290410998496128058832,98,25
192,192_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,201.000000000000000000000000000000,4543,5000,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,25
193,193_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,154.000000000000000000000000000000,4908,2773,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,84,25
194,194_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,169.000000000000000000000000000000,2578,4960,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.613912183194944560682415612973,75,25
195,195_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,168.000000000000000000000000000000,1926,4016,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.964244401184866095633196891868,1,25
196,196_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,156.000000000000000000000000000000,2310,536,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,44,25
197,197_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,162.000000000000000000000000000000,1074,5000,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,42,25
198,198_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,158.000000000000000000000000000000,49,1639,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,25,25
199,199_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,159.000000000000000000000000000000,55,5000,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.438300019741893420732736785794,1,25
200,200_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,162.000000000000000000000000000000,1662,3309,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,86,25
201,201_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,158.000000000000000000000000000000,2226,3753,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.441789082012099487695166999401,100,25
202,202_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,160.000000000000000000000000000000,578,5000,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.778745386396359484670881556667,51,25
203,203_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,178.000000000000000000000000000000,2658,2251,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,20,25
204,204_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,250.000000000000000000000000000000,5000,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,63,25
205,205_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,165.000000000000000000000000000000,282,668,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.551039150465345350937695911853,27,25
206,206_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,172.000000000000000000000000000000,521,4000,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.261869710345817574559390550348,83,25
207,207_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,163.000000000000000000000000000000,2034,2365,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,61,25
208,208_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,176.000000000000000000000000000000,2181,400,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.530188935663614802074050658121,24,25
209,209_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,148.000000000000000000000000000000,3579,1301,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,100,25
210,210_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,162.000000000000000000000000000000,1,1297,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,58,25
211,211_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,163.000000000000000000000000000000,1,879,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,48,25
212,212_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,163.000000000000000000000000000000,3680,1928,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,99,25
213,213_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,172.000000000000000000000000000000,995,3133,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,100,25
214,214_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,171.000000000000000000000000000000,323,3354,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.173092786510225971063903216418,100,25
215,215_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,148.000000000000000000000000000000,5000,1623,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,93,25
216,216_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,158.000000000000000000000000000000,1,28,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,100,25
217,217_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,151.000000000000000000000000000000,687,1746,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,68,25
218,218_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,147.000000000000000000000000000000,1,2795,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,100,25
219,219_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,163.000000000000000000000000000000,1092,1774,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.843914292796544285302218213474,100,25
220,220_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,183.000000000000000000000000000000,5000,333,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,25
221,221_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,166.000000000000000000000000000000,2678,5000,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.492837654999773444597366278686,61,25
222,222_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,162.000000000000000000000000000000,4188,5000,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,65,25
223,223_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,160.000000000000000000000000000000,171,904,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,100,25
224,224_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,167.000000000000000000000000000000,811,130,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,33,25
225,225_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,171.000000000000000000000000000000,4794,2630,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,93,25
226,226_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,172.000000000000000000000000000000,4515,1220,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,98,25
227,227_0,FAILED,BoTorch,GenerationStep_1,,,4,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,41,25
228,228_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,155.000000000000000000000000000000,4934,3465,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,100,25
229,229_0,COMPLETED,BoTorch,GenerationStep_1,0.119999999999999995559107901499,176.000000000000000000000000000000,1,4871,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,27,25
230,230_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,159.000000000000000000000000000000,2906,3980,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,27,25
231,231_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,174.000000000000000000000000000000,1,4649,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,25
232,232_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,160.000000000000000000000000000000,4631,3961,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,38,25
233,233_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,185.000000000000000000000000000000,438,5000,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.613646157455354557264115555881,1,25
234,234_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,151.000000000000000000000000000000,1,1530,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,52,25
235,235_0,FAILED,BoTorch,GenerationStep_1,,,2783,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,17,25
236,236_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,146.000000000000000000000000000000,1,1888,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,100,25
237,237_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,160.000000000000000000000000000000,109,1852,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.656988487280723898464884769055,21,25
238,238_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,163.000000000000000000000000000000,1,5000,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,15,25
239,239_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,169.000000000000000000000000000000,1,3678,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,100,25
240,240_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,164.000000000000000000000000000000,1,1026,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,92,25
241,241_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,179.000000000000000000000000000000,1587,5000,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,55,25
242,242_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,175.000000000000000000000000000000,4359,4766,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,52,25
243,243_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,154.000000000000000000000000000000,1,712,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,100,25
244,244_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,154.000000000000000000000000000000,1,3897,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,100,25
245,245_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,151.000000000000000000000000000000,4673,1284,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,27,25
246,246_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,179.000000000000000000000000000000,1,3950,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,12,25
247,247_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,166.000000000000000000000000000000,1,4682,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,20,25
248,248_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,166.000000000000000000000000000000,5000,5000,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,61,25
249,249_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,168.000000000000000000000000000000,2783,1295,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,33,25
250,250_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,148.000000000000000000000000000000,4103,1251,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,30,25
251,251_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,158.000000000000000000000000000000,605,4416,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,12,25
252,252_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,176.000000000000000000000000000000,1978,5000,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,41,25
253,253_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,162.000000000000000000000000000000,5000,5000,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,40,25
254,254_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,165.000000000000000000000000000000,5000,5000,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,44,25
255,255_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,166.000000000000000000000000000000,1,4203,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,20,25
256,256_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,153.000000000000000000000000000000,5000,2900,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,31,25
257,257_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,161.000000000000000000000000000000,2850,1062,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,94,25
258,258_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,172.000000000000000000000000000000,585,5000,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,60,25
259,259_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,173.000000000000000000000000000000,2905,673,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,21,25
260,260_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,161.000000000000000000000000000000,5000,3513,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,75,25
261,261_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,181.000000000000000000000000000000,5000,5000,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,26,25
262,262_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,161.000000000000000000000000000000,287,4440,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,50,25
263,263_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,167.000000000000000000000000000000,5000,4190,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,53,25
264,264_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,168.000000000000000000000000000000,3030,4136,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,47,25
265,265_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,188.000000000000000000000000000000,1,909,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,25
266,266_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,175.000000000000000000000000000000,4227,4989,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.628296524094222763601180758997,58,25
267,267_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,161.000000000000000000000000000000,3961,4961,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.641356436373760385727393895650,55,25
268,268_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,163.000000000000000000000000000000,206,5000,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.371429348298845107834154077864,100,25
269,269_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,176.000000000000000000000000000000,4653,5000,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,61,25
270,270_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,179.000000000000000000000000000000,426,1360,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.143445624160254331380670578255,70,25
271,271_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,167.000000000000000000000000000000,5000,353,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,100,25
272,272_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,159.000000000000000000000000000000,3624,3234,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,28,25
273,273_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,153.000000000000000000000000000000,4955,1361,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,21,25
274,274_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,176.000000000000000000000000000000,265,3097,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,35,25
275,275_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,149.000000000000000000000000000000,2516,5000,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,24,25
276,276_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,164.000000000000000000000000000000,1,4027,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,100,25
277,277_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,199.000000000000000000000000000000,3274,2805,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,77,25
278,278_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,190.000000000000000000000000000000,1263,5000,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.929617650776776938137402339635,73,25
279,279_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,173.000000000000000000000000000000,1157,2958,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,62,25
280,280_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,154.000000000000000000000000000000,674,4335,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,31,25
281,281_0,FAILED,BoTorch,GenerationStep_1,,,1495,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,24,25
282,282_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,156.000000000000000000000000000000,4992,4777,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,74,25
283,283_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,167.000000000000000000000000000000,4929,1364,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,24,25
284,284_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,163.000000000000000000000000000000,2957,5000,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.593471271779253517486552027549,56,25
285,285_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,186.000000000000000000000000000000,4174,2867,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,73,25
286,286_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,165.000000000000000000000000000000,432,1367,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,31,25
287,287_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,183.000000000000000000000000000000,1,3558,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,100,25
288,288_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,1164.000000000000000000000000000000,1,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,28,25
289,289_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,158.000000000000000000000000000000,3536,661,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,24,25
290,290_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,168.000000000000000000000000000000,4316,3939,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.542980406313094743353531157481,57,25
291,291_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,194.000000000000000000000000000000,842,151,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,36,25
292,292_0,FAILED,BoTorch,GenerationStep_1,,,5000,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.723337542880256312294307008415,31,25
293,293_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,166.000000000000000000000000000000,4580,3149,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,25
294,294_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,152.000000000000000000000000000000,4429,2985,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,29,25
295,295_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,272.000000000000000000000000000000,61,31,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,35,25
296,296_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,175.000000000000000000000000000000,3668,407,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,38,25
297,297_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,182.000000000000000000000000000000,3652,1867,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,26,25
298,298_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,152.000000000000000000000000000000,2085,5000,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,29,25
299,299_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,182.000000000000000000000000000000,917,195,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.385874291994510287828745731531,8,25
300,300_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,167.000000000000000000000000000000,4652,462,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.247344377057235553785119464010,15,25
301,301_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,168.000000000000000000000000000000,3351,667,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.490892099778257984254992152273,36,25
302,302_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,201.000000000000000000000000000000,1,2218,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,25
303,303_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,233.000000000000000000000000000000,1134,1106,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.913164544378584963624234660529,93,25
304,304_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,161.000000000000000000000000000000,5000,517,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,8,25
305,305_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,197.000000000000000000000000000000,3569,243,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.661258043578607290768900384137,50,25
306,306_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,171.000000000000000000000000000000,4974,696,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.301530939231251404741840360657,37,25
307,307_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,196.000000000000000000000000000000,3987,412,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.543708621970852346017011313961,1,25
308,308_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,162.000000000000000000000000000000,1,2948,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,60,25
309,309_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,207.000000000000000000000000000000,2920,812,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.955961895642333914224764157552,66,25
310,310_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,268.000000000000000000000000000000,5000,932,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,25
311,311_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,169.000000000000000000000000000000,2890,1087,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.455345875448971038057521809606,20,25
312,312_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,184.000000000000000000000000000000,5000,207,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.440208373172518929727914382966,41,25
313,313_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,165.000000000000000000000000000000,4516,668,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,31,25
314,314_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,161.000000000000000000000000000000,4851,10,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.716892033802374650797162303206,66,25
315,315_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,246.000000000000000000000000000000,1,1623,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,25
316,316_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,225.000000000000000000000000000000,5000,3587,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,25
317,317_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,211.000000000000000000000000000000,5000,587,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.434652732490832249823142774403,1,25
318,318_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,268.000000000000000000000000000000,5000,659,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.296808226833867816463197186749,1,25
319,319_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,203.000000000000000000000000000000,5000,138,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.147883750816170056463505488864,2,25
320,320_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,243.000000000000000000000000000000,269,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.569936472742659572254808608704,100,25
321,321_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,200.000000000000000000000000000000,642,1531,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.721796341756688497603988707851,74,25
322,322_0,RUNNING,BoTorch,GenerationStep_1,,,5000,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.832734446011483053773361007188,83,25
323,323_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,401.000000000000000000000000000000,764,600,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,25
324,324_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,196.000000000000000000000000000000,5000,4079,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.803829100998839196634548898146,100,25
325,325_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,207.000000000000000000000000000000,156,1846,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,68,25
326,326_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,167.000000000000000000000000000000,5000,594,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.446332051571011578783299000861,20,25
327,327_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,174.000000000000000000000000000000,4893,4337,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.348849923590979438259296330216,1,25
328,328_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,244.000000000000000000000000000000,4699,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.322855188433874396025657915743,100,25
329,329_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,1570.000000000000000000000000000000,5000,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,31,25
330,330_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,167.000000000000000000000000000000,1185,1018,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.012932205019385974165135877456,7,25
331,331_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,174.000000000000000000000000000000,1320,913,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.015414413932158992429077848385,26,25
332,332_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,251.000000000000000000000000000000,1032,1202,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,25
333,333_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,206.000000000000000000000000000000,1327,780,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.131641567666801378999608118647,1,25
334,334_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,160.000000000000000000000000000000,1045,1229,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,45,25
335,335_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,198.000000000000000000000000000000,1284,558,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.138210966592687917176007772468,40,25
336,336_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,216.000000000000000000000000000000,1336,879,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,25
337,337_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,212.000000000000000000000000000000,1546,456,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,25
338,338_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,162.000000000000000000000000000000,1232,963,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,58,25
339,339_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,213.000000000000000000000000000000,4009,4083,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,25
340,340_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,190.000000000000000000000000000000,1530,714,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.005399085796964481036297467398,45,25
341,341_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,205.000000000000000000000000000000,1289,889,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,25
342,342_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,247.000000000000000000000000000000,1930,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.517467779511990189078574076120,80,25
343,343_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,211.000000000000000000000000000000,1087,1221,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,25
344,344_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,194.000000000000000000000000000000,3998,1577,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.915573227508305276245437198668,1,25
345,345_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,303.000000000000000000000000000000,1622,1636,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,25
346,346_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,211.000000000000000000000000000000,1044,1308,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.144689324319884710101646874136,1,25
347,347_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,196.000000000000000000000000000000,1275,815,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.117066489569364953760022274309,57,25
348,348_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,282.000000000000000000000000000000,2061,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,4,25
349,349_0,FAILED,BoTorch,GenerationStep_1,,,3416,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,100,25
350,350_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,216.000000000000000000000000000000,2053,4050,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,25
351,351_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,171.000000000000000000000000000000,4693,2005,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,100,25
352,352_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,186.000000000000000000000000000000,4669,1696,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.815245592038954858260524360958,79,25
353,353_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,202.000000000000000000000000000000,890,4317,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,25
354,354_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,171.000000000000000000000000000000,2961,4698,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.935660738091772192781547801133,1,25
355,355_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,181.000000000000000000000000000000,1038,989,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.136181079525958897979975859016,33,25
356,356_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,221.000000000000000000000000000000,2133,4195,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.745979368852484392427015791327,100,25
357,357_0,FAILED,BoTorch,GenerationStep_1,,,3488,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,25
358,358_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,3137.000000000000000000000000000000,2504,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,39,25
359,359_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,262.000000000000000000000000000000,2546,1753,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,25
360,360_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,207.000000000000000000000000000000,1875,208,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.106239504518715430214648165475,1,25
361,361_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,203.000000000000000000000000000000,1982,1332,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.314446224728111012325371120824,1,25
362,362_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,206.000000000000000000000000000000,1881,488,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,25
363,363_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,272.000000000000000000000000000000,3371,506,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,25
364,364_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,254.000000000000000000000000000000,1879,9,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.270234962760957764249525325795,28,25
365,365_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,214.000000000000000000000000000000,2248,2136,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.610084622247039520814837487706,100,25
366,366_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,249.000000000000000000000000000000,1867,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,25
367,367_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,200.000000000000000000000000000000,1853,1029,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.127458626441503991566506215349,1,25
368,368_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,202.000000000000000000000000000000,1923,1424,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,25
369,369_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,183.000000000000000000000000000000,1879,709,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.250030272477203496794828652128,36,25
370,370_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,207.000000000000000000000000000000,2386,1619,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.698335188364988868059413107403,1,25
371,371_0,FAILED,BoTorch,GenerationStep_1,,,3487,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,25
372,372_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,223.000000000000000000000000000000,2116,2517,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.155149798694846463575913730892,1,25
373,373_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,267.000000000000000000000000000000,3991,838,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,25
374,374_0,FAILED,BoTorch,GenerationStep_1,,,4219,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.765007859824111124957823903969,1,25
375,375_0,FAILED,BoTorch,GenerationStep_1,,,3691,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,91,25
376,376_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,239.000000000000000000000000000000,2035,1613,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.480737888570965887780062075763,100,25
377,377_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,213.000000000000000000000000000000,1899,775,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.459659345703515909153935581344,1,25
378,378_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,173.000000000000000000000000000000,1509,4489,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,67,25
379,379_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,171.000000000000000000000000000000,2574,5000,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,82,25
380,380_0,FAILED,BoTorch,GenerationStep_1,,,4127,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,100,25
381,381_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,325.000000000000000000000000000000,1844,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.609136786333944080240598850651,1,25
382,382_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,173.000000000000000000000000000000,3090,4557,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,100,25
383,383_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,1301.000000000000000000000000000000,4140,85,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.933105489287526568276120997325,88,25
384,384_0,FAILED,BoTorch,GenerationStep_1,,,1377,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,25
385,385_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,266.000000000000000000000000000000,3929,154,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.681098475747072718000652002956,1,25
386,386_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,214.000000000000000000000000000000,3439,353,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.343527877076413301615787077026,4,25
387,387_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,248.000000000000000000000000000000,2228,1485,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.741532952518698329491542153846,100,25
388,388_0,FAILED,BoTorch,GenerationStep_1,,,4369,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,25
389,389_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,169.000000000000000000000000000000,2049,706,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.801263922969548958441521335772,34,25
390,390_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,210.000000000000000000000000000000,3758,435,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.528355725566471257081957446644,54,25
391,391_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,199.000000000000000000000000000000,297,1899,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,25
392,392_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,212.000000000000000000000000000000,2880,2188,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.486429946089650233620460539896,1,25
393,393_0,FAILED,BoTorch,GenerationStep_1,,,1291,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,25
394,394_0,FAILED,BoTorch,GenerationStep_1,,,3682,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.637242071752991967592549826804,100,25
395,395_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,189.000000000000000000000000000000,3620,43,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.779998524686435934505368550163,24,25
396,396_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,206.000000000000000000000000000000,494,74,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.774196562957898293255709631921,1,25
397,397_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,283.000000000000000000000000000000,3807,43,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.422805966163716850925169410402,43,25
398,398_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,268.000000000000000000000000000000,3770,727,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.477184413124626727320531927035,1,25
399,399_0,FAILED,BoTorch,GenerationStep_1,,,387,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,60,25
400,400_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,161.000000000000000000000000000000,2590,4409,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.026184771363501644497739917483,65,25
401,401_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,271.000000000000000000000000000000,3812,525,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.416958825526664966787393495906,1,25
402,402_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,166.000000000000000000000000000000,3610,21,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.580617295154744028629067997826,65,25
403,403_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,205.000000000000000000000000000000,3045,2636,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.417252158429571862185980535287,1,25
404,404_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,170.000000000000000000000000000000,2948,774,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.528791586544473668496380014403,100,25
405,405_0,FAILED,BoTorch,GenerationStep_1,,,1553,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,100,25
406,406_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,241.000000000000000000000000000000,3255,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,100,25
407,407_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,163.000000000000000000000000000000,3391,125,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.039161055407632379410376444184,44,25
408,408_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,267.000000000000000000000000000000,3640,517,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.792429430086777020214583444613,1,25
409,409_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,169.000000000000000000000000000000,3121,3359,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.438931774119498019359753016033,36,25
410,410_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,238.000000000000000000000000000000,1418,102,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.692311796909405807731729964871,36,25
411,411_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,196.000000000000000000000000000000,4734,4219,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.519467378914756139351993624587,1,25
412,412_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,169.000000000000000000000000000000,3288,4368,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.457388308380446306777855625114,100,25
413,413_0,FAILED,BoTorch,GenerationStep_1,,,1221,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,25
414,414_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,206.000000000000000000000000000000,3416,4663,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.170364060751760054701620106243,100,25
415,415_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,177.000000000000000000000000000000,1655,4614,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.443257578970954746466759388568,41,25
416,416_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,202.000000000000000000000000000000,2940,3525,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.479010826323223337652734699077,1,25
417,417_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,283.000000000000000000000000000000,1208,747,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.735088170006104602016705484857,1,25
418,418_0,FAILED,BoTorch,GenerationStep_1,,,166,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,57,25
419,419_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,279.000000000000000000000000000000,3758,18,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.506224772414589851976529644162,1,25
420,420_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,238.000000000000000000000000000000,418,323,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,64,25
421,421_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,189.000000000000000000000000000000,2863,4506,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,100,25
422,422_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,250.000000000000000000000000000000,1692,3586,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,25
423,423_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,222.000000000000000000000000000000,2315,666,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,44,25
424,424_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,200.000000000000000000000000000000,2620,4578,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.818861875458588572840312735934,36,25
425,425_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,293.000000000000000000000000000000,4822,1266,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,25
426,426_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,244.000000000000000000000000000000,4084,293,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,73,25
427,427_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,190.000000000000000000000000000000,2577,221,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,34,25
428,428_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,157.000000000000000000000000000000,4858,1123,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,21,25
429,429_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,197.000000000000000000000000000000,2881,4269,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,62,25
430,430_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,222.000000000000000000000000000000,4795,421,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,40,25
431,431_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,162.000000000000000000000000000000,2829,220,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.656174438689502981247869684012,64,25
432,432_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,177.000000000000000000000000000000,1072,4755,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,58,25
433,433_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,267.000000000000000000000000000000,4309,1242,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.353306517041787004895780910374,1,25
434,434_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,201.000000000000000000000000000000,40,3875,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.464082716004398265763342124046,1,25
435,435_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,160.000000000000000000000000000000,318,4420,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.263815770913058800228867539772,100,25
436,436_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,256.000000000000000000000000000000,510,416,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.320464021982252211806496688951,25,25
437,437_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,210.000000000000000000000000000000,2090,3135,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.278615762748492146183565409956,1,25
438,438_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,266.000000000000000000000000000000,180,2183,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,25
439,439_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,200.000000000000000000000000000000,4560,318,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,33,25
440,440_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,171.000000000000000000000000000000,31,596,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.562203554552934248178530651785,71,25
441,441_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,172.000000000000000000000000000000,1807,4349,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.246513779050833936601350160345,36,25
442,442_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,192.000000000000000000000000000000,1836,3626,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.390199849604466020291937411457,100,25
443,443_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,195.000000000000000000000000000000,4369,711,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.376257676993542899968048232040,45,25
444,444_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,215.000000000000000000000000000000,812,3389,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,25
445,445_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,163.000000000000000000000000000000,2557,3839,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.295517791837619281380966640427,1,25
446,446_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,166.000000000000000000000000000000,367,532,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.252842970575296366320117158466,100,25
447,447_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,363.000000000000000000000000000000,4545,1113,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,25
448,448_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,233.000000000000000000000000000000,4128,3647,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,25
449,449_0,COMPLETED,BoTorch,GenerationStep_1,0.100000000000000005551115123126,176.000000000000000000000000000000,3812,4712,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,25
450,450_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,229.000000000000000000000000000000,3120,488,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.561376764967602359668319422781,48,25
451,451_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,232.000000000000000000000000000000,4914,2008,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.943742951781810890388157986308,1,25
452,452_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,207.000000000000000000000000000000,1293,4144,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.570789554437399426767285604001,100,25
453,453_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,196.000000000000000000000000000000,3347,4583,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.298039142153652070188485367908,62,25
454,454_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,202.000000000000000000000000000000,4948,1863,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.725045928301556341644129588531,1,25
455,455_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,264.000000000000000000000000000000,2010,232,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,25
456,456_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,260.000000000000000000000000000000,1308,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,25
457,457_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,321.000000000000000000000000000000,2054,1273,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,25
458,458_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,166.000000000000000000000000000000,3438,5000,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,60,25
459,459_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,244.000000000000000000000000000000,3045,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,72,25
460,460_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,202.000000000000000000000000000000,3173,962,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.186484602056419396243214237074,1,25
461,461_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,180.000000000000000000000000000000,3651,4871,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,52,25
462,462_0,FAILED,BoTorch,GenerationStep_1,,,2518,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,90,25
463,463_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,249.000000000000000000000000000000,2034,1,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,66,25
464,464_0,FAILED,BoTorch,GenerationStep_1,,,707,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,25
465,465_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,649.000000000000000000000000000000,3245,45,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.758481435134582437918027153501,63,25
466,466_0,FAILED,BoTorch,GenerationStep_1,,,427,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,89,25
467,467_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,210.000000000000000000000000000000,3065,302,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.626930194162442222527431567869,1,25
468,468_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,192.000000000000000000000000000000,396,702,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.738483330678875060648636008409,18,25
469,469_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,194.000000000000000000000000000000,2473,74,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,95,25
470,470_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,163.000000000000000000000000000000,2293,5000,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,51,25
471,471_0,FAILED,BoTorch,GenerationStep_1,,,2304,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,39,25
472,472_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,173.000000000000000000000000000000,1302,5000,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.430073708150368327896018172396,69,25
473,473_0,FAILED,BoTorch,GenerationStep_1,,,1765,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,65,25
474,474_0,FAILED,BoTorch,GenerationStep_1,,,3295,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,25
475,475_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,208.000000000000000000000000000000,1255,4263,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.307874714667338122975337455500,1,25
476,476_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,179.000000000000000000000000000000,467,4794,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.541148149064331951407780252339,56,25
477,477_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,167.000000000000000000000000000000,3520,4295,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,100,25
478,478_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,181.000000000000000000000000000000,1642,566,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,25
479,479_0,COMPLETED,BoTorch,GenerationStep_1,0.110000000000000000555111512313,184.000000000000000000000000000000,434,4447,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.256551467520271969657841282242,100,25
480,480_0,COMPLETED,Sobol,SOBOL,0.110000000000000000555111512313,232.000000000000000000000000000000,4470,3863,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.568587420940399157487377124198,94,25
481,481_0,COMPLETED,Sobol,SOBOL,0.100000000000000005551115123126,275.000000000000000000000000000000,350,1193,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.288193865431472684424107910672,49,25
482,482_0,COMPLETED,Sobol,SOBOL,0.100000000000000005551115123126,224.000000000000000000000000000000,1438,2534,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.005175765106454491629173197964,51,25
483,483_0,COMPLETED,Sobol,SOBOL,0.100000000000000005551115123126,244.000000000000000000000000000000,3685,2373,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.847669251957908320704859761463,10,25
484,484_0,COMPLETED,Sobol,SOBOL,0.100000000000000005551115123126,211.000000000000000000000000000000,2517,3136,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.629304999629035632935369903862,65,25
485,485_0,COMPLETED,Sobol,SOBOL,0.110000000000000000555111512313,199.000000000000000000000000000000,2304,1725,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.473071187803521753245661329856,20,25
486,486_0,COMPLETED,Sobol,SOBOL,0.110000000000000000555111512313,218.000000000000000000000000000000,891,4472,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.194686448944732554133807411745,79,25
487,487_0,COMPLETED,Sobol,SOBOL,0.110000000000000000555111512313,235.000000000000000000000000000000,4232,552,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.911565582675859298333875813114,37,25
488,488_0,COMPLETED,Sobol,SOBOL,0.100000000000000005551115123126,228.000000000000000000000000000000,3969,2966,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.769208437506109454773195466259,73,25
489,489_0,COMPLETED,Sobol,SOBOL,0.110000000000000000555111512313,229.000000000000000000000000000000,1214,2171,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.114824077699333434998685277151,19,25
490,490_0,COMPLETED,Sobol,SOBOL,0.110000000000000000555111512313,229.000000000000000000000000000000,2000,4134,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.334498279251158214808725688272,84,25
491,491_0,COMPLETED,Sobol,SOBOL,0.110000000000000000555111512313,213.000000000000000000000000000000,2878,848,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.553470517344772816592524122825,27,25
492,492_0,COMPLETED,Sobol,SOBOL,0.100000000000000005551115123126,274.000000000000000000000000000000,3422,4738,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.958840798802673810463659265224,94,25
493,493_0,COMPLETED,Sobol,SOBOL,0.110000000000000000555111512313,252.000000000000000000000000000000,1760,203,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.178598730958998197504428162574,40,25
494,494_0,COMPLETED,Sobol,SOBOL,0.100000000000000005551115123126,234.000000000000000000000000000000,47,3572,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.395581175658851869059162709164,62,25
495,495_0,COMPLETED,Sobol,SOBOL,0.110000000000000000555111512313,295.000000000000000000000000000000,4831,1527,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.737982509914785644866697111866,4,25
496,496_0,COMPLETED,Sobol,SOBOL,0.110000000000000000555111512313,232.000000000000000000000000000000,4915,3709,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.136014410797506563044478866686,45,25
497,497_0,COMPLETED,Sobol,SOBOL,0.110000000000000000555111512313,245.000000000000000000000000000000,285,1350,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.978026630733162205544317657768,90,25
498,498_0,COMPLETED,Sobol,SOBOL,0.110000000000000000555111512313,237.000000000000000000000000000000,1698,4877,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.695527879156172312846706518030,13,25
499,499_0,COMPLETED,Sobol,SOBOL,0.110000000000000000555111512313,570.000000000000000000000000000000,3201,28,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.414653044648468471766733500772,54,25
500,500_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,25
501,501_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,302.000000000000000000000000000000,22,1008,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,44,25
502,502_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,246.000000000000000000000000000000,334,598,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.558225362864634089277160455822,100,25
503,503_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,305.000000000000000000000000000000,497,3889,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.318969811712510042944757060468,1,25
504,504_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,256.000000000000000000000000000000,4632,274,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,22,25
505,505_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,236.000000000000000000000000000000,996,3623,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.444527716181782717175252628294,1,25
506,506_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,421.000000000000000000000000000000,1136,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.949638093018795537147980212467,51,25
507,507_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,228.000000000000000000000000000000,4798,4056,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.446681838351661808506065654001,29,25
508,508_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,210.000000000000000000000000000000,1006,4486,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,25
509,509_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,176.000000000000000000000000000000,1387,4303,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.242748234590536848820363502455,45,25
510,510_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,235.000000000000000000000000000000,2801,4217,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,25,25
511,511_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,199.000000000000000000000000000000,4709,1314,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.186299878830038873056551551599,45,25
512,512_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,260.000000000000000000000000000000,712,4617,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,47,25
513,513_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,261.000000000000000000000000000000,3137,3628,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.591531042765077508249760285253,65,25
514,514_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,238.000000000000000000000000000000,2853,4250,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,52,25
515,515_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,248.000000000000000000000000000000,132,346,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,77,25
516,516_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,298.000000000000000000000000000000,886,258,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,57,25
517,517_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,402.000000000000000000000000000000,3804,643,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,74,25
518,518_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,243.000000000000000000000000000000,851,3891,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,50,25
519,519_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,356.000000000000000000000000000000,1356,1,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,25
520,520_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.100000000000000005551115123126,229.000000000000000000000000000000,422,2570,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.164697644332714776549408952633,31,25
521,521_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,388.000000000000000000000000000000,434,2527,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.113181777465687430361818144320,4,25
522,522_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,234.000000000000000000000000000000,60,4387,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.611790645430995594367118428636,22,25
523,523_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,322.000000000000000000000000000000,3259,4569,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.735195455422403831846622779267,100,25
524,524_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,251.000000000000000000000000000000,2126,3940,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,44,25
525,525_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,286.000000000000000000000000000000,1982,4691,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,25
526,526_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,235.000000000000000000000000000000,961,4059,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.684211789341599985192488020402,1,25
527,527_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,275.000000000000000000000000000000,4060,3251,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.330377661934819821798470229623,1,25
528,528_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,262.000000000000000000000000000000,4,4587,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,43,25
529,529_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,268.000000000000000000000000000000,2049,4242,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.653807936792050070629045421811,59,25
530,530_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,247.000000000000000000000000000000,1749,3540,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.427464207771481030651017363198,1,25
531,531_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,174.000000000000000000000000000000,3788,210,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,29,25
532,532_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,360.000000000000000000000000000000,2572,2324,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,25
533,533_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,325.000000000000000000000000000000,3596,3085,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,25
534,534_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,411.000000000000000000000000000000,5000,1849,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,25
535,535_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,187.000000000000000000000000000000,3643,4043,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,66,25
536,536_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,227.000000000000000000000000000000,2761,227,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,90,25
537,537_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,245.000000000000000000000000000000,170,4836,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,29,25
538,538_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,303.000000000000000000000000000000,3474,3935,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,100,25
539,539_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,252.000000000000000000000000000000,3262,3894,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,25
540,540_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,321.000000000000000000000000000000,4945,2848,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.487983487036425078731127769061,1,25
541,541_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,235.000000000000000000000000000000,4861,688,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,70,25
542,542_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,277.000000000000000000000000000000,2453,3400,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.506992999583983028344391641440,1,25
543,543_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,246.000000000000000000000000000000,4432,4976,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.269338980529308880118577462781,26,25
544,544_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.100000000000000005551115123126,293.000000000000000000000000000000,2513,945,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,39,25
545,545_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,196.000000000000000000000000000000,2712,3907,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,100,25
546,546_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,264.000000000000000000000000000000,923,4834,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.537436401671924968148630341602,82,25
547,547_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4639,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.723639473958450962776112191932,1,25
548,548_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,291.000000000000000000000000000000,2350,4546,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,25
549,549_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,253.000000000000000000000000000000,3657,4259,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.148792952062735628349088301547,80,25
550,550_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1022,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.713628445002457700852005473280,1,25
551,551_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,269.000000000000000000000000000000,4181,1158,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,25
552,552_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,197.000000000000000000000000000000,617,3294,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.432900275344055840420764980081,1,25
553,553_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,280.000000000000000000000000000000,1436,4562,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,72,25
554,554_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,245.000000000000000000000000000000,864,4250,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.094556772260360605342199846746,1,25
555,555_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,231.000000000000000000000000000000,2426,394,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.664158417931471567463574956491,77,25
556,556_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,332.000000000000000000000000000000,1960,3615,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,100,25
557,557_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,235.000000000000000000000000000000,413,4170,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,28,25
558,558_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,249.000000000000000000000000000000,3955,237,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.438355603493796153191652820169,45,25
559,559_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,201.000000000000000000000000000000,4575,3824,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.130579296807009859193726697413,24,25
560,560_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.100000000000000005551115123126,231.000000000000000000000000000000,3211,2878,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.569669314440646945563173630944,1,25
561,561_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,25
562,562_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,224.000000000000000000000000000000,1965,4505,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,25
563,561_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,25
564,564_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,246.000000000000000000000000000000,2791,3928,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.745003105818614730360138764809,43,25
565,565_0,RUNNING,BoTorch,BOTORCH_MODULAR,,,5000,1,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,100,25
566,566_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,270.000000000000000000000000000000,4684,902,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.188456004993952264126022555502,88,25
567,567_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,167.000000000000000000000000000000,4405,4850,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,25
568,568_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,308.000000000000000000000000000000,2680,1318,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.355707798032781241648336845174,40,25
569,569_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,251.000000000000000000000000000000,1242,3667,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.354216904199870119551718516959,38,25
570,570_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,275.000000000000000000000000000000,2159,967,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,9,25
571,571_0,FAILED,BoTorch,BOTORCH_MODULAR,,,2662,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,25
572,572_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,272.000000000000000000000000000000,3756,3661,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,25
573,573_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,277.000000000000000000000000000000,3749,408,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,38,25
574,574_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,256.000000000000000000000000000000,4853,3876,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,19,25
575,575_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,314.000000000000000000000000000000,1273,4874,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,71,25
576,576_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,226.000000000000000000000000000000,824,4760,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,82,25
577,577_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,312.000000000000000000000000000000,78,4103,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,25
578,578_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,312.000000000000000000000000000000,395,3320,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.716589876220009025509227740258,100,25
579,579_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,240.000000000000000000000000000000,3835,4375,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.006884260712372454980856328888,100,25
580,580_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,258.000000000000000000000000000000,1044,4261,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,65,25
581,581_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,485.000000000000000000000000000000,760,1201,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.421655438000955173905026640568,100,25
582,582_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.100000000000000005551115123126,244.000000000000000000000000000000,4218,1852,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,25
583,583_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,298.000000000000000000000000000000,1843,1211,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,70,25
584,584_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,257.000000000000000000000000000000,3390,3601,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,68,25
585,585_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1370,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.617234658705579475324043414730,1,25
586,586_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,233.000000000000000000000000000000,3091,4051,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,100,25
587,587_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,324.000000000000000000000000000000,5000,5000,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,25
588,588_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,251.000000000000000000000000000000,208,1041,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.480357341856725073014899862756,44,25
589,589_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4264,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,25
590,590_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,274.000000000000000000000000000000,3142,3451,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,65,25
591,591_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,236.000000000000000000000000000000,2583,199,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,100,25
592,592_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,260.000000000000000000000000000000,191,4000,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,25
593,593_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,323.000000000000000000000000000000,4993,4560,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,100,25
594,594_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,239.000000000000000000000000000000,3889,4010,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,76,25
595,595_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,201.000000000000000000000000000000,948,525,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.402023364291021034766515640513,32,25
596,596_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,224.000000000000000000000000000000,3819,222,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,25
597,597_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,256.000000000000000000000000000000,4300,1094,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.450857019376496748197524766510,100,25
598,598_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3702,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.473132416159768587338163570166,1,25
599,599_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,239.000000000000000000000000000000,2601,3845,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,73,25
600,600_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,308.000000000000000000000000000000,3650,2258,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.512648226352792169002725586324,1,25
601,601_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1718,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,25
602,602_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,253.000000000000000000000000000000,282,148,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.331853195202929773799382928701,73,25
603,603_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,249.000000000000000000000000000000,3123,171,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,72,25
604,604_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,276.000000000000000000000000000000,1,4794,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,25
605,605_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,216.000000000000000000000000000000,1332,1489,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.683542567803650413793548068497,100,25
606,606_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,681.000000000000000000000000000000,2106,781,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,100,25
607,607_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,266.000000000000000000000000000000,195,3845,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,87,25
608,608_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,359.000000000000000000000000000000,1780,4323,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,25
609,609_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,25
610,610_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,296.000000000000000000000000000000,1807,1622,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.279119837526944525318839396277,1,25
611,611_0,FAILED,BoTorch,BOTORCH_MODULAR,,,822,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.419441909528645462401641452743,1,25
612,612_0,FAILED,BoTorch,BOTORCH_MODULAR,,,2208,1,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,100,25
613,613_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,247.000000000000000000000000000000,1351,4212,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,29,25
614,614_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,288.000000000000000000000000000000,3181,422,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,50,25
615,615_0,FAILED,BoTorch,BOTORCH_MODULAR,,,616,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.746574320106507927086170184339,1,25
616,616_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.100000000000000005551115123126,242.000000000000000000000000000000,1,1804,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.740726896947487056799275251251,100,25
617,617_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.100000000000000005551115123126,251.000000000000000000000000000000,502,2010,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.697670084552463709570702121709,40,25
618,618_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,237.000000000000000000000000000000,4673,1629,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,52,25
619,561_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,25
620,561_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,25
621,621_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.100000000000000005551115123126,189.000000000000000000000000000000,231,838,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.940581827373391687885373357858,78,25
622,622_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,254.000000000000000000000000000000,3507,4366,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,38,25
623,609_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,25
624,624_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,267.000000000000000000000000000000,5000,4239,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,100,25
625,625_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,269.000000000000000000000000000000,3644,5000,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,100,25
626,561_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,25
627,627_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,252.000000000000000000000000000000,495,4549,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,70,25
628,628_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,175.000000000000000000000000000000,3433,4010,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,25
629,629_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,267.000000000000000000000000000000,4957,4796,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.815524207845276905004539003130,32,25
630,630_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,226.000000000000000000000000000000,1005,4515,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,27,25
631,631_0,FAILED,BoTorch,BOTORCH_MODULAR,,,868,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.942371749071947095721668574697,1,25
632,632_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,234.000000000000000000000000000000,4273,4741,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.588651453848575201277526502963,1,25
633,633_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,319.000000000000000000000000000000,4925,3807,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,25
634,634_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,288.000000000000000000000000000000,2546,1162,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,33,25
635,635_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,230.000000000000000000000000000000,1179,639,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,25
636,636_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,223.000000000000000000000000000000,2105,3390,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,41,25
637,637_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4009,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,1,25
638,638_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,241.000000000000000000000000000000,4938,3134,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,39,25
639,639_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,285.000000000000000000000000000000,4537,4470,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,97,25
640,640_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,209.000000000000000000000000000000,1741,4429,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.347596805431886923809514655659,39,25
641,500_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,25
642,642_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.100000000000000005551115123126,251.000000000000000000000000000000,1272,2967,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,34,25
643,643_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,227.000000000000000000000000000000,2491,3305,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,31,25
644,644_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,230.000000000000000000000000000000,1336,788,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.186718652510031418723102092372,1,25
645,645_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.100000000000000005551115123126,201.000000000000000000000000000000,4087,2152,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,25
646,646_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,273.000000000000000000000000000000,4264,3597,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,25
647,647_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,209.000000000000000000000000000000,529,3728,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,100,25
648,648_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.100000000000000005551115123126,270.000000000000000000000000000000,2192,1983,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,60,25
649,649_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,251.000000000000000000000000000000,4635,1305,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,43,25
650,650_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,256.000000000000000000000000000000,4537,1092,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.051550465683067349387247446657,1,25
651,651_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,248.000000000000000000000000000000,3086,3453,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,100,25
652,652_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,230.000000000000000000000000000000,4854,2721,str\(\&#039;KL\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,39,25
653,653_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.100000000000000005551115123126,226.000000000000000000000000000000,1079,1557,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.064768959365835113151099733386,1,25
654,654_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,228.000000000000000000000000000000,2849,1458,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,44,25
655,655_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,184.000000000000000000000000000000,2502,3347,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,71,25
656,656_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,255.000000000000000000000000000000,1372,3016,str\(\&#039;H\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,1,25
657,657_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,249.000000000000000000000000000000,4959,2201,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,59,25
658,658_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,231.000000000000000000000000000000,4158,1945,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,60,25
659,659_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,236.000000000000000000000000000000,3354,1351,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,73,25
660,660_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,224.000000000000000000000000000000,3552,3573,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.571641189404822669395400680514,28,25
661,661_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,222.000000000000000000000000000000,2123,3898,str\(\&#039;KL\&#039;\),3.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.001000000000000000020816681712,24,25
662,662_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.110000000000000000555111512313,280.000000000000000000000000000000,1,3708,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.998999999999999999111821580300,1,25
663,663_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.119999999999999995559107901499,225.000000000000000000000000000000,1295,4848,str\(\&#039;H\&#039;\),2.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.952289383452741167168653646513,14,25
664,664_0,FAILED,BoTorch,BOTORCH_MODULAR,,,2394,1,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,1,25
665,665_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4745,1,str\(\&#039;H\&#039;\),1.000000000000000000000000000000,str\(\&#039;stdev\&#039;\),0.998999999999999999111821580300,23,25
666,666_0,RUNNING,BoTorch,BOTORCH_MODULAR,,,3155,653,str\(\&#039;KL\&#039;\),1.000000000000000000000000000000,str\(\&#039;tstat\&#039;\),0.001000000000000000020816681712,29,25
</pre>
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			<button onclick='download_as_file("tab_results_csv_table_pre", "results.csv")'> Download &raquo;results.csv&laquo; as file</button>
			<script>
				createTable(tab_results_csv_json, tab_results_headers_json, 'tab_results_csv_table');</script>
			
			<h1>&nbsp;Errors</h1>
			<button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("simple_pre_tab_tab_errors")'> Copy raw data to clipboard</button>
			<button onclick='download_as_file("simple_pre_tab_tab_errors", "oo_errors.txt")'> Download &raquo;oo_errors.txt&laquo; as file</button>
<pre id='simple_pre_tab_tab_errors'><span style="background-color: black; color: white">
/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4549978/4549978_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4566518/4566518_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4567373/4567373_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4571480/4571480_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4571987/4571987_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4574647/4574647_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4579217/4579217_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4580431/4580431_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4583064/4583064_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4584367/4584367_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4586876/4586876_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4587471/4587471_0_log.err not found


⚠ Job 4587754 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4587754/4587754_0_result.pkl
has not produced any output (state: TIMEOUT)
No error stream produced. Look at stdout: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4587754/4587754_0_log.out
----------------------------------------
submitit INFO (2025-04-19 10:10:54,152) - Starting with JobEnvironment(job_id=4587754, hostname=i7170, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-04-19 10:10:54,164) - Loading pickle: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4587754/4587754_submitted.pkl
slurmstepd: error: *** JOB 4587754 ON i7170 CANCELLED AT 2025-04-19T10:41:16 DUE TO TIME LIMIT ***



/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4587754/4587754_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4588675/4588675_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4589973/4589973_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4590342/4590342_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4591260/4591260_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4592177/4592177_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4593648/4593648_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4595576/4595576_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4596982/4596982_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4604733/4604733_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDBD_RialtoBridgeTimelapse_ft_25_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4604853/4604853_0_log.err not found

</span></pre><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("simple_pre_tab_tab_errors")'> Copy raw data to clipboard</button>
			<button onclick='download_as_file("simple_pre_tab_tab_errors", "oo_errors.txt")'> Download &raquo;oo_errors.txt&laquo; as file</button>
			
			<h1>&nbsp;Args Overview</h1>
			<h2>Arguments Overview:                                                                                      </h2><table cellspacing="0" cellpadding="5"><thead><tr><th> Key</th><th>Value                                                                                                                                          </th></tr></thead><tbody><tr><td> config_yaml</td><td>None                                                                                                                                           </td></tr><tr><td> config_toml</td><td>None                                                                                                                                           </td></tr><tr><td> config_json</td><td>None                                                                                                                                           </td></tr><tr><td> num_random_steps</td><td>20                                                                                                                                             </td></tr><tr><td> max_eval</td><td>None                                                                                                                                           </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/CDBD_RialtoBridgeTimelapse_ft_25_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>30                                                                                                                                             </td></tr><tr><td> slurm_use_srun</td><td>False                                                                                                                                          </td></tr><tr><td> time</td><td></td></tr><tr><td> partition</td><td></td></tr><tr><td> reservation</td><td>None                                                                                                                                           </td></tr><tr><td> force_local_execution</td><td>False                                                                                                                                          </td></tr><tr><td> slurm_signal_delay_s</td><td>0                                                                                                                                              </td></tr><tr><td> nodes_per_job</td><td>1                                                                                                                                              </td></tr><tr><td> cpus_per_task</td><td>1                                                                                                                                              </td></tr><tr><td> account</td><td>None                                                                                                                                           </td></tr><tr><td> gpus</td><td>0                                                                                                                                              </td></tr><tr><td> run_mode</td><td>local                                                                                                                                          </td></tr><tr><td> verbose</td><td>False                                                                                                                                          </td></tr><tr><td> verbose_break_run_search_table</td><td>False                                                                                                                                          </td></tr><tr><td> debug</td><td>False                                                                                                                                          </td></tr><tr><td> no_sleep</td><td>False                                                                                                                                          </td></tr><tr><td> tests</td><td>False                                                                                                                                          </td></tr><tr><td> show_worker_percentage_table_at_end</td><td>False                                                                                                                                          </td></tr><tr><td> auto_exclude_defective_hosts</td><td>False                                                                                                                                          </td></tr><tr><td> run_tests_that_fail_on_taurus</td><td>False                                                                                                                                          </td></tr><tr><td> raise_in_eval</td><td>False                                                                                                                                          </td></tr><tr><td> show_ram_every_n_seconds</td><td>False                                                                                                                                          </td></tr></tbody></table>
			<h1>&nbsp;Worker-Usage</h1>
			<div class='invert_in_dark_mode' id='workerUsagePlot'></div><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("pre_tab_worker_usage")'> Copy raw data to clipboard</button>
			<button onclick='download_as_file("pre_tab_worker_usage", "worker_usage.csv")'> Download &raquo;worker_usage.csv&laquo; as file</button>
<pre id="pre_tab_worker_usage">1744998970.9520757,20,0,0
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1745080128.1429791,20,1,5
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			<h1>&nbsp;CPU/RAM-Usage (main)</h1>
			<div class='invert_in_dark_mode' id='mainWorkerCPURAM'></div><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("pre_tab_main_worker_cpu_ram")'> Copy raw data to clipboard</button>
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<pre id="pre_tab_main_worker_cpu_ram">timestamp,ram_usage_mb,cpu_usage_percent
1744998970,646.27734375,21.6
1744998970,646.28125,22.9
1744998970,646.33203125,22.6
1744998970,646.33203125,25.5
1744998970,646.33203125,20.0
1744998971,646.33203125,23.0
1744998971,646.33203125,24.5
1744999658,708.50390625,31.9
1744999658,708.50390625,32.5
1744999659,708.50390625,25.7
1744999659,708.50390625,26.1
1745007163,956.96484375,8.9
1745007163,956.96484375,7.3
1745007164,956.96484375,7.2
1745007164,956.96484375,3.1
1745015042,968.09765625,7.1
1745015042,968.09765625,7.2
1745015042,968.09765625,7.1
1745015042,968.09765625,7.0
1745024256,1032.59765625,7.3
1745024256,1032.59765625,7.0
1745024256,1032.59765625,7.2
1745024256,1032.59765625,7.5
1745033287,1031.38671875,7.3
1745033287,1031.38671875,6.2
1745033287,1031.38671875,6.1
1745033287,1031.38671875,4.9
1745043126,1069.73046875,7.4
1745043126,1069.73046875,6.5
1745043126,1069.73046875,6.9
1745043126,1069.73046875,3.2
1745054372,1045.80859375,7.5
1745054372,1045.80859375,7.2
1745054372,1045.80859375,7.1
1745054372,1045.80859375,3.1
1745066122,1057.9375,7.4
1745066122,1057.9375,6.4
1745066122,1057.9375,6.5
1745066122,1057.9375,6.3
1745080135,1092.99609375,7.5
1745080135,1092.99609375,7.3
1745080135,1092.99609375,7.3
1745080135,1092.99609375,5.9
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			<h1>&nbsp;Parallel Plot</h1>
			<div class="invert_in_dark_mode" id="parallel-plot"></div>
			<h1>&nbsp;Scatter-2D</h1>
			<div class='invert_in_dark_mode' id='plotScatter2d'></div>
			<h1>&nbsp;Scatter-3D</h1>
			<div class='invert_in_dark_mode' id='plotScatter3d'></div>
			<h1>&nbsp;Job Status Distribution</h1>
			<div class="invert_in_dark_mode" id="plotJobStatusDistribution"></div>
			<h1>&nbsp;Boxplots</h1>
			<div class="invert_in_dark_mode" id="plotBoxplot"></div>
			<h1>&nbsp;Violin</h1>
			<div class="invert_in_dark_mode" id="plotViolin"></div>
			<h1>&nbsp;Histogram</h1>
			<div class="invert_in_dark_mode" id="plotHistogram"></div>
			<h1>&nbsp;Heatmap</h1>
			<div class="invert_in_dark_mode" id="plotHeatmap"></div><br>
			    <h1>Correlation Heatmap Explanation</h1>
			
			    <p>
			        This is a heatmap that visualizes the correlation between numerical columns in a dataset. The values represented in the heatmap show the strength and direction of relationships between different variables.
			    </p>
			
			    <h2>How It Works</h2>
			    <p>
			        The heatmap uses a matrix to represent correlations between each pair of numerical columns. The calculation behind this is based on the concept of "correlation," which measures how strongly two variables are related. A correlation can be positive, negative, or zero:
			    </p>
			    <ul>
			        <li><strong>Positive correlation</strong>: Both variables increase or decrease together (e.g., if the temperature rises, ice cream sales increase).</li>
			        <li><strong>Negative correlation</strong>: As one variable increases, the other decreases (e.g., as the price of a product rises, the demand for it decreases).</li>
			        <li><strong>Zero correlation</strong>: There is no relationship between the two variables (e.g., height and shoe size might show zero correlation in some contexts).</li>
			    </ul>
			
			    <h2>Color Scale: Yellow to Purple (Viridis)</h2>
			    <p>
			        The heatmap uses a color scale called "Viridis," which ranges from yellow to purple. Here's what the colors represent:
			    </p>
			    <ul>
			        <li><strong>Yellow (brightest)</strong>: A strong positive correlation (close to +1). This indicates that as one variable increases, the other increases in a very predictable manner.</li>
			        <li><strong>Green</strong>: A moderate positive correlation. Variables are still positively related, but the relationship is not as strong.</li>
			        <li><strong>Blue</strong>: A weak or near-zero correlation. There is a small or no discernible relationship between the variables.</li>
			        <li><strong>Purple (darkest)</strong>: A strong negative correlation (close to -1). This indicates that as one variable increases, the other decreases in a very predictable manner.</li>
			    </ul>
			
			    <h2>What the Heatmap Shows</h2>
			    <p>
			        In the heatmap, each cell represents the correlation between two numerical columns. The color of the cell is determined by the correlation coefficient: from yellow for strong positive correlations, through green and blue for weaker correlations, to purple for strong negative correlations.
			    </p>
			
			<h1>&nbsp;Result-Pairs</h1>
			<div class="invert_in_dark_mode" id="plotResultPairs"></div>
			<h1>&nbsp;Evolution</h1>
			<div class="invert_in_dark_mode" id="plotResultEvolution"></div>
			<h1>&nbsp;Exit-Codes</h1>
			<div class="invert_in_dark_mode" id="plotExitCodesPieChart"></div>
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