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lambda_exploration_scipy.txt
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Loaded voltage protocol for model fitting.
Loaded voltage protocol for validation.
Inner optimisation is split into 27 segments based on protocol steps.
Number of B-spline coeffs per segment: 32.
Produced synthetic data for the Kemp model based on the pre-loaded voltage protocol.
===========================================================================================================
Starting optimisation for lambda: 1.00E+05.
Iteration: 0
Best parameters: [ -8.38605314 -2.7626238 -10.20205684 -2.80569737 -2.52986044
-4.69450614 -5.27506692 -3.39848363 -1.80584604]
Best objective: 1760.2696266388843
Mean objective: 3013.295545181043
Inner objective at best sample: 2468.399566410424
Gradient objective at best sample: 0.0070812993977154
Time elapsed: 119.8998658657074
Iteration: 1
Best parameters: [ -8.35689785 -2.84484695 -10.17475501 -2.65777055 -2.4510016
-4.71982416 -5.18056545 -3.57371877 -1.69605645]
Best objective: 1314.9963063650794
Mean objective: 2322.811280043243
Inner objective at best sample: 1854.276402421738
Gradient objective at best sample: 0.005392800960566588
Time elapsed: 117.45059275627136
Iteration: 2
Best parameters: [ -8.37079666 -2.57854131 -10.4003341 -2.65577081 -2.53122273
-4.79196554 -5.09572848 -3.62256189 -1.59766087]
Best objective: 531.4713749425343
Mean objective: 1834.6646508435558
Inner objective at best sample: 867.0571043771838
Gradient objective at best sample: 0.0033558572943464945
Time elapsed: 119.33432078361511
Iteration: 3
Best parameters: [ -8.02776204 -2.88721924 -10.438161 -2.68807047 -2.74060804
-4.87570868 -5.0894384 -3.5708848 -1.59533885]
Best objective: 335.87431729765603
Mean objective: 1164.2242022566977
Inner objective at best sample: 596.282731852906
Gradient objective at best sample: 0.0026040841455524984
Time elapsed: 120.4277892112732
Iteration: 4
Best parameters: [-8.41897102 -2.80455908 -9.97176044 -2.63978432 -2.51970159 -5.15335686
-4.39775462 -3.41609204 -1.60391356]
Best objective: 303.7365486353153
Mean objective: 824.271507404999
Inner objective at best sample: 2022.3060812897154
Gradient objective at best sample: 0.017185695326544
Time elapsed: 127.2904098033905
Iteration: 5
Best parameters: [ -8.78644217 -2.87180504 -10.13096713 -2.57362017 -2.43602513
-4.99773659 -4.41116113 -3.61656012 -1.32266618]
Best objective: 311.1669893532753
Mean objective: 789.2679823353486
Inner objective at best sample: 892.0642809142603
Gradient objective at best sample: 0.00580897291560985
Time elapsed: 136.07221007347107
Iteration: 6
Best parameters: [ -8.55353956 -3.08769034 -10.60883967 -2.67168462 -2.70361205
-5.26729292 -4.28654462 -3.34784217 -1.26559188]
Best objective: 289.74484070362604
Mean objective: 918.5743874096931
Inner objective at best sample: 4567.845198986256
Gradient objective at best sample: 0.0427810035828263
Time elapsed: 149.3226125240326
Iteration: 7
Best parameters: [ -8.46983477 -3.43953069 -11.26293657 -2.62066579 -2.49732157
-4.46581568 -4.77540185 -3.75333555 -0.91203581]
Best objective: 284.99304412815655
Mean objective: 964.6767885909399
Inner objective at best sample: 495.55072893837877
Gradient objective at best sample: 0.002105576848102222
Time elapsed: 142.80567026138306
Iteration: 8
Best parameters: [-8.49528883 -3.6310356 -9.7547541 -2.94476566 -2.63711331 -3.87565498
-3.27440246 -3.85230423 -0.03090353]
Best objective: 154.88263864063964
Mean objective: 981.9784846612836
Inner objective at best sample: 1072.3665310456354
Gradient objective at best sample: 0.009174838924049957
Time elapsed: 120.90904808044434
Iteration: 9
Best parameters: [ -8.12996257 -3.78083621 -10.25305527 -2.73162381 -1.82958862
-4.89997434 -3.51992072 -3.83488798 -1.03175211]
Best objective: 208.64115563190396
Mean objective: 829.5173305041994
Inner objective at best sample: 941.2898131079805
Gradient objective at best sample: 0.007326486574760765
Time elapsed: 158.25079345703125
Iteration: 10
Best parameters: [ -8.97503317 -4.97536818 -10.30889511 -2.74545467 -1.94211289
-5.53888914 -2.73134229 -3.62659367 0.44474455]
Best objective: 149.61802819530502
Mean objective: 671.7583125429339
Inner objective at best sample: 12981.108282499328
Gradient objective at best sample: 0.12831490254304023
Time elapsed: 161.06346344947815
Iteration: 11
Best parameters: [-9.70407237 -4.22813104 -8.33265081 -2.99223457 -2.28799711 -3.69985644
-0.92667651 -3.42256364 1.30951926]
Best objective: 136.25525908246894
Mean objective: 556.8748165199988
Inner objective at best sample: 4606641.581465165
Gradient objective at best sample: 46.06505326206083
Time elapsed: 158.94502305984497
Iteration: 12
Best parameters: [-9.97230842 -6.26803199 -9.81712291 -2.85293885 -3.04075373 -3.97500857
-5.11355716 -3.23764991 1.91828446]
Best objective: 158.44588240488946
Mean objective: 1632.4102937422301
Inner objective at best sample: 2216.708387000605
Gradient objective at best sample: 0.02058262504595716
Time elapsed: 148.55988025665283
Iteration: 13
Best parameters: [-9.07169033 -3.69207617 -8.41646475 -3.89980261 -0.42414114 -3.26397393
-0.52023043 -5.2206452 -0.44396146]
Best objective: 162.33018041279826
Mean objective: 2464.2226699446064
Inner objective at best sample: 39927.66914726677
Gradient objective at best sample: 0.39765338966853975
Time elapsed: 138.96279764175415
Iteration: 14
Best parameters: [-9.83393947 -3.65149851 -8.83591107 -3.65208435 -1.22014051 -3.35588014
-2.16838756 -6.08687474 0.54706792]
Best objective: 153.27868657722067
Mean objective: 4458.615985183043
Inner objective at best sample: 8369.647294212866
Gradient objective at best sample: 0.08216368607635643
Time elapsed: 215.92501068115234
Iteration: 15
Best parameters: [-11.14160286 -2.84628641 -10.81270749 -4.4047037 -2.57627112
-4.16226031 -4.15950321 -4.46159302 1.85764471]
Best objective: 149.705797722577
Mean objective: 4557.652066603658
Inner objective at best sample: 221.0603750488229
Gradient objective at best sample: 0.0007135457732624591
Time elapsed: 244.41695928573608
Iteration: 16
Best parameters: [-9.6956275 -3.95340785 -7.5085738 -4.91971127 -2.37916194 -4.08726118
-1.14041829 -5.82311891 0.18907597]
Best objective: 161.298549972761
Mean objective: 2182.455052181471
Inner objective at best sample: 649.5155839037045
Gradient objective at best sample: 0.004882170339309435
Time elapsed: 156.22217106819153
Iteration: 17
Best parameters: [-9.84550165 -5.48856937 -6.07736836 -3.49526085 -3.14652282 -4.90385286
-3.11894933 -3.38212912 1.62642064]
Best objective: 134.572428171549
Mean objective: 604.6320317878473
Inner objective at best sample: 22425.780706204565
Gradient objective at best sample: 0.22291208278033017
Time elapsed: 183.47776293754578
Iteration: 18
Best parameters: [-12.14092026 -2.28191194 -7.57697537 -3.06668441 -1.8658002
-5.27637802 -0.52413305 -5.01370503 2.2641036 ]
Best objective: 133.2895944281305
Mean objective: 347.2428055792571
Inner objective at best sample: 1295.8295798260574
Gradient objective at best sample: 0.01162539985397927
Time elapsed: 190.30594325065613
Iteration: 19
Best parameters: [-11.54753803 -2.72493495 -6.43830322 -5.304913 -1.0897858
-3.36815905 1.56717072 -6.66098938 2.05377942]
Best objective: 133.38649340013643
Mean objective: 256933.0596461158
Inner objective at best sample: 554531.8000852914
Gradient objective at best sample: 5.5439841359189135
Time elapsed: 165.77941226959229
Iteration: 20
Best parameters: [-10.98034778 -5.1757029 -6.61973459 -3.79348969 -1.76032901
-3.43909263 -1.37669462 -3.85091401 1.96811851]
Best objective: 133.49610568079316
Mean objective: 3923.2349851213685
Inner objective at best sample: 107817.56568622435
Gradient objective at best sample: 1.0768406958054355
Time elapsed: 124.31051731109619
Iteration: 21
Best parameters: [-13.81674193 -2.13260199 -4.4583871 -5.7521632 -2.35978406
-4.84307577 4.25223023 -6.6773919 2.20296478]
Best objective: 132.97535067050913
Mean objective: 685.3323936754721
Inner objective at best sample: 617071656.6600287
Gradient objective at best sample: 6170.7152368467805
Time elapsed: 120.79117274284363
Iteration: 22
Best parameters: [-11.15117312 -3.92183961 -5.68826243 -4.13651164 -2.22956809
-4.40404433 -0.68512894 -6.39437908 2.27813838]
Best objective: 133.30080183251334
Mean objective: 154.7727320506566
Inner objective at best sample: 546.3209774451136
Gradient objective at best sample: 0.004130201756126003
Time elapsed: 129.7972493171692
Iteration: 23
Best parameters: [-13.74859952 -2.35136677 -5.62544297 -4.55594826 -1.10599855
-4.98868333 1.09138356 -6.10899267 2.18236773]
Best objective: 133.1414624739593
Mean objective: 147.70186990906387
Inner objective at best sample: 804.8921465074477
Gradient objective at best sample: 0.006717506840334884
Time elapsed: 78.30866169929504
Iteration: 24
Best parameters: [-12.04044087 -3.61590234 -4.22740987 -4.55359422 -2.75464393
-4.24752567 0.81604018 -6.53103111 2.15349275]
Best objective: 133.12550017071356
Mean objective: 121860.5137034247
Inner objective at best sample: 34056.05263686356
Gradient objective at best sample: 0.3392292713669285
Time elapsed: 140.92099618911743
Iteration: 25
Best parameters: [-11.92791949 -3.16419599 -6.4231855 -3.69867216 -1.93233645
-4.24986574 -0.40001942 -6.74962123 1.99317979]
Best objective: 134.06038058270212
Mean objective: 388.719867595404
Inner objective at best sample: 1145.9753105118598
Gradient objective at best sample: 0.010119149299291575
Time elapsed: 161.97697806358337
Iteration: 26
Best parameters: [-10.15898483 -5.24541053 -4.55853903 -4.76371262 -1.98037352
-4.82854256 2.48248167 -5.49612404 2.26128178]
Best objective: 132.93625338929613
Mean objective: 150.43478720568325
Inner objective at best sample: 5332383.130333099
Gradient objective at best sample: 53.322501940797096
Time elapsed: 105.8512876033783
Iteration: 27
Best parameters: [-10.53286773 -5.12122001 -4.94135234 -4.76902172 -4.4774482
-5.49532055 3.6827577 -4.86188341 2.28424935]
Best objective: 132.91290682240142
Mean objective: 655.4684730568571
Inner objective at best sample: 444416998.4188248
Gradient objective at best sample: 4444.168655059179
Time elapsed: 160.04068994522095
Iteration: 28
Best parameters: [-11.2803428 -3.41685802 -4.80980745 -5.0170298 -3.37530706
-5.83719546 2.04980291 -6.98206574 1.89926844]
Best objective: 133.77044515715465
Mean objective: 141.63280504398958
Inner objective at best sample: 3451813.651245533
Gradient objective at best sample: 34.516798808003756
Time elapsed: 162.0398461818695
Iteration: 29
Best parameters: [-11.40845832 -4.17786189 -4.74824907 -5.13991517 -2.55737663
-3.92673022 4.0059875 -6.49952921 2.12613368]
Best objective: 133.14073591196131
Mean objective: 442.54240963496176
Inner objective at best sample: 385422533.41272295
Gradient objective at best sample: 3854.2240027198704
Time elapsed: 154.20910596847534
Iteration: 30
Best parameters: [-12.22963362 -2.69357739 -5.00687447 -6.33054737 -1.8999842
-4.86764513 3.65941102 -6.23208866 2.26670241]
Best objective: 132.85730637547178
Mean objective: 135.2848791759807
Inner objective at best sample: 126002186.44253604
Gradient objective at best sample: 1260.0205358522967
Time elapsed: 66.87962436676025
Iteration: 31
Best parameters: [-11.94722867 -2.94312844 -6.27301517 -5.60787544 -2.46613133
-5.1440902 1.95042243 -5.72339172 2.20034117]
Best objective: 133.00296629671286
Mean objective: 171.97872611641614
Inner objective at best sample: 904928.7785996132
Gradient objective at best sample: 9.047957756333165
Time elapsed: 49.00385522842407
Iteration: 32
Best parameters: [-12.99506893 -2.15165477 -4.14244707 -5.50088726 -2.9744491
-4.64938217 2.64912985 -7.16679175 2.25440868]
Best objective: 132.87103712326018
Mean objective: 152.7553013696184
Inner objective at best sample: 15697741.321217466
Gradient objective at best sample: 156.97608450180343
Time elapsed: 90.24937677383423
Iteration: 33
Best parameters: [-12.08189149 -2.07277243 -3.68568144 -6.03236904 -3.22769505
-5.16769659 2.62035703 -5.96001558 2.27499617]
Best objective: 132.81440884710574
Mean objective: 133.9197823824837
Inner objective at best sample: 19803093.389866054
Gradient objective at best sample: 198.0296057545721
Time elapsed: 81.89633893966675
Iteration: 34
Best parameters: [-12.0192852 -2.93166695 -5.22473473 -5.70200909 -2.75460076
-4.63355215 0.71006185 -5.43788941 2.28429054]
Best objective: 132.84306282268713
Mean objective: 1937.8246172509005
Inner objective at best sample: 22595.39479040592
Gradient objective at best sample: 0.22462551727583233
Time elapsed: 71.96203875541687
Iteration: 35
Best parameters: [-13.25746185 -2.37440072 -5.32768272 -6.46811617 -2.50460325
-4.59084243 2.81423987 -6.24510123 2.25036616]
Best objective: 132.8845297679897
Mean objective: 277.3160211209698
Inner objective at best sample: 20009479.715395536
Gradient objective at best sample: 200.09346830865766
Time elapsed: 94.16713237762451
Iteration: 36
Best parameters: [-11.4569617 -2.88046171 -5.06864232 -6.16193164 -3.09515479
-4.86254698 1.7668995 -4.93491831 2.28539725]
Best objective: 132.8298905929796
Mean objective: 133.14503303719457
Inner objective at best sample: 4193104.040556475
Gradient objective at best sample: 41.92971210665882
Time elapsed: 71.20582008361816
Iteration: 37
Best parameters: [-11.77454747 -3.36253338 -5.05381526 -5.4721594 -2.81380654
-4.94899643 2.5681608 -5.56707145 2.30204797]
Best objective: 132.7999874517235
Mean objective: 133.30876155179783
Inner objective at best sample: 15891708.237935022
Gradient objective at best sample: 158.9157543794757
Time elapsed: 77.89690065383911
Iteration: 38
Best parameters: [-11.17351354 -3.73599146 -5.55468414 -5.66256747 -3.105842
-4.89503429 3.32355176 -4.19816728 2.24122823]
Best objective: 132.92357719462103
Mean objective: 133.52292120578085
Inner objective at best sample: 627337346.6226652
Gradient objective at best sample: 6273.37213699088
Time elapsed: 85.9584493637085
Iteration: 39
Best parameters: [-11.76392918 -2.8882456 -6.26169102 -4.65712275 -3.27242503
-5.88231702 1.8559294 -3.51924068 2.2705933 ]
Best objective: 132.85788397499448
Mean objective: 133.39664547618187
Inner objective at best sample: 631644448.1266348
Gradient objective at best sample: 6316.443152687509
Time elapsed: 57.17237639427185
Iteration: 40
Best parameters: [-12.47483189 -2.80878033 -6.1960808 -6.05764506 -3.0969128
-5.8709066 1.60094905 -4.19257815 2.30218893]
Best objective: 132.82700265974444
Mean objective: 134.00137701790223
Inner objective at best sample: 13524804.545076137
Gradient objective at best sample: 135.24671718073478
Time elapsed: 59.760969400405884
Iteration: 41
Best parameters: [-12.42308694 -3.21612862 -5.4908774 -6.60583656 -3.01912981
-5.27995453 1.678169 -5.33922676 2.2492408 ]
Best objective: 132.90566799385127
Mean objective: 133.29779421027138
Inner objective at best sample: 1370986.7863770667
Gradient objective at best sample: 13.708538807090727
Time elapsed: 54.20409393310547
Iteration: 42
Best parameters: [-12.79849461 -2.29224662 -5.52230147 -7.01983716 -2.61457846
-5.35704049 2.40205445 -5.17300214 2.29891272]
Best objective: 132.8123687698789
Mean objective: 133.1126911461763
Inner objective at best sample: 10531913.176416885
Gradient objective at best sample: 105.31780364048116
Time elapsed: 82.20068407058716
Iteration: 43
Best parameters: [-12.19250427 -2.11853786 -4.79759997 -5.53026902 -2.61079029
-6.02048058 2.85246087 -5.96587029 2.29813599]
Best objective: 132.76269503337602
Mean objective: 133.14837908772358
Inner objective at best sample: 21778248.6832415
Gradient objective at best sample: 217.7811592054647
Time elapsed: 60.46772837638855
Iteration: 44
Best parameters: [-12.5798494 -2.25568845 -5.6919762 -5.95937824 -3.21215118
-6.68507348 1.57472562 -5.68700421 2.27894775]
Best objective: 132.8376146063706
Mean objective: 133.3292853756762
Inner objective at best sample: 505390.927856175
Gradient objective at best sample: 5.052580902415686
Time elapsed: 104.97146320343018
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Best parameters: [-12.70252021 -1.91831323 -5.29406932 -5.48186572 -2.62135695
-5.74254782 3.27209134 -5.48500735 2.28948796]
Best objective: 132.7571798206522
Mean objective: 132.98167599033823
Inner objective at best sample: 86685822.62484759
Gradient objective at best sample: 866.8568986766776
Time elapsed: 93.1121289730072
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Best parameters: [-12.57934966 -1.96028793 -5.45871024 -5.12775038 -2.63031848
-5.76355846 2.59921825 -5.80349132 2.26381604]
Best objective: 132.80237577664047
Mean objective: 138.965170927634
Inner objective at best sample: 10964290.295873247
Gradient objective at best sample: 109.64157493497471
Time elapsed: 81.25241541862488
Iteration: 47
Best parameters: [-13.00148285 -1.73877492 -5.67994109 -6.41201618 -2.95412019
-5.57580896 2.36841574 -4.5922434 2.28372653]
Best objective: 132.7859113058001
Mean objective: 142.41482099356173
Inner objective at best sample: 29098922.01078618
Gradient objective at best sample: 290.9878922487487
Time elapsed: 102.93213987350464
Iteration: 48
Best parameters: [-12.95030881 -1.7777644 -5.1450492 -5.44918851 -3.07002737
-6.86349792 1.50296203 -4.68900259 2.27195139]
Best objective: 132.7986352440276
Mean objective: 134.22280785352953
Inner objective at best sample: 1865728.5077402894
Gradient objective at best sample: 18.655957091050453
Time elapsed: 67.89928674697876
Iteration: 49
Best parameters: [-12.83980313 -1.89110146 -5.64572499 -6.713587 -2.82602048
-5.37126783 2.27646511 -5.13952255 2.27539546]
Best objective: 132.7955251669606
Mean objective: 132.92191698624595
Inner objective at best sample: 9245033.47317367
Gradient objective at best sample: 92.44900677648504
Time elapsed: 90.57422757148743
Iteration: 50
Best parameters: [-12.86500624 -2.10065166 -5.73595948 -5.53303888 -2.40188474
-6.08060902 1.81025686 -4.64785567 2.29417254]
Best objective: 132.805549887059
Mean objective: 132.87816854026048
Inner objective at best sample: 2592421.364656972
Gradient objective at best sample: 25.922885591070848
Time elapsed: 48.28258752822876
Iteration: 51
Best parameters: [-12.96070326 -2.32712325 -5.88411745 -6.21571557 -2.63351484
-5.25956737 2.54865726 -5.13988935 2.29680496]
Best objective: 132.80102063546715
Mean objective: 132.88055502137078
Inner objective at best sample: 17491404.275745686
Gradient objective at best sample: 174.9127147472505
Time elapsed: 50.579362869262695
Iteration: 52
Best parameters: [-12.42832319 -2.18794786 -5.74014658 -5.32279502 -2.38921975
-5.83868365 3.2062417 -4.95873502 2.29467556]
Best objective: 132.7975813115745
Mean objective: 133.0442089151374
Inner objective at best sample: 98662125.4747935
Gradient objective at best sample: 986.6199267721217
Time elapsed: 54.37299156188965
Iteration: 53
Best parameters: [-12.268755 -1.98234411 -4.33200474 -6.59733183 -2.67768643
-5.92416638 3.35296417 -4.69175244 2.29599954]
Best objective: 132.7509759350644
Mean objective: 132.89414984243402
Inner objective at best sample: 221216904.61693683
Gradient objective at best sample: 2212.167718659609
Time elapsed: 47.35390019416809
Iteration: 54
Best parameters: [-12.54602841 -1.79784394 -4.68660158 -5.80349129 -2.24559815
-6.72904975 3.17251301 -4.82934012 2.30147311]
Best objective: 132.78252853489
Mean objective: 133.36251527930716
Inner objective at best sample: 93760327.42504197
Gradient objective at best sample: 937.6019464251344
Time elapsed: 41.996023178100586
Iteration: 55
Best parameters: [-12.64957978 -1.84218467 -5.5985696 -6.04862572 -2.30964508
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Best objective: 132.74520475352224
Mean objective: 133.61391488248717
Inner objective at best sample: 46702917.73733891
Gradient objective at best sample: 467.02784992134156
Time elapsed: 81.28859400749207
Iteration: 56
Best parameters: [-12.9979838 -1.84341823 -5.31605088 -5.46513345 -2.15390593
-6.05563763 3.56558339 -4.44172306 2.2967959 ]
Best objective: 132.74271658012051
Mean objective: 133.0125710203655
Inner objective at best sample: 487675140.01475435
Gradient objective at best sample: 4876.750072720378
Time elapsed: 73.73872089385986
Iteration: 57
Best parameters: [-12.68078826 -1.88889061 -4.94142424 -5.74559864 -2.39094334
-6.0800364 2.92095277 -4.93436263 2.29877979]
Best objective: 132.73961260109166
Mean objective: 133.97368185098526
Inner objective at best sample: 47058757.7648781
Gradient objective at best sample: 470.586250252655
Time elapsed: 58.770548582077026
Iteration: 58
Best parameters: [-12.3504667 -2.00154192 -5.61715503 -5.80682445 -2.2260864
-6.32419859 2.40900957 -4.35886372 2.29901442]
Best objective: 132.74212809972545
Mean objective: 133.60010680968986
Inner objective at best sample: 35532438.89983647
Gradient objective at best sample: 355.32306157708376
Time elapsed: 68.53065013885498
Iteration: 59
Best parameters: [-12.94110613 -1.84978324 -5.78282413 -5.65943222 -1.93932504
-6.46157742 2.76628881 -4.31312996 2.2891773 ]
Best objective: 132.74965147369005
Mean objective: 132.83647434841717
Inner objective at best sample: 87497622.01586078
Gradient objective at best sample: 874.9748926620931
Time elapsed: 53.3257691860199
Iteration: 60
Best parameters: [-12.63225787 -1.94370269 -5.19985737 -5.84037844 -2.54859642
-6.45058775 2.51952284 -4.53936084 2.29492725]
Best objective: 132.74828033621606
Mean objective: 133.03014207612912
Inner objective at best sample: 35683225.47813673
Gradient objective at best sample: 356.83092729856395
Time elapsed: 53.61143183708191
Iteration: 61
Best parameters: [-12.85073174 -1.87479853 -5.26869639 -6.14626864 -2.506993
-6.31661009 2.46958084 -4.1603885 2.30046195]
Best objective: 132.74159832267944
Mean objective: 132.8036361887637
Inner objective at best sample: 93316541.54551148
Gradient objective at best sample: 933.1640880391316
Time elapsed: 46.372984886169434
Iteration: 62
Best parameters: [-12.76154633 -1.94578292 -5.33965988 -5.58294231 -2.37762866
-6.09724558 2.9805998 -4.3937007 2.30139642]
Best objective: 132.74156344075197
Mean objective: 132.76703572727345
Inner objective at best sample: 150621613.1420509
Gradient objective at best sample: 1506.2148040048746
Time elapsed: 56.979262351989746
Iteration: 63
Best parameters: [-12.9609412 -1.83249707 -5.32137437 -5.74066823 -2.42240326
-6.20317195 2.80248306 -4.25200334 2.30043822]
Best objective: 132.73411397241316
Mean objective: 132.75997818046326
Inner objective at best sample: 147843449.18386388
Gradient objective at best sample: 1478.433164497499
Time elapsed: 73.6816635131836
Iteration: 64
Best parameters: [-12.84756443 -1.83138186 -5.48200479 -5.5545007 -2.23550375
-6.22148208 2.90585614 -4.72720345 2.30129422]
Best objective: 132.73400039404473
Mean objective: 132.75505518748653
Inner objective at best sample: 55499426.41871504
Gradient objective at best sample: 554.9929368471464
Time elapsed: 47.40771293640137
Iteration: 65
Best parameters: [-13.1202479 -1.81034452 -5.39763338 -5.88178578 -2.28087546
-6.26774794 2.80996168 -4.47896371 2.3008281 ]
Best objective: 132.73361568797637
Mean objective: 132.77624257851008
Inner objective at best sample: 75872005.596762
Gradient objective at best sample: 758.7187286314631
Time elapsed: 58.58536505699158
Iteration: 66
Best parameters: [-13.15132172 -1.78470742 -5.61782409 -5.59708688 -2.27435718
-6.11871431 2.84374917 -4.60014484 2.29802398]
Best objective: 132.73675600671686
Mean objective: 132.75826261069543
Inner objective at best sample: 63013345.03742189
Gradient objective at best sample: 630.1321230066588
Time elapsed: 52.680516958236694
Iteration: 67
Best parameters: [-12.95330726 -1.82159444 -5.49356009 -5.68176203 -2.29064495
-6.15741599 2.89421154 -4.61979703 2.30026631]
Best objective: 132.73301019484248
Mean objective: 132.75161098418022
Inner objective at best sample: 69474537.08552809
Gradient objective at best sample: 694.744043525179
Time elapsed: 56.67522931098938
Iteration: 68
Best parameters: [-12.86793749 -1.83716186 -5.53974329 -5.55497754 -2.262199
-6.15417561 2.78885462 -4.70576243 2.30121667]
Best objective: 132.73242094980895
Mean objective: 132.74174842039872
Inner objective at best sample: 43023911.15929568
Gradient objective at best sample: 430.2377842687473
Time elapsed: 51.70740342140198
Iteration: 69
Best parameters: [-12.9308533 -1.83603342 -5.58865995 -5.58735141 -2.31279364
-6.25897519 2.77209727 -4.60411165 2.30154635]
Best objective: 132.73138738328973
Mean objective: 132.7409980723823
Inner objective at best sample: 52318615.41916976
Gradient objective at best sample: 523.1848268778238
Time elapsed: 47.453251123428345
Iteration: 70
Best parameters: [-13.10780348 -1.79458224 -5.83009525 -5.24870966 -2.17529959
-6.15661394 2.82519561 -4.39323017 2.30257352]
Best objective: 132.73181572372346
Mean objective: 132.73906031438156
Inner objective at best sample: 94044146.84930427
Gradient objective at best sample: 940.4401411748855
Time elapsed: 50.120824098587036
Iteration: 71
Best parameters: [-12.99740508 -1.8281969 -5.51259902 -5.59921693 -2.33510886
-6.2863321 2.49561476 -4.50434504 2.30228869]
Best objective: 132.7295625066158
Mean objective: 132.73890114268386
Inner objective at best sample: 31885433.734119896
Gradient objective at best sample: 318.8530100455739
Time elapsed: 44.088334798812866