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output_kemp_model.txt
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Steady state at V=-80mv: [0.00128227 0.00086883 0.85823026]
Number of B-spline coeffs per segment: 26
Costs at truth:
True theta: [ -8.39497556 -2.66068963 -10.27455123 -2.90735516 -2.43840482
-4.72058104 -5.26875856 -3.45523127]
Lambda: 1000000.000
Inner cost: 34118.86880739 Data cost: 31594.39467016 Gradient matching cost: 0.00252447
Iteration: 0
Best parameters: [ -8.22992189 -2.54798183 -10.24149755 -2.91020919 -2.52138196
-4.67998376 -5.09217053 -3.33189106]
Best objective: 27724.08599508116
Mean objective: 31554.57887002104
Inner objective at best sample: 36942.771437489755
Gradient objective at best sample: 0.009218685442408595
Time elapsed: 3015.266534090042
Iteration: 1
Best parameters: [ -8.18219463 -2.53905662 -10.40296808 -2.92097465 -2.61760169
-4.67736665 -4.95064778 -3.09796261]
Best objective: 22940.56495173903
Mean objective: 28385.253806186607
Inner objective at best sample: 288599.42517864384
Gradient objective at best sample: 0.2656588602269048
Time elapsed: 2640.5189847946167
Iteration: 2
Best parameters: [ -7.92442145 -2.38868397 -10.13625354 -2.81616661 -2.81711023
-4.04746464 -4.75487153 -3.04776776]
Best objective: 16492.31941845095
Mean objective: 25628.99495347046
Inner objective at best sample: 948454.3649539585
Gradient objective at best sample: 0.9319620455355077
Time elapsed: 3036.863179206848
Iteration: 3
Best parameters: [ -7.84198632 -2.44663904 -10.43675195 -3.24566717 -3.32269821
-4.46668554 -4.68356685 -3.04260106]
Best objective: 10597.4437516003
Mean objective: 19972.601348905704
Inner objective at best sample: 1028319.196284386
Gradient objective at best sample: 1.0177217525327857
Time elapsed: 2691.143267393112
Iteration: 4
Best parameters: [ -7.24098664 -3.07036938 -10.23737036 -3.0364757 -3.74638493
-4.16998192 -4.13568897 -3.28635321]
Best objective: 1606.838337094898
Mean objective: 15594.93023994911
Inner objective at best sample: 286264.97472009226
Gradient objective at best sample: 0.28465813638299736
Time elapsed: 2983.616235971451
Iteration: 5
Best parameters: [-6.70999157 -3.52106063 -9.71572909 -3.382877 -3.52291742 -3.99597439
-3.96337536 -3.89313934]
Best objective: 2395.829803298803
Mean objective: 11427.142128268679
Inner objective at best sample: 4186.223582919406
Gradient objective at best sample: 0.0017903937796206028
Time elapsed: 1721.084553718567
Iteration: 6
Best parameters: [ -8.64248559 -4.06724705 -10.03656163 -2.94253637 -4.92366857
-4.86830403 -4.46776884 -4.23332775]
Best objective: 3416.7765512461206
Mean objective: 21046.79354912657
Inner objective at best sample: 5304.397793572604
Gradient objective at best sample: 0.0018876212423264837
Time elapsed: 2792.258443593979
Iteration: 7
Best parameters: [ -9.8732624 -4.15013428 -11.44502813 -2.6695952 -3.99353363
-7.19363045 -4.26952175 -3.10851736]
Best objective: 2389.832935410885
Mean objective: 9146.513929016768
Inner objective at best sample: 735568.774840359
Gradient objective at best sample: 0.7331789419049481
Time elapsed: 1570.636304616928
Iteration: 8
Best parameters: [-10.07347223 -4.25087122 -8.77986761 -5.03383764 -4.99549153
-4.28883618 -4.73228109 -3.43877628]
Best objective: 3144.050271544213
Mean objective: 7837.620019783538
Inner objective at best sample: 17866.43843118163
Gradient objective at best sample: 0.014722388159637416
Time elapsed: 2002.208009004593
Iteration: 9
Best parameters: [ -9.62011761 -5.02190116 -10.59949542 -5.97429208 -2.28960494
-10.83571437 -1.2069417 -3.03365259]
Best objective: 2852.0499394895405
Mean objective: 9063.404435052857
Inner objective at best sample: 824353892.1155452
Gradient objective at best sample: 824.3510400656056
Time elapsed: 1423.7906293869019
Iteration: 10
Best parameters: [ -8.63744028 -3.85785895 -11.77763206 -2.91400696 -3.02991165
-7.4441308 -2.53365002 -3.8225396 ]
Best objective: 2914.8018421688844
Mean objective: 9294.795849765045
Inner objective at best sample: 37858.65418428365
Gradient objective at best sample: 0.03494385234211477
Time elapsed: 1477.0051147937775
Iteration: 11
Best parameters: [-11.07498245 -3.7748078 -10.30607163 -3.00944276 -5.39324756
-7.26899187 -4.92243016 -2.71181367]
Best objective: 2610.696042092015
Mean objective: 13160.96815859011
Inner objective at best sample: 46959688.02283037
Gradient objective at best sample: 46.95707732678828
Time elapsed: 1402.8693189620972
Iteration: 12
Best parameters: [ -7.7453814 -2.45758246 -10.03179384 -3.13343315 -4.07190039
-3.84252635 -4.3727412 -3.66920675]
Best objective: 1854.1129407963629
Mean objective: 6022.4227800407
Inner objective at best sample: 6290.2761533224375
Gradient objective at best sample: 0.004436163212526075
Time elapsed: 2179.3021898269653
Iteration: 13
Best parameters: [-8.39080884 -1.66131585 -9.74350622 -2.75257021 -3.04408397 -2.88600328
-3.18529734 -4.86491916]
Best objective: 1928.6564949824804
Mean objective: 19305.53314245359
Inner objective at best sample: 89037.9044299948
Gradient objective at best sample: 0.08710924793501232
Time elapsed: 2056.4387962818146
Iteration: 14
Best parameters: [-9.19096128 -4.90469422 -8.85804393 -3.52585545 -2.80776306 -3.47642543
-2.31889353 -4.76475476]
Best objective: 1964.8816421535407
Mean objective: 8648.50868338163
Inner objective at best sample: 9324.330233078328
Gradient objective at best sample: 0.007359448590924787
Time elapsed: 1668.0571491718292
Iteration: 15
Best parameters: [-10.00836996 -3.86846338 -13.56731997 -2.64994238 -5.93427741
-9.19270227 -2.38747341 -2.62671422]
Best objective: 3454.26421052054
Mean objective: 7041.669418465967
Inner objective at best sample: 28906060938.309425
Gradient objective at best sample: 28906.057484045217
Time elapsed: 2235.107710838318
Iteration: 16
Best parameters: [-11.29904234 -3.91166668 -13.10748133 -2.7131563 -1.19014177
-10.20391246 -1.49411511 -3.55043535]
Best objective: 2532.281532724859
Mean objective: 5565.251936913848
Inner objective at best sample: 912092.1682004778
Gradient objective at best sample: 0.909559886667753
Time elapsed: 1537.9896409511566
Iteration: 17
Best parameters: [ -9.35194518 -5.61363383 -12.0624099 -2.44198185 -6.18450716
-5.66289207 -1.88904345 -4.85052867]
Best objective: 3609.925193862014
Mean objective: 5221.206715816444
Inner objective at best sample: 18203.237857917135
Gradient objective at best sample: 0.01459331266405512
Time elapsed: 1503.1688857078552
Iteration: 18
Best parameters: [ -9.06383167 -4.88519566 -11.83726424 -2.77040402 -3.9506114
-11.80494245 -0.49511553 -2.96430745]
Best objective: 3189.711744055065
Mean objective: 5343.97408267025
Inner objective at best sample: 9063406612.913177
Gradient objective at best sample: 9063.403423201433
Time elapsed: 2249.7895815372467
Iteration: 19
Best parameters: [-10.22773824 -4.12634346 -9.44138536 -3.1521862 -3.99828874
-5.76068443 -2.28981537 -2.8614738 ]
Best objective: 2347.753893690316
Mean objective: 5368.469848085466
Inner objective at best sample: 990223208.5831693
Gradient objective at best sample: 990.2208608292756
Time elapsed: 1541.3367788791656
Iteration: 20
Best parameters: [-9.42828536 -4.28177523 -9.69269326 -3.63249113 -2.47084283 -8.98162712
-2.92407308 -3.46189798]
Best objective: 2854.539064735592
Mean objective: 4920.2917935871055
Inner objective at best sample: 630727.5952040007
Gradient objective at best sample: 0.627873056139265
Time elapsed: 2351.681908607483
Iteration: 21
Best parameters: [-7.45659906 -5.69010379 -9.37337652 -2.95460162 -4.49077888 -4.74879593
-3.54009117 -2.97432073]
Best objective: 2086.156321514147
Mean objective: 4913.719777072294
Inner objective at best sample: 18881994.67115791
Gradient objective at best sample: 18.879908514836398
Time elapsed: 1793.9470567703247
Iteration: 22
Best parameters: [ -9.756559 -4.21771342 -11.64445823 -3.85451396 -3.27054287
-8.76145417 -2.16022988 -2.95027756]
Best objective: 2435.3812417078543
Mean objective: 4903.278721624309
Inner objective at best sample: 367829139.4677401
Gradient objective at best sample: 367.82670408649847
Time elapsed: 2443.667287826538
Iteration: 23
Best parameters: [ -8.07026766 -5.83242125 -11.39615637 -2.6409824 -3.15232092
-8.03108476 -1.70281389 -3.08393798]
Best objective: 2383.548977394281
Mean objective: 3615.799072264829
Inner objective at best sample: 174852596.65261734
Gradient objective at best sample: 174.85021310363993
Time elapsed: 1343.4238622188568
Iteration: 24
Best parameters: [ -8.7204819 -5.19923997 -10.14006549 -3.05320906 -2.87630334
-6.40771579 -3.11042898 -3.41888312]
Best objective: 1894.384410342783
Mean objective: 3721.326540491443
Inner objective at best sample: 553993.4260444801
Gradient objective at best sample: 0.5520990416341373
Time elapsed: 2481.030648469925
Iteration: 25
Best parameters: [ -7.2683532 -5.7147744 -10.14790808 -2.72785445 -2.8800481
-6.1535499 -3.13774501 -3.21348311]
Best objective: 1369.355989872018
Mean objective: 3120.56932685908
Inner objective at best sample: 1033790.7866529111
Gradient objective at best sample: 1.032421430663039
Time elapsed: 2060.516080379486
Iteration: 26
Best parameters: [ -7.04855887 -4.81678724 -10.26747152 -2.62253644 -3.05442305
-4.23430712 -2.77511679 -3.37757549]
Best objective: 1622.7940976166938
Mean objective: 2911.739970198797
Inner objective at best sample: 1472787.5328431737
Gradient objective at best sample: 1.4711647387455569
Time elapsed: 1896.136271238327
Iteration: 27
Best parameters: [ -7.97249582 -5.66785879 -10.23507555 -2.80087215 -2.46635908
-7.10486049 -2.61740693 -3.34342606]
Best objective: 1665.9111042861316
Mean objective: 2976.017689929841
Inner objective at best sample: 712771.2299000106
Gradient objective at best sample: 0.7111053187957246
Time elapsed: 2368.117552757263
Iteration: 28
Best parameters: [ -8.35872645 -4.58549469 -10.38527811 -3.18180835 -3.376657
-5.35717902 -2.60230042 -3.05808039]
Best objective: 1703.1435633935132
Mean objective: 3299.56352202275
Inner objective at best sample: 39923150.769006476
Gradient objective at best sample: 39.92144762544308
Time elapsed: 2736.1984779834747
Iteration: 29
Best parameters: [ -8.21698564 -4.32499567 -11.74164538 -2.68730863 -3.01043583
-5.64146729 -2.61380672 -3.16358792]
Best objective: 1480.3942811168574
Mean objective: 2858.443415137034
Inner objective at best sample: 8669107.338216875
Gradient objective at best sample: 8.667626943935758
Time elapsed: 2557.749972343445
Iteration: 30
Best parameters: [ -8.25065298 -3.5319016 -11.04475085 -2.72047128 -1.88700493
-5.67423046 -1.83387222 -3.25773348]
Best objective: 1380.815607924233
Mean objective: 2404.3289251436604
Inner objective at best sample: 7215857.444619527
Gradient objective at best sample: 7.214476629011603
Time elapsed: 2758.575040102005
Iteration: 31
Best parameters: [ -7.43031112 -4.49573522 -11.4876233 -2.69289992 -1.89905006
-6.40616341 -2.11939187 -3.05012885]
Best objective: 1129.090199805377
Mean objective: 2799.1521900593793
Inner objective at best sample: 67680130.55551505
Gradient objective at best sample: 67.67900146531525
Time elapsed: 3107.2126166820526
Iteration: 32
Best parameters: [-7.32367023 -3.99924059 -9.74952286 -3.05618236 -2.07158413 -4.18054083
-2.08808424 -3.37244753]
Best objective: 1030.8548415084092
Mean objective: 2434.873179133956
Inner objective at best sample: 4328694.80719534
Gradient objective at best sample: 4.3276639523538325
Time elapsed: 3139.4055058956146
Iteration: 33
Best parameters: [ -6.79699653 -4.69200172 -10.61411278 -2.66808468 -1.17044916
-4.04482022 -1.51149346 -3.6140146 ]
Best objective: 965.6644462593957
Mean objective: 1992.979965396843
Inner objective at best sample: 1499226.6470603426
Gradient objective at best sample: 1.4982609826140831
Time elapsed: 2787.756061553955
Iteration: 34
Best parameters: [ -6.39627 -4.1534215 -11.07925337 -2.79733399 -1.7500354
-4.88147309 -2.22607673 -3.18352765]
Best objective: 1228.6971680988768
Mean objective: 3006.469235352225
Inner objective at best sample: 10682071.490789942
Gradient objective at best sample: 10.680842793621844
Time elapsed: 3760.961576461792
Iteration: 35
Best parameters: [ -6.83090509 -4.18530615 -11.36422933 -2.62793237 -0.07048
-5.9980548 -0.50237974 -3.29579999]
Best objective: 957.8205660343269
Mean objective: 3291.3197638932766
Inner objective at best sample: 44603187.03494694
Gradient objective at best sample: 44.602229214380905
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Best parameters: [ -8.08506866 -4.05044507 -12.50728028 -2.59267073 -2.12741569
-6.42396362 -1.92667401 -3.13561319]
Best objective: 1314.149093384031
Mean objective: 2274.927219414318
Inner objective at best sample: 36470196.36871827
Gradient objective at best sample: 36.46888221962489
Time elapsed: 3300.790513277054
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Best parameters: [ -7.13635246 -2.60773875 -10.64620973 -2.86235879 -1.60810289
-4.45460546 -1.77636236 -3.08704034]
Best objective: 873.4328683077963
Mean objective: 2501.799441939419
Inner objective at best sample: 147730442.6356182
Gradient objective at best sample: 147.7295692027499
Time elapsed: 3835.093874692917
Iteration: 38
Best parameters: [ -7.62298818 -3.12269666 -10.91615539 -2.64763934 0.65588813
-6.37546413 0.4199411 -3.20689056]
Best objective: 1230.4862956804259
Mean objective: 2126.317060922323
Inner objective at best sample: 649189538.9054481
Gradient objective at best sample: 649.1883084191523
Time elapsed: 4479.655410289764
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Best parameters: [ -6.86159807 -3.49974281 -11.33686201 -2.76260119 0.49805522
-4.36390347 0.51662914 -3.09752668]
Best objective: 1032.1560524461768
Mean objective: 2111.6165978828435
Inner objective at best sample: 13810651892.781414
Gradient objective at best sample: 13810.650860625363
Time elapsed: 4604.5820915699005
Iteration: 40
Best parameters: [ -7.26676538 -2.60193836 -12.55148061 -2.46392984 -0.97309304
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Mean objective: 3050.05495250896
Inner objective at best sample: 1142448325.182105
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Time elapsed: 5112.786458492279
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Best parameters: [ -7.09577582 -1.70161939 -11.62321482 -2.56965598 -0.06781078
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Mean objective: 2207.0368412063826
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Best parameters: [ -6.62160084 -3.00104524 -11.3639215 -2.60090685 -1.6630947
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Mean objective: 2041.0932712202155
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Best parameters: [ -6.00340237 -2.65155365 -10.55055772 -2.64184847 0.09843705
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Best objective: 911.6305106598294
Mean objective: 2210.289906136363
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Best parameters: [ -6.86773869 -3.6173682 -10.86286774 -2.698025 -2.15507935
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Mean objective: 2146.3419157640137
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Best parameters: [ -7.0146075 -2.39876645 -10.60974563 -2.78464103 -1.06040439
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Best parameters: [ -6.67781431 -3.07757919 -11.22817181 -2.80777741 -2.67068059
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Best parameters: [ -6.40613819 -2.90396168 -10.31986359 -2.89354625 -2.4587658
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Mean objective: 1504.6388973834535
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Best parameters: [-5.49443841 -3.22285465 -9.35529901 -3.02799618 -2.66329975 -4.11566677
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Best parameters: [ -5.50067377 -2.28222771 -10.06749332 -2.91735997 -1.23981707
-5.62283637 -1.54928046 -3.14015634]
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Mean objective: 1371.243235057005
Inner objective at best sample: 56091834.54200022
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Time elapsed: 4119.187679052353
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Best parameters: [ -6.34679215 -3.33333558 -10.59763782 -2.83379941 -1.708506
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Mean objective: 1396.0970930110523
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Best parameters: [ -5.48509533 -3.19373268 -10.13434431 -2.8358986 -1.52228164
-6.60216411 -1.81403938 -3.14809233]
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Best parameters: [ -5.75218996 -2.62282794 -10.49241542 -2.77631057 -0.15422194
-6.04891917 -0.45992261 -3.15323785]
Best objective: 364.6978829763052
Mean objective: 1038.5434984297947
Inner objective at best sample: 320245742.5546056
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Best parameters: [-5.6615467 -2.65134942 -9.93579119 -3.01892321 -1.1288225 -6.79646024
-1.43497431 -3.05366994]
Best objective: 350.28414801197897
Mean objective: 673.5623572422343
Inner objective at best sample: 220849888.59404436
Gradient objective at best sample: 220.84953830989636
Time elapsed: 4577.810209035873
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Best parameters: [ -5.59019777 -2.91642841 -10.29294553 -2.82599781 -1.57587012
-5.52426631 -1.96550339 -3.23454871]
Best objective: 243.38130969320028
Mean objective: 599.6714958781267
Inner objective at best sample: 4317482.412210438
Gradient objective at best sample: 4.317239030900746
Time elapsed: 4797.458429098129
Iteration: 55
Best parameters: [-5.18597951 -2.71179769 -9.9257583 -2.96719352 -1.54124018 -5.10670793
-1.86213635 -3.15176593]
Best objective: 218.96177072721147
Mean objective: 542.7589336231124
Inner objective at best sample: 34170400.73337759
Gradient objective at best sample: 34.17018177160686
Time elapsed: 4345.046765089035
Iteration: 56
Best parameters: [-5.4181622 -2.92988059 -9.42061714 -3.01028277 -1.81642308 -6.18130577
-2.17910755 -3.15555825]
Best objective: 264.118105960829
Mean objective: 502.85080694650316
Inner objective at best sample: 8343018.667195629
Gradient objective at best sample: 8.342754549089669
Time elapsed: 4167.412667512894
Iteration: 57
Best parameters: [-4.89282182 -2.60629892 -9.79922956 -2.87906281 -1.794492 -5.07114183
-2.13737638 -3.22067044]
Best objective: 229.65627639101623
Mean objective: 469.7668252174058
Inner objective at best sample: 6833032.585715867
Gradient objective at best sample: 6.832802929439476
Time elapsed: 4001.4493777751923
Iteration: 58
Best parameters: [ -5.20971121 -2.7553859 -10.19007824 -2.82816321 -1.90147401
-5.60433309 -2.20151815 -3.12425151]
Best objective: 213.06503030181088
Mean objective: 381.3330140173017
Inner objective at best sample: 20272852.48232855
Gradient objective at best sample: 20.272639417298247
Time elapsed: 4189.651166915894
Iteration: 59
Best parameters: [-5.20213981 -2.64060547 -9.95492474 -2.92082246 -1.58000714 -5.0022672
-1.9182408 -3.22950972]
Best objective: 177.02646308255848
Mean objective: 383.18910318896747
Inner objective at best sample: 9841794.482252553
Gradient objective at best sample: 9.841617455789471
Time elapsed: 3818.8194065093994
Iteration: 60
Best parameters: [ -5.13722975 -2.61673659 -10.10790425 -2.88583999 -1.54206404
-5.02832275 -1.8831122 -3.1560887 ]
Best objective: 190.8184923370682
Mean objective: 319.41787961019315
Inner objective at best sample: 31922172.005760908
Gradient objective at best sample: 31.92198118726857
Time elapsed: 4249.855665206909
Iteration: 61
Best parameters: [ -5.15596369 -2.71945187 -10.16502526 -2.82979509 -1.29130307
-5.40756827 -1.65337688 -3.18274104]
Best objective: 183.12974673900436
Mean objective: 363.2438554312748
Inner objective at best sample: 24154194.466503832
Gradient objective at best sample: 24.154011336757094
Time elapsed: 3907.23783493042
Iteration: 62
Best parameters: [ -4.97569729 -2.53151554 -10.20089787 -2.8638939 -0.955585
-5.31524979 -1.31157319 -3.22168563]
Best objective: 189.1935390091762
Mean objective: 287.2182363979829
Inner objective at best sample: 25433534.106340937
Gradient objective at best sample: 25.433344912801928
Time elapsed: 4411.828290939331
Iteration: 63
Best parameters: [ -5.19222963 -2.68026567 -10.32567972 -2.84248611 -1.30752301
-4.69859413 -1.65776538 -3.26396401]
Best objective: 172.6595802830384
Mean objective: 264.3077873013609
Inner objective at best sample: 13994871.5933465
Gradient objective at best sample: 13.994698933766218
Time elapsed: 4328.156988143921
Iteration: 64
Best parameters: [ -5.25039091 -2.67415771 -10.39788178 -2.80209014 -1.74736986
-4.62252614 -2.1297867 -3.32377889]
Best objective: 171.0821569641121
Mean objective: 295.32859141490036
Inner objective at best sample: 2715112.569487036
Gradient objective at best sample: 2.714941487330072
Time elapsed: 4436.908363342285
Iteration: 65
Best parameters: [ -5.21735204 -2.69013767 -10.32777707 -2.83460149 -1.62174179
-5.3024373 -2.01667336 -3.19541865]
Best objective: 172.73841733169505
Mean objective: 316.6920667728002
Inner objective at best sample: 9606631.526024975
Gradient objective at best sample: 9.606458787607643
Time elapsed: 4310.399448871613
Iteration: 66
Best parameters: [ -5.09944405 -2.58139078 -10.33064022 -2.8460163 -1.20443978
-5.0297488 -1.59805759 -3.24540182]
Best objective: 173.63897289038584
Mean objective: 265.536795959293
Inner objective at best sample: 12611734.605057074
Gradient objective at best sample: 12.611560966084184
Time elapsed: 3999.1919882297516
Iteration: 67
Best parameters: [ -5.09518628 -2.65076342 -10.23562545 -2.84104909 -1.62635098
-4.86608347 -1.99846223 -3.25224126]
Best objective: 163.7416645907596
Mean objective: 229.15976092439374
Inner objective at best sample: 6699661.826103442
Gradient objective at best sample: 6.699498084438852
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Best parameters: [ -5.02179886 -2.56114006 -10.2160778 -2.84292596 -1.4249928
-4.90339149 -1.80533218 -3.25690507]
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Mean objective: 206.95655085639322
Inner objective at best sample: 8466564.991080943
Gradient objective at best sample: 8.466397883376036
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Iteration: 69
Best parameters: [ -5.09490263 -2.57359692 -10.23913056 -2.84888402 -1.37131191
-4.86085054 -1.74874312 -3.24695769]
Best objective: 167.74018925493854
Mean objective: 219.44786670256627
Inner objective at best sample: 11766828.55247074
Gradient objective at best sample: 11.766660812281486
Time elapsed: 4355.621275424957
Iteration: 70
Best parameters: [ -5.12200595 -2.63408581 -10.06754277 -2.87892265 -1.45652739
-4.88253367 -1.81244692 -3.25672936]
Best objective: 165.5938648834628
Mean objective: 237.13614042264973
Inner objective at best sample: 8919835.201174004
Gradient objective at best sample: 8.91966960730912
Time elapsed: 4243.5339884758
Iteration: 71
Best parameters: [ -5.09028133 -2.64170718 -10.21701232 -2.84953309 -1.6205323
-4.92053482 -1.99066815 -3.24963683]
Best objective: 163.04741513882163
Mean objective: 216.70057693444426
Inner objective at best sample: 6603309.327307077
Gradient objective at best sample: 6.603146279891938
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Iteration: 72
Best parameters: [ -5.04234656 -2.567418 -10.20434729 -2.85081702 -1.43480095
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Best objective: 165.83763006261123
Mean objective: 211.30765512749292
Inner objective at best sample: 10371107.348543994
Gradient objective at best sample: 10.37094151091393
Time elapsed: 4220.248423576355
Iteration: 73
Best parameters: [ -5.10595758 -2.66108933 -10.12209916 -2.87034947 -1.61535191
-4.78614158 -1.9788687 -3.27876225]
Best objective: 163.33538505951762
Mean objective: 247.4796783477265
Inner objective at best sample: 5272309.250969874
Gradient objective at best sample: 5.272145915584813
Time elapsed: 3868.5303111076355
Iteration: 74
Best parameters: [ -5.15696465 -2.6344967 -10.20132736 -2.86002475 -1.44864706
-4.72059494 -1.80472376 -3.27490859]
Best objective: 163.05921648002737
Mean objective: 213.40858943671222
Inner objective at best sample: 8630869.874084597
Gradient objective at best sample: 8.630706814868116
Time elapsed: 3946.055167913437
Iteration: 75
Best parameters: [ -5.09203697 -2.62560709 -10.286512 -2.84559997 -1.57064709
-4.7407824 -1.94194057 -3.2752639 ]
Best objective: 162.61380992961418
Mean objective: 184.7207245500635
Inner objective at best sample: 6297934.569087116
Gradient objective at best sample: 6.297771955277187
Time elapsed: 3954.8733339309692
Iteration: 76
Best parameters: [ -5.04189924 -2.60214192 -10.18558603 -2.85485455 -1.43615059
-4.70826203 -1.80090831 -3.28767738]
Best objective: 162.22603496946343
Mean objective: 221.6088669482561
Inner objective at best sample: 7257847.837762399
Gradient objective at best sample: 7.25768561172743
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Iteration: 77
Best parameters: [ -5.07377512 -2.60936479 -10.19526738 -2.85252393 -1.43857399
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Best objective: 162.27338768588172
Mean objective: 218.72131814975307
Inner objective at best sample: 6912150.488384718
Gradient objective at best sample: 6.911988214997033
Time elapsed: 4326.489027261734
Iteration: 78
Best parameters: [ -5.08008153 -2.61172559 -10.19081931 -2.85706713 -1.44260031
-4.73231854 -1.80797789 -3.27954852]
Best objective: 161.7002014734093
Mean objective: 182.26475271476406
Inner objective at best sample: 7778168.32539839
Gradient objective at best sample: 7.778006625196917
Time elapsed: 4046.6306986808777
Iteration: 79
Best parameters: [ -5.05021125 -2.61653211 -10.22946689 -2.85598518 -1.54829309
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Best objective: 161.9342407577471
Mean objective: 189.6448074786975
Inner objective at best sample: 5094426.887842776
Gradient objective at best sample: 5.094264953602019
Time elapsed: 4737.940023183823
Iteration: 80
Best parameters: [ -5.11791874 -2.62998028 -10.29975317 -2.83900463 -1.46193787
-4.75276533 -1.82368463 -3.26954006]
Best objective: 162.21526522977604
Mean objective: 252.8507704426253
Inner objective at best sample: 8540939.427633986
Gradient objective at best sample: 8.540777212368756
Time elapsed: 3890.858124256134
Iteration: 81
Best parameters: [ -5.14416345 -2.65503682 -10.20115624 -2.85236288 -1.46971788
-4.91091956 -1.83844073 -3.24657579]
Best objective: 162.3469757331993
Mean objective: 187.69802162466172
Inner objective at best sample: 9415228.62092067
Gradient objective at best sample: 9.415066273944937
Time elapsed: 4139.815164804459
Iteration: 82
Best parameters: [ -5.14845726 -2.63681147 -10.24603817 -2.85005519 -1.50244424
-4.85518682 -1.86459187 -3.24741009]
Best objective: 162.11345220547852
Mean objective: 171.5045624930692
Inner objective at best sample: 9587791.199491125
Gradient objective at best sample: 9.58762908603892
Time elapsed: 3874.641526699066
Iteration: 83
Best parameters: [ -5.13211815 -2.6501795 -10.18678607 -2.86400876 -1.50089964
-4.82371823 -1.86565396 -3.26346967]
Best objective: 161.79459378445628
Mean objective: 207.9181525787666
Inner objective at best sample: 7777070.02535445
Gradient objective at best sample: 7.776908230760665
Time elapsed: 4268.8417909145355
Iteration: 84
Best parameters: [ -5.124209 -2.64098376 -10.20197182 -2.85898178 -1.54034996
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Best objective: 161.41343233922234
Mean objective: 235.34920329023439
Inner objective at best sample: 7174170.98076255
Gradient objective at best sample: 7.17400956733021
Time elapsed: 4045.023281097412
Iteration: 85
Best parameters: [ -5.11182178 -2.63013183 -10.2336726 -2.85491272 -1.51290514
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Best objective: 161.74437083668988
Mean objective: 215.09327442698955
Inner objective at best sample: 8118970.033316716
Gradient objective at best sample: 8.118808288945878
Time elapsed: 4377.483685493469
Iteration: 86
Best parameters: [ -5.08715151 -2.61585532 -10.18644788 -2.86110235 -1.49668232
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Best objective: 161.6504971380797
Mean objective: 202.86338025663397
Inner objective at best sample: 7549870.180197025
Gradient objective at best sample: 7.5497085296998865
Time elapsed: 4143.1046714782715
Iteration: 87
Best parameters: [ -5.13235942 -2.63270124 -10.21551618 -2.85478045 -1.53440546
-4.80786698 -1.90148634 -3.26481301]
Best objective: 161.40872845332296
Mean objective: 267.8392407655085
Inner objective at best sample: 7254556.316523603
Gradient objective at best sample: 7.25439490779515
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Iteration: 88
Best parameters: [ -5.11002312 -2.62755459 -10.22457961 -2.85304521 -1.51438406
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Best objective: 161.04619921797922
Mean objective: 217.2639522645403
Inner objective at best sample: 7229030.458960099
Gradient objective at best sample: 7.228869412760881
Time elapsed: 3990.069725036621
Iteration: 89
Best parameters: [ -5.11078172 -2.62290543 -10.2621262 -2.84542973 -1.50548842
-4.74874811 -1.87096644 -3.27364538]
Best objective: 161.1512095021498
Mean objective: 193.42360959139197
Inner objective at best sample: 7699682.31528483
Gradient objective at best sample: 7.699521164075327
Time elapsed: 3909.7084863185883
Iteration: 90
Best parameters: [ -5.11017574 -2.63082716 -10.20531257 -2.85757596 -1.59375821
-4.77649289 -1.96099089 -3.27271759]
Best objective: 159.4010004660165
Mean objective: 203.13178953561984
Inner objective at best sample: 6920091.616722308
Gradient objective at best sample: 6.9199322157218415
Time elapsed: 4260.661334037781
Iteration: 91
Best parameters: [ -5.11727506 -2.62574114 -10.30024271 -2.83750568 -1.50871918
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Best objective: 161.36912655824676
Mean objective: 228.13175942294535
Inner objective at best sample: 6796588.29589316
Gradient objective at best sample: 6.7964269267666015
Time elapsed: 4152.37620639801
Iteration: 92
Best parameters: [ -5.12927372 -2.62720384 -10.23230981 -2.85473219 -1.53543359
-4.7240962 -1.89628532 -3.28303675]
Best objective: 161.19149096019692
Mean objective: 187.2992031629748
Inner objective at best sample: 6363061.4656166835
Gradient objective at best sample: 6.362900274125723
Time elapsed: 3817.737758874893
Iteration: 93
Best parameters: [ -5.14224581 -2.64846615 -10.26162207 -2.84548931 -1.52660262
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Best objective: 161.2124950228919
Mean objective: 189.1194772860408
Inner objective at best sample: 5623242.803570792
Gradient objective at best sample: 5.62308159107577
Time elapsed: 4047.626067876816
Iteration: 94
Best parameters: [ -5.13609895 -2.63397276 -10.25445394 -2.84763359 -1.5524321
-4.75811766 -1.91714707 -3.27898058]
Best objective: 161.12385648632883
Mean objective: 208.0826246212135
Inner objective at best sample: 6140276.808270659
Gradient objective at best sample: 6.140115684414172
Time elapsed: 3823.5726013183594
Iteration: 95
Best parameters: [ -5.08664406 -2.62377223 -10.23274771 -2.85320335 -1.52013272
-4.67036543 -1.89043929 -3.30025849]
Best objective: 160.92889893972625
Mean objective: 195.21722516553123
Inner objective at best sample: 5733827.027370516
Gradient objective at best sample: 5.733666098471576
Time elapsed: 3997.8623247146606
Iteration: 96
Best parameters: [ -5.0993987 -2.61696825 -10.21040613 -2.85781201 -1.56141913
-4.62547947 -1.92778267 -3.30809275]
Best objective: 160.74144693871767
Mean objective: 249.7193657173519
Inner objective at best sample: 4865228.206981594
Gradient objective at best sample: 4.865067465534655
Time elapsed: 3664.8573410511017
Iteration: 97
Best parameters: [ -5.11933774 -2.63015512 -10.20699003 -2.85763575 -1.53305202
-4.6123981 -1.89983504 -3.30757732]
Best objective: 160.96587466977886
Mean objective: 252.27377824189534
Inner objective at best sample: 5267307.206857031
Gradient objective at best sample: 5.2671462409823615
Time elapsed: 3975.044251203537
Iteration: 98
Best parameters: [ -5.11620794 -2.63920558 -10.2049532 -2.86032453 -1.54933788
-4.6487947 -1.91306079 -3.30647319]
Best objective: 160.93386884140682
Mean objective: 182.51096604462427
Inner objective at best sample: 4938113.522702287
Gradient objective at best sample: 4.937952588833446
Time elapsed: 3848.8371765613556
Iteration: 99
Best parameters: [ -5.10175077 -2.62243493 -10.21779649 -2.85713656 -1.59128184
-4.61665027 -1.95786427 -3.31067107]
Best objective: 160.72706999676765
Mean objective: 238.58463788435617
Inner objective at best sample: 4507005.5944365775
Gradient objective at best sample: 4.50684486736658
Time elapsed: 3860.396065711975
Iteration: 100
Best parameters: [ -5.09382723 -2.63358422 -10.23785334 -2.8488637 -1.58318642
-4.59200912 -1.95325336 -3.3204974 ]
Best objective: 160.75021988138167
Mean objective: 198.36511552788218
Inner objective at best sample: 4122675.94965578
Gradient objective at best sample: 4.122515199435899
Time elapsed: 3860.530308008194
Iteration: 101
Best parameters: [ -5.10873302 -2.63026101 -10.20647623 -2.8541428 -1.57027493
-4.52366482 -1.93903225 -3.3387886 ]
Best objective: 160.33391447918677
Mean objective: 185.43832315682033
Inner objective at best sample: 3739564.184614838
Gradient objective at best sample: 3.739403850700359
Time elapsed: 3692.7312932014465
Iteration: 102
Best parameters: [ -5.09220589 -2.61790199 -10.22049778 -2.85201398 -1.53174532
-4.55364342 -1.89891863 -3.33047452]
Best objective: 160.38503081219298
Mean objective: 189.41382553428306
Inner objective at best sample: 4261617.555933457
Gradient objective at best sample: 4.261457170902644
Time elapsed: 4141.722902297974
Iteration: 103
Best parameters: [ -5.135772 -2.65075819 -10.22896484 -2.84845205 -1.58321705
-4.57927356 -1.94673828 -3.32138927]
Best objective: 160.5733268016851
Mean objective: 195.81792050739165
Inner objective at best sample: 4244933.251378783
Gradient objective at best sample: 4.244772678051981
Time elapsed: 3717.483808994293
Iteration: 104
Best parameters: [ -5.06555769 -2.59956103 -10.19592652 -2.85677823 -1.5765996
-4.45240134 -1.9431147 -3.35806758]
Best objective: 160.41442107430822
Mean objective: 257.8902878679186
Inner objective at best sample: 3315516.23273589
Gradient objective at best sample: 3.3153558183148157
Time elapsed: 4003.474101305008
Iteration: 105
Best parameters: [ -5.08955569 -2.61300504 -10.17052223 -2.85857118 -1.58316633
-4.45387445 -1.94580176 -3.3623533 ]
Best objective: 160.41298722824342
Mean objective: 189.20329323443056
Inner objective at best sample: 3136737.747911648
Gradient objective at best sample: 3.1365773349244197
Time elapsed: 3799.988701581955
Iteration: 106
Best parameters: [ -5.12722385 -2.63819843 -10.1919484 -2.85694742 -1.66834672
-4.47720241 -2.03144456 -3.35143131]
Best objective: 160.28343323448166
Mean objective: 265.0377685485507
Inner objective at best sample: 2969219.365990396
Gradient objective at best sample: 2.9690590825571617
Time elapsed: 3827.7146067619324
Iteration: 107
Best parameters: [ -5.08765965 -2.61310603 -10.2214705 -2.84878051 -1.61552385
-4.41262687 -1.98238539 -3.37191293]
Best objective: 160.07567707486174
Mean objective: 224.30347768281845
Inner objective at best sample: 2823452.998879228
Gradient objective at best sample: 2.823292923202153
Time elapsed: 4020.6722967624664
Iteration: 108
Best parameters: [ -5.09277918 -2.62165464 -10.18346524 -2.85794621 -1.59950383
-4.45542522 -1.96358738 -3.35866574]
Best objective: 160.02850712745953
Mean objective: 198.69723926843565
Inner objective at best sample: 3168410.447400449
Gradient objective at best sample: 3.1682504188933214
Time elapsed: 3485.5487892627716
Iteration: 109
Best parameters: [ -5.10220567 -2.61809979 -10.24156962 -2.85129543 -1.63952691
-4.42621833 -2.00566469 -3.37151263]
Best objective: 159.910288811821
Mean objective: 184.78525297880012
Inner objective at best sample: 2664830.068150107
Gradient objective at best sample: 2.6646701578612952
Time elapsed: 3891.3842396736145
Iteration: 110
Best parameters: [ -5.09501033 -2.61597782 -10.2538353 -2.84648059 -1.57243568
-4.40042302 -1.93767544 -3.37459938]
Best objective: 159.9412841037476
Mean objective: 187.57630445202662
Inner objective at best sample: 3021099.2503289077
Gradient objective at best sample: 3.020939309044804
Time elapsed: 3546.4059932231903
Iteration: 111
Best parameters: [ -5.09685359 -2.61503542 -10.20609039 -2.85105788 -1.61299411
-4.40199783 -1.97873791 -3.37359148]
Best objective: 160.16960494377142
Mean objective: 182.20224598035236
Inner objective at best sample: 2843658.688890902
Gradient objective at best sample: 2.843498519285958
Time elapsed: 3951.9129066467285
Iteration: 112
Best parameters: [ -5.07494346 -2.61054946 -10.25231426 -2.83985865 -1.67720294
-4.43671375 -2.04130525 -3.36478115]
Best objective: 151.45411603803942
Mean objective: 200.96180410617586
Inner objective at best sample: 2759674.1807588255
Gradient objective at best sample: 2.7595227266427873
Time elapsed: 3697.139276742935
Iteration: 113
Best parameters: [ -5.11961832 -2.63298209 -10.21277302 -2.85113458 -1.64952546
-4.40341069 -2.01196407 -3.37690916]
Best objective: 159.82813069505983
Mean objective: 196.71255458502063
Inner objective at best sample: 2593923.387587498
Gradient objective at best sample: 2.5937635594568027
Time elapsed: 3814.8284928798676
Iteration: 114
Best parameters: [ -5.12570855 -2.62489127 -10.26500347 -2.84116092 -1.62919994
-4.44861427 -1.99111592 -3.35870328]
Best objective: 159.91150146647186
Mean objective: 219.60379903834078
Inner objective at best sample: 3196746.7351726447
Gradient objective at best sample: 3.1965868236711783
Time elapsed: 3775.956143140793
Iteration: 115
Best parameters: [ -5.08563784 -2.62592001 -10.21681784 -2.85212336 -1.62483819
-4.36116201 -1.98665482 -3.38623777]
Best objective: 160.05195324414817
Mean objective: 191.59984318128411
Inner objective at best sample: 2630901.328921671
Gradient objective at best sample: 2.630741276968427
Time elapsed: 3652.2408604621887
Iteration: 116
Best parameters: [ -5.10489685 -2.63160859 -10.20029213 -2.85682379 -1.66042903
-4.36451201 -2.02701155 -3.39276132]
Best objective: 159.70126846891125
Mean objective: 194.18565945901852
Inner objective at best sample: 2271856.005692162
Gradient objective at best sample: 2.2716963044236933
Time elapsed: 3507.47150015831
Iteration: 117
Best parameters: [ -5.07439344 -2.59864986 -10.21871858 -2.84673904 -1.66854107
-4.34772598 -2.03341633 -3.39274699]
Best objective: 159.25015167459617
Mean objective: 199.9037070835877
Inner objective at best sample: 2499797.534569145
Gradient objective at best sample: 2.4996382844174705
Time elapsed: 4039.301741838455
Iteration: 118
Best parameters: [ -5.08845698 -2.61247666 -10.1985046 -2.85696157 -1.59305108
-4.34168549 -1.95940231 -3.39763444]
Best objective: 159.7252641556534
Mean objective: 180.39068751696746
Inner objective at best sample: 2502874.6256414973
Gradient objective at best sample: 2.5027149003773417
Time elapsed: 3396.806581735611
Iteration: 119
Best parameters: [ -5.09033494 -2.61634222 -10.23403832 -2.8496435 -1.60182901
-4.38891288 -1.96802687 -3.38444813]
Best objective: 159.63767442210326
Mean objective: 177.8559618896725
Inner objective at best sample: 2616315.32937579
Gradient objective at best sample: 2.6161556917013677
Time elapsed: 3501.443703651428
Iteration: 120
Best parameters: [ -5.10838832 -2.63421304 -10.18703386 -2.85914862 -1.6547504
-4.36658741 -2.02223055 -3.39848492]
Best objective: 159.6047499598213
Mean objective: 208.20785373685385
Inner objective at best sample: 2291245.377919102
Gradient objective at best sample: 2.2910857731691423
Time elapsed: 3573.329011440277
Iteration: 121
Best parameters: [ -5.10589502 -2.62237842 -10.23447715 -2.84863236 -1.60879051
-4.37434813 -1.97538579 -3.3911632 ]
Best objective: 159.59899157899108
Mean objective: 173.92294930992614
Inner objective at best sample: 2462633.581071322
Gradient objective at best sample: 2.462473982079743
Time elapsed: 4019.910966873169
Iteration: 122
Best parameters: [ -5.09273894 -2.61934145 -10.22755145 -2.85147578 -1.62986153
-4.32280381 -1.99488631 -3.41200762]
Best objective: 159.40835270677064
Mean objective: 180.99959359590713
Inner objective at best sample: 2110738.083375118
Gradient objective at best sample: 2.1105786750224116
Time elapsed: 3706.879526615143
Iteration: 123
Best parameters: [ -5.09718208 -2.61548604 -10.23220315 -2.84923709 -1.64083692
-4.34102568 -2.0034484 -3.40159258]
Best objective: 159.26976739276364
Mean objective: 201.29308955016685
Inner objective at best sample: 2365149.0899569234
Gradient objective at best sample: 2.3649898201895305
Time elapsed: 4113.548926115036
Iteration: 124