In [1]:

    

%run loss_per_iter.py


    

    




******************************
clip_sgd
Step: 1
Best Cost: 0.0393756386145
Step: 1
Best Cost: 0.0405687973229
Step: 1
Best Cost: 0.0396306874477
Step: 1
Best Cost: 0.0411368339292
Step: 1
Best Cost: 0.0406409828273
Step: 1
Best Cost: 0.041348424588
Step: 1
Best Cost: 0.0396872132427
Step: 1
Best Cost: 0.039201254155
Step: 1
Best Cost: 0.0398418732166
Step: 1
Best Cost: 0.0398770113021
Step: 1
Best Cost: 0.0391202841291
Step: 1
Best Cost: 0.038609344927
Step: 1
Best Cost: 0.0401593425644
Step: 1
Best Cost: 0.0393047471696
Step: 1
Best Cost: 0.0400767093146
Step: 1
Best Cost: 0.0393229830898
Step: 1
Best Cost: 0.0395169372241
Step: 1
Best Cost: 0.0405875929437
Step: 1
Best Cost: 0.0405578097245
Step: 1
Best Cost: 0.0397782499411
Step: 1
Best Cost: 0.0398374035505
Step: 1
Best Cost: 0.0397589541623
Step: 1
Best Cost: 0.0390866862127
Step: 1
Best Cost: 0.0412052642791
Step: 1
Best Cost: 0.0386350395528
Step: 1
Best Cost: 0.041345753109
Step: 1
Best Cost: 0.0395072714719
Step: 1
Best Cost: 0.0402866724751
Step: 1
Best Cost: 0.0404317738734
Step: 1
Best Cost: 0.0397209064273
Step: 1
Best Cost: 0.0391776355819
Step: 1
Best Cost: 0.0403105411272
Step: 1
Best Cost: 0.0407475522108
Step: 1
Best Cost: 0.0393293263637
Step: 1
Best Cost: 0.0389754685353
Step: 1
Best Cost: 0.0419361102593
Step: 1
Best Cost: 0.0399379313426
Step: 1
Best Cost: 0.0399965331904
Step: 1
Best Cost: 0.040494936686
Step: 1
Best Cost: 0.0396156549206
Step: 1
Best Cost: 0.0401167418036
Step: 1
Best Cost: 0.0386345989374
Step: 1
Best Cost: 0.039543640105
Step: 1
Best Cost: 0.0402104182248
Step: 1
Best Cost: 0.0409252194535
Step: 1
Best Cost: 0.0408033198298
Step: 1
Best Cost: 0.0396435923184
Step: 1
Best Cost: 0.0400101366946
Step: 1
Best Cost: 0.0409768786316
Step: 1
Best Cost: 0.0407576387308
Step: 1
Best Cost: 0.0402533127292
Step: 1
Best Cost: 0.0401754706757
Step: 1
Best Cost: 0.0400568101706
Step: 1
Best Cost: 0.0392713596372
Step: 1
Best Cost: 0.0391973164029
Step: 1
Best Cost: 0.0401329612137
Step: 1
Best Cost: 0.0407797846164
Step: 1
Best Cost: 0.0407613938855
Step: 1
Best Cost: 0.039484458709
Step: 1
Best Cost: 0.0400353549795
Step: 1
Best Cost: 0.0402516415662
Step: 1
Best Cost: 0.0402828180827
Step: 1
Best Cost: 0.0387235794306
Step: 1
Best Cost: 0.0395140950563
Step: 1
Best Cost: 0.0394574104809
Step: 1
Best Cost: 0.0396911152692
Step: 1
Best Cost: 0.0405176383027
Step: 1
Best Cost: 0.0411722736974
Step: 1
Best Cost: 0.0392155801096
Step: 1
Best Cost: 0.0401292378151
Step: 1
Best Cost: 0.0406161853104
Step: 1
Best Cost: 0.0402109541084
Step: 1
Best Cost: 0.0398033808967
Step: 1
Best Cost: 0.0392321131108
Step: 1
Best Cost: 0.0390989043586
Step: 1
Best Cost: 0.0396258406783
Step: 1
Best Cost: 0.0403804282864
Step: 1
Best Cost: 0.0400337036641
Step: 1
Best Cost: 0.0399529479917
Step: 1
Best Cost: 0.0407467821262
Step: 1
Best Cost: 0.0397237128695
Step: 1
Best Cost: 0.0400859106344
Step: 1
Best Cost: 0.0405831073995
Step: 1
Best Cost: 0.0399664482887
Step: 1
Best Cost: 0.041009742189
Step: 1
Best Cost: 0.0398105577673
Step: 1
Best Cost: 0.0393083316354
Step: 1
Best Cost: 0.0393661078256
Step: 1
Best Cost: 0.0401895822769
Step: 1
Best Cost: 0.0388738808845
Step: 1
Best Cost: 0.0409190627464
Step: 1
Best Cost: 0.0392384603542
Step: 1
Best Cost: 0.0405270460369
Step: 1
Best Cost: 0.0400760900714
Step: 1
Best Cost: 0.0387398464747
Step: 1
Best Cost: 0.0393895795268
Step: 1
Best Cost: 0.0398778488683
Step: 1
Best Cost: 0.0398188500697
Step: 1
Best Cost: 0.0392497020011
Step: 1
Best Cost: 0.0408635650539
Step: 1
Best Cost: 0.0388253774653
Step: 1
Best Cost: 0.0400534083022
Step: 1
Best Cost: 0.0401669918064
Step: 1
Best Cost: 0.0399849184098
Step: 1
Best Cost: 0.0396407898457
Step: 1
Best Cost: 0.0410002828513
Step: 1
Best Cost: 0.0393486935936
Step: 1
Best Cost: 0.0397170798215
Step: 1
Best Cost: 0.0398205926838
Step: 1
Best Cost: 0.0400541744173
Step: 1
Best Cost: 0.0395539568565
Step: 1
Best Cost: 0.039336844612
Step: 1
Best Cost: 0.0397220536152
Step: 1
Best Cost: 0.0387028030253
Step: 1
Best Cost: 0.0406129064967
Step: 1
Best Cost: 0.0397284127671
Step: 1
Best Cost: 0.0409124257289
Step: 1
Best Cost: 0.0404050392365
Step: 1
Best Cost: 0.0402248751733
Step: 1
Best Cost: 0.0393055887054
Step: 1
Best Cost: 0.0395282106271
Step: 1
Best Cost: 0.0394045604503
Step: 1
Best Cost: 0.0410304550822
Step: 1
Best Cost: 0.0399116809857
Step: 1
Best Cost: 0.0406841035936
Step: 1
Best Cost: 0.04027928919
Step: 1
Best Cost: 0.0416690893898
Step: 1
Best Cost: 0.0392500195617
Step: 1
Best Cost: 0.0398783609349
Step: 1
Best Cost: 0.0394155083536
Step: 1
Best Cost: 0.039961442739
Step: 1
Best Cost: 0.0396484708439
Step: 1
Best Cost: 0.0400372206483
Step: 1
Best Cost: 0.0392103602065
Step: 1
Best Cost: 0.039507303228
Step: 1
Best Cost: 0.0395207836774
Step: 1
Best Cost: 0.0403588857661
Step: 1
Best Cost: 0.0407608897579
Step: 1
Best Cost: 0.0402174045591
Step: 1
Best Cost: 0.039937121563
Step: 1
Best Cost: 0.0395117887721
Step: 1
Best Cost: 0.0399288848337
Step: 1
Best Cost: 0.0396809017249
Step: 1
Best Cost: 0.0385819037176
Step: 1
Best Cost: 0.0393083236964
Step: 1
Best Cost: 0.0400343427549
Step: 1
Best Cost: 0.0395828826618
Step: 1
Best Cost: 0.0400769752717
Step: 1
Best Cost: 0.040372362246
Step: 1
Best Cost: 0.039255529239
Step: 1
Best Cost: 0.0395950690517
Step: 1
Best Cost: 0.0391432556724
Step: 1
Best Cost: 0.0411344561939
Step: 1
Best Cost: 0.0399860933842
Step: 1
Best Cost: 0.0395180645644
Step: 1
Best Cost: 0.0399421906248
Step: 1
Best Cost: 0.0391870909501
Step: 1
Best Cost: 0.0407693725967
Step: 1
Best Cost: 0.0400089339337
Step: 1
Best Cost: 0.0408224409502
Step: 1
Best Cost: 0.0402233389736
Step: 1
Best Cost: 0.0398043653347
Step: 1
Best Cost: 0.0401018839349
Step: 1
Best Cost: 0.0404285228463
Step: 1
Best Cost: 0.0408606950996
Step: 1
Best Cost: 0.0397105817368
Step: 1
Best Cost: 0.0390881668393
Step: 1
Best Cost: 0.0396954102769
Step: 1
Best Cost: 0.0407040146462
Step: 1
Best Cost: 0.0396936914799
Step: 1
Best Cost: 0.0406216275059
Step: 1
Best Cost: 0.0384912758787
Step: 1
Best Cost: 0.0388968444888
Step: 1
Best Cost: 0.040045203329
Step: 1
Best Cost: 0.0392938230834
Step: 1
Best Cost: 0.0401546625143
Step: 1
Best Cost: 0.039688558906
Step: 1
Best Cost: 0.039666698825
Step: 1
Best Cost: 0.0393794175862
Step: 1
Best Cost: 0.0398968072389
Step: 1
Best Cost: 0.0405868109506
Step: 1
Best Cost: 0.0408105840296
Step: 1
Best Cost: 0.0390993052789
Step: 1
Best Cost: 0.0396942273635
Step: 1
Best Cost: 0.0401868711029
Step: 1
Best Cost: 0.0392299735459
Step: 1
Best Cost: 0.0405978620611
Step: 1
Best Cost: 0.0396765630526
Step: 1
Best Cost: 0.0416136155143
Step: 1
Best Cost: 0.0408389580734
Step: 1
Best Cost: 0.040074196616
Step: 1
Best Cost: 0.0398049567914
Step: 1
Best Cost: 0.040090158008
Step: 1
Best Cost: 0.0394531075342
Step: 1
Best Cost: 0.0394688982373
Step: 1
Best Cost: 0.0401445085127
Step: 1
Best Cost: 0.0397480578626
Step: 1
Best Cost: 0.0397244869236
Step: 1
Best Cost: 0.0393500829214
Step: 1
Best Cost: 0.0400138402457
Avg. Time
0.65811971426

NMI
[0.0039116925504340929, 0.0036109949259624141, 0.014119314794470867, 0.0018656866872284079, 3.80161038597303e-06, 0.016540701117224759, 0.01928456555209412, 0.00037572709296588994, 0.020369985981670162, 0.00031062579217721285, 0.0014000112495545984, 0.00037572709296588994, 0.010217997982160122, 0.0043446687990854899, 0.0036109949259624141, 0.00037572709296588994, 0.024000440526313706, 0.034381273979279293, 0.0097855838248664881, 0.0013287866592082548, 0.027727652034549657, 0.0097855838248664881, 0.021786338296317379, 0.00031062579217721285, 0.03245125422830189, 0.093282755650511626, 0.0016595712035244348, 0.0016595712035244348, 0.0018656866872284079, 0.0061204880800294721, 1.5819268970631766e-05, 0.03245125422830189, 0.10456220596808552, 0.003306866462860482, 0.0018656866872284079, 0.032209404269889587, 0.025369557116165606, 0.032836404694826779, 0.0063218874478553101, 0.0061204880800294721, 1.5819268970631766e-05, 0.003306866462860482, 0.058458157413647675, 0.020369985981670162, 0.0072708540867058961, 0.00037572709296588994, 3.3633451524789452e-16, 0.025369557116165606, 1.5819268970631766e-05, 0.027727652034549657, 0.014119314794470867, 0.049941715410177064, 0.0014000112495545984, 0.010217997982160122, 0.0034139081680096433, 0.00088959404890583062, 0.014119314794470867, 0.040285248550803052, 0.014499141437310323, 3.80161038597303e-06, 0.0034139081680096433, 0.0097855838248664881, 1.5819268970631766e-05, 0.025450517127019043, 0.0097855838248664881, 0.015277928871235346, 0.00037572709296588994, 0.00037572709296588994, 0.00069964954636247316, 0.00045711703858285945, 0.032836404694826779, 0.015277928871235346, 0.027474620464465298, 0.003306866462860482, 0.048621306182437353, 0.02621228682865448, 0.00025738902988997516, 0.027474620464465298, 0.084366562991679536, 0.0066940745027972946, 0.01956398506867656, 0.039905711293898131, 0.0018656866872284079, 0.039905711293898131, 0.0014000112495545984, 0.0036109949259624141, 0.0066940745027972946, 0.0016595712035244348, 0.010217997982160122, 0.0096685128569730557, 0.0015082682251279557, 0.091522115159181669, 0.10563938429373532, 0.014499141437310323, 0.0016595712035244348, 3.3633451524789452e-16, 0.00037572709296588994, 3.80161038597303e-06, 0.003306866462860482, 0.00031062579217721285, 0.015277928871235346, 0.049941715410177064, 0.0043446687990854899, 0.0014000112495545984, 0.0036109949259624141, 0.0096685128569730557, 3.80161038597303e-06, 0.061682766476326215, 3.80161038597303e-06, 0.0061204880800294721, 0.0039116925504340929, 0.010217997982160122, 0.0098136619944997963, 0.00037572709296588994, 0.0015082682251279557, 0.02621228682865448, 0.00045711703858285945, 0.010915130325223931, 0.041773704733695988, 0.0066940745027972946, 0.041773704733695988, 0.052754855448359936, 0.020369985981670162, 0.0063218874478553101, 0.0039116925504340929, 0.040626754665685695, 3.3633451524789452e-16, 0.0014000112495545984, 1.5819268970631766e-05, 0.0021469170480561258, 0.00045711703858285945, 0.032836404694826779, 0.00045711703858285945, 0.0061204880800294721, 3.8118872831827854e-05, 0.05789317381925322, 0.032836404694826779, 0.0039116925504340929, 0.0016595712035244348, 0.0061204880800294721, 0.00031062579217721285, 0.014112824607315342, 0.052754855448359936, 0.0039116925504340929, 0.01928456555209412, 0.0063218874478553101, 0.0072708540867058961, 0.014119314794470867, 0.0063218874478553101, 0.010217997982160122, 0.0098136619944997963, 0.0098136619944997963, 0.049941715410177064, 0.0096685128569730557, 0.11905256108637619, 0.010915130325223931, 0.020369985981670162, 0.048614264428063735, 0.025450517127019043, 0.0039116925504340929, 0.0039116925504340929, 0.0016595712035244348, 0.15859043157846817, 0.0034139081680096433, 0.0036109949259624141, 3.80161038597303e-06, 0.014119314794470867, 0.066538299367064499, 0.014112824607315342, 0.010217997982160122, 0.0063218874478553101, 0.082032694343450716, 3.80161038597303e-06, 0.040626754665685695, 0.0015082682251279557, 0.01928456555209412, 0.00025738902988997516, 0.024000440526313706, 0.0063218874478553101, 0.0060802221692300784, 0.0039116925504340929, 0.00037572709296588994, 0.003306866462860482, 3.80161038597303e-06, 0.0043446687990854899, 0.020369985981670162, 0.032836404694826779, 0.0061204880800294721, 0.010217997982160122, 0.0098136619944997963, 0.0014000112495545984, 0.0018656866872284079, 0.020369985981670162, 0.0034139081680096433, 0.0039116925504340929, 0.058933144644992684, 0.039905711293898131, 0.00031062579217721285, 3.80161038597303e-06, 0.0015082682251279557]

Costs
[matrix([[ 291.80954143]]), matrix([[ 299.66303373]]), matrix([[ 294.78577276]]), matrix([[ 293.74997346]]), matrix([[ 298.88646644]]), matrix([[ 299.77884081]]), matrix([[ 289.56806122]]), matrix([[ 290.78752765]]), matrix([[ 295.54674954]]), matrix([[ 291.70980889]]), matrix([[ 291.4242361]]), matrix([[ 290.04950053]]), matrix([[ 299.66017739]]), matrix([[ 293.6610923]]), matrix([[ 294.91651205]]), matrix([[ 294.69577582]]), matrix([[ 295.77632686]]), matrix([[ 297.87718258]]), matrix([[ 293.9123433]]), matrix([[ 293.48856373]]), matrix([[ 296.65212595]]), matrix([[ 292.23715906]]), matrix([[ 291.46404541]]), matrix([[ 303.3928834]]), matrix([[ 288.7434576]]), matrix([[ 298.61241422]]), matrix([[ 293.79558732]]), matrix([[ 298.72115799]]), matrix([[ 297.52286652]]), matrix([[ 293.96659912]]), matrix([[ 293.1914844]]), matrix([[ 295.90653119]]), matrix([[ 295.41641527]]), matrix([[ 294.13920225]]), matrix([[ 292.35096116]]), matrix([[ 300.3727955]]), matrix([[ 296.45132841]]), matrix([[ 298.55662083]]), matrix([[ 298.37270132]]), matrix([[ 293.11402995]]), matrix([[ 293.79095518]]), matrix([[ 290.57715877]]), matrix([[ 293.9592024]]), matrix([[ 294.23272452]]), matrix([[ 298.64155843]]), matrix([[ 299.70512379]]), matrix([[ 297.78105555]]), matrix([[ 296.70521419]]), matrix([[ 299.58073452]]), matrix([[ 296.6418951]]), matrix([[ 298.23792143]]), matrix([[ 297.4593262]]), matrix([[ 294.29351212]]), matrix([[ 304.42014408]]), matrix([[ 290.53283783]]), matrix([[ 300.89160015]]), matrix([[ 297.61510728]]), matrix([[ 295.15889624]]), matrix([[ 296.48182579]]), matrix([[ 289.25915838]]), matrix([[ 296.47654895]]), matrix([[ 295.5186721]]), matrix([[ 290.14879527]]), matrix([[ 292.85941869]]), matrix([[ 293.73344548]]), matrix([[ 294.53764991]]), matrix([[ 298.2699412]]), matrix([[ 295.77464071]]), matrix([[ 289.02142269]]), matrix([[ 296.15883793]]), matrix([[ 294.31993691]]), matrix([[ 291.94502099]]), matrix([[ 291.08812733]]), matrix([[ 291.97225798]]), matrix([[ 294.13723709]]), matrix([[ 294.63618815]]), matrix([[ 298.15666516]]), matrix([[ 297.59703903]]), matrix([[ 295.59116806]]), matrix([[ 296.1825843]]), matrix([[ 294.67452556]]), matrix([[ 293.05389927]]), matrix([[ 296.89786921]]), matrix([[ 294.98029554]]), matrix([[ 297.70166554]]), matrix([[ 291.66077529]]), matrix([[ 293.73041352]]), matrix([[ 293.4938704]]), matrix([[ 294.71801037]]), matrix([[ 292.37119467]]), matrix([[ 300.55993098]]), matrix([[ 291.64371999]]), matrix([[ 292.9553646]]), matrix([[ 296.06283082]]), matrix([[ 289.63243287]]), matrix([[ 295.12953491]]), matrix([[ 298.40116865]]), matrix([[ 295.64301822]]), matrix([[ 291.69839968]]), matrix([[ 295.67445395]]), matrix([[ 288.90270315]]), matrix([[ 291.73361107]]), matrix([[ 292.88521805]]), matrix([[ 297.20402405]]), matrix([[ 298.00821598]]), matrix([[ 297.70745407]]), matrix([[ 293.48300681]]), matrix([[ 294.94220503]]), matrix([[ 295.05658553]]), matrix([[ 295.04003532]]), matrix([[ 293.73834653]]), matrix([[ 294.80826237]]), matrix([[ 293.59889776]]), matrix([[ 291.29244027]]), matrix([[ 295.93087774]]), matrix([[ 294.22400624]]), matrix([[ 299.05605614]]), matrix([[ 297.10784381]]), matrix([[ 300.28736084]]), matrix([[ 291.49103004]]), matrix([[ 294.55780604]]), matrix([[ 291.64237908]]), matrix([[ 297.27292173]]), matrix([[ 297.20067674]]), matrix([[ 297.32818121]]), matrix([[ 294.75920032]]), matrix([[ 296.72150665]]), matrix([[ 293.65826074]]), matrix([[ 294.78696296]]), matrix([[ 294.46373505]]), matrix([[ 294.15794779]]), matrix([[ 296.053149]]), matrix([[ 297.81939939]]), matrix([[ 292.32859637]]), matrix([[ 293.45310869]]), matrix([[ 293.75590229]]), matrix([[ 357.02118731]]), matrix([[ 296.10252445]]), matrix([[ 295.69774362]]), matrix([[ 295.88059582]]), matrix([[ 294.63434792]]), matrix([[ 296.95106977]]), matrix([[ 292.81160503]]), matrix([[ 290.58028612]]), matrix([[ 290.88176403]]), matrix([[ 298.26563613]]), matrix([[ 293.38136986]]), matrix([[ 294.55783753]]), matrix([[ 299.78948531]]), matrix([[ 295.10107713]]), matrix([[ 293.88592427]]), matrix([[ 290.58442254]]), matrix([[ 299.70220174]]), matrix([[ 294.97737445]]), matrix([[ 292.64244044]]), matrix([[ 297.1925987]]), matrix([[ 291.28108627]]), matrix([[ 297.70767042]]), matrix([[ 293.58622317]]), matrix([[ 299.29772753]]), matrix([[ 323.32194396]]), matrix([[ 294.14993753]]), matrix([[ 293.64338678]]), matrix([[ 298.82776904]]), matrix([[ 301.11091635]]), matrix([[ 296.23007298]]), matrix([[ 292.57952095]]), matrix([[ 293.29844599]]), matrix([[ 294.26247431]]), matrix([[ 294.65408569]]), matrix([[ 298.33344259]]), matrix([[ 288.00724458]]), matrix([[ 291.19919671]]), matrix([[ 293.83552113]]), matrix([[ 291.60099896]]), matrix([[ 293.49375475]]), matrix([[ 293.62827909]]), matrix([[ 292.91374247]]), matrix([[ 293.46242643]]), matrix([[ 293.92335039]]), matrix([[ 295.85155752]]), matrix([[ 294.16458825]]), matrix([[ 293.29489371]]), matrix([[ 297.57851518]]), matrix([[ 291.94207193]]), matrix([[ 295.25615236]]), matrix([[ 299.63056134]]), matrix([[ 298.41656936]]), matrix([[ 298.3745453]]), matrix([[ 297.77145556]]), matrix([[ 295.58640433]]), matrix([[ 294.44212828]]), matrix([[ 294.41483184]]), matrix([[ 292.44047603]]), matrix([[ 294.59370573]]), matrix([[ 296.56422772]]), matrix([[ 293.91397318]]), matrix([[ 291.89620789]]), matrix([[ 294.50305601]]), matrix([[ 296.94088218]])]

******************************
update_rule
Step: 1
Best Cost: 0.0384405217483
Step: 1
Best Cost: 0.0393827122779
Step: 1
Best Cost: 0.0400114386933
Step: 1
Best Cost: 0.0401361090336
Step: 1
Best Cost: 0.039483216253
Step: 1
Best Cost: 0.0396537542591
Step: 1
Best Cost: 0.0396638050536
Step: 1
Best Cost: 0.0394887140216
Step: 1
Best Cost: 0.039753428607
Step: 1
Best Cost: 0.0398993397851
Step: 1
Best Cost: 0.0386429349044
Step: 1
Best Cost: 0.0398486332888
Step: 1
Best Cost: 0.0397633761943
Step: 1
Best Cost: 0.039787038432
Step: 1
Best Cost: 0.0397041352557
Step: 1
Best Cost: 0.0395537544116
Step: 1
Best Cost: 0.0401022967637
Step: 1
Best Cost: 0.0396001857476
Step: 1
Best Cost: 0.0394298859119
Step: 1
Best Cost: 0.0395140633003
Step: 1
Best Cost: 0.0392908777084
Step: 1
Best Cost: 0.0391948989725
Step: 1
Best Cost: 0.0397958070753
Step: 1
Best Cost: 0.0404838141244
Step: 1
Best Cost: 0.0399315721907
Step: 1
Best Cost: 0.0393357093327
Step: 1
Best Cost: 0.0398938142298
Step: 1
Best Cost: 0.0400365736184
Step: 1
Best Cost: 0.0407107231148
Step: 1
Best Cost: 0.0396388805123
Step: 1
Best Cost: 0.0396135113862
Step: 1
Best Cost: 0.0395118562538
Step: 1
Best Cost: 0.0403195955751
Step: 1
Best Cost: 0.0399544722828
Step: 1
Best Cost: 0.0398805004997
Step: 1
Best Cost: 0.0396414130585
Step: 1
Best Cost: 0.039261936025
Step: 1
Best Cost: 0.0394841848129
Step: 1
Best Cost: 0.0396223197246
Step: 1
Best Cost: 0.0395452834813
Step: 1
Best Cost: 0.0398777655086
Step: 1
Best Cost: 0.0402211835307
Step: 1
Best Cost: 0.0402191828987
Step: 1
Best Cost: 0.0392873051511
Step: 1
Best Cost: 0.0395330216708
Step: 1
Best Cost: 0.0397925639872
Step: 1
Best Cost: 0.0396708469609
Step: 1
Best Cost: 0.0395113600652
Step: 1
Best Cost: 0.040157433231
Step: 1
Best Cost: 0.0403081832394
Step: 1
Best Cost: 0.0397513922494
Step: 1
Best Cost: 0.0397253165508
Step: 1
Best Cost: 0.0401082192698
Step: 1
Best Cost: 0.0393307990512
Step: 1
Best Cost: 0.0390891314297
Step: 1
Best Cost: 0.0395818029557
Step: 1
Best Cost: 0.0395529247844
Step: 1
Best Cost: 0.0397115066322
Step: 1
Best Cost: 0.0395827953327
Step: 1
Best Cost: 0.0396430802519
Step: 1
Best Cost: 0.0396462995229
Step: 1
Best Cost: 0.0389968999095
Step: 1
Best Cost: 0.039568445561
Step: 1
Best Cost: 0.0406858938418
Step: 1
Best Cost: 0.0392775322222
Step: 1
Best Cost: 0.0396518608038
Step: 1
Best Cost: 0.0398219264385
Step: 1
Best Cost: 0.0395395912067
Step: 1
Best Cost: 0.0392319265439
Step: 1
Best Cost: 0.0393499995618
Step: 1
Best Cost: 0.039779702781
Step: 1
Best Cost: 0.0391721179657
Step: 1
Best Cost: 0.0393192715997
Step: 1
Best Cost: 0.0395816997484
Step: 1
Best Cost: 0.0398012373624
Step: 1
Best Cost: 0.0399138602456
Step: 1
Best Cost: 0.0397642693336
Step: 1
Best Cost: 0.040216380426
Step: 1
Best Cost: 0.0395668577577
Step: 1
Best Cost: 0.039548562295
Step: 1
Best Cost: 0.0395473674731
Step: 1
Best Cost: 0.039517889906
Step: 1
Best Cost: 0.0392188549538
Step: 1
Best Cost: 0.0394202955804
Step: 1
Best Cost: 0.0393131109232
Step: 1
Best Cost: 0.0388827686131
Step: 1
Best Cost: 0.0394629519142
Step: 1
Best Cost: 0.0395925682616
Step: 1
Best Cost: 0.039868846024
Step: 1
Best Cost: 0.0393254322763
Step: 1
Best Cost: 0.0396188543441
Step: 1
Best Cost: 0.0397235143941
Step: 1
Best Cost: 0.0402799560674
Step: 1
Best Cost: 0.0395532661621
Step: 1
Best Cost: 0.0394732885132
Step: 1
Best Cost: 0.0397378840134
Step: 1
Best Cost: 0.0397274600852
Step: 1
Best Cost: 0.0397871257611
Step: 1
Best Cost: 0.0391960302823
Step: 1
Best Cost: 0.0396966725805
Step: 1
Best Cost: 0.0396201801598
Step: 1
Best Cost: 0.0397448624086
Step: 1
Best Cost: 0.0397062192474
Step: 1
Best Cost: 0.0395594347776
Step: 1
Best Cost: 0.0397467757115
Step: 1
Best Cost: 0.0399343389378
Step: 1
Best Cost: 0.0395846530625
Step: 1
Best Cost: 0.0399087356107
Step: 1
Best Cost: 0.0391578912487
Step: 1
Best Cost: 0.0395069975759
Step: 1
Best Cost: 0.0396384359274
Step: 1
Best Cost: 0.0397423258929
Step: 1
Best Cost: 0.0393030124946
Step: 1
Best Cost: 0.0389142984158
Step: 1
Best Cost: 0.0397833785455
Step: 1
Best Cost: 0.0396758644191
Step: 1
Best Cost: 0.0399708226866
Step: 1
Best Cost: 0.0391552713734
Step: 1
Best Cost: 0.0395821403638
Step: 1
Best Cost: 0.0399746254753
Step: 1
Best Cost: 0.0395722126241
Step: 1
Best Cost: 0.0397711326131
Step: 1
Best Cost: 0.0397342280964
Step: 1
Best Cost: 0.0400015308011
Step: 1
Best Cost: 0.0401853428423
Step: 1
Best Cost: 0.0399682623539
Step: 1
Best Cost: 0.0391257422027
Step: 1
Best Cost: 0.0399374351541
Step: 1
Best Cost: 0.0397935444557
Step: 1
Best Cost: 0.0387323004398
Step: 1
Best Cost: 0.0394933226205
Step: 1
Best Cost: 0.0394648294915
Step: 1
Best Cost: 0.0400545078559
Step: 1
Best Cost: 0.0398287262058
Step: 1
Best Cost: 0.0398175560101
Step: 1
Best Cost: 0.0390503294882
Step: 1
Best Cost: 0.0391742059269
Step: 1
Best Cost: 0.0392930966634
Step: 1
Best Cost: 0.0398013088135
Step: 1
Best Cost: 0.0394527066138
Step: 1
Best Cost: 0.0396800720977
Step: 1
Best Cost: 0.0392487691667
Step: 1
Best Cost: 0.0390025961536
Step: 1
Best Cost: 0.0396061479487
Step: 1
Best Cost: 0.0400775746674
Step: 1
Best Cost: 0.0392119361012
Step: 1
Best Cost: 0.0398112603703
Step: 1
Best Cost: 0.0397888604362
Step: 1
Best Cost: 0.0399231012604
Step: 1
Best Cost: 0.0396876776752
Step: 1
Best Cost: 0.0394566761219
Step: 1
Best Cost: 0.0391827602168
Step: 1
Best Cost: 0.0397473870157
Step: 1
Best Cost: 0.0396035280734
Step: 1
Best Cost: 0.0403909712999
Step: 1
Best Cost: 0.0395195094653
Step: 1
Best Cost: 0.0398027140194
Step: 1
Best Cost: 0.0398818342544
Step: 1
Best Cost: 0.0395657304174
Step: 1
Best Cost: 0.0400301072898
Step: 1
Best Cost: 0.0392180967778
Step: 1
Best Cost: 0.0395092244699
Step: 1
Best Cost: 0.0397727005688
Step: 1
Best Cost: 0.039501412478
Step: 1
Best Cost: 0.0399986449687
Step: 1
Best Cost: 0.0400716997954
Step: 1
Best Cost: 0.0400160949262
Step: 1
Best Cost: 0.0395242530275
Step: 1
Best Cost: 0.0398215890303
Step: 1
Best Cost: 0.039726880537
Step: 1
Best Cost: 0.0394318190623
Step: 1
Best Cost: 0.0395635868831
Step: 1
Best Cost: 0.0395262377815
Step: 1
Best Cost: 0.0398580172059
Step: 1
Best Cost: 0.0397490383311
Step: 1
Best Cost: 0.0398094582136
Step: 1
Best Cost: 0.0393198868735
Step: 1
Best Cost: 0.039693957437
Step: 1
Best Cost: 0.0397605260875
Step: 1
Best Cost: 0.0395964305929
Step: 1
Best Cost: 0.0395952238625
Step: 1
Best Cost: 0.0392691248041
Step: 1
Best Cost: 0.0390430335324
Step: 1
Best Cost: 0.0396316242516
Step: 1
Best Cost: 0.0394035799818
Step: 1
Best Cost: 0.0395659646184
Step: 1
Best Cost: 0.0395967838791
Step: 1
Best Cost: 0.0397465057849
Step: 1
Best Cost: 0.0394615864034
Step: 1
Best Cost: 0.0396501737628
Step: 1
Best Cost: 0.0396866773591
Step: 1
Best Cost: 0.0392001942963
Step: 1
Best Cost: 0.0405557614584
Step: 1
Best Cost: 0.0389795333116
Step: 1
Best Cost: 0.0395882494368
Step: 1
Best Cost: 0.0391060812292
Step: 1
Best Cost: 0.0390527350101
Step: 1
Best Cost: 0.039552031645
Step: 1
Best Cost: 0.0390990829865
Step: 1
Best Cost: 0.0398045836577
Avg. Time
0.374646325111

NMI
[3.3633451524789452e-16, 0.039905711293898131, 0.0039116925504340929, 0.0014000112495545984, 0.0049619932222596053, 0.0061204880800294721, 0.020369985981670162, 0.02621228682865448, 0.0039116925504340929, 0.049941715410177064, 0.014499141437310323, 0.0061204880800294721, 0.0034139081680096433, 0.00037572709296588994, 0.020357780440473091, 0.00037572709296588994, 0.0072708540867058961, 0.032836404694826779, 1.5819268970631766e-05, 0.032836404694826779, 0.027727652034549657, 0.00037572709296588994, 0.0062147980019104862, 0.00069964954636247316, 0.01956398506867656, 0.0066940745027972946, 0.0066940745027972946, 0.027377302593907211, 1.5819268970631766e-05, 0.00045711703858285945, 3.80161038597303e-06, 0.040285248550803052, 0.0066940745027972946, 0.0015082682251279557, 3.3633451524789452e-16, 0.0093645942086020388, 0.0016595712035244348, 0.048621306182437353, 0.0098136619944997963, 0.0063218874478553101, 0.0060802221692300784, 0.0036109949259624141, 0.13363651385646241, 0.032209404269889587, 0.0016595712035244348, 0.0015082682251279557, 0.014499141437310323, 0.0061204880800294721, 0.058933144644992684, 0.00056151965855826241, 0.016540701117224759, 0.0066940745027972946, 0.0034139081680096433, 0.011983958070948958, 0.05789317381925322, 0.0016595712035244348, 0.00045711703858285945, 0.0036109949259624141, 0.00069964954636247316, 0.014112824607315342, 0.01956398506867656, 0.071376161295855861, 0.0039116925504340929, 3.80161038597303e-06, 0.0063218874478553101, 0.0066940745027972946, 0.015277928871235346, 0.0043446687990854899, 0.00025738902988997516, 1.5819268970631766e-05, 0.032836404694826779, 0.0013287866592082548, 0.010217997982160122, 0.040626754665685695, 0.025996594351713552, 0.049941715410177064, 3.80161038597303e-06, 0.030191388309364967, 0.032209404269889587, 0.014499141437310323, 0.0014000112495545984, 3.80161038597303e-06, 0.0098136619944997963, 0.0061204880800294721, 0.010915130325223931, 0.05789317381925322, 0.010217997982160122, 0.0098136619944997963, 0.064941564132711502, 0.0018656866872284079, 0.0016595712035244348, 0.00031062579217721285, 0.014499141437310323, 0.00031062579217721285, 0.057466820585683656, 0.0039116925504340929, 0.0060802221692300784, 0.014119314794470867, 0.01928456555209412, 0.00037572709296588994, 0.0015082682251279557, 0.02621228682865448, 3.80161038597303e-06, 0.049941715410177064, 0.010217997982160122, 0.010217997982160122, 0.030191388309364967, 0.0014000112495545984, 0.0081195548326033051, 0.053093877451679101, 0.02621228682865448, 0.0061204880800294721, 0.00045711703858285945, 0.00045711703858285945, 0.040626754665685695, 0.0014000112495545984, 0.00037572709296588994, 0.014499141437310323, 0.030191388309364967, 0.040285248550803052, 0.030191388309364967, 0.02621228682865448, 0.0039116925504340929, 0.058458157413647675, 0.0015082682251279557, 0.0015082682251279557, 0.014499141437310323, 0.10563938429373532, 0.00037572709296588994, 0.0060802221692300784, 0.0015082682251279557, 0.02621228682865448, 0.0096685128569730557, 0.040626754665685695, 0.02621228682865448, 0.018459756328547638, 0.015277928871235346, 0.01928456555209412, 0.0039116925504340929, 0.00056151965855826241, 3.3633451524789452e-16, 0.11889572369200396, 0.00025738902988997516, 0.079666253413707228, 0.00045711703858285945, 0.040626754665685695, 0.0049619932222596053, 0.0014000112495545984, 0.020369985981670162, 0.068808136095082656, 0.0013287866592082548, 3.3633451524789452e-16, 1.5819268970631766e-05, 0.0034139081680096433, 0.00037572709296588994, 0.019524986146721119, 0.00037572709296588994, 0.0036109949259624141, 0.0097855838248664881, 0.0072708540867058961, 0.032836404694826779, 0.0034139081680096433, 0.0016595712035244348, 0.0062147980019104862, 3.80161038597303e-06, 0.010915130325223931, 0.0018656866872284079, 0.01928456555209412, 0.040285248550803052, 0.00037572709296588994, 0.00045711703858285945, 0.00056151965855826241, 0.0043446687990854899, 0.093282755650511626, 0.0034139081680096433, 0.00031062579217721285, 0.00045711703858285945, 0.014499141437310323, 0.079666253413707228, 0.003306866462860482, 0.0036109949259624141, 0.015277928871235346, 0.071376161295855861, 0.01956398506867656, 0.016540701117224759, 0.0061204880800294721, 0.0018656866872284079, 0.010915130325223931, 0.040285248550803052, 0.0039116925504340929, 0.041773704733695988, 0.049941715410177064, 0.0015082682251279557, 0.025996594351713552, 0.016540701117224759, 0.032209404269889587, 0.048621306182437353, 0.01956398506867656, 0.032836404694826779, 0.010915130325223931]

Costs
[matrix([[ 277.83685207]]), matrix([[ 283.40254693]]), matrix([[ 280.18126482]]), matrix([[ 286.7547111]]), matrix([[ 282.06710071]]), matrix([[ 283.16102218]]), matrix([[ 282.88020741]]), matrix([[ 281.32831513]]), matrix([[ 284.25684717]]), matrix([[ 280.7730884]]), matrix([[ 283.27224412]]), matrix([[ 280.56067219]]), matrix([[ 281.09406454]]), matrix([[ 281.64402331]]), matrix([[ 281.54810693]]), matrix([[ 281.46555659]]), matrix([[ 283.11940234]]), matrix([[ 282.83605248]]), matrix([[ 282.01299076]]), matrix([[ 281.94318819]]), matrix([[ 278.93723461]]), matrix([[ 280.40253162]]), matrix([[ 279.25455492]]), matrix([[ 286.76895838]]), matrix([[ 284.00551351]]), matrix([[ 282.14070894]]), matrix([[ 285.87901315]]), matrix([[ 285.67081537]]), matrix([[ 284.2886955]]), matrix([[ 282.73612864]]), matrix([[ 282.58779863]]), matrix([[ 279.94100557]]), matrix([[ 286.46822035]]), matrix([[ 280.77527814]]), matrix([[ 283.85591917]]), matrix([[ 281.67863744]]), matrix([[ 279.43314712]]), matrix([[ 280.92462325]]), matrix([[ 282.10953706]]), matrix([[ 281.9323647]]), matrix([[ 283.09812428]]), matrix([[ 283.33542417]]), matrix([[ 279.6688934]]), matrix([[ 282.58662031]]), matrix([[ 279.48099043]]), matrix([[ 280.04917164]]), matrix([[ 282.66000678]]), matrix([[ 280.49233469]]), matrix([[ 283.12808619]]), matrix([[ 283.82874851]]), matrix([[ 282.25282185]]), matrix([[ 283.84570137]]), matrix([[ 284.82884114]]), matrix([[ 276.61243697]]), matrix([[ 277.67587677]]), matrix([[ 284.98640832]]), matrix([[ 283.89574753]]), matrix([[ 282.32320396]]), matrix([[ 281.39323706]]), matrix([[ 286.00632166]]), matrix([[ 283.72515858]]), matrix([[ 278.91769132]]), matrix([[ 281.26003832]]), matrix([[ 286.09215792]]), matrix([[ 281.06773912]]), matrix([[ 282.90410203]]), matrix([[ 282.43225949]]), matrix([[ 280.92103903]]), matrix([[ 280.71578506]]), matrix([[ 281.08918377]]), matrix([[ 283.13695093]]), matrix([[ 281.94771273]]), matrix([[ 282.3653115]]), matrix([[ 281.00263938]]), matrix([[ 283.19298055]]), matrix([[ 283.81790537]]), matrix([[ 284.06088162]]), matrix([[ 283.92591287]]), matrix([[ 282.85075035]]), matrix([[ 280.85252145]]), matrix([[ 278.27810808]]), matrix([[ 278.05706693]]), matrix([[ 280.5781891]]), matrix([[ 280.3860141]]), matrix([[ 283.75065947]]), matrix([[ 277.82865824]]), matrix([[ 281.67678486]]), matrix([[ 282.44675029]]), matrix([[ 281.77371245]]), matrix([[ 278.26215073]]), matrix([[ 283.13224129]]), matrix([[ 283.74581507]]), matrix([[ 282.67073355]]), matrix([[ 283.44863078]]), matrix([[ 281.03868666]]), matrix([[ 284.57010067]]), matrix([[ 283.41071627]]), matrix([[ 280.71540034]]), matrix([[ 281.61541226]]), matrix([[ 281.89241685]]), matrix([[ 282.61610205]]), matrix([[ 284.03381225]]), matrix([[ 285.56678737]]), matrix([[ 281.13664602]]), matrix([[ 282.80890142]]), matrix([[ 281.10548148]]), matrix([[ 283.86185984]]), matrix([[ 283.54882899]]), matrix([[ 277.59047901]]), matrix([[ 278.67839185]]), matrix([[ 283.02487037]]), matrix([[ 282.58450879]]), matrix([[ 282.6223205]]), matrix([[ 276.41110747]]), matrix([[ 283.84304219]]), matrix([[ 281.32991961]]), matrix([[ 283.94466925]]), matrix([[ 276.90483481]]), matrix([[ 282.60956145]]), matrix([[ 282.93531946]]), matrix([[ 278.1291942]]), matrix([[ 281.04540929]]), matrix([[ 279.70268231]]), matrix([[ 282.81206392]]), matrix([[ 284.91915572]]), matrix([[ 283.00889341]]), matrix([[ 284.75560195]]), matrix([[ 279.37055518]]), matrix([[ 281.93593753]]), matrix([[ 280.71639004]]), matrix([[ 282.15736061]]), matrix([[ 281.53617235]]), matrix([[ 283.29078955]]), matrix([[ 281.32059664]]), matrix([[ 285.28678066]]), matrix([[ 278.42823471]]), matrix([[ 279.02327887]]), matrix([[ 280.61663798]]), matrix([[ 280.6230193]]), matrix([[ 279.92134199]]), matrix([[ 285.57961141]]), matrix([[ 281.22094667]]), matrix([[ 279.70454148]]), matrix([[ 279.83660367]]), matrix([[ 284.18076232]]), matrix([[ 279.19054057]]), matrix([[ 283.52682999]]), matrix([[ 280.59205511]]), matrix([[ 283.04865044]]), matrix([[ 281.00968497]]), matrix([[ 279.6548506]]), matrix([[ 281.88345928]]), matrix([[ 287.98567965]]), matrix([[ 279.40600269]]), matrix([[ 284.36937304]]), matrix([[ 280.85375468]]), matrix([[ 282.23689148]]), matrix([[ 281.46967645]]), matrix([[ 281.92288919]]), matrix([[ 286.86359935]]), matrix([[ 279.21783079]]), matrix([[ 280.83380035]]), matrix([[ 280.74987265]]), matrix([[ 281.03702519]]), matrix([[ 288.17260759]]), matrix([[ 284.03800551]]), matrix([[ 284.40813295]]), matrix([[ 281.49789436]]), matrix([[ 281.03629801]]), matrix([[ 281.48127098]]), matrix([[ 284.47992792]]), matrix([[ 283.42017681]]), matrix([[ 279.49950263]]), matrix([[ 283.23394527]]), matrix([[ 280.85723772]]), matrix([[ 285.39177846]]), matrix([[ 281.7276869]]), matrix([[ 280.70104278]]), matrix([[ 281.33839639]]), matrix([[ 279.60205235]]), matrix([[ 284.47030165]]), matrix([[ 282.51286099]]), matrix([[ 277.95388487]]), matrix([[ 281.0878298]]), matrix([[ 280.79698759]]), matrix([[ 281.73290771]]), matrix([[ 279.30499734]]), matrix([[ 280.47443435]]), matrix([[ 279.96924495]]), matrix([[ 284.88110488]]), matrix([[ 281.10810448]]), matrix([[ 280.21893826]]), matrix([[ 283.85597041]]), matrix([[ 277.59305447]]), matrix([[ 280.61125995]]), matrix([[ 278.00115023]]), matrix([[ 278.39062897]]), matrix([[ 279.48124326]]), matrix([[ 278.93864255]]), matrix([[ 282.25724991]])]

******************************
abs_sgd
Step: 1
Best Cost: 0.0401327786163
Step: 1
Best Cost: 0.0387924345177
Step: 1
Best Cost: 0.0404014349232
Step: 1
Best Cost: 0.040041273516
Step: 1
Best Cost: 0.0394094469148
Step: 1
Best Cost: 0.0400562465005
Step: 1
Best Cost: 0.0395978993109
Step: 1
Best Cost: 0.0398710094059
Step: 1
Best Cost: 0.0396193703801
Step: 1
Best Cost: 0.0393259681598
Step: 1
Best Cost: 0.0402250260146
Step: 1
Best Cost: 0.0398114072421
Step: 1
Best Cost: 0.039643362087
Step: 1
Best Cost: 0.040054039454
Step: 1
Best Cost: 0.0391608604407
Step: 1
Best Cost: 0.0408069797163
Step: 1
Best Cost: 0.0398666389775
Step: 1
Best Cost: 0.0397173973822
Step: 1
Best Cost: 0.0404500772752
Step: 1
Best Cost: 0.038836539722
Step: 1
Best Cost: 0.0402533444852
Step: 1
Best Cost: 0.0399638482609
Step: 1
Best Cost: 0.0403472312903
Step: 1
Best Cost: 0.0404035467015
Step: 1
Best Cost: 0.0397174926504
Step: 1
Best Cost: 0.0398258641905
Step: 1
Best Cost: 0.0400068142164
Step: 1
Best Cost: 0.0413934943827
Step: 1
Best Cost: 0.0396437987329
Step: 1
Best Cost: 0.0388233172906
Step: 1
Best Cost: 0.0400940917905
Step: 1
Best Cost: 0.0388997104736
Step: 1
Best Cost: 0.0398394716642
Step: 1
Best Cost: 0.0401170633338
Step: 1
Best Cost: 0.0400392054023
Step: 1
Best Cost: 0.0405449921829
Step: 1
Best Cost: 0.0388382863056
Step: 1
Best Cost: 0.0399052186265
Step: 1
Best Cost: 0.0397115423578
Step: 1
Best Cost: 0.0381114018943
Step: 1
Best Cost: 0.0397917700856
Step: 1
Best Cost: 0.0388771557287
Step: 1
Best Cost: 0.0387437207146
Step: 1
Best Cost: 0.0401257327394
Step: 1
Best Cost: 0.0399936830836
Step: 1
Best Cost: 0.0405074168194
Step: 1
Best Cost: 0.0385963328795
Step: 1
Best Cost: 0.0404337268714
Step: 1
Best Cost: 0.0406700634435
Step: 1
Best Cost: 0.0404228266022
Step: 1
Best Cost: 0.0390965425013
Step: 1
Best Cost: 0.0390757780045
Step: 1
Best Cost: 0.0398247408197
Step: 1
Best Cost: 0.0393578909438
Step: 1
Best Cost: 0.0401676428058
Step: 1
Best Cost: 0.0403980965669
Step: 1
Best Cost: 0.0398857124638
Step: 1
Best Cost: 0.0400416268022
Step: 1
Best Cost: 0.0397911429033
Step: 1
Best Cost: 0.0399742840976
Step: 1
Best Cost: 0.0395703826809
Step: 1
Best Cost: 0.0407040781583
Step: 1
Best Cost: 0.0391905722087
Step: 1
Best Cost: 0.0406559161167
Step: 1
Best Cost: 0.0397119472476
Step: 1
Best Cost: 0.0395989631391
Step: 1
Best Cost: 0.0390414854242
Step: 1
Best Cost: 0.0399295159855
Step: 1
Best Cost: 0.0400139355138
Step: 1
Best Cost: 0.0398540794539
Step: 1
Best Cost: 0.039868861902
Step: 1
Best Cost: 0.0402460286818
Step: 1
Best Cost: 0.0385096030975
Step: 1
Best Cost: 0.0395510551461
Step: 1
Best Cost: 0.0394379638608
Step: 1
Best Cost: 0.0403121328999
Step: 1
Best Cost: 0.0401786462822
Step: 1
Best Cost: 0.0405575993406
Step: 1
Best Cost: 0.0408398393042
Step: 1
Best Cost: 0.0388163190478
Step: 1
Best Cost: 0.0405344452
Step: 1
Best Cost: 0.0397526902785
Step: 1
Best Cost: 0.0400338108408
Step: 1
Best Cost: 0.0397506817074
Step: 1
Best Cost: 0.0413045138896
Step: 1
Best Cost: 0.039248685807
Step: 1
Best Cost: 0.0390551643491
Step: 1
Best Cost: 0.0396383366897
Step: 1
Best Cost: 0.0405842704654
Step: 1
Best Cost: 0.0391693154929
Step: 1
Best Cost: 0.0403612277758
Step: 1
Best Cost: 0.0409108101391
Step: 1
Best Cost: 0.0391244521126
Step: 1
Best Cost: 0.0412788986539
Step: 1
Best Cost: 0.0409292405651
Step: 1
Best Cost: 0.039840360834
Step: 1
Best Cost: 0.0388435101782
Step: 1
Best Cost: 0.0400679208237
Step: 1
Best Cost: 0.0395825452537
Step: 1
Best Cost: 0.0387615636534
Step: 1
Best Cost: 0.0396959937946
Step: 1
Best Cost: 0.039696652733
Step: 1
Best Cost: 0.0403887047108
Step: 1
Best Cost: 0.0400140347516
Step: 1
Best Cost: 0.0395610067028
Step: 1
Best Cost: 0.0400605454777
Step: 1
Best Cost: 0.0390069507039
Step: 1
Best Cost: 0.0403015819474
Step: 1
Best Cost: 0.0386903030443
Step: 1
Best Cost: 0.041759117833
Step: 1
Best Cost: 0.039418862588
Step: 1
Best Cost: 0.0393220859809
Step: 1
Best Cost: 0.0400249905939
Step: 1
Best Cost: 0.0397387612747
Step: 1
Best Cost: 0.0416727611847
Step: 1
Best Cost: 0.0399293691137
Step: 1
Best Cost: 0.0395260154891
Step: 1
Best Cost: 0.0403403918279
Step: 1
Best Cost: 0.0401334772497
Step: 1
Best Cost: 0.0398211166588
Step: 1
Best Cost: 0.0392589191989
Step: 1
Best Cost: 0.0393195415263
Step: 1
Best Cost: 0.0412904062579
Step: 1
Best Cost: 0.0394534171558
Step: 1
Best Cost: 0.0393936522421
Step: 1
Best Cost: 0.0405301184361
Step: 1
Best Cost: 0.0400464854801
Step: 1
Best Cost: 0.0401806191277
Step: 1
Best Cost: 0.0407201268795
Step: 1
Best Cost: 0.0396118561013
Step: 1
Best Cost: 0.0398292541504
Step: 1
Best Cost: 0.0398325925067
Step: 1
Best Cost: 0.0410452097437
Step: 1
Best Cost: 0.0394654368263
Step: 1
Best Cost: 0.0397608317396
Step: 1
Best Cost: 0.0392876187423
Step: 1
Best Cost: 0.0409526884494
Step: 1
Best Cost: 0.0392175331076
Step: 1
Best Cost: 0.0393942516379
Step: 1
Best Cost: 0.0392577045294
Step: 1
Best Cost: 0.0383084204889
Step: 1
Best Cost: 0.0402423291003
Step: 1
Best Cost: 0.0419788618614
Step: 1
Best Cost: 0.0403807537861
Step: 1
Best Cost: 0.039782640217
Step: 1
Best Cost: 0.0397000823879
Step: 1
Best Cost: 0.0401201674891
Step: 1
Best Cost: 0.0403925511641
Step: 1
Best Cost: 0.0396331961768
Step: 1
Best Cost: 0.0398488516118
Step: 1
Best Cost: 0.0407741757015
Step: 1
Best Cost: 0.0408291176628
Step: 1
Best Cost: 0.0397646027723
Step: 1
Best Cost: 0.039203496927
Step: 1
Best Cost: 0.039457426359
Step: 1
Best Cost: 0.0400458900539
Step: 1
Best Cost: 0.0403594891313
Step: 1
Best Cost: 0.0393931798707
Step: 1
Best Cost: 0.0395868045358
Step: 1
Best Cost: 0.0384212339086
Step: 1
Best Cost: 0.0412339797005
Step: 1
Best Cost: 0.0407127991675
Step: 1
Best Cost: 0.0416042236582
Step: 1
Best Cost: 0.0396505389576
Step: 1
Best Cost: 0.0414191374049
Step: 1
Best Cost: 0.0398605259351
Step: 1
Best Cost: 0.0402796782018
Step: 1
Best Cost: 0.0403569883412
Step: 1
Best Cost: 0.0403533205157
Step: 1
Best Cost: 0.0408682728905
Step: 1
Best Cost: 0.0393523574496
Step: 1
Best Cost: 0.0390937360591
Step: 1
Best Cost: 0.0400016578254
Step: 1
Best Cost: 0.0385556612997
Step: 1
Best Cost: 0.0396926395603
Step: 1
Best Cost: 0.0400686234267
Step: 1
Best Cost: 0.0393978877073
Step: 1
Best Cost: 0.0389839315266
Step: 1
Best Cost: 0.0395600381428
Step: 1
Best Cost: 0.0400298492717
Step: 1
Best Cost: 0.0388931409377
Step: 1
Best Cost: 0.0399997524615
Step: 1
Best Cost: 0.0395692394626
Step: 1
Best Cost: 0.0404826669366
Step: 1
Best Cost: 0.0398596288262
Step: 1
Best Cost: 0.0401895267038
Step: 1
Best Cost: 0.0395405041936
Step: 1
Best Cost: 0.0406586550773
Step: 1
Best Cost: 0.0408986753529
Step: 1
Best Cost: 0.0411899300693
Step: 1
Best Cost: 0.0405295111014
Step: 1
Best Cost: 0.0399087594277
Step: 1
Best Cost: 0.0399442269824
Step: 1
Best Cost: 0.0390923983349
Step: 1
Best Cost: 0.0400400588465
Step: 1
Best Cost: 0.0393819818884
Step: 1
Best Cost: 0.0408633427615
Step: 1
Best Cost: 0.0390370276666
Step: 1
Best Cost: 0.040683801911
Step: 1
Best Cost: 0.0405460441026
Avg. Time
0.535617429018

NMI
[0.014499141437310323, 0.0018656866872284079, 0.074367665986504267, 0.016540701117224759, 3.8118872831827854e-05, 0.032209404269889587, 0.03245125422830189, 0.0066940745027972946, 0.020369985981670162, 0.0012934634946875801, 0.0066940745027972946, 0.00056151965855826241, 0.040285248550803052, 3.80161038597303e-06, 0.025450517127019043, 0.0072708540867058961, 0.0061204880800294721, 0.0015082682251279557, 0.0036109949259624141, 0.016540701117224759, 0.0013287866592082548, 0.040285248550803052, 0.040285248550803052, 0.0034139081680096433, 0.0081195548326033051, 1.5819268970631766e-05, 0.034381273979279293, 3.80161038597303e-06, 0.010915130325223931, 0.00037572709296588994, 3.80161038597303e-06, 0.0063218874478553101, 3.3633451524789452e-16, 0.037036777328865532, 0.010915130325223931, 3.3633451524789452e-16, 0.015277928871235346, 0.025996594351713552, 0.02621228682865448, 0.015277928871235346, 0.08188788171513213, 0.066538299367064499, 0.0034139081680096433, 0.027727652034549657, 1.5819268970631766e-05, 0.00037572709296588994, 0.00045711703858285945, 0.0098136619944997963, 0.032836404694826779, 0.0034139081680096433, 0.00031062579217721285, 3.8118872831827854e-05, 0.00088959404890583062, 0.10991750053900075, 0.00031062579217721285, 0.00056151965855826241, 0.014499141437310323, 0.010915130325223931, 3.80161038597303e-06, 3.80161038597303e-06, 0.01956398506867656, 0.014112824607315342, 0.10456220596808552, 0.0034139081680096433, 0.025996594351713552, 0.00037572709296588994, 0.0049619932222596053, 0.00025738902988997516, 3.80161038597303e-06, 0.00056151965855826241, 3.3633451524789452e-16, 0.0098136619944997963, 0.010915130325223931, 0.071376161295855861, 1.5819268970631766e-05, 0.00045711703858285945, 0.00037572709296588994, 0.0039116925504340929, 0.014119314794470867, 0.0063218874478553101, 0.020357780440473091, 0.014112824607315342, 0.0016595712035244348, 0.00025738902988997516, 3.80161038597303e-06, 0.0043446687990854899, 0.044550290105995788, 0.014499141437310323, 0.014112824607315342, 3.80161038597303e-06, 0.0043446687990854899, 0.044550290105995788, 0.00037572709296588994, 0.0018656866872284079, 0.064941564132711502, 0.039905711293898131, 0.00037572709296588994, 1.5819268970631766e-05, 0.0063218874478553101, 0.0061204880800294721, 0.010915130325223931, 0.0015082682251279557, 0.0034139081680096433, 0.0014000112495545984, 0.0016595712035244348, 0.0036109949259624141, 0.0034139081680096433, 0.0060802221692300784, 0.0016595712035244348, 0.0036109949259624141, 3.3633451524789452e-16, 0.037036777328865532, 0.019524986146721119, 0.011983958070948958, 0.0061204880800294721, 0.032836404694826779, 0.00045711703858285945, 0.0018656866872284079, 0.0032886209022759323, 0.0036109949259624141, 3.3633451524789452e-16, 0.039905711293898131, 0.0016595712035244348, 0.037036777328865532, 0.0062147980019104862, 0.0061204880800294721, 0.0015082682251279557, 0.0014000112495545984, 0.01928456555209412, 0.0081195548326033051, 0.0039116925504340929, 0.010217997982160122, 0.0016595712035244348, 3.8118872831827854e-05, 0.025450517127019043, 0.01956398506867656, 0.020369985981670162, 0.0034139081680096433, 0.0036109949259624141, 0.00025738902988997516, 0.0034139081680096433, 0.00045711703858285945, 0.021786338296317379, 1.5819268970631766e-05, 0.034381273979279293, 0.0034139081680096433, 0.0013287866592082548, 0.014112824607315342, 0.03245125422830189, 0.014499141437310323, 0.020369985981670162, 0.13664939900157785, 0.011983958070948958, 0.067475244760940092, 0.0036109949259624141, 0.01928456555209412, 0.015277928871235346, 0.0097855838248664881, 0.0014000112495545984, 0.00037572709296588994, 0.00045711703858285945, 0.00031062579217721285, 0.0043446687990854899, 0.0034139081680096433, 0.01956398506867656, 0.00045711703858285945, 0.00056151965855826241, 0.003306866462860482, 0.068808136095082656, 0.071376161295855861, 0.00037572709296588994, 0.015277928871235346, 0.0039116925504340929, 0.010217997982160122, 0.0063218874478553101, 0.014499141437310323, 0.025369557116165606, 0.015277928871235346, 0.0063218874478553101, 0.0098136619944997963, 0.020369985981670162, 0.27651210643358792, 0.05789317381925322, 0.011983958070948958, 0.00037572709296588994, 0.0034139081680096433, 0.0015082682251279557, 0.020369985981670162, 0.0013287866592082548, 0.032836404694826779, 0.025369557116165606, 0.003306866462860482, 0.052754855448359936, 0.024000440526313706, 0.010915130325223931, 0.12280207712637509, 0.0016595712035244348, 0.032209404269889587, 0.0072708540867058961, 0.0015082682251279557]

Costs
[matrix([[ 296.08937341]]), matrix([[ 293.26414455]]), matrix([[ 300.21898633]]), matrix([[ 299.44496257]]), matrix([[ 291.76846111]]), matrix([[ 296.32673615]]), matrix([[ 294.31250881]]), matrix([[ 292.66782343]]), matrix([[ 297.06735364]]), matrix([[ 293.60167748]]), matrix([[ 294.05220054]]), matrix([[ 291.74248869]]), matrix([[ 295.65759125]]), matrix([[ 297.652756]]), matrix([[ 294.78691582]]), matrix([[ 299.80485317]]), matrix([[ 297.11768967]]), matrix([[ 293.518405]]), matrix([[ 299.65647721]]), matrix([[ 291.08509817]]), matrix([[ 295.12795604]]), matrix([[ 297.67067061]]), matrix([[ 296.88333422]]), matrix([[ 296.75078833]]), matrix([[ 293.97197965]]), matrix([[ 296.348178]]), matrix([[ 300.30962606]]), matrix([[ 296.31259604]]), matrix([[ 298.56878867]]), matrix([[ 293.56608147]]), matrix([[ 298.81673706]]), matrix([[ 291.94181356]]), matrix([[ 294.29119159]]), matrix([[ 294.38918692]]), matrix([[ 290.99858207]]), matrix([[ 298.54571236]]), matrix([[ 291.2439375]]), matrix([[ 295.46542649]]), matrix([[ 294.48890732]]), matrix([[ 287.27803487]]), matrix([[ 294.29527853]]), matrix([[ 290.60404938]]), matrix([[ 292.12572129]]), matrix([[ 295.86280374]]), matrix([[ 294.28366625]]), matrix([[ 296.59112475]]), matrix([[ 289.96245894]]), matrix([[ 296.63219357]]), matrix([[ 300.56383775]]), matrix([[ 295.43729929]]), matrix([[ 292.71690704]]), matrix([[ 291.22594116]]), matrix([[ 293.48226383]]), matrix([[ 291.87115667]]), matrix([[ 294.10195816]]), matrix([[ 308.14836534]]), matrix([[ 295.32452535]]), matrix([[ 296.16472176]]), matrix([[ 292.06227504]]), matrix([[ 295.47717697]]), matrix([[ 293.26099933]]), matrix([[ 295.56399537]]), matrix([[ 289.57623908]]), matrix([[ 293.70858669]]), matrix([[ 295.86975254]]), matrix([[ 294.17954863]]), matrix([[ 291.48555308]]), matrix([[ 297.23161126]]), matrix([[ 295.80945878]]), matrix([[ 291.76707115]]), matrix([[ 303.75426089]]), matrix([[ 292.50122369]]), matrix([[ 289.82177679]]), matrix([[ 293.7949751]]), 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matrix([[ 296.86141478]]), matrix([[ 293.39364967]]), matrix([[ 297.03295081]]), matrix([[ 298.67345948]]), matrix([[ 299.32290832]]), matrix([[ 297.38154566]]), matrix([[ 296.95411295]]), matrix([[ 295.32533307]]), matrix([[ 289.94338666]]), matrix([[ 296.74447679]]), matrix([[ 289.86275364]]), matrix([[ 302.86284627]]), matrix([[ 290.9025308]]), matrix([[ 298.82430923]]), matrix([[ 298.58413506]])]

******************************
abs_adam
Step: 1
Best Cost: 0.039961442739
Step: 1
Best Cost: 0.0398129355027
Step: 1
Best Cost: 0.0395082757575
Step: 1
Best Cost: 0.0389373175932
Step: 1
Best Cost: 0.040447497095
Step: 1
Best Cost: 0.0396141544465
Step: 1
Best Cost: 0.0400696277122
Step: 1
Best Cost: 0.0399674962388
Step: 1
Best Cost: 0.0402078658311
Step: 1
Best Cost: 0.0388595469908
Step: 1
Best Cost: 0.0406503627749
Step: 1
Best Cost: 0.0407245330334
Step: 1
Best Cost: 0.0401084336232
Step: 1
Best Cost: 0.0401522808095
Step: 1
Best Cost: 0.0396537502896
Step: 1
Best Cost: 0.039650737433
Step: 1
Best Cost: 0.0391760557177
Step: 1
Best Cost: 0.040697552287
Step: 1
Best Cost: 0.0395143729219
Step: 1
Best Cost: 0.0396555286292
Step: 1
Best Cost: 0.0397521385169
Step: 1
Best Cost: 0.0396592639363
Step: 1
Best Cost: 0.0393814936389
Step: 1
Best Cost: 0.0398210610857
Step: 1
Best Cost: 0.0392497059706
Step: 1
Best Cost: 0.0401137090995
Step: 1
Best Cost: 0.0392752219685
Step: 1
Best Cost: 0.0401051984741
Step: 1
Best Cost: 0.0400363791125
Step: 1
Best Cost: 0.0417488566546
Step: 1
Best Cost: 0.0398446955368
Step: 1
Best Cost: 0.0396802864511
Step: 1
Best Cost: 0.0398998756687
Step: 1
Best Cost: 0.0387225394194
Step: 1
Best Cost: 0.038768490445
Step: 1
Best Cost: 0.0407819718153
Step: 1
Best Cost: 0.0398107046391
Step: 1
Best Cost: 0.040809563866
Step: 1
Best Cost: 0.039874986853
Step: 1
Best Cost: 0.0400877763032
Step: 1
Best Cost: 0.0404824764002
Step: 1
Best Cost: 0.0403151576651
Step: 1
Best Cost: 0.0395526627968
Step: 1
Best Cost: 0.0392414890889
Step: 1
Best Cost: 0.0398137651299
Step: 1
Best Cost: 0.0399001654427
Step: 1
Best Cost: 0.0392382063057
Step: 1
Best Cost: 0.0403474456438
Step: 1
Best Cost: 0.0407701823763
Step: 1
Best Cost: 0.0393862888046
Step: 1
Best Cost: 0.0391487335935
Step: 1
Best Cost: 0.0388798033906
Step: 1
Best Cost: 0.0398810840174
Step: 1
Best Cost: 0.0390007106372
Step: 1
Best Cost: 0.0410420976494
Step: 1
Best Cost: 0.040729951412
Step: 1
Best Cost: 0.0403454966153
Step: 1
Best Cost: 0.0391950140883
Step: 1
Best Cost: 0.0392195853433
Step: 1
Best Cost: 0.0400544006792
Step: 1
Best Cost: 0.0405988345905
Step: 1
Best Cost: 0.0397746615058
Step: 1
Best Cost: 0.0386086701106
Step: 1
Best Cost: 0.0397606015081
Step: 1
Best Cost: 0.0403424043685
Step: 1
Best Cost: 0.0389997539858
Step: 1
Best Cost: 0.038651838511
Step: 1
Best Cost: 0.0395685011341
Step: 1
Best Cost: 0.0402539796065
Step: 1
Best Cost: 0.039593258956
Step: 1
Best Cost: 0.0404102551701
Step: 1
Best Cost: 0.0396972719762
Step: 1
Best Cost: 0.0398908410683
Step: 1
Best Cost: 0.0400251255571
Step: 1
Best Cost: 0.0401006652959
Step: 1
Best Cost: 0.039393580791
Step: 1
Best Cost: 0.0397296631622
Step: 1
Best Cost: 0.0400180479242
Step: 1
Best Cost: 0.0415855471227
Step: 1
Best Cost: 0.0405721555267
Step: 1
Best Cost: 0.039131501959
Step: 1
Best Cost: 0.0391975783905
Step: 1
Best Cost: 0.0406881008883
Step: 1
Best Cost: 0.042261125642
Step: 1
Best Cost: 0.0399633322248
Step: 1
Best Cost: 0.0396802586646
Step: 1
Best Cost: 0.0402832626676
Step: 1
Best Cost: 0.0402209453603
Step: 1
Best Cost: 0.0389536044848
Step: 1
Best Cost: 0.0392847527574
Step: 1
Best Cost: 0.0394597643992
Step: 1
Best Cost: 0.0395163457674
Step: 1
Best Cost: 0.0389859361281
Step: 1
Best Cost: 0.0411692290847
Step: 1
Best Cost: 0.0409427329231
Step: 1
Best Cost: 0.0403075362095
Step: 1
Best Cost: 0.0391699863398
Step: 1
Best Cost: 0.0405096595915
Step: 1
Best Cost: 0.0414480592408
Step: 1
Best Cost: 0.0389519333219
Step: 1
Best Cost: 0.0399226725536
Step: 1
Best Cost: 0.0399633520724
Step: 1
Best Cost: 0.0400357162047
Step: 1
Best Cost: 0.0391098324144
Step: 1
Best Cost: 0.0399369349961
Step: 1
Best Cost: 0.0389616506777
Step: 1
Best Cost: 0.0406282526149
Step: 1
Best Cost: 0.0394391547133
Step: 1
Best Cost: 0.0393900638068
Step: 1
Best Cost: 0.0410445508054
Step: 1
Best Cost: 0.0394699461874
Step: 1
Best Cost: 0.0396618599946
Step: 1
Best Cost: 0.0398391699816
Step: 1
Best Cost: 0.0397073942218
Step: 1
Best Cost: 0.0399225137732
Step: 1
Best Cost: 0.0400996649799
Step: 1
Best Cost: 0.040826525574
Step: 1
Best Cost: 0.0399057783272
Step: 1
Best Cost: 0.0392729117148
Step: 1
Best Cost: 0.0395011425514
Step: 1
Best Cost: 0.0402429562826
Step: 1
Best Cost: 0.040492451774
Step: 1
Best Cost: 0.0399407139678
Step: 1
Best Cost: 0.0399439848424
Step: 1
Best Cost: 0.0392027109644
Step: 1
Best Cost: 0.040707380789
Step: 1
Best Cost: 0.0392119718268
Step: 1
Best Cost: 0.0396777936001
Step: 1
Best Cost: 0.0397292622418
Step: 1
Best Cost: 0.0404488506972
Step: 1
Best Cost: 0.0396512177435
Step: 1
Best Cost: 0.0399186315943
Step: 1
Best Cost: 0.0401420712347
Step: 1
Best Cost: 0.0394571127678
Step: 1
Best Cost: 0.0396670441722
Step: 1
Best Cost: 0.039500420101
Step: 1
Best Cost: 0.0400742402806
Step: 1
Best Cost: 0.0398548932031
Step: 1
Best Cost: 0.0396296474365
Step: 1
Best Cost: 0.0404796501104
Step: 1
Best Cost: 0.0392847448184
Step: 1
Best Cost: 0.0398172106629
Step: 1
Best Cost: 0.0396305326369
Step: 1
Best Cost: 0.0387286246753
Step: 1
Best Cost: 0.0400993513887
Step: 1
Best Cost: 0.0388813514987
Step: 1
Best Cost: 0.0395346769557
Step: 1
Best Cost: 0.0393550725931
Step: 1
Best Cost: 0.0409066223081
Step: 1
Best Cost: 0.0396283335294
Step: 1
Best Cost: 0.040788203943
Step: 1
Best Cost: 0.0407015376731
Step: 1
Best Cost: 0.0396282819258
Step: 1
Best Cost: 0.0396184573933
Step: 1
Best Cost: 0.0411025453184
Step: 1
Best Cost: 0.0409297685097
Step: 1
Best Cost: 0.0393015159901
Step: 1
Best Cost: 0.0388635045904
Step: 1
Best Cost: 0.0406226992731
Step: 1
Best Cost: 0.0397832277042
Step: 1
Best Cost: 0.0404719849903
Step: 1
Best Cost: 0.0404803288963
Step: 1
Best Cost: 0.0399754551025
Step: 1
Best Cost: 0.039379596214
Step: 1
Best Cost: 0.0396808937859
Step: 1
Best Cost: 0.0400664640143
Step: 1
Best Cost: 0.0385898228863
Step: 1
Best Cost: 0.0395251382278
Step: 1
Best Cost: 0.0400530589855
Step: 1
Best Cost: 0.0408812452429
Step: 1
Best Cost: 0.0404064285644
Step: 1
Best Cost: 0.0398616651839
Step: 1
Best Cost: 0.0401682223539
Step: 1
Best Cost: 0.0397524679861
Step: 1
Best Cost: 0.0398146781167
Step: 1
Best Cost: 0.039495998069
Step: 1
Best Cost: 0.0399181433448
Step: 1
Best Cost: 0.039376392821
Step: 1
Best Cost: 0.0398150314029
Step: 1
Best Cost: 0.0397104626516
Step: 1
Best Cost: 0.0397982086277
Step: 1
Best Cost: 0.0396097840181
Step: 1
Best Cost: 0.0402264550375
Step: 1
Best Cost: 0.0401876094314
Step: 1
Best Cost: 0.0399964379222
Step: 1
Best Cost: 0.0411008582775
Step: 1
Best Cost: 0.0404525661568
Step: 1
Best Cost: 0.0397352045954
Step: 1
Best Cost: 0.0402020147762
Step: 1
Best Cost: 0.0395164767612
Step: 1
Best Cost: 0.04011644806
Step: 1
Best Cost: 0.0401952745515
Step: 1
Best Cost: 0.0393684776219
Step: 1
Best Cost: 0.0411201540563
Step: 1
Best Cost: 0.0399338427493
Step: 1
Best Cost: 0.040028515517
Step: 1
Best Cost: 0.0402527093639
Step: 1
Best Cost: 0.0405962583798
Step: 1
Best Cost: 0.0396952118015
Step: 1
Best Cost: 0.040465427363
Avg. Time
0.65398283124

NMI
[0.014119314794470867, 0.00037572709296588994, 0.020369985981670162, 0.061682766476326215, 0.010915130325223931, 0.00037572709296588994, 0.00025738902988997516, 0.010217997982160122, 0.0098136619944997963, 0.086718189279395924, 0.032209404269889587, 0.0098136619944997963, 0.0018656866872284079, 0.0081195548326033051, 0.0036109949259624141, 0.0015082682251279557, 0.0043446687990854899, 0.00037572709296588994, 0.015277928871235346, 0.0063218874478553101, 0.010217997982160122, 0.0096685128569730557, 0.01928456555209412, 0.01956398506867656, 0.014112824607315342, 0.01928456555209412, 0.03245125422830189, 0.0036109949259624141, 0.0066940745027972946, 0.0063218874478553101, 0.0034139081680096433, 0.00037572709296588994, 0.079666253413707228, 0.003306866462860482, 0.0021469170480561258, 0.014119314794470867, 0.01928456555209412, 0.014119314794470867, 0.01928456555209412, 0.049941715410177064, 0.041773704733695988, 0.0034139081680096433, 0.025450517127019043, 0.014112824607315342, 0.00037572709296588994, 0.00056151965855826241, 0.0015082682251279557, 0.0036109949259624141, 0.0036109949259624141, 0.00056151965855826241, 0.020369985981670162, 0.0066940745027972946, 0.034381273979279293, 0.020369985981670162, 0.015277928871235346, 0.0072708540867058961, 0.0098136619944997963, 0.011983958070948958, 0.00045711703858285945, 0.0096685128569730557, 3.80161038597303e-06, 0.0066940745027972946, 0.00045711703858285945, 0.00037572709296588994, 0.014119314794470867, 0.014499141437310323, 0.01956398506867656, 0.032209404269889587, 0.0014000112495545984, 0.0014000112495545984, 0.014119314794470867, 0.01956398506867656, 0.0021469170480561258, 0.0039116925504340929, 0.0096685128569730557, 0.00031062579217721285, 0.003306866462860482, 0.032836404694826779, 3.80161038597303e-06, 3.3633451524789452e-16, 0.01928456555209412, 0.0036109949259624141, 0.0016595712035244348, 0.00025738902988997516, 3.80161038597303e-06, 0.0081195548326033051, 0.0063218874478553101, 0.020369985981670162, 0.040285248550803052, 0.0018656866872284079, 0.0096685128569730557, 0.020369985981670162, 0.032836404694826779, 0.027727652034549657, 0.025996594351713552, 0.0036109949259624141, 3.80161038597303e-06, 3.80161038597303e-06, 0.032836404694826779, 0.016540701117224759, 0.0098136619944997963, 0.0063218874478553101, 0.0036109949259624141, 0.0063218874478553101, 0.0081195548326033051, 0.0034139081680096433, 0.0015082682251279557, 3.3633451524789452e-16, 3.3633451524789452e-16, 1.5819268970631766e-05, 0.014119314794470867, 0.00056151965855826241, 3.80161038597303e-06, 0.0034139081680096433, 0.00037572709296588994, 0.014499141437310323, 0.0015082682251279557, 0.014499141437310323, 0.021786338296317379, 0.025369557116165606, 0.015277928871235346, 0.0034139081680096433, 0.0018656866872284079, 0.0098136619944997963, 0.034381273979279293, 0.0036109949259624141, 0.00037572709296588994, 0.00031062579217721285, 0.013575344754214038, 0.010217997982160122, 0.00025738902988997516, 0.003306866462860482, 0.015277928871235346, 0.00031062579217721285, 0.00056151965855826241, 3.3633451524789452e-16, 0.00056151965855826241, 0.00037572709296588994, 0.048614264428063735, 0.025450517127019043, 0.037036777328865532, 0.014499141437310323, 0.00037572709296588994, 0.014119314794470867, 0.0039116925504340929, 0.0036109949259624141, 3.80161038597303e-06, 0.010217997982160122, 0.0066940745027972946, 0.0061204880800294721, 0.0096685128569730557, 0.014119314794470867, 0.015277928871235346, 0.0016595712035244348, 1.5819268970631766e-05, 0.014499141437310323, 0.0061204880800294721, 3.3633451524789452e-16, 0.0034139081680096433, 0.0098136619944997963, 0.0036109949259624141, 0.0013287866592082548, 0.0039116925504340929, 0.02621228682865448, 0.00037572709296588994, 0.044550290105995788, 0.00031062579217721285, 0.00037572709296588994, 0.032209404269889587, 0.015277928871235346, 0.0018656866872284079, 0.0034139081680096433, 0.058933144644992684, 0.020369985981670162, 0.027727652034549657, 0.0018656866872284079, 3.3633451524789452e-16, 0.0034139081680096433, 0.0066940745027972946, 0.0096685128569730557, 0.02621228682865448, 0.01956398506867656, 0.020369985981670162, 0.00037572709296588994, 1.5819268970631766e-05, 0.0081195548326033051, 0.00045711703858285945, 0.020369985981670162, 0.058933144644992684, 0.0018656866872284079, 0.00031062579217721285, 0.0015082682251279557, 0.014499141437310323, 3.3633451524789452e-16, 0.0060802221692300784, 0.0096685128569730557, 0.0036109949259624141, 0.010217997982160122, 0.018459756328547638, 0.00045711703858285945]

Costs
[matrix([[ 300.54474797]]), matrix([[ 301.42685425]]), matrix([[ 300.29245091]]), matrix([[ 297.81395967]]), matrix([[ 302.80118872]]), matrix([[ 302.12348971]]), matrix([[ 303.69205642]]), matrix([[ 304.63827193]]), matrix([[ 303.85361151]]), matrix([[ 294.83326315]]), matrix([[ 307.95584389]]), matrix([[ 305.38112499]]), matrix([[ 304.51175214]]), matrix([[ 305.43105087]]), matrix([[ 300.14028776]]), matrix([[ 301.93670127]]), matrix([[ 296.14740232]]), matrix([[ 307.48341319]]), matrix([[ 301.95123292]]), matrix([[ 299.92404362]]), matrix([[ 300.77617249]]), matrix([[ 301.61372888]]), matrix([[ 299.19798007]]), matrix([[ 303.68873285]]), matrix([[ 297.52940463]]), matrix([[ 304.53096619]]), matrix([[ 297.50372582]]), matrix([[ 301.58342689]]), matrix([[ 301.01608137]]), matrix([[ 312.36330783]]), matrix([[ 299.88172589]]), matrix([[ 300.30234952]]), matrix([[ 303.52406284]]), matrix([[ 296.59787602]]), matrix([[ 296.24809448]]), matrix([[ 307.94225772]]), matrix([[ 303.3098407]]), matrix([[ 306.10734039]]), matrix([[ 301.12106626]]), matrix([[ 302.42940928]]), matrix([[ 302.84795139]]), matrix([[ 304.79390486]]), matrix([[ 300.78442261]]), matrix([[ 296.66406251]]), matrix([[ 303.30932103]]), matrix([[ 302.52585056]]), matrix([[ 298.19792105]]), matrix([[ 304.86866592]]), matrix([[ 303.15795062]]), matrix([[ 298.25164438]]), matrix([[ 299.40860048]]), matrix([[ 297.35969034]]), matrix([[ 303.94757603]]), matrix([[ 297.17557023]]), matrix([[ 307.48987087]]), matrix([[ 306.72820536]]), matrix([[ 305.08775665]]), matrix([[ 299.34182245]]), matrix([[ 298.92013933]]), matrix([[ 303.56700653]]), matrix([[ 303.44517764]]), matrix([[ 300.63742897]]), matrix([[ 294.11884362]]), matrix([[ 300.60968254]]), matrix([[ 306.66682241]]), matrix([[ 297.72277144]]), matrix([[ 296.2269066]]), matrix([[ 301.50214493]]), matrix([[ 304.39684415]]), matrix([[ 300.30116209]]), matrix([[ 307.76279857]]), matrix([[ 301.55188234]]), matrix([[ 302.73410019]]), matrix([[ 303.94058525]]), matrix([[ 306.4376849]]), matrix([[ 298.52864434]]), matrix([[ 301.76485571]]), matrix([[ 303.4427816]]), matrix([[ 306.04203329]]), matrix([[ 302.66747812]]), matrix([[ 297.55073455]]), matrix([[ 296.21760362]]), matrix([[ 307.44249205]]), matrix([[ 315.03972837]]), matrix([[ 304.25217674]]), matrix([[ 300.01591961]]), matrix([[ 303.08958908]]), matrix([[ 301.48489032]]), matrix([[ 297.99715967]]), matrix([[ 300.23831099]]), matrix([[ 300.82137973]]), matrix([[ 298.57381613]]), matrix([[ 297.16711211]]), matrix([[ 305.96585709]]), matrix([[ 306.46755146]]), matrix([[ 307.53025502]]), matrix([[ 297.71266926]]), matrix([[ 306.45420032]]), matrix([[ 308.22166961]]), matrix([[ 296.4557887]]), matrix([[ 303.22060425]]), matrix([[ 302.02872361]]), matrix([[ 303.29391805]]), matrix([[ 298.4411003]]), matrix([[ 302.76645102]]), matrix([[ 297.40823821]]), matrix([[ 305.04877333]]), matrix([[ 298.31730841]]), matrix([[ 296.94537367]]), matrix([[ 304.04741929]]), matrix([[ 296.5572882]]), matrix([[ 302.20035396]]), matrix([[ 302.25152987]]), matrix([[ 302.99711007]]), matrix([[ 305.92218609]]), matrix([[ 301.75460963]]), matrix([[ 302.9672884]]), matrix([[ 301.29056022]]), matrix([[ 298.20612166]]), matrix([[ 298.78676292]]), matrix([[ 300.7043635]]), matrix([[ 306.55151826]]), matrix([[ 301.18166784]]), matrix([[ 300.24057594]]), matrix([[ 297.34859503]]), matrix([[ 305.91480499]]), matrix([[ 299.56494438]]), matrix([[ 303.90251646]]), matrix([[ 300.01464329]]), matrix([[ 301.68597674]]), matrix([[ 302.35032182]]), matrix([[ 302.55122804]]), matrix([[ 302.29261054]]), matrix([[ 299.48609216]]), matrix([[ 299.62194398]]), matrix([[ 298.48578752]]), matrix([[ 305.96267725]]), matrix([[ 303.91773917]]), matrix([[ 298.386162]]), matrix([[ 303.57132608]]), matrix([[ 300.79189014]]), matrix([[ 304.56422653]]), matrix([[ 299.17807904]]), matrix([[ 296.59291498]]), matrix([[ 300.60404187]]), matrix([[ 297.6307723]]), matrix([[ 300.19093959]]), matrix([[ 299.21163347]]), matrix([[ 310.47594903]]), matrix([[ 300.91319034]]), matrix([[ 304.11267388]]), matrix([[ 307.3979768]]), matrix([[ 301.26724764]]), matrix([[ 301.08773752]]), matrix([[ 309.63624692]]), matrix([[ 301.66142203]]), matrix([[ 300.21204704]]), matrix([[ 296.71777865]]), matrix([[ 306.49790562]]), matrix([[ 304.09473459]]), matrix([[ 305.18126696]]), matrix([[ 305.52389603]]), matrix([[ 301.05715117]]), matrix([[ 298.84154568]]), matrix([[ 300.80663152]]), matrix([[ 302.65814445]]), matrix([[ 296.1409495]]), matrix([[ 299.30712718]]), matrix([[ 300.11631522]]), matrix([[ 304.43692355]]), matrix([[ 306.96939566]]), matrix([[ 301.48101263]]), matrix([[ 303.96582623]]), matrix([[ 298.59107859]]), matrix([[ 302.49453399]]), matrix([[ 300.52511559]]), matrix([[ 303.92921495]]), matrix([[ 301.02458076]]), matrix([[ 304.07165266]]), matrix([[ 301.9303793]]), matrix([[ 302.56814029]]), matrix([[ 302.85398722]]), matrix([[ 302.83523206]]), matrix([[ 305.37970551]]), matrix([[ 300.55699538]]), matrix([[ 304.81206557]]), matrix([[ 304.14923699]]), matrix([[ 305.03151454]]), matrix([[ 300.85515425]]), matrix([[ 296.53552271]]), matrix([[ 302.11585391]]), matrix([[ 305.97999902]]), matrix([[ 301.37772421]]), matrix([[ 301.25510894]]), matrix([[ 300.64144369]]), matrix([[ 299.0120506]]), matrix([[ 302.60978822]]), matrix([[ 305.74380321]]), matrix([[ 303.75192795]]), matrix([[ 305.22089398]])]

******************************
clip_adam
Step: 1
Best Cost: 0.0404221795724
Step: 1
Best Cost: 0.0400520586695
Step: 1
Best Cost: 0.039856322226
Step: 1
Best Cost: 0.039233700914
Step: 1
Best Cost: 0.039269569389
Step: 1
Best Cost: 0.0391188868623
Step: 1
Best Cost: 0.0399681273906
Step: 1
Best Cost: 0.0392133452766
Step: 1
Best Cost: 0.0408677012814
Step: 1
Best Cost: 0.0412022553919
Step: 1
Best Cost: 0.0400624548111
Step: 1
Best Cost: 0.0400760503763
Step: 1
Best Cost: 0.0398941556075
Step: 1
Best Cost: 0.0402213343721
Step: 1
Best Cost: 0.0395979270975
Step: 1
Best Cost: 0.0398190961792
Step: 1
Best Cost: 0.0394330257928
Step: 1
Best Cost: 0.0402271814575
Step: 1
Best Cost: 0.03921404391
Step: 1
Best Cost: 0.0393380473729
Step: 1
Best Cost: 0.0403459451697
Step: 1
Best Cost: 0.0413858729272
Step: 1
Best Cost: 0.040478967355
Step: 1
Best Cost: 0.039267608452
Step: 1
Best Cost: 0.0396947632471
Step: 1
Best Cost: 0.0407190868683
Step: 1
Best Cost: 0.0394559258849
Step: 1
Best Cost: 0.0400165395111
Step: 1
Best Cost: 0.040452451041
Step: 1
Best Cost: 0.0399377685928
Step: 1
Best Cost: 0.0402073497951
Step: 1
Best Cost: 0.0392735428666
Step: 1
Best Cost: 0.0403601917342
Step: 1
Best Cost: 0.0391911398484
Step: 1
Best Cost: 0.0400308218012
Step: 1
Best Cost: 0.0407900457948
Step: 1
Best Cost: 0.0392848083306
Step: 1
Best Cost: 0.0396360065885
Step: 1
Best Cost: 0.0400513640055
Step: 1
Best Cost: 0.0397447552319
Step: 1
Best Cost: 0.0404470247235
Step: 1
Best Cost: 0.0389697445047
Step: 1
Best Cost: 0.0395049374012
Step: 1
Best Cost: 0.0406971791532
Step: 1
Best Cost: 0.0399906305319
Step: 1
Best Cost: 0.0396335891581
Step: 1
Best Cost: 0.039769890157
Step: 1
Best Cost: 0.0395499595618
Step: 1
Best Cost: 0.039717052035
Step: 1
Best Cost: 0.0390309225632
Step: 1
Best Cost: 0.0401083621721
Step: 1
Best Cost: 0.040522921718
Step: 1
Best Cost: 0.0392414136682
Step: 1
Best Cost: 0.0400996967359
Step: 1
Best Cost: 0.040316368365
Step: 1
Best Cost: 0.0400699651204
Step: 1
Best Cost: 0.0403476917533
Step: 1
Best Cost: 0.0397534683021
Step: 1
Best Cost: 0.0400837551915
Step: 1
Best Cost: 0.0395754954073
Step: 1
Best Cost: 0.0400160353836
Step: 1
Best Cost: 0.0409995881874
Step: 1
Best Cost: 0.040403332348
Step: 1
Best Cost: 0.0406571744508
Step: 1
Best Cost: 0.0403277727617
Step: 1
Best Cost: 0.0399321596779
Step: 1
Best Cost: 0.0404537570092
Step: 1
Best Cost: 0.0398896502158
Step: 1
Best Cost: 0.0396384915006
Step: 1
Best Cost: 0.0407750450237
Step: 1
Best Cost: 0.0391275086338
Step: 1
Best Cost: 0.0398055680957
Step: 1
Best Cost: 0.0405006249911
Step: 1
Best Cost: 0.0395565449757
Step: 1
Best Cost: 0.0386219838407
Step: 1
Best Cost: 0.0400063775705
Step: 1
Best Cost: 0.0408414429854
Step: 1
Best Cost: 0.0413530927295
Step: 1
Best Cost: 0.0401459692916
Step: 1
Best Cost: 0.0386945107229
Step: 1
Best Cost: 0.0402697544316
Step: 1
Best Cost: 0.0399588506502
Step: 1
Best Cost: 0.039612407863
Step: 1
Best Cost: 0.0408075632339
Step: 1
Best Cost: 0.0403840524473
Step: 1
Best Cost: 0.0414485554293
Step: 1
Best Cost: 0.0414568517012
Step: 1
Best Cost: 0.0400826238817
Step: 1
Best Cost: 0.0408341708466
Step: 1
Best Cost: 0.0390895720451
Step: 1
Best Cost: 0.0400762766383
Step: 1
Best Cost: 0.0399168254682
Step: 1
Best Cost: 0.0390127938198
Step: 1
Best Cost: 0.0401117044979
Step: 1
Best Cost: 0.0412492940627
Step: 1
Best Cost: 0.0397256222029
Step: 1
Best Cost: 0.0393288460532
Step: 1
Best Cost: 0.0399908567939
Step: 1
Best Cost: 0.0391530166928
Step: 1
Best Cost: 0.0405349572665
Step: 1
Best Cost: 0.0391451094327
Step: 1
Best Cost: 0.0390994283337
Step: 1
Best Cost: 0.0399782853618
Step: 1
Best Cost: 0.039573883787
Step: 1
Best Cost: 0.0408339485542
Step: 1
Best Cost: 0.0408296257599
Step: 1
Best Cost: 0.039455255038
Step: 1
Best Cost: 0.0406661336305
Step: 1
Best Cost: 0.0397314256237
Step: 1
Best Cost: 0.0400037934207
Step: 1
Best Cost: 0.0401519553098
Step: 1
Best Cost: 0.0400585686627
Step: 1
Best Cost: 0.0397855419274
Step: 1
Best Cost: 0.0397684968597
Step: 1
Best Cost: 0.0393987808466
Step: 1
Best Cost: 0.0390146197935
Step: 1
Best Cost: 0.0401215329999
Step: 1
Best Cost: 0.0401879785957
Step: 1
Best Cost: 0.0393976098417
Step: 1
Best Cost: 0.0383365643012
Step: 1
Best Cost: 0.0384525493578
Step: 1
Best Cost: 0.0404941983575
Step: 1
Best Cost: 0.0387197925198
Step: 1
Best Cost: 0.0401990257366
Step: 1
Best Cost: 0.0394836171733
Step: 1
Best Cost: 0.039967357306
Step: 1
Best Cost: 0.0401921584877
Step: 1
Best Cost: 0.040487045304
Step: 1
Best Cost: 0.0396795243056
Step: 1
Best Cost: 0.0402371568313
Step: 1
Best Cost: 0.0396155239268
Step: 1
Best Cost: 0.0395946601923
Step: 1
Best Cost: 0.0401295831623
Step: 1
Best Cost: 0.039553742503
Step: 1
Best Cost: 0.0394588156868
Step: 1
Best Cost: 0.0394227566754
Step: 1
Best Cost: 0.0405732352329
Step: 1
Best Cost: 0.039194371028
Step: 1
Best Cost: 0.039917246236
Step: 1
Best Cost: 0.0395698428278
Step: 1
Best Cost: 0.0397246060089
Step: 1
Best Cost: 0.0410779462769
Step: 1
Best Cost: 0.0397130110758
Step: 1
Best Cost: 0.0405075200266
Step: 1
Best Cost: 0.0386812882915
Step: 1
Best Cost: 0.0395756264011
Step: 1
Best Cost: 0.039708692251
Step: 1
Best Cost: 0.0401324134215
Step: 1
Best Cost: 0.0391120751864
Step: 1
Best Cost: 0.0395701365714
Step: 1
Best Cost: 0.0402297100341
Step: 1
Best Cost: 0.0406781255144
Step: 1
Best Cost: 0.0412201658124
Step: 1
Best Cost: 0.0396806238593
Step: 1
Best Cost: 0.0395309337096
Step: 1
Best Cost: 0.0415506710247
Step: 1
Best Cost: 0.0395875071388
Step: 1
Best Cost: 0.0408464882302
Step: 1
Best Cost: 0.0403290310958
Step: 1
Best Cost: 0.0402582547667
Step: 1
Best Cost: 0.040243646977
Step: 1
Best Cost: 0.0401980730547
Step: 1
Best Cost: 0.0394999556685
Step: 1
Best Cost: 0.0396523292057
Step: 1
Best Cost: 0.0400229780533
Step: 1
Best Cost: 0.0392994518459
Step: 1
Best Cost: 0.0404708457415
Step: 1
Best Cost: 0.0394010752222
Step: 1
Best Cost: 0.0390912154215
Step: 1
Best Cost: 0.0400698063401
Step: 1
Best Cost: 0.0402396377738
Step: 1
Best Cost: 0.040802172642
Step: 1
Best Cost: 0.0401120577841
Step: 1
Best Cost: 0.040062665195
Step: 1
Best Cost: 0.0388898780021
Step: 1
Best Cost: 0.0400102518103
Step: 1
Best Cost: 0.0427441869889
Step: 1
Best Cost: 0.0391349038274
Step: 1
Best Cost: 0.0389194627458
Step: 1
Best Cost: 0.0405957502828
Step: 1
Best Cost: 0.0399203424523
Step: 1
Best Cost: 0.0399473271683
Step: 1
Best Cost: 0.0387204832143
Step: 1
Best Cost: 0.0399928137614
Step: 1
Best Cost: 0.0394366459842
Step: 1
Best Cost: 0.0384695428219
Step: 1
Best Cost: 0.0404147526228
Step: 1
Best Cost: 0.039502162715
Step: 1
Best Cost: 0.0397456483712
Step: 1
Best Cost: 0.040596345709
Step: 1
Best Cost: 0.0400782216972
Step: 1
Best Cost: 0.0397712239118
Step: 1
Best Cost: 0.0398641540654
Step: 1
Best Cost: 0.0389901517457
Step: 1
Best Cost: 0.0408017836302
Step: 1
Best Cost: 0.0396478436616
Step: 1
Best Cost: 0.0404630694752
Step: 1
Best Cost: 0.0393092684393
Step: 1
Best Cost: 0.0392935610959
Step: 1
Best Cost: 0.0399729701905
Avg. Time
0.671148172617

NMI
[0.0016595712035244348, 0.01928456555209412, 0.025369557116165606, 0.0039116925504340929, 0.0061204880800294721, 0.0016595712035244348, 0.011983958070948958, 0.00021298448018247591, 0.027727652034549657, 0.0039116925504340929, 0.01956398506867656, 0.048614264428063735, 1.5819268970631766e-05, 0.02621228682865448, 0.025369557116165606, 0.0016595712035244348, 0.041773704733695988, 0.027727652034549657, 0.0015082682251279557, 0.0021469170480561258, 0.025369557116165606, 3.3633451524789452e-16, 0.00069964954636247316, 0.01928456555209412, 0.00056151965855826241, 0.00037572709296588994, 0.068808136095082656, 0.00045711703858285945, 0.0016595712035244348, 0.00031062579217721285, 0.08188788171513213, 0.021786338296317379, 0.010915130325223931, 0.068808136095082656, 0.0014000112495545984, 0.0066940745027972946, 0.06954283561482176, 0.00056151965855826241, 3.3633451524789452e-16, 0.00037572709296588994, 0.0043446687990854899, 3.80161038597303e-06, 0.00056151965855826241, 0.00037572709296588994, 0.0072708540867058961, 0.00056151965855826241, 1.5819268970631766e-05, 0.048614264428063735, 0.0018656866872284079, 0.0060802221692300784, 0.00037572709296588994, 0.016540701117224759, 0.0015082682251279557, 0.00045711703858285945, 0.00045711703858285945, 0.0093645942086020388, 0.0032886209022759323, 0.0066940745027972946, 0.00037572709296588994, 3.3633451524789452e-16, 0.049941715410177064, 0.0072708540867058961, 0.0016595712035244348, 0.014119314794470867, 0.025369557116165606, 0.00037572709296588994, 0.049941715410177064, 0.032209404269889587, 0.0066940745027972946, 0.0066940745027972946, 0.0043446687990854899, 0.015277928871235346, 0.048614264428063735, 0.027727652034549657, 0.040285248550803052, 0.0016595712035244348, 0.00045711703858285945, 0.00031062579217721285, 0.032836404694826779, 0.0063218874478553101, 0.003306866462860482, 0.025450517127019043, 0.0014000112495545984, 0.0063218874478553101, 0.015277928871235346, 0.010915130325223931, 3.80161038597303e-06, 0.0066940745027972946, 0.0036109949259624141, 0.040285248550803052, 0.020369985981670162, 0.049941715410177064, 0.015277928871235346, 0.048614264428063735, 0.0039116925504340929, 0.015277928871235346, 0.048614264428063735, 0.0018656866872284079, 0.0043446687990854899, 0.003306866462860482, 0.014499141437310323, 0.00037572709296588994, 0.00045711703858285945, 0.049941715410177064, 0.0066940745027972946, 3.80161038597303e-06, 0.0066940745027972946, 0.0015082682251279557, 0.00037572709296588994, 0.020369985981670162, 0.020369985981670162, 3.80161038597303e-06, 0.040626754665685695, 0.1223645497127871, 0.0015082682251279557, 0.0061204880800294721, 0.014119314794470867, 0.00056151965855826241, 0.0036109949259624141, 0.0066940745027972946, 0.0034139081680096433, 0.0066940745027972946, 0.0061204880800294721, 3.80161038597303e-06, 0.0014000112495545984, 0.0063218874478553101, 0.01956398506867656, 0.0015082682251279557, 0.0060802221692300784, 3.8118872831827854e-05, 0.048621306182437353, 0.0081195548326033051, 0.016540701117224759, 0.0066940745027972946, 0.0081195548326033051, 0.0063218874478553101, 0.0039116925504340929, 0.0061204880800294721, 0.020369985981670162, 3.80161038597303e-06, 0.032209404269889587, 0.0039116925504340929, 0.0015082682251279557, 0.032836404694826779, 0.020369985981670162, 0.0036109949259624141, 0.0043446687990854899, 0.00069964954636247316, 0.071376161295855861, 0.010217997982160122, 0.00025738902988997516, 0.091522115159181669, 0.011983958070948958, 0.015277928871235346, 0.0096685128569730557, 0.02621228682865448, 1.5819268970631766e-05, 3.80161038597303e-06, 0.0014000112495545984, 0.0018656866872284079, 0.00045711703858285945, 0.0063218874478553101, 0.044550290105995788, 0.021786338296317379, 0.0018656866872284079, 0.02621228682865448, 0.0034139081680096433, 0.0034139081680096433, 0.0072708540867058961, 0.020369985981670162, 0.0096685128569730557, 0.052754855448359936, 0.01928456555209412, 0.015277928871235346, 0.0043446687990854899, 0.00045711703858285945, 0.0098136619944997963, 0.048614264428063735, 0.0072708540867058961, 0.00045711703858285945, 0.010217997982160122, 0.033643856413456588, 0.00045711703858285945, 3.80161038597303e-06, 0.00037572709296588994, 0.02621228682865448, 0.00037572709296588994, 0.0015082682251279557, 0.01928456555209412, 0.0036109949259624141, 0.0034139081680096433, 0.0016595712035244348, 0.00031062579217721285, 0.0061204880800294721, 0.0016595712035244348, 0.003306866462860482, 0.0096685128569730557, 0.02621228682865448, 0.0016595712035244348, 0.034381273979279293]

Costs
[matrix([[ 306.48798971]]), matrix([[ 301.85640914]]), matrix([[ 305.48254008]]), matrix([[ 300.43034209]]), matrix([[ 299.2134036]]), matrix([[ 296.99861167]]), matrix([[ 302.08511003]]), matrix([[ 300.06006448]]), matrix([[ 308.28125255]]), matrix([[ 311.92577318]]), matrix([[ 306.12650344]]), matrix([[ 303.34051569]]), matrix([[ 305.65663396]]), matrix([[ 302.40476383]]), matrix([[ 302.47572511]]), matrix([[ 305.2170895]]), matrix([[ 301.0290182]]), matrix([[ 300.64542426]]), matrix([[ 299.35770397]]), matrix([[ 300.95093301]]), matrix([[ 303.41783757]]), matrix([[ 308.08291818]]), matrix([[ 302.11055655]]), matrix([[ 300.16947676]]), matrix([[ 300.79115714]]), matrix([[ 305.90143841]]), matrix([[ 301.96065088]]), matrix([[ 303.36657242]]), matrix([[ 303.95428754]]), matrix([[ 303.66552787]]), matrix([[ 304.11810679]]), matrix([[ 297.33761819]]), matrix([[ 304.84854716]]), matrix([[ 297.04412907]]), matrix([[ 306.15346068]]), matrix([[ 305.4203134]]), matrix([[ 299.25939476]]), matrix([[ 300.29893977]]), matrix([[ 303.76905173]]), matrix([[ 298.95015234]]), matrix([[ 307.8302672]]), matrix([[ 297.16219833]]), matrix([[ 297.97890679]]), matrix([[ 305.05649759]]), matrix([[ 300.24472521]]), matrix([[ 299.45493706]]), matrix([[ 300.16766669]]), matrix([[ 301.86299998]]), matrix([[ 302.72039135]]), matrix([[ 297.45126393]]), matrix([[ 301.5729048]]), matrix([[ 302.00876117]]), matrix([[ 299.5300697]]), matrix([[ 303.63872488]]), matrix([[ 305.18023002]]), matrix([[ 304.13469659]]), matrix([[ 305.70207218]]), matrix([[ 302.64388824]]), matrix([[ 305.14428679]]), matrix([[ 301.26845285]]), matrix([[ 304.14571836]]), matrix([[ 307.41781145]]), matrix([[ 305.64329794]]), matrix([[ 302.08625625]]), matrix([[ 303.73554959]]), matrix([[ 301.39164314]]), matrix([[ 308.14148159]]), matrix([[ 301.28805652]]), matrix([[ 298.39072851]]), matrix([[ 307.46614367]]), matrix([[ 298.84598534]]), matrix([[ 300.54477876]]), matrix([[ 306.14758505]]), matrix([[ 303.04708009]]), matrix([[ 295.7340791]]), matrix([[ 305.6881041]]), matrix([[ 309.46386039]]), matrix([[ 308.82603034]]), matrix([[ 300.01646524]]), matrix([[ 295.72187469]]), matrix([[ 303.287754]]), matrix([[ 303.11364618]]), matrix([[ 300.22368761]]), matrix([[ 307.95949746]]), matrix([[ 307.58754725]]), matrix([[ 308.76395168]]), matrix([[ 305.96861808]]), matrix([[ 303.15202873]]), matrix([[ 308.20942096]]), matrix([[ 298.40557384]]), matrix([[ 302.91586643]]), matrix([[ 301.15646574]]), matrix([[ 296.59524749]]), matrix([[ 303.26086527]]), matrix([[ 306.77306086]]), matrix([[ 301.77516144]]), matrix([[ 299.33569104]]), matrix([[ 304.05280358]]), matrix([[ 297.11168694]]), matrix([[ 303.47294018]]), matrix([[ 299.32019665]]), matrix([[ 294.0702312]]), matrix([[ 302.81025525]]), matrix([[ 298.82136733]]), matrix([[ 304.0350583]]), matrix([[ 309.02704572]]), matrix([[ 298.17422704]]), matrix([[ 307.89139527]]), matrix([[ 301.03386653]]), matrix([[ 300.84962257]]), matrix([[ 302.8776635]]), matrix([[ 305.89236487]]), matrix([[ 304.39430688]]), matrix([[ 302.90903593]]), matrix([[ 298.94084667]]), matrix([[ 299.12210474]]), matrix([[ 301.79243351]]), matrix([[ 303.0715089]]), matrix([[ 301.11513734]]), matrix([[ 293.61453936]]), matrix([[ 294.26477969]]), matrix([[ 302.51565185]]), matrix([[ 296.75114614]]), matrix([[ 303.72745519]]), matrix([[ 302.91655552]]), matrix([[ 301.9752832]]), matrix([[ 303.8419181]]), matrix([[ 307.95644871]]), matrix([[ 303.84951403]]), matrix([[ 301.4080528]]), matrix([[ 300.51592706]]), matrix([[ 297.0189916]]), matrix([[ 306.01046385]]), matrix([[ 299.68838915]]), matrix([[ 302.61262928]]), matrix([[ 300.31732982]]), matrix([[ 305.71535542]]), matrix([[ 296.6465948]]), matrix([[ 300.14820009]]), matrix([[ 300.64043568]]), matrix([[ 302.26945346]]), matrix([[ 305.60536256]]), matrix([[ 303.84117199]]), matrix([[ 303.01047034]]), matrix([[ 297.45337498]]), matrix([[ 301.08496885]]), matrix([[ 298.18016648]]), matrix([[ 304.17419631]]), matrix([[ 298.27863605]]), matrix([[ 301.97388427]]), matrix([[ 304.70236489]]), matrix([[ 308.5366119]]), matrix([[ 310.71445347]]), matrix([[ 302.87599887]]), matrix([[ 298.84289106]]), matrix([[ 308.0497883]]), matrix([[ 301.8429498]]), matrix([[ 305.90210119]]), matrix([[ 302.17183232]]), matrix([[ 304.02558841]]), matrix([[ 305.29844415]]), matrix([[ 305.47531549]]), matrix([[ 300.11476082]]), matrix([[ 298.17145085]]), matrix([[ 304.28891955]]), matrix([[ 299.89009272]]), matrix([[ 308.96018642]]), matrix([[ 300.26823946]]), matrix([[ 299.61392887]]), matrix([[ 301.80553358]]), matrix([[ 305.15733718]]), matrix([[ 307.97188662]]), matrix([[ 304.48227085]]), matrix([[ 304.65309093]]), matrix([[ 293.53726685]]), matrix([[ 303.74211334]]), matrix([[ 315.02886116]]), matrix([[ 297.68968208]]), matrix([[ 297.64646835]]), matrix([[ 306.19208227]]), matrix([[ 299.78378467]]), matrix([[ 303.77546458]]), matrix([[ 296.55969989]]), matrix([[ 302.72403137]]), matrix([[ 300.70455182]]), matrix([[ 294.20222383]]), matrix([[ 302.32552257]]), matrix([[ 299.6997359]]), matrix([[ 302.1975512]]), matrix([[ 302.51390412]]), matrix([[ 299.34392197]]), matrix([[ 303.44595188]]), matrix([[ 304.30185577]]), matrix([[ 296.84862644]]), matrix([[ 304.88127583]]), matrix([[ 298.93443]]), matrix([[ 304.62526533]]), matrix([[ 300.11484244]]), matrix([[ 297.48834344]]), matrix([[ 303.16012388]])]

In [7]:

    

const2 = pd.read_pickle("data/const/degree_dolphins_0.1.pkl")


    

In [9]:

    

const_path


    

    
Out[9]:





'data/const/degree_dolphins_0.pkl'

In [10]:

    

densities


    

    
Out[10]:





[0.1]

In [11]:

    

"{:.1f}".format(1.23)


    

    
Out[11]:





'1.2'

In [3]:

    

for name, time in times.items():
    print(name, numpy.mean(time))


    

    




clip_sgd 0.65811971426
update_rule 0.374646325111
abs_sgd 0.535617429018
abs_adam 0.65398283124
clip_adam 0.671148172617

In [5]:

    

x = range(max_iters)


    

In [6]:

    

%matplotlib inline
import matplotlib.pyplot as plt


    

In [7]:

    

plt.plot(x, nmis["abs_adam"])


    

    
Out[7]:





[<matplotlib.lines.Line2D at 0x10edcc828>]






    

In [9]:

    

plt.plot(x, costs["abs_adam"])


    

    




---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-9-0cb4a19740b9> in <module>()
----> 1 plt.plot(x, costs["abs_adam"][0,0])

TypeError: list indices must be integers or slices, not tuple

In [ ]: