Summary Errors
Per Model Errors
Unexpected Crashes

Algorithms: 6

Summary Tables

Total

Algorithm
--------
Value
Blended Mobius Voting Best Conformal GMDS HKM 1 corr HKM 2 corrs
Average Error 0.034162 0.0984677 0.0840756 0.308529 0.239495 0.22871
Maximal Error 0.31125 0.446499 0.53724 0.97009 1.27089 1.21384

NRW_cat

Algorithm
--------
Value
Blended Mobius Voting Best Conformal GMDS HKM 1 corr HKM 2 corrs
Average Error 0.0429963 0.0999533 0.102726 0.149015 0.189947 0.181499
Maximal Error 0.207475 0.533004 0.460798 0.485472 0.879472 0.82029

NRW_centaur

Algorithm
--------
Value
Blended Mobius Voting Best Conformal GMDS HKM 1 corr HKM 2 corrs
Average Error 0.0602307 0.0406538 0.0839941 0.145579 0.153793 0.120493
Maximal Error 0.546046 0.362131 0.477646 0.618263 0.944531 0.895913

NRW_david

Algorithm
--------
Value
Blended Mobius Voting Best Conformal GMDS HKM 1 corr HKM 2 corrs
Average Error 0.0290288 0.211845 0.0842856 0.246312 0.271014 0.179879
Maximal Error 0.141289 0.727017 0.609431 0.87851 1.44829 1.30711

NRW_dog

Algorithm
--------
Value
Blended Mobius Voting Best Conformal GMDS HKM 1 corr HKM 2 corrs
Average Error 0.0369711 0.0499479 0.0970863 0.540326 0.23029 0.229084
Maximal Error 0.230664 0.294243 0.512391 1.16177 1.15414 1.18216

NRW_gorilla

Algorithm
--------
Value
Blended Mobius Voting Best Conformal GMDS HKM 1 corr HKM 2 corrs
Average Error 0.0309295 0.0363288 0.0723188 0.364032 0.228642 0.190014
Maximal Error 0.3297 0.188841 0.449263 1.05939 1.31934 1.16255

NRW_horse

Algorithm
--------
Value
Blended Mobius Voting Best Conformal GMDS HKM 1 corr HKM 2 corrs
Average Error 0.0234855 0.0342346 0.0661911 0.334968 0.169564 0.156836
Maximal Error 0.120558 0.211632 0.51072 0.978106 1.17489 1.06562

NRW_michael

Algorithm
--------
Value
Blended Mobius Voting Best Conformal GMDS HKM 1 corr HKM 2 corrs
Average Error 0.0329491 0.13923 0.0869618 0.281964 0.267939 0.25928
Maximal Error 0.325947 0.497807 0.608271 0.989057 1.4591 1.44282

NRW_victoria

Algorithm
--------
Value
Blended Mobius Voting Best Conformal GMDS HKM 1 corr HKM 2 corrs
Average Error 0.0305686 0.112868 0.0790197 0.391837 0.326958 0.360233
Maximal Error 0.603413 0.590651 0.598191 1.43518 1.58909 1.52402

NRW_wolf

Algorithm
--------
Value
Blended Mobius Voting Best Conformal GMDS HKM 1 corr HKM 2 corrs
Average Error 0.00842215 0.0144519 0.0406828 0.36846 0.208127 0.24443
Maximal Error 0.0777808 0.151459 0.313498 0.962075 0.958929 0.866402

Per Experiment Values

Values in each cell: average geodesic error, maximal geodesic error, images
Blended Mobius Voting Best Conformal GMDS HKM 1 corr HKM 2 corrs
cat0_to_cat6 Ave=0.051583
Max=0.225116
Dense

Ave=0.0596654
Max=0.239712
Dense
Sparse
Ave=0.0899471
Max=0.359546
Dense

Ave=0.232681
Max=0.649229
Dense
Sparse
Ave=0.383311
Max=0.98315
Dense
Sparse
Ave=0.273929
Max=0.735451
Dense
Sparse
cat1_to_cat10 Ave=0.043349
Max=0.271927
Dense

Ave=0.103164
Max=0.67455
Dense
Sparse
Ave=0.074127
Max=0.371199
Dense

Ave=0.110157
Max=0.654293
Dense
Sparse
Ave=0.158108
Max=0.732389
Dense
Sparse
Ave=0.145372
Max=0.732389
Dense
Sparse
cat2_to_cat6 Ave=0.0333473
Max=0.222152
Dense

Ave=0.0402861
Max=0.382441
Dense
Sparse
Ave=0.0509785
Max=0.354849
Dense

Ave=0.0446753
Max=0.283302
Dense
Sparse
Ave=0.137885
Max=1.07875
Dense
Sparse
Ave=0.0868674
Max=1.07875
Dense
Sparse
cat3_to_cat2 Ave=0.0495791
Max=0.221769
Dense

Ave=0.211942
Max=0.72469
Dense
Sparse
Ave=0.0779102
Max=0.376611
Dense

Ave=0.207985
Max=0.698247
Dense
Sparse
Ave=0.223366
Max=0.814835
Dense
Sparse
Ave=0.21867
Max=0.814835
Dense
Sparse
cat4_to_cat1 Ave=0.0214585
Max=0.0956718
Dense

Ave=0.0584393
Max=0.437884
Dense
Sparse
Ave=0.0461152
Max=0.391872
Dense

Ave=0.0359803
Max=0.240015
Dense
Sparse
Ave=0.171943
Max=0.626625
Dense
Sparse
Ave=0.199221
Max=0.626625
Dense
Sparse
cat5_to_cat4 Ave=0.0404379
Max=0.207731
Dense

Ave=0.112301
Max=0.698762
Dense
Sparse
Ave=0.0780366
Max=0.442848
Dense

Ave=0.0646213
Max=0.321743
Dense
Sparse
Ave=0.151069
Max=0.77025
Dense
Sparse
Ave=0.186058
Max=0.97852
Dense
Sparse
cat6_to_cat3 Ave=0.0571628
Max=0.231542
Dense

Ave=0.141018
Max=0.639323
Dense
Sparse
Ave=0.206768
Max=0.687818
Dense

Ave=0.105522
Max=0.296214
Dense
Sparse
Ave=0.163317
Max=1.03923
Dense
Sparse
Ave=0.154592
Max=0.690677
Dense
Sparse
cat7_to_cat1 Ave=0.0768488
Max=0.252887
Dense

Ave=0.113492
Max=0.582483
Dense
Sparse
Ave=0.121667
Max=0.482038
Dense

Ave=0.286391
Max=0.626169
Dense
Sparse
Ave=0.169386
Max=0.982
Dense
Sparse
Ave=0.161051
Max=0.982
Dense
Sparse
cat8_to_cat7 Ave=0.0331693
Max=0.25581
Dense

Ave=0.0411643
Max=0.212211
Dense
Sparse
Ave=0.058031
Max=0.291741
Dense

Ave=0.0415944
Max=0.150255
Dense
Sparse
Ave=0.160888
Max=0.62101
Dense
Sparse
Ave=0.204577
Max=0.77796
Dense
Sparse
cat9_to_cat5 Ave=0.033146
Max=0.122133
Dense

Ave=0.135183
Max=0.62746
Dense
Sparse
Ave=0.162599
Max=0.674236
Dense

Ave=0.284634
Max=0.732058
Dense
Sparse
Ave=0.189063
Max=0.888496
Dense
Sparse
Ave=0.195894
Max=0.841636
Dense
Sparse
cat10_to_cat3 Ave=0.0328778
Max=0.175487
Dense

Ave=0.0828317
Max=0.643532
Dense
Sparse
Ave=0.163806
Max=0.636019
Dense

Ave=0.224929
Max=0.688664
Dense
Sparse
Ave=0.181082
Max=1.13746
Dense
Sparse
Ave=0.170261
Max=0.764342
Dense
Sparse
centaur0_to_centaur5 Ave=0.0182938
Max=0.111098
Dense

Ave=0.0307983
Max=0.165039
Dense
Sparse
Ave=0.0794758
Max=0.501054
Dense

Ave=0.0324711
Max=0.154511
Dense
Sparse
Ave=0.135755
Max=0.949281
Dense
Sparse
Ave=0.0979367
Max=0.949281
Dense
Sparse
centaur1_to_centaur4 Ave=0.0673759
Max=0.778481
Dense

Ave=0.0440688
Max=0.210611
Dense
Sparse
Ave=0.0848083
Max=0.430374
Dense

Ave=0.262743
Max=0.83931
Dense
Sparse
Ave=0.191805
Max=0.957437
Dense
Sparse
Ave=0.150201
Max=0.819629
Dense
Sparse
centaur2_to_centaur0 Ave=0.0513766
Max=0.570865
Dense

Ave=0.0301913
Max=0.162134
Dense
Sparse
Ave=0.0907269
Max=0.480816
Dense

Ave=0.0399024
Max=0.167548
Dense
Sparse
Ave=0.123181
Max=0.864636
Dense
Sparse
Ave=0.0741086
Max=0.881775
Dense
Sparse
centaur3_to_centaur0 Ave=0.0198047
Max=0.0878335
Dense

Ave=0.0393966
Max=0.471322
Dense
Sparse
Ave=0.0939458
Max=0.488307
Dense

Ave=0.118033
Max=0.884433
Dense
Sparse
Ave=0.13625
Max=1.07969
Dense
Sparse
Ave=0.122138
Max=1.07969
Dense
Sparse
centaur4_to_centaur5 Ave=0.0657782
Max=0.718276
Dense

Ave=0.0368012
Max=0.184579
Dense
Sparse
Ave=0.0813935
Max=0.494559
Dense

Ave=0.217904
Max=0.819127
Dense
Sparse
Ave=0.124743
Max=0.832976
Dense
Sparse
Ave=0.0864696
Max=0.824143
Dense
Sparse
centaur5_to_centaur2 Ave=0.138755
Max=1.00972
Dense

Ave=0.0626668
Max=0.9791
Dense
Sparse
Ave=0.0736143
Max=0.470765
Dense

Ave=0.202421
Max=0.844649
Dense
Sparse
Ave=0.211023
Max=0.983163
Dense
Sparse
Ave=0.192105
Max=0.820957
Dense
Sparse
david0_to_david12 Ave=0.0151656
Max=0.132396
Dense

Ave=0.0145146
Max=0.138697
Dense
Sparse
Ave=0.0618711
Max=0.624659
Dense

Ave=0.0266473
Max=0.14137
Dense
Sparse
Ave=0.382793
Max=1.57747
Dense
Sparse
Ave=0.241707
Max=1.57747
Dense
Sparse
david1_to_david6 Ave=0.0458398
Max=0.159656
Dense

Ave=0.0565514
Max=0.211152
Dense
Sparse
Ave=0.0934626
Max=0.672403
Dense

Ave=0.0586979
Max=0.268265
Dense
Sparse
Ave=0.216607
Max=1.51651
Dense
Sparse
Ave=0.0818844
Max=1.15969
Dense
Sparse
david6_to_david12 Ave=0.0334443
Max=0.153408
Dense

Ave=0.0358331
Max=0.212238
Dense
Sparse
Ave=0.0797265
Max=0.538586
Dense

Ave=0.50857
Max=1.44983
Dense
Sparse
Ave=0.404087
Max=1.4194
Dense
Sparse
Ave=0.256639
Max=1.3146
Dense
Sparse
david10_to_david12 Ave=0.0280337
Max=0.131161
Dense

Ave=0.546177
Max=1.45873
Dense
Sparse
Ave=0.0742647
Max=0.538864
Dense

Ave=0.0516569
Max=0.200247
Dense
Sparse
Ave=0.188121
Max=1.38046
Dense
Sparse
Ave=0.0819965
Max=1.2874
Dense
Sparse
david11_to_david13 Ave=0.0230992
Max=0.145598
Dense

Ave=0.0289601
Max=0.185185
Dense
Sparse
Ave=0.0815261
Max=0.624896
Dense

Ave=0.336607
Max=1.44199
Dense
Sparse
Ave=0.208251
Max=1.42482
Dense
Sparse
Ave=0.333654
Max=1.44707
Dense
Sparse
david12_to_david1 Ave=0.0345013
Max=0.137392
Dense

Ave=0.515311
Max=1.42439
Dense
Sparse
Ave=0.0967944
Max=0.65747
Dense

Ave=0.252054
Max=1.20018
Dense
Sparse
Ave=0.206166
Max=1.40168
Dense
Sparse
Ave=0.0785787
Max=1.10708
Dense
Sparse
david13_to_david12 Ave=0.023118
Max=0.129411
Dense

Ave=0.28557
Max=1.45873
Dense
Sparse
Ave=0.102354
Max=0.60914
Dense

Ave=0.489952
Max=1.44769
Dense
Sparse
Ave=0.29107
Max=1.41768
Dense
Sparse
Ave=0.18469
Max=1.25647
Dense
Sparse
dog0_to_dog6 Ave=0.0261652
Max=0.214726
Dense

Ave=0.0337433
Max=0.1505
Dense
Sparse
Ave=0.0867917
Max=0.568118
Dense

Ave=0.301287
Max=0.835605
Dense
Sparse
Ave=0.126109
Max=0.982611
Dense
Sparse
Ave=0.122008
Max=1.34201
Dense
Sparse
dog1_to_dog0 Ave=0.0270723
Max=0.231561
Dense

Ave=0.048395
Max=0.251976
Dense
Sparse
Ave=0.105043
Max=0.502538
Dense

Ave=0.65926
Max=1.25037
Dense
Sparse
Ave=0.205407
Max=1.20576
Dense
Sparse
Ave=0.233489
Max=1.16802
Dense
Sparse
dog2_to_dog0 Ave=0.0257799
Max=0.161103
Dense

Ave=0.0355511
Max=0.196997
Dense
Sparse
Ave=0.0818054
Max=0.522737
Dense

Ave=0.385989
Max=0.981552
Dense
Sparse
Ave=0.178136
Max=1.19961
Dense
Sparse
Ave=0.125517
Max=1.19993
Dense
Sparse
dog3_to_dog6 Ave=0.0259152
Max=0.152867
Dense

Ave=0.0453295
Max=0.254378
Dense
Sparse
Ave=0.0815267
Max=0.617966
Dense

Ave=0.722216
Max=1.39966
Dense
Sparse
Ave=0.180997
Max=1.35668
Dense
Sparse
Ave=0.132579
Max=1.35721
Dense
Sparse
dog5_to_dog3 Ave=0.0250938
Max=0.191005
Dense

Ave=0.0404039
Max=0.263313
Dense
Sparse
Ave=0.0866688
Max=0.473791
Dense

Ave=0.707258
Max=1.38667
Dense
Sparse
Ave=0.196621
Max=1.12858
Dense
Sparse
Ave=0.177053
Max=1.12163
Dense
Sparse
dog6_to_dog1 Ave=0.0419598
Max=0.173645
Dense

Ave=0.071071
Max=0.399645
Dense
Sparse
Ave=0.114958
Max=0.552688
Dense

Ave=0.702069
Max=1.27784
Dense
Sparse
Ave=0.573099
Max=1.15168
Dense
Sparse
Ave=0.584822
Max=1.07319
Dense
Sparse
dog7_to_dog8 Ave=0.039542
Max=0.295387
Dense

Ave=0.016557
Max=0.121885
Dense
Sparse
Ave=0.0614531
Max=0.346312
Dense

Ave=0.250725
Max=0.873685
Dense
Sparse
Ave=0.173275
Max=0.974526
Dense
Sparse
Ave=0.215446
Max=1.00278
Dense
Sparse
dog8_to_dog5 Ave=0.063917
Max=0.352945
Dense

Ave=0.0800722
Max=0.258704
Dense
Sparse
Ave=0.135809
Max=0.545706
Dense

Ave=0.708631
Max=1.4485
Dense
Sparse
Ave=0.245082
Max=1.37275
Dense
Sparse
Ave=0.251484
Max=1.37275
Dense
Sparse
dog10_to_dog8 Ave=0.0572949
Max=0.302736
Dense

Ave=0.0784079
Max=0.75079
Dense
Sparse
Ave=0.119721
Max=0.481663
Dense

Ave=0.425503
Max=1.00203
Dense
Sparse
Ave=0.193884
Max=1.01504
Dense
Sparse
Ave=0.219359
Max=1.00195
Dense
Sparse
gorilla1_to_gorilla5 Ave=0.0198626
Max=0.0762007
Dense

Ave=0.0324438
Max=0.198474
Dense
Sparse
Ave=0.0648391
Max=0.416223
Dense

Ave=0.482941
Max=1.28447
Dense
Sparse
Ave=0.358418
Max=1.36243
Dense
Sparse
Ave=0.424994
Max=1.39425
Dense
Sparse
gorilla5_to_gorilla14 Ave=0.0386425
Max=0.424303
Dense

Ave=0.0419241
Max=0.188469
Dense
Sparse
Ave=0.0829849
Max=0.490544
Dense

Ave=0.494098
Max=1.319
Dense
Sparse
Ave=0.145512
Max=1.31265
Dense
Sparse
Ave=0.121412
Max=1.28602
Dense
Sparse
gorilla8_to_gorilla1 Ave=0.0319106
Max=0.124066
Dense

Ave=0.0389082
Max=0.206029
Dense
Sparse
Ave=0.0781333
Max=0.511693
Dense

Ave=0.429481
Max=1.35947
Dense
Sparse
Ave=0.258436
Max=1.3836
Dense
Sparse
Ave=0.127565
Max=0.911946
Dense
Sparse
gorilla14_to_gorilla8 Ave=0.0333024
Max=0.694232
Dense

Ave=0.0320392
Max=0.16239
Dense
Sparse
Ave=0.063318
Max=0.378592
Dense

Ave=0.0496076
Max=0.274606
Dense
Sparse
Ave=0.152202
Max=1.21869
Dense
Sparse
Ave=0.0860832
Max=1.058
Dense
Sparse
horse0_to_horse10 Ave=0.0105245
Max=0.0634653
Dense

Ave=0.0168567
Max=0.168207
Dense
Sparse
Ave=0.0379367
Max=0.430427
Dense

Ave=0.0194669
Max=0.113716
Dense
Sparse
Ave=0.0991999
Max=0.846741
Dense
Sparse
Ave=0.0603432
Max=0.846741
Dense
Sparse
horse5_to_horse7 Ave=0.0349788
Max=0.158512
Dense

Ave=0.0454406
Max=0.20138
Dense
Sparse
Ave=0.0701715
Max=0.502989
Dense

Ave=0.704897
Max=1.42731
Dense
Sparse
Ave=0.191797
Max=1.1726
Dense
Sparse
Ave=0.152855
Max=1.1726
Dense
Sparse
horse6_to_horse14 Ave=0.0189204
Max=0.08183
Dense

Ave=0.0261643
Max=0.342745
Dense
Sparse
Ave=0.053675
Max=0.488097
Dense

Ave=0.25681
Max=0.982239
Dense
Sparse
Ave=0.209945
Max=1.34633
Dense
Sparse
Ave=0.243171
Max=1.25601
Dense
Sparse
horse7_to_horse15 Ave=0.0325881
Max=0.114682
Dense

Ave=0.0517029
Max=0.195148
Dense
Sparse
Ave=0.127908
Max=0.820749
Dense

Ave=0.217632
Max=0.951636
Dense
Sparse
Ave=0.168133
Max=1.38086
Dense
Sparse
Ave=0.128501
Max=1.11576
Dense
Sparse
horse10_to_horse7 Ave=0.0249021
Max=0.150918
Dense

Ave=0.0341028
Max=0.175572
Dense
Sparse
Ave=0.0602426
Max=0.457443
Dense

Ave=0.735882
Max=1.438
Dense
Sparse
Ave=0.180352
Max=1.42638
Dense
Sparse
Ave=0.127823
Max=0.910002
Dense
Sparse
horse14_to_horse10 Ave=0.0220549
Max=0.170485
Dense

Ave=0.0277415
Max=0.154319
Dense
Sparse
Ave=0.0522811
Max=0.440166
Dense

Ave=0.259214
Max=0.948516
Dense
Sparse
Ave=0.134413
Max=1.29136
Dense
Sparse
Ave=0.0814395
Max=1.29136
Dense
Sparse
horse15_to_horse10 Ave=0.018219
Max=0.0837302
Dense

Ave=0.0369083
Max=0.237504
Dense
Sparse
Ave=0.0585466
Max=0.465487
Dense

Ave=0.214348
Max=0.980509
Dense
Sparse
Ave=0.203575
Max=0.972934
Dense
Sparse
Ave=0.254913
Max=0.970577
Dense
Sparse
horse17_to_horse5 Ave=0.0256965
Max=0.14084
Dense

Ave=0.0349599
Max=0.218182
Dense
Sparse
Ave=0.0687674
Max=0.480402
Dense

Ave=0.271494
Max=0.982922
Dense
Sparse
Ave=0.169098
Max=0.96195
Dense
Sparse
Ave=0.205645
Max=0.96195
Dense
Sparse
michael0_to_michael2 Ave=0.0288037
Max=1.00639
Dense

Ave=0.0457813
Max=0.217145
Dense
Sparse
Ave=0.110352
Max=0.72688
Dense

Ave=0.336531
Max=1.49661
Dense
Sparse
Ave=0.306761
Max=1.47464
Dense
Sparse
Ave=0.436816
Max=1.47878
Dense
Sparse
michael1_to_michael10 Ave=0.0364254
Max=0.114023
Dense

Ave=0.547468
Max=1.53718
Dense
Sparse
Ave=0.102432
Max=0.62874
Dense

Ave=0.294641
Max=1.19812
Dense
Sparse
Ave=0.237253
Max=1.56236
Dense
Sparse
Ave=0.101574
Max=1.51439
Dense
Sparse
michael2_to_michael16 Ave=0.0427193
Max=0.47206
Dense

Ave=0.0471836
Max=0.235348
Dense
Sparse
Ave=0.0848162
Max=0.588388
Dense

Ave=0.0504166
Max=1.05955
Dense
Sparse
Ave=0.222523
Max=1.51067
Dense
Sparse
Ave=0.0931369
Max=1.51067
Dense
Sparse
michael3_to_michael1 Ave=0.0192354
Max=0.103337
Dense

Ave=0.0271732
Max=0.170271
Dense
Sparse
Ave=0.0568648
Max=0.527492
Dense

Ave=0.488891
Max=1.47051
Dense
Sparse
Ave=0.426053
Max=1.45597
Dense
Sparse
Ave=0.489839
Max=1.48456
Dense
Sparse
michael4_to_michael5 Ave=0.0212739
Max=0.0872308
Dense

Ave=0.0431449
Max=0.263449
Dense
Sparse
Ave=0.077083
Max=0.627942
Dense

Ave=0.504653
Max=1.51759
Dense
Sparse
Ave=0.158757
Max=1.49476
Dense
Sparse
Ave=0.352635
Max=1.5011
Dense
Sparse
michael5_to_michael7 Ave=0.0290637
Max=0.0990729
Dense

Ave=0.530868
Max=1.52226
Dense
Sparse
Ave=0.0737388
Max=0.549153
Dense

Ave=0.0472293
Max=0.193834
Dense
Sparse
Ave=0.202021
Max=1.53265
Dense
Sparse
Ave=0.0860854
Max=1.53265
Dense
Sparse
michael6_to_michael16 Ave=0.0567787
Max=0.537516
Dense

Ave=0.036334
Max=0.212595
Dense
Sparse
Ave=0.0774922
Max=0.524727
Dense

Ave=0.229496
Max=1.22729
Dense
Sparse
Ave=0.319829
Max=1.41115
Dense
Sparse
Ave=0.447202
Max=1.44832
Dense
Sparse
michael7_to_michael6 Ave=0.0308232
Max=0.119586
Dense

Ave=0.0454459
Max=0.623881
Dense
Sparse
Ave=0.0911178
Max=0.646529
Dense

Ave=0.49093
Max=1.49427
Dense
Sparse
Ave=0.469332
Max=1.59335
Dense
Sparse
Ave=0.3421
Max=1.48515
Dense
Sparse
michael8_to_michael9 Ave=0.0253481
Max=0.115985
Dense

Ave=0.0393798
Max=0.212752
Dense
Sparse
Ave=0.0577961
Max=0.490373
Dense

Ave=0.0394615
Max=0.152725
Dense
Sparse
Ave=0.232937
Max=1.53902
Dense
Sparse
Ave=0.0781886
Max=1.47666
Dense
Sparse
michael9_to_michael13 Ave=0.0293311
Max=0.135557
Dense

Ave=0.045913
Max=0.185555
Dense
Sparse
Ave=0.0878829
Max=0.598598
Dense

Ave=0.495116
Max=1.47334
Dense
Sparse
Ave=0.266573
Max=1.59732
Dense
Sparse
Ave=0.119275
Max=1.5844
Dense
Sparse
michael10_to_michael17 Ave=0.0396712
Max=0.111677
Dense

Ave=0.561412
Max=1.48873
Dense
Sparse
Ave=0.0897083
Max=0.629758
Dense

Ave=0.057313
Max=0.231852
Dense
Sparse
Ave=0.178705
Max=1.31643
Dense
Sparse
Ave=0.359872
Max=1.47938
Dense
Sparse
michael11_to_michael4 Ave=0.0334171
Max=0.1253
Dense

Ave=0.455659
Max=1.30172
Dense
Sparse
Ave=0.120492
Max=0.674454
Dense

Ave=0.108495
Max=0.370272
Dense
Sparse
Ave=0.172742
Max=1.13806
Dense
Sparse
Ave=0.10625
Max=1.11578
Dense
Sparse
michael12_to_michael15 Ave=0.0354309
Max=0.137349
Dense

Ave=0.0420716
Max=0.223791
Dense
Sparse
Ave=0.0785478
Max=0.61938
Dense

Ave=0.108723
Max=0.354466
Dense
Sparse
Ave=0.332693
Max=1.41866
Dense
Sparse
Ave=0.202479
Max=1.26012
Dense
Sparse
michael13_to_michael2 Ave=0.0391957
Max=0.997119
Dense

Ave=0.0436311
Max=0.238557
Dense
Sparse
Ave=0.0950649
Max=0.658773
Dense

Ave=0.493503
Max=1.49786
Dense
Sparse
Ave=0.224575
Max=1.42447
Dense
Sparse
Ave=0.366485
Max=1.47981
Dense
Sparse
michael14_to_michael5 Ave=0.0349704
Max=0.142836
Dense

Ave=0.0531812
Max=0.221253
Dense
Sparse
Ave=0.0960152
Max=0.638776
Dense

Ave=0.0579306
Max=0.298615
Dense
Sparse
Ave=0.220129
Max=1.50584
Dense
Sparse
Ave=0.346441
Max=1.50584
Dense
Sparse
michael15_to_michael14 Ave=0.0411319
Max=0.922919
Dense

Ave=0.0633116
Max=0.318595
Dense
Sparse
Ave=0.11332
Max=0.650734
Dense

Ave=0.531099
Max=1.46743
Dense
Sparse
Ave=0.169794
Max=1.32773
Dense
Sparse
Ave=0.0934625
Max=1.24871
Dense
Sparse
michael16_to_michael7 Ave=0.0269325
Max=0.129498
Dense

Ave=0.0424167
Max=0.304092
Dense
Sparse
Ave=0.0951958
Max=0.669215
Dense

Ave=0.232711
Max=1.17725
Dense
Sparse
Ave=0.422126
Max=1.5282
Dense
Sparse
Ave=0.504625
Max=1.5282
Dense
Sparse
michael17_to_michael14 Ave=0.0371933
Max=0.9188
Dense

Ave=0.0407573
Max=0.229307
Dense
Sparse
Ave=0.0736985
Max=0.560104
Dense

Ave=0.0317276
Max=0.152476
Dense
Sparse
Ave=0.177793
Max=1.43638
Dense
Sparse
Ave=0.0832141
Max=1.44235
Dense
Sparse
michael18_to_michael4 Ave=0.0310391
Max=0.155839
Dense

Ave=0.0434157
Max=0.231306
Dense
Sparse
Ave=0.0998557
Max=0.609574
Dense

Ave=0.503361
Max=1.48702
Dense
Sparse
Ave=0.445047
Max=1.48393
Dense
Sparse
Ave=0.51234
Max=1.48393
Dense
Sparse
michael19_to_michael3 Ave=0.0201974
Max=0.086847
Dense

Ave=0.0300497
Max=0.218345
Dense
Sparse
Ave=0.0577621
Max=0.54582
Dense

Ave=0.537051
Max=1.46006
Dense
Sparse
Ave=0.173127
Max=1.43034
Dense
Sparse
Ave=0.0635836
Max=1.29565
Dense
Sparse
victoria0_to_victoria2 Ave=0.0228517
Max=1.27588
Dense

Ave=0.0330116
Max=0.151363
Dense
Sparse
Ave=0.0637142
Max=0.620435
Dense

Ave=0.191468
Max=1.25471
Dense
Sparse
Ave=0.287929
Max=1.51107
Dense
Sparse
Ave=0.403939
Max=1.51107
Dense
Sparse
victoria1_to_victoria17 Ave=0.0332984
Max=0.791916
Dense

Ave=0.0434939
Max=0.322622
Dense
Sparse
Ave=0.075312
Max=0.553719
Dense

Ave=0.486615
Max=1.51923
Dense
Sparse
Ave=0.433071
Max=1.50352
Dense
Sparse
Ave=0.479943
Max=1.50352
Dense
Sparse
victoria2_to_victoria21 Ave=0.0524995
Max=1.27457
Dense

Ave=0.0723207
Max=0.394309
Dense
Sparse
Ave=0.11017
Max=0.654431
Dense

Ave=0.380509
Max=1.58488
Dense
Sparse
Ave=0.320961
Max=1.55805
Dense
Sparse
Ave=0.479096
Max=1.57715
Dense
Sparse
victoria4_to_victoria0 Ave=0.0174983
Max=0.0848443
Dense

Ave=0.0253512
Max=0.165771
Dense
Sparse
Ave=0.0578552
Max=0.58308
Dense

Ave=0.533049
Max=1.52063
Dense
Sparse
Ave=0.197981
Max=1.71139
Dense
Sparse
Ave=0.339399
Max=1.50578
Dense
Sparse
victoria7_to_victoria4 Ave=0.0340028
Max=0.116945
Dense

Ave=0.441255
Max=1.47448
Dense
Sparse
Ave=0.0952637
Max=0.590363
Dense

Ave=0.485027
Max=1.55316
Dense
Sparse
Ave=0.306347
Max=1.70291
Dense
Sparse
Ave=0.166437
Max=1.70291
Dense
Sparse
victoria10_to_victoria25 Ave=0.0210312
Max=0.105935
Dense

Ave=0.0316855
Max=0.219659
Dense
Sparse
Ave=0.0689392
Max=0.603149
Dense

Ave=0.336047
Max=1.58618
Dense
Sparse
Ave=0.206522
Max=1.56725
Dense
Sparse
Ave=0.0817638
Max=1.18537
Dense
Sparse
victoria12_to_victoria2 Ave=0.0309587
Max=1.36302
Dense

Ave=0.108409
Max=1.20353
Dense
Sparse
Ave=0.0756503
Max=0.604902
Dense

Ave=0.520176
Max=1.54256
Dense
Sparse
Ave=0.208888
Max=1.76273
Dense
Sparse
Ave=0.23534
Max=1.78122
Dense
Sparse
victoria17_to_victoria0 Ave=0.0167165
Max=0.0771651
Dense

Ave=0.0241904
Max=0.126522
Dense
Sparse
Ave=0.0570179
Max=0.558363
Dense

Ave=0.264851
Max=1.24084
Dense
Sparse
Ave=0.315023
Max=1.48403
Dense
Sparse
Ave=0.419996
Max=1.48744
Dense
Sparse
victoria21_to_victoria0 Ave=0.0376092
Max=0.124776
Dense

Ave=0.402894
Max=1.45066
Dense
Sparse
Ave=0.114104
Max=0.648503
Dense

Ave=0.25062
Max=1.25657
Dense
Sparse
Ave=0.65065
Max=1.58894
Dense
Sparse
Ave=0.705536
Max=1.68451
Dense
Sparse
victoria23_to_victoria21 Ave=0.0494084
Max=1.29105
Dense

Ave=0.0924321
Max=1.1259
Dense
Sparse
Ave=0.097784
Max=0.667482
Dense

Ave=0.198144
Max=1.12175
Dense
Sparse
Ave=0.35421
Max=1.54542
Dense
Sparse
Ave=0.491717
Max=1.58187
Dense
Sparse
victoria24_to_victoria0 Ave=0.0239647
Max=0.0894714
Dense

Ave=0.0364808
Max=0.142296
Dense
Sparse
Ave=0.0657877
Max=0.588684
Dense

Ave=0.529383
Max=1.52247
Dense
Sparse
Ave=0.420974
Max=1.50283
Dense
Sparse
Ave=0.428006
Max=1.50533
Dense
Sparse
victoria25_to_victoria17 Ave=0.0269839
Max=0.645379
Dense

Ave=0.0428863
Max=0.310703
Dense
Sparse
Ave=0.0666385
Max=0.505179
Dense

Ave=0.526154
Max=1.51923
Dense
Sparse
Ave=0.220935
Max=1.63092
Dense
Sparse
Ave=0.0916288
Max=1.26203
Dense
Sparse
wolf0_to_wolf1 Ave=0.0053208
Max=0.0883482
Dense

Ave=0.00670015
Max=0.101946
Dense
Sparse
Ave=0.0311681
Max=0.246418
Dense

Ave=0.624385
Max=1.24389
Dense
Sparse
Ave=0.223332
Max=1.10759
Dense
Sparse
Ave=0.239465
Max=0.809803
Dense
Sparse
wolf1_to_wolf2 Ave=0.00867894
Max=0.0655666
Dense

Ave=0.0172345
Max=0.184186
Dense
Sparse
Ave=0.0445947
Max=0.344952
Dense

Ave=0.232678
Max=0.811421
Dense
Sparse
Ave=0.199332
Max=0.969005
Dense
Sparse
Ave=0.244618
Max=0.969005
Dense
Sparse
wolf2_to_wolf0 Ave=0.0112667
Max=0.0794276
Dense

Ave=0.0194212
Max=0.168244
Dense
Sparse
Ave=0.0462856
Max=0.349124
Dense

Ave=0.248316
Max=0.830913
Dense
Sparse
Ave=0.201716
Max=0.800191
Dense
Sparse
Ave=0.249206
Max=0.820397
Dense
Sparse