In [1]:
import h2o
import numpy as np
import matplotlib.patches as mpatches
import matplotlib.pyplot as plt
In [2]:
h2o.init()
Warning: Version mismatch. H2O is version (unknown), but the python package is version UNKNOWN.
H2O cluster uptime:
12 minutes 31 seconds 995 milliseconds H2O cluster version:
(unknown) H2O cluster name:
spIdea H2O cluster total nodes:
1 H2O cluster total memory:
12.44 GB H2O cluster total cores:
8 H2O cluster allowed cores:
8 H2O cluster healthy:
True H2O Connection ip:
127.0.0.1 H2O Connection port:
54321
In [3]:
from h2o.h2o import _locate # private function. used to find files within h2o git project directory.
# Import walking gait data
gait = h2o.upload_file(path=_locate("smalldata/glrm_test/subject01_walk1.csv"))
gait.describe()
Parse Progress: [##################################################] 100%
Rows:151 Cols:124
Chunk compression summary:
chunk_type
chunk_name
count
count_percentage
size
size_percentage C2S
2-Byte Fractions
1
0.8
386 B
0.5 C4S
4-Byte Fractions
123
99.19355
82.6 KB
99.54594
Frame distribution summary:
size
number_of_rows
number_of_chunks_per_column
number_of_chunks 192.168.1.106:54321
83.0 KB
151.0
1.0
124.0 mean
83.0 KB
151.0
1.0
124.0 min
83.0 KB
151.0
1.0
124.0 max
83.0 KB
151.0
1.0
124.0 stddev
0 B
0.0
0.0
0.0 total
83.0 KB
151.0
1.0
124.0
Time R.ASIS.X R.ASIS.Y R.ASIS.Z L.ASIS.X L.ASIS.Y L.ASIS.Z V.Sacral.X V.Sacral.Y V.Sacral.Z R.Thigh.Upper.X R.Thigh.Upper.Y R.Thigh.Upper.Z R.Thigh.Front.X R.Thigh.Front.Y R.Thigh.Front.Z R.Thigh.Rear.X R.Thigh.Rear.Y R.Thigh.Rear.Z L.Thigh.Upper.X L.Thigh.Upper.Y L.Thigh.Upper.Z L.Thigh.Front.X L.Thigh.Front.Y L.Thigh.Front.Z L.Thigh.Rear.X L.Thigh.Rear.Y L.Thigh.Rear.Z R.Shank.Upper.X R.Shank.Upper.Y R.Shank.Upper.Z R.Shank.Front.X R.Shank.Front.Y R.Shank.Front.Z R.Shank.Rear.X R.Shank.Rear.Y R.Shank.Rear.Z L.Shank.Upper.X L.Shank.Upper.Y L.Shank.Upper.Z L.Shank.Front.X L.Shank.Front.Y L.Shank.Front.Z L.Shank.Rear.X L.Shank.Rear.Y L.Shank.Rear.Z R.Heel.X R.Heel.Y R.Heel.Z R.Midfoot.Sup.X R.Midfoot.Sup.Y R.Midfoot.Sup.Z R.Midfoot.Lat.X R.Midfoot.Lat.Y R.Midfoot.Lat.Z R.Toe.Tip.X R.Toe.Tip.Y R.Toe.Tip.Z L.Heel.X L.Heel.Y L.Heel.Z L.Midfoot.Sup.X L.Midfoot.Sup.Y L.Midfoot.Sup.Z L.Midfoot.Lat.X L.Midfoot.Lat.Y L.Midfoot.Lat.Z L.Toe.Tip.X L.Toe.Tip.Y L.Toe.Tip.Z Sternum.X Sternum.Y Sternum.Z R.Acromium.X R.Acromium.Y R.Acromium.Z L.Acromium.X L.Acromium.Y L.Acromium.Z R.Bicep.X R.Bicep.Y R.Bicep.Z L.Bicep.X L.Bicep.Y L.Bicep.Z R.Elbow.X R.Elbow.Y R.Elbow.Z L.Elbow.X L.Elbow.Y L.Elbow.Z R.Wrist.Med.X R.Wrist.Med.Y R.Wrist.Med.Z R.Wrist.Lat.X R.Wrist.Lat.Y R.Wrist.Lat.Z L.Wrist.Med.X L.Wrist.Med.Y L.Wrist.Med.Z L.Wrist.Lat.X L.Wrist.Lat.Y L.Wrist.Lat.Z R.Toe.Lat.X R.Toe.Lat.Y R.Toe.Lat.Z R.Toe.Med.X R.Toe.Med.Y R.Toe.Med.Z L.Toe.Lat.X L.Toe.Lat.Y L.Toe.Lat.Z L.Toe.Med.X L.Toe.Med.Y L.Toe.Med.Z R.Temple.X R.Temple.Y R.Temple.Z L.Temple.X L.Temple.Y L.Temple.Z Top.Head.X Top.Head.Y Top.Head.Z type real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real mins 0.0 588.90717 1042.57324 107.79163 600.01556 1028.72498 -152.53879 399.40009 1034.90125 -21.44083 481.83603 732.70135 169.71159 535.63422 657.21033 74.20708 443.03299 613.54547 168.15961 468.19415 737.72083 -194.25998 550.69415 684.75494 -133.588 435.01773 627.49988 -170.86086 319.34705 444.43289 157.69023 376.44724 403.25574 102.54192 293.89526 368.28577 165.6133 341.2023 438.80435 -172.96315 365.72482 375.95242 -120.97533 304.46347 393.67728 -173.38676 68.60076 56.43383 59.948 190.98845 76.90237 57.86759 157.32503 62.79 159.97461 242.90858 33.52863 102.0894 76.37951 58.7473 -74.0361 211.85968 69.02702 -69.30095 185.39088 48.22646 -140.09074 254.42706 36.65646 -88.18266 627.38177 1342.85413 -35.20795 511.80032 1427.44507 164.48206 551.72424 1453.58936 -249.89265 485.94559 1227.90454 216.05853 531.12134 1217.64429 -266.60974 424.32767 1129.09949 242.29697 460.03223 1123.80298 -304.79358 535.87439 889.81964 262.1105 486.99316 876.53882 304.71069 554.35272 895.92426 -240.59163 502.82971 886.58942 -300.87775 179.7708 33.33099 181.24631 218.04131 36.96362 71.79319 199.80693 36.02512 -153.13719 228.04898 42.9706 -54.88903 675.97009 1562.28418 44.15432 683.50897 1567.27209 -94.07465 614.13971 1740.38916 -19.48838 mean 1.25 613.813053113 1066.03966086 147.31687457 621.755521457 1053.96356967 -113.089856821 419.620581921 1059.09006815 21.623491457 604.893643709 752.113870596 198.394967219 673.92189702 697.923971391 108.985077152 611.822258874 633.86881755 191.199856954 585.490775166 756.997120795 -165.268507152 678.686755497 728.699455298 -105.36090649 595.940002185 651.790140662 -150.845648344 546.594923974 475.604231126 178.16108404 612.071029735 427.534634437 128.650221921 542.267098675 394.823727682 183.756735099 576.596701656 453.573593974 -145.618441656 613.395788808 399.520259007 -93.8556917881 549.878182384 417.993665894 -150.945941523 416.548852914 129.322338543 90.8570246358 548.338234106 111.610775563 69.8090160265 529.694246291 98.3406530464 174.189332185 666.887220464 65.945897351 120.554062252 434.366901192 129.883908411 -51.1272676159 586.82315649 102.770866821 -29.9103321192 567.242079536 96.3386950993 -123.750955033 681.115977881 67.4584038411 -57.791522649 644.354285166 1368.8750157 7.55812370861 541.691537748 1458.71663887 215.413897881 579.531399603 1480.71707828 -200.599469404 546.953904172 1259.33734742 262.773222517 596.142476887 1244.48540172 -229.894727285 504.195181391 1157.84870225 292.136987417 548.273977351 1148.84251642 -267.919419669 659.505460066 943.758934768 282.79209596 620.86491457 926.046368675 331.252252252 672.867474437 938.097762583 -214.624156623 631.51934298 921.968321854 -274.012433179 601.509835033 61.8959264238 194.682855828 619.82417 68.488927947 86.619324106 618.338146887 65.9296156291 -132.648733775 638.645186556 72.3171915894 -31.812834702 705.727743576 1598.03973987 94.054633245 718.731032185 1603.03232914 -44.3193054305 698.879092384 1772.96821272 33.5554295364 maxs 2.5 641.12048 1091.43665 180.07411 661.46918 1078.02356 -80.37424 451.5914 1077.82214 55.36993 692.89514 788.11365 217.07512 766.44531 750.72375 136.25021 728.67242 672.42242 209.89946 674.53168 783.71576 -138.11635 773.97705 780.81445 -66.30186 713.16107 681.38623 -123.1844 719.69702 531.05676 200.56787 799.47015 457.5513 154.56749 751.88885 458.64368 202.59061 764.30676 494.35605 -116.46951 821.66901 425.57733 -63.51654 750.77588 473.02411 -124.50978 812.50183 320.70309 108.161 935.61414 198.72064 86.30818 934.44775 211.37376 188.70589 1073.86951 179.28133 153.59363 821.7641 321.80249 -34.92287 971.31763 178.00603 -6.83138 955.73096 184.36398 -104.3698 1082.51477 168.6488 -32.92321 673.89301 1393.88806 43.75163 573.68665 1486.25891 262.06827 609.36566 1507.81018 -155.85466 593.64148 1288.58093 305.86801 643.91699 1271.75806 -196.56128 567.0025 1193.14404 339.82635 608.93268 1186.43945 -230.94901 772.61859 1003.08368 312.96448 751.62823 969.89471 362.03549 793.86859 998.83923 -188.33229 768.91589 958.34167 -249.44443 1026.04944 136.89597 218.5173 1029.85803 153.3546 113.4589 1024.06946 133.35187 -111.9407 1039.38684 146.49858 -9.44173 740.63611 1640.01184 139.15808 754.62506 1647.88391 0.84904 752.89178 1809.14917 85.29955 sigma 0.72889825536 14.8399507642 14.3099952602 24.5838335602 15.3677970781 14.0282453512 24.3642762901 14.1124334017 12.7241422431 23.931459574 67.0255944127 14.4107151097 15.398480375 76.6538306984 25.8965081059 17.9751517137 95.4829458294 14.7834053354 12.6782408184 67.4179857687 11.6102683293 17.7639347083 73.040033179 26.2159867753 21.0864733194 94.2449453289 12.0232053396 13.8046061608 134.930612075 25.3498613621 10.7941403585 144.498909651 16.4732077493 12.0116914558 154.777481865 28.8364017246 8.39934844479 142.955246928 17.0828143121 14.8797324463 154.967889521 15.5600291412 14.9111135721 151.59465566 25.4350233434 13.2750249416 237.439442068 86.8034378025 9.2980736571 244.640717957 37.9104309568 7.58286243387 251.0617538 44.4134860871 6.39345776071 267.456893801 36.2326423983 13.6139276486 241.499431107 83.2859510473 9.6227673508 252.604885991 30.5819037441 12.5094752144 255.37425204 36.2988928164 9.2533009528 271.414052473 34.5463781912 13.739176762 12.0575605705 14.7489202628 26.9944295326 15.758774149 16.4250913412 32.9166484667 16.7955939253 15.4351581381 31.8075911475 32.6890480809 16.8573660375 29.3019110993 36.888188302 15.2498944443 23.3207475249 45.8558828835 18.3560382066 31.2674620144 50.6461886974 17.7763401004 23.1330378551 78.968700452 29.9621390536 13.8396899391 88.3169035165 24.8449448608 15.1498440635 79.9007206582 27.5133023226 13.2411262719 87.4650070732 19.7761164082 13.5545574936 267.810037453 31.2500342955 8.97018090732 262.604274456 31.3561696475 10.501730118 269.238419685 30.6993655665 10.9843433787 265.851645925 28.943564086 11.7760485335 19.0206668849 19.8249619372 31.9419164347 20.3329819999 20.8522401211 31.714968886 43.736467518 17.6838642112 34.452035784 zeros 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 missing 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.0 617.24762 1055.27502 170.78198 639.60638 1044.25842 -88.90979 430.86984 1051.26465 29.96675 517.3327 741.09601 212.08337 570.20148 666.70557 123.68554 480.06427 626.51483 199.55385 659.57892 745.05798 -145.97218 750.4809 735.8501 -73.48505 697.42963 642.68182 -137.3696 360.9039 474.04004 186.84929 420.86743 412.36603 134.71933 343.73737 388.03668 189.83162 750.32623 446.17697 -128.52777 819.76385 415.13217 -81.7 750.04584 397.94098 -138.884 156.44276 113.07307 104.00257 297.18088 88.12213 67.0685 288.24664 73.76623 176.63014 429.09286 43.0861 110.59769 815.76416 63.39788 -51.75869 967.98993 122.58054 -32.7704 943.78925 105.3372 -122.34442 1078.70935 143.54796 -60.93587 660.82678 1353.77527 20.19839 566.59839 1449.57959 229.99652 596.42383 1468.96814 -186.70021 593.64148 1249.10791 279.7764 580.73468 1233.74133 -222.92732 567.0025 1143.10925 315.56631 518.10278 1146.32483 -260.95828 771.56329 973.77911 273.7876 746.20697 944.37811 327.45282 619.82306 916.1698 -218.32727 574.16254 905.87732 -276.12146 366.12296 35.90821 193.14078 375.86584 39.8688 81.17185 1022.03961 113.13824 -136.45811 1034.97046 125.07877 -34.93821 736.52234 1571.58154 106.42087 748.242 1574.96411 -31.66723 749.33246 1747.60767 46.74146 1 0.017 617.99811 1053.21753 168.51317 641.23621 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409.98972 136.62299 328.7959 397.80103 192.13521 764.30676 441.88095 -129.77544 819.4068 403.62671 -75.05777 749.66199 395.97159 -137.4687 104.66998 154.01006 107.811 239.74205 104.37802 72.63148 226.07957 85.6586 179.6458 353.20926 42.46198 109.34061 754.4303 71.63676 -49.6439 920.41016 91.70379 -20.19499 907.75677 83.828 -119.12199 1034.05762 88.69792 -48.79842 666.13251 1351.51563 4.62811 568.55597 1448.63647 211.90868 600.12726 1460.2915 -206.09744 591.9776 1249.31384 263.23383 590.49182 1223.49988 -236.03795 560.85986 1144.38464 300.73502 528.6322 1134.04504 -271.92065 750.10632 955.17444 269.17526 721.46777 930.05811 323.39139 633.41034 904.04944 -227.97125 586.00677 894.02283 -285.90546 292.77032 33.78799 194.14709 306.8887 38.66298 80.80763 971.72296 68.74927 -126.63988 985.93829 77.90832 -24.6681 737.62549 1572.04834 87.80447 750.3457 1572.99023 -51.10457 750.73419 1748.23279 25.32117 5 0.083 628.15863 1051.42017 158.44899 652.04126 1043.04651 -101.85737 441.57205 1048.66125 15.77033 526.8028 738.1261 205.65331 584.08734 660.59796 120.84705 490.79364 622.24158 197.31982 671.81549 744.88806 -152.9505 766.9668 739.85303 -85.03291 709.17731 643.27905 -136.13054 366.04211 481.02042 188.67352 413.34131 408.71753 136.33844 330.84656 400.64767 193.439 759.47589 442.17343 -130.73776 816.06543 402.27618 -75.44473 747.88531 396.32391 -140.11632 97.06428 169.38722 108.161 228.38951 110.30775 73.80885 212.84218 91.66736 179.95212 335.07321 41.7686 108.90065 738.8324 72.80952 -51.15369 905.33636 86.73385 -21.0414 893.1098 79.00209 -119.56252 1019.03333 78.89088 -49.1244 667.78387 1352.00989 -0.13134 570.76257 1450.02661 206.86226 600.59558 1460.49719 -211.4072 590.94012 1250.75122 259.04285 593.76056 1223.08325 -239.71443 558.84601 1145.63745 295.84277 533.79944 1131.96716 -274.53073 742.86133 950.51917 268.83356 712.263 929.03009 323.78958 635.94586 902.42853 -228.98778 588.33478 891.75726 -287.01593 276.40588 34.30354 194.01968 290.22995 39.31117 80.83173 955.87006 60.79351 -127.01521 970.42456 70.22808 -25.11532 738.612 1573.10339 82.11092 751.77826 1575.62683 -55.8147 751.36084 1749.58252 19.81245 6 0.1 630.80774 1051.99683 155.28273 654.94336 1045.55249 -104.84258 444.30652 1049.38757 13.38743 535.10321 738.08984 203.62639 592.51501 659.99243 121.33315 501.20685 620.82605 196.24577 673.89844 747.01788 -156.03423 772.35175 742.25787 -89.25005 713.16107 646.65497 -139.52066 375.77795 482.22336 189.33501 419.00134 407.60028 138.39725 336.90884 403.77454 193.3508 756.08441 442.23431 -133.99379 810.97333 400.24454 -77.5945 744.59918 396.7373 -143.63443 93.53649 187.30023 107.96611 219.47504 117.48801 74.71632 201.41972 99.71858 179.93013 317.67944 40.65249 108.82865 722.45453 73.57777 -52.95034 889.22516 83.06837 -22.64718 877.13904 75.46108 -120.58668 1002.74866 71.09254 -50.28877 669.5058 1354.10547 -5.01989 572.24451 1451.80005 201.81273 602.06042 1461.08044 -216.3876 590.79205 1252.99475 254.13115 595.74579 1222.85925 -242.9707 557.37036 1148.6759 291.07318 537.13202 1131.83167 -277.63904 734.74261 946.59851 269.14612 702.83514 926.27173 323.48404 640.10693 901.14435 -232.70107 588.76013 890.19757 -287.25162 260.43735 35.30923 193.34642 274.95285 41.20525 80.87572 939.07227 54.59298 -128.03491 953.66071 64.3698 -26.14897 739.5401 1575.36292 78.13955 752.88104 1577.24341 -60.55132 751.64526 1751.11572 15.08665 7 0.117 634.3573 1053.59888 151.48531 656.46411 1048.43481 -108.35542 446.83075 1050.62231 11.01402 544.72296 738.2121 201.64484 604.5097 661.62036 121.05774 513.22986 619.92859 196.53305 674.53168 749.12817 -159.46423 773.97705 743.04993 -93.60475 711.73584 648.34937 -143.10452 387.18112 484.59857 188.88277 428.80124 406.8931 139.40385 345.48553 408.36984 193.09653 753.82123 442.04764 -138.77199 802.93207 398.62927 -80.64492 739.24146 397.03458 -147.34126 94.98832 207.4904 107.03399 213.69908 125.96996 75.26598 192.58446 110.03806 179.48466 301.42526 38.93748 109.33791 705.33765 74.03343 -54.66131 872.37952 80.52281 -24.27218 860.03241 72.9679 -121.8632 985.63171 65.12334 -51.84297 670.83313 1356.67114 -9.29258 572.75836 1454.59961 196.92804 602.85883 1462.02185 -221.10623 590.00787 1255.53772 250.09286 601.24188 1223.48523 -246.66733 554.96899 1151.4834 286.39725 542.94934 1130.97559 -280.45694 725.07544 942.78583 269.30731 692.7287 924.33771 323.41968 643.68225 900.94678 -234.15486 590.58203 888.88293 -288.93704 243.86186 38.16441 193.58971 261.57364 44.61509 81.12685 921.75916 50.09772 -129.25052 936.06396 60.11494 -27.36638 739.60699 1577.74219 73.24436 753.17957 1579.51819 -65.44061 752.39709 1753.56885 10.2251 8 0.133 636.58606 1055.25659 148.46054 658.6814 1051.14209 -111.49577 448.95215 1052.28821 8.53319 554.57361 738.0722 201.58772 617.51031 662.07452 121.77839 526.78558 618.5899 197.48357 673.34198 750.94318 -162.9929 771.89703 742.33643 -96.90478 709.09875 649.05853 -147.66277 402.69037 485.76764 188.44481 442.54022 406.66714 140.14063 358.56879 411.94595 193.13004 746.61304 442.07925 -142.18994 794.79785 397.89108 -83.96312 731.43372 397.14545 -150.63176 101.89561 229.2522 105.10458 211.66443 135.6129 75.40372 187.05954 122.54012 178.54959 287.03329 36.68252 110.60543 687.62341 74.29313 -55.97468 854.96057 78.81071 -25.52192 842.02069 71.28556 -123.03375 967.95386 60.73584 -53.41936 672.2514 1359.22534 -13.84572 573.2486 1458.17261 192.6459 604.14795 1463.29358 -225.73322 588.66913 1259.12073 245.03398 605.93121 1224.2688 -249.36713 551.07391 1155.10571 281.79312 548.08496 1131.09924 -281.66373 715.24152 940.14618 269.76904 680.81293 923.0174 323.19675 649.44653 900.4809 -236.19994 597.42749 890.09033 -290.82834 230.53894 44.00678 193.9955 250.70145 49.75068 81.76305 904.15027 47.12564 -130.31641 918.01147 57.20811 -28.49127 740.34119 1580.11731 68.04765 754.19202 1582.02112 -69.93488 752.81946 1756.18616 5.61364 9 0.15 637.73926 1057.85437 144.71632 660.52991 1054.05298 -115.06461 450.49979 1054.27356 5.88769 563.95862 737.61774 199.39542 632.10297 663.87402 122.62301 543.71594 617.5484 197.32835 670.47327 752.45715 -166.39114 766.67487 741.15271 -100.99368 701.96729 649.32263 -149.93629 422.95267 488.47433 188.63586 458.14078 406.71533 140.77057 373.53732 415.87027 192.30505 736.60419 441.1543 -144.48372 783.63556 396.66898 -85.91944 720.98749 397.0899 -153.14619 113.94633 251.35576 101.89884 213.77849 146.09308 75.11986 185.43004 136.78993 177.14098 275.70932 34.46534 112.73006 669.49695 74.45683 -56.78135 837.11652 77.71363 -26.307 823.43048 70.25358 -123.87254 949.86023 57.66205 -54.74788 673.31812 1362.27649 -16.97451 573.64575 1461.2915 188.83058 603.48907 1465.21875 -229.00102 587.18243 1262.35596 241.46214 610.59033 1225.60803 -252.14532 547.87537 1159.11731 276.40805 554.20758 1132.03687 -284.90427 704.80261 938.80182 270.11826 669.29614 922.38171 322.03412 654.29071 900.93335 -237.27509 605.25018 890.51007 -294.28757 217.73599 52.18552 193.07756 243.3329 56.69575 82.82691 886.22406 45.35707 -131.08205 899.70392 55.34391 -29.3687 740.63611 1582.93115 64.22716 754.62506 1584.87378 -74.39068 752.89178 1758.74548 1.274
In [4]:
# Plot first row of data on x- vs. y-coordinate features
gait_row = gait[1,:].drop("Time")
gait_row_np = np.array(h2o.as_list(gait_row))
x_coords = range(0, gait_row_np.shape[1], 3)
y_coords = range(1, gait_row_np.shape[1], 3)
x_pts = gait_row_np[0,x_coords]
y_pts = gait_row_np[0,y_coords]
plt.plot(x_pts, y_pts, 'bo')
# Add feature labels to each point
feat_names = [nam[:-2] for nam in gait_row.col_names[1::3]]
for i in xrange(len(feat_names)):
plt.annotate(feat_names[i], xy = [x_pts[i], y_pts[i]])
plt.title("Location of Body Parts at Time 0")
plt.xlabel("X-Coordinate Weight")
plt.ylabel("Y-Coordinate Weight")
plt.show()
In [5]:
# Basic GLRM using quadratic loss and no regularization (PCA)
model = h2o.glrm(x=gait[1:], k=10, loss="Quadratic", regularization_x="None", regularization_y="None", max_iterations=1000)
model.show()
glrm Model Build Progress: [##################################################] 100%
Model Details
=============
H2OEstimator : Beta - Generalized Low Rank Model
Model Key: GLRM_model_python_1446185816814_8
Model Summary:
/Library/Python/2.7/site-packages/IPython/kernel/__main__.py:2: DeprecationWarning: `h2o.glrm` is deprecated. Use the estimators sub module to build an H2OGeneralizedLowRankEstimator.
from IPython.kernel.zmq import kernelapp as app
number_of_iterations
final_step_size
final_objective_value 15.0
0.0
191201.6
ModelMetricsGLRM: glrm
** Reported on train data. **
MSE: NaN
Sum of Squared Error (Numeric): 191201.617112
Misclassification Error (Categorical): 0.0
Scoring History:
timestamp
duration
iteration
step_size
objective 2015-10-29 23:29:35
0.250 sec
0.0
1.05
199867.4 2015-10-29 23:29:35
0.290 sec
1.0
0.7
199867.4 2015-10-29 23:29:35
0.327 sec
2.0
0.5
199867.4 2015-10-29 23:29:35
0.338 sec
3.0
0.3
199867.4 2015-10-29 23:29:35
0.348 sec
4.0
0.2
199867.4 2015-10-29 23:29:35
0.358 sec
5.0
0.1
199867.4 2015-10-29 23:29:35
0.368 sec
6.0
0.0
199867.4 2015-10-29 23:29:35
0.379 sec
7.0
0.0
199867.4 2015-10-29 23:29:35
0.389 sec
8.0
0.0
191201.6 2015-10-29 23:29:35
0.400 sec
9.0
0.0
191201.6 2015-10-29 23:29:35
0.411 sec
10.0
0.0
191201.6 2015-10-29 23:29:35
0.422 sec
11.0
0.0
191201.6 2015-10-29 23:29:35
0.433 sec
12.0
0.0
191201.6 2015-10-29 23:29:35
0.443 sec
13.0
0.0
191201.6 2015-10-29 23:29:35
0.453 sec
14.0
0.0
191201.6
In [6]:
# Plot objective function value each iteration
model_score = model.score_history()
plt.xlabel("Iteration")
plt.ylabel("Objective")
plt.title("Objective Function Value per Iteration")
plt.plot(model_score["iteration"], model_score["objective"])
plt.show()
In [7]:
# Archetype to feature mapping (Y)
gait_y = model._model_json["output"]["archetypes"]
print gait_y
gait_y_np = np.array(model.archetypes())
x_coords = range(0, gait_y_np.shape[1], 3)
y_coords = range(1, gait_y_np.shape[1], 3)
# Plot archetypes on x- vs. y-coordinate features
for k in xrange(gait_y_np.shape[0]):
x_pts = gait_y_np[k, x_coords]
y_pts = gait_y_np[k, y_coords]
plt.plot(x_pts, y_pts, 'bo')
# Add feature labels to each point
feat_names = [nam[:-1] for nam in gait_y.col_header[1::3]]
for i in xrange(len(feat_names)):
plt.annotate(feat_names[i], xy = [x_pts[i], y_pts[i]])
plt.title("Feature Weights of Archetype " + str(k+1))
plt.xlabel("X-Coordinate Weight")
plt.ylabel("Y-Coordinate Weight")
plt.show()
Archetypes:
rasisx
rasisy
rasisz
lasisx
lasisy
lasisz
vsacralx
vsacraly
vsacralz
rthighupperx
rthighuppery
rthighupperz
rthighfrontx
rthighfronty
rthighfrontz
rthighrearx
rthighreary
rthighrearz
lthighupperx
lthighuppery
lthighupperz
lthighfrontx
lthighfronty
lthighfrontz
lthighrearx
lthighreary
lthighrearz
rshankupperx
rshankuppery
rshankupperz
rshankfrontx
rshankfronty
rshankfrontz
rshankrearx
rshankreary
rshankrearz
lshankupperx
lshankuppery
lshankupperz
lshankfrontx
lshankfronty
lshankfrontz
lshankrearx
lshankreary
lshankrearz
rheelx
rheely
rheelz
rmidfootsupx
rmidfootsupy
rmidfootsupz
rmidfootlatx
rmidfootlaty
rmidfootlatz
rtoetipx
rtoetipy
rtoetipz
lheelx
lheely
lheelz
lmidfootsupx
lmidfootsupy
lmidfootsupz
lmidfootlatx
lmidfootlaty
lmidfootlatz
ltoetipx
ltoetipy
ltoetipz
sternumx
sternumy
sternumz
racromiumx
racromiumy
racromiumz
lacromiumx
lacromiumy
lacromiumz
rbicepx
rbicepy
rbicepz
lbicepx
lbicepy
lbicepz
relbowx
relbowy
relbowz
lelbowx
lelbowy
lelbowz
rwristmedx
rwristmedy
rwristmedz
rwristlatx
rwristlaty
rwristlatz
lwristmedx
lwristmedy
lwristmedz
lwristlatx
lwristlaty
lwristlatz
rtoelatx
rtoelaty
rtoelatz
rtoemedx
rtoemedy
rtoemedz
ltoelatx
ltoelaty
ltoelatz
ltoemedx
ltoemedy
ltoemedz
rtemplex
rtempley
rtemplez
ltemplex
ltempley
ltemplez
topheadx
topheady
topheadz Arch1
608.8
1075.7
177.7
612.7
1071.1
-83.5
411.9
1073.4
52.2
559.1
752.6
215.7
618.1
690.1
121.6
545.5
631.1
202.3
644.8
775.7
-148.0
745.9
770.7
-91.3
685.9
673.7
-141.2
464.2
461.2
184.7
536.9
417.8
131.7
466.8
374.1
187.9
689.1
483.3
-139.0
724.8
423.2
-92.1
657.3
449.3
-143.6
352.4
74.5
92.9
496.7
78.4
65.4
484.6
63.5
171.8
638.4
46.9
112.8
521.3
162.7
-41.7
675.9
118.9
-35.8
648.7
117.0
-129.7
766.6
68.5
-75.7
639.1
1384.9
39.8
548.1
1469.5
256.4
557.5
1500.9
-162.2
577.3
1267.2
300.6
546.1
1264.9
-202.1
550.1
1160.3
332.9
481.5
1177.7
-238.1
745.2
979.1
296.5
716.1
951.6
348.2
579.7
943.7
-205.8
530.4
936.5
-262.4
571.0
37.9
189.9
582.0
45.1
80.4
696.5
77.0
-144.5
725.8
79.9
-45.4
697.9
1618.0
131.7
706.2
1625.4
-7.2
677.5
1791.5
73.8 Arch2
634.5
1078.8
124.7
652.0
1066.6
-135.2
445.0
1069.1
-9.0
636.4
757.3
189.7
719.1
702.3
113.1
649.4
636.3
191.2
625.1
761.7
-182.5
716.0
734.5
-116.1
634.3
653.6
-162.5
558.0
515.7
178.8
590.8
430.9
136.4
504.3
447.2
182.5
635.3
441.0
-154.0
680.8
391.9
-97.7
614.4
398.0
-160.3
245.5
302.7
72.7
337.5
187.2
67.3
298.8
193.4
165.9
384.6
60.4
127.0
537.8
76.9
-59.3
707.4
75.6
-29.6
691.4
68.6
-126.7
818.7
50.3
-58.5
666.6
1380.7
-29.8
559.5
1480.0
172.0
607.5
1482.3
-244.9
559.3
1281.3
226.4
635.2
1242.1
-260.7
510.8
1182.1
258.1
590.6
1143.0
-294.5
638.4
944.4
270.6
594.0
934.7
318.3
703.9
919.5
-240.7
660.0
906.5
-300.8
322.2
107.8
190.9
357.8
98.5
88.6
753.9
42.0
-134.4
769.0
51.5
-32.9
731.2
1602.9
47.5
746.3
1603.1
-90.9
741.7
1777.5
-17.5 Arch3
625.6
1050.1
137.1
618.0
1034.2
-123.5
425.6
1039.8
28.5
681.4
746.4
187.1
754.9
710.0
89.4
717.6
629.6
175.7
502.0
746.4
-174.4
590.3
688.7
-125.3
478.6
640.2
-161.0
708.5
453.5
167.1
787.5
430.3
108.8
736.4
371.1
173.7
382.6
450.1
-161.3
395.0
379.9
-110.6
340.8
427.0
-165.7
699.3
66.0
93.2
841.1
86.3
64.0
832.2
70.3
170.5
984.9
74.4
109.2
93.2
194.4
-66.1
228.8
105.1
-37.7
205.1
92.2
-131.1
296.1
40.2
-55.0
646.9
1351.9
19.8
535.3
1431.8
227.8
588.5
1470.7
-185.6
522.4
1231.7
266.6
623.6
1235.9
-220.0
468.4
1132.1
286.9
587.0
1136.2
-264.5
600.3
897.0
289.8
553.3
882.5
333.2
733.0
936.9
-205.9
697.0
916.2
-268.1
920.2
53.5
187.3
930.6
64.2
77.8
234.7
45.6
-133.1
262.5
51.1
-32.5
702.4
1584.6
111.3
716.0
1592.0
-26.7
686.6
1759.7
52.8 Arch4
608.7
1086.4
116.7
619.4
1064.6
-143.2
415.2
1072.4
-8.3
665.6
781.3
185.8
751.6
742.2
101.3
703.9
665.0
185.9
544.1
763.9
-184.3
632.1
722.3
-118.2
534.9
654.8
-161.3
648.4
515.9
173.0
711.6
453.4
131.9
629.4
433.6
180.9
501.0
441.1
-149.3
544.6
389.2
-94.8
477.3
399.6
-154.6
460.6
186.1
79.3
593.8
138.9
75.2
560.7
127.1
175.0
699.4
59.9
137.9
378.5
78.9
-50.8
546.5
74.8
-25.5
533.9
64.0
-118.2
658.8
48.1
-49.1
639.8
1383.6
-26.0
526.4
1479.4
173.7
587.9
1490.8
-240.1
508.6
1283.1
226.1
632.3
1254.9
-257.4
451.2
1187.7
253.3
600.3
1150.8
-295.2
568.3
945.1
272.3
520.1
936.5
316.5
756.6
965.9
-219.2
722.5
938.9
-280.2
624.0
70.2
203.1
657.1
77.0
98.8
594.4
41.0
-125.8
608.5
49.7
-24.2
703.2
1609.0
54.9
720.2
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561.5
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450.5
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13.9
In [8]:
# Projection into archetype space (X)
x_key = model._model_json["output"]["representation_name"]
gait_x = h2o.get_frame(x_key)
gait_x.show()
time_np = np.array(h2o.as_list(gait["Time"]))
gait_x_np = np.array(h2o.as_list(gait_x))
# Plot archetypes over time
lines = []
for i in xrange(gait_x_np.shape[1]):
lines += plt.plot(time_np, gait_x_np[:,i], '-')
plt.title("Archetypes over Time")
plt.xlabel("Time")
plt.ylabel("Archetypal Projection")
plt.legend(lines, gait_x.col_names)
plt.show()
Arch1 Arch2 Arch3 Arch4 Arch5 Arch6 Arch7 Arch8 Arch9 Arch10 -0.118016 0.173982 -0.0727759 0.0136446 0.833921 -0.589754 0.641842 0.0375436 0.0768216 0.00452708 -0.0887461 0.0532799 -0.0695895 0.0218382 0.933027 -0.425148 0.467147 0.031643 0.0616354 0.0159697 -0.0591975 -0.0719449 -0.0453946 0.0334023 1.03165 -0.252666 0.28866 0.0249121 0.0322057 0.0191561 -0.0264588 -0.156831 -0.0206126 0.0385205 1.10497 -0.106183 0.128145 0.0138942 0.00526113 0.0196686 0.00428291 -0.209212 -0.0107357 0.0483267 1.1651 0.0124812 -0.0237941 -0.0052785 -0.00667249 0.0253444 0.0237295 -0.221958 0.0130989 0.0438355 1.17146 0.124488 -0.133782 -0.00368511 -0.0228774 0.00555454 0.0573816 -0.17232 0.0234272 0.03015 1.14788 0.191832 -0.229626 -0.00481057 -0.0320997 -0.0125472 0.0674349 -0.0809166 0.0303819 0.010251 1.08198 0.239398 -0.283441 -0.00458047 -0.0311103 -0.0304398 0.0601635 0.0469727 0.0357643 -0.0265873 0.985682 0.271071 -0.306071 -0.0085012 -0.0269355 -0.0325116 0.0431959 0.21589 0.0514907 -0.0756018 0.840083 0.285192 -0.284789 -0.00677648 -0.0287666 -0.0405667
In [9]:
# Reconstruct data from X and Y
pred = model.predict(gait)
pred.head()
reconstr_R.ASIS.X reconstr_R.ASIS.Y reconstr_R.ASIS.Z reconstr_L.ASIS.X reconstr_L.ASIS.Y reconstr_L.ASIS.Z reconstr_V.Sacral.X reconstr_V.Sacral.Y reconstr_V.Sacral.Z reconstr_R.Thigh.Upper.X reconstr_R.Thigh.Upper.Y reconstr_R.Thigh.Upper.Z reconstr_R.Thigh.Front.X reconstr_R.Thigh.Front.Y reconstr_R.Thigh.Front.Z reconstr_R.Thigh.Rear.X reconstr_R.Thigh.Rear.Y reconstr_R.Thigh.Rear.Z reconstr_L.Thigh.Upper.X reconstr_L.Thigh.Upper.Y reconstr_L.Thigh.Upper.Z reconstr_L.Thigh.Front.X reconstr_L.Thigh.Front.Y reconstr_L.Thigh.Front.Z reconstr_L.Thigh.Rear.X reconstr_L.Thigh.Rear.Y reconstr_L.Thigh.Rear.Z reconstr_R.Shank.Upper.X reconstr_R.Shank.Upper.Y reconstr_R.Shank.Upper.Z reconstr_R.Shank.Front.X reconstr_R.Shank.Front.Y reconstr_R.Shank.Front.Z reconstr_R.Shank.Rear.X reconstr_R.Shank.Rear.Y reconstr_R.Shank.Rear.Z reconstr_L.Shank.Upper.X reconstr_L.Shank.Upper.Y reconstr_L.Shank.Upper.Z reconstr_L.Shank.Front.X reconstr_L.Shank.Front.Y reconstr_L.Shank.Front.Z reconstr_L.Shank.Rear.X reconstr_L.Shank.Rear.Y reconstr_L.Shank.Rear.Z reconstr_R.Heel.X reconstr_R.Heel.Y reconstr_R.Heel.Z reconstr_R.Midfoot.Sup.X reconstr_R.Midfoot.Sup.Y reconstr_R.Midfoot.Sup.Z reconstr_R.Midfoot.Lat.X reconstr_R.Midfoot.Lat.Y reconstr_R.Midfoot.Lat.Z reconstr_R.Toe.Tip.X reconstr_R.Toe.Tip.Y reconstr_R.Toe.Tip.Z reconstr_L.Heel.X reconstr_L.Heel.Y reconstr_L.Heel.Z reconstr_L.Midfoot.Sup.X reconstr_L.Midfoot.Sup.Y reconstr_L.Midfoot.Sup.Z reconstr_L.Midfoot.Lat.X reconstr_L.Midfoot.Lat.Y reconstr_L.Midfoot.Lat.Z reconstr_L.Toe.Tip.X reconstr_L.Toe.Tip.Y reconstr_L.Toe.Tip.Z reconstr_Sternum.X reconstr_Sternum.Y reconstr_Sternum.Z reconstr_R.Acromium.X reconstr_R.Acromium.Y reconstr_R.Acromium.Z reconstr_L.Acromium.X reconstr_L.Acromium.Y reconstr_L.Acromium.Z reconstr_R.Bicep.X reconstr_R.Bicep.Y reconstr_R.Bicep.Z reconstr_L.Bicep.X reconstr_L.Bicep.Y reconstr_L.Bicep.Z reconstr_R.Elbow.X reconstr_R.Elbow.Y reconstr_R.Elbow.Z reconstr_L.Elbow.X reconstr_L.Elbow.Y reconstr_L.Elbow.Z reconstr_R.Wrist.Med.X reconstr_R.Wrist.Med.Y reconstr_R.Wrist.Med.Z reconstr_R.Wrist.Lat.X reconstr_R.Wrist.Lat.Y reconstr_R.Wrist.Lat.Z reconstr_L.Wrist.Med.X reconstr_L.Wrist.Med.Y reconstr_L.Wrist.Med.Z reconstr_L.Wrist.Lat.X reconstr_L.Wrist.Lat.Y reconstr_L.Wrist.Lat.Z reconstr_R.Toe.Lat.X reconstr_R.Toe.Lat.Y reconstr_R.Toe.Lat.Z reconstr_R.Toe.Med.X reconstr_R.Toe.Med.Y reconstr_R.Toe.Med.Z reconstr_L.Toe.Lat.X reconstr_L.Toe.Lat.Y reconstr_L.Toe.Lat.Z reconstr_L.Toe.Med.X reconstr_L.Toe.Med.Y reconstr_L.Toe.Med.Z reconstr_R.Temple.X reconstr_R.Temple.Y reconstr_R.Temple.Z reconstr_L.Temple.X reconstr_L.Temple.Y reconstr_L.Temple.Z reconstr_Top.Head.X reconstr_Top.Head.Y reconstr_Top.Head.Z 620.248 1054.12 164.851 641.888 1043.09 -96.1185 432.445 1053.09 23.6123 513.954 741.504 205.023 564.204 664.962 115.642 474.201 626.45 192.483 657.081 743.802 -150.036 752.361 735.53 -80.8198 694.574 641.241 -138.472 352.101 472.604 180.015 412.556 412.699 127.397 334.8 386.53 184.151 752.952 443.916 -132.851 818.402 413.419 -83.0296 748.842 396.772 -141.273 149.677 105.682 99.5551 295.421 85.6184 64.2647 285.725 66.5934 173.037 429.59 44.2025 104.687 810.613 67.4197 -56.3858 965.97 118.625 -32.7623 950.189 108.49 -127.954 1076.39 133.95 -63.5178 664.168 1356.82 10.6937 570.843 1452.84 221.148 594.118 1467.9 -197.961 598.753 1252.22 270.485 579.482 1231.17 -230.124 572.108 1145.97 306.396 515.01 1142.38 -264.974 774.481 974.625 263.331 750.487 945.764 317.368 619.934 912.353 -223.73 570.223 901.559 -280.076 366.604 29.0949 188.964 375.79 36.6892 76.0584 1017.39 105.82 -138.786 1031.71 117.483 -37.2945 731.339 1586.24 93.6066 741.418 1588.53 -45.6478 725.714 1758.09 31.338 621.179 1052.57 164.157 643.628 1042.54 -96.5124 433.853 1051.38 22.4164 513.913 739.871 205.47 565.167 662.448 117.451 474.149 624.598 193.909 660.832 743.668 -150.065 756.793 736.578 -81.5187 699.117 641.605 -137.78 350.775 472.607 182.22 409.068 410.837 129.961 330.784 387.756 186.495 756.269 443.415 -132.01 819.963 411.025 -81.066 750.924 396.504 -140.701 138.52 116.379 102.495 280.754 89.2083 66.8437 269.95 69.7384 175.172 409.111 42.9638 105.854 798.919 67.563 -54.7499 956.42 112.246 -30.0173 941.496 102.318 -125.527 1067.91 123.277 -59.8446 664.476 1354.93 8.84953 570.491 1451.38 218.553 594.964 1465.43 -200.218 597.128 1251.13 268.4 581.358 1228.66 -231.862 569.458 1145.16 304.559 517.7 1139.6 -266.77 768.383 969.013 264.716 743.351 941.363 318.877 622.374 910.548 -224.338 572.952 899.54 -280.601 346.994 28.3763 190.568 357.362 36.3485 77.4669 1008.3 96.9882 -135.713 1022.23 108.263 -34.0857 732.639 1582.15 91.9447 743.456 1584.46 -47.0684 731.368 1755.01 29.8595 622.429 1051.2 163.285 645.651 1042.16 -97.1969 435.503 1049.81 21.1061 514.887 738.512 205.85 567.372 660.379 119.207 475.464 623.009 195.264 663.822 743.747 -150.267 760.344 737.452 -82.3671 702.427 642.153 -137.17 351.048 472.947 184.436 407.091 409.15 132.458 328.235 389.321 188.848 757.751 442.808 -131.236 819.734 408.411 -79.1355 751.146 396.042 -140.243 128.19 127.842 105.446 266.885 92.9087 69.4229 254.845 73.0612 177.326 389.22 41.3357 106.988 784.864 66.8217 -53.3194 944.977 105.145 -27.1901 930.983 95.0957 -123.119 1057.83 112.029 -55.901 665.056 1353.3 6.90058 570.184 1450.18 215.858 596.2 1463.26 -202.708 595.259 1250.27 266.228 583.853 1226.36 -233.804 566.383 1144.58 302.585 521.13 1136.92 -268.836 761.579 963.23 266.237 735.389 936.862 320.489 625.935 908.838 -225.046 576.809 897.514 -281.272 327.864 27.4411 192.189 339.546 35.7406 78.8564 997.41 87.1449 -132.492 1011.03 98.1538 -30.6711 734.265 1578.34 90.1843 745.866 1580.65 -48.6381 737.571 1752.32 28.2291 623.922 1050.33 162.204 647.701 1042.17 -98.0677 437.327 1048.65 19.7799 517.251 737.447 206.061 571.149 658.934 120.767 478.616 621.638 196.421 666.895 744.059 -150.775 763.907 738.412 -83.5155 705.711 642.809 -136.973 353.382 473.804 186.301 406.947 407.732 134.625 327.407 391.447 190.754 759.007 442.407 -130.94 819.194 406.01 -77.8112 751.064 395.869 -140.183 118.727 140.665 107.441 253.613 97.3434 71.4333 240.138 77.6737 178.832 369.522 39.6428 107.975 770.523 66.8728 -52.255 932.915 98.777 -24.9134 919.601 88.6991 -121.25 1046.74 101.373 -52.7684 665.785 1352.22 4.93922 570.082 1449.45 213.198 597.475 1461.58 -205.136 593.735 1249.81 264.027 586.492 1224.52 -235.615 563.714 1144.41 300.505 524.633 1134.74 -270.7 755.023 958.037 267.641 727.658 932.935 321.899 629.096 907.001 -225.977 580.156 895.582 -282.202 308.836 27.5354 193.317 321.949 35.7337 79.9543 985.535 78.0604 -129.917 998.988 88.784 -27.9668 735.761 1575.33 88.3018 748.029 1577.61 -50.3354 742.995 1750.22 26.4284 625.782 1050.27 160.666 649.97 1042.73 -99.3511 439.456 1048.12 18.1238 521.451 737.014 206.069 577.011 658.472 122.132 484.19 620.833 197.45 670.411 744.614 -151.755 767.973 739.585 -85.1465 709.434 643.54 -137.294 358.323 475.489 187.903 409.212 406.807 136.648 328.764 394.392 192.352 760.515 442.199 -131.185 818.642 403.773 -77.0454 751.101 396.057 -140.563 110.31 154.952 108.664 241.237 102.616 73.1012 226.095 83.5071 179.898 350.37 37.9112 109.037 755.636 68.435 -51.4024 919.689 93.2509 -23.0636 906.888 83.454 -119.752 1033.95 90.9968 -50.2954 666.776 1351.93 2.60019 570.217 1449.5 210.13 599.029 1460.62 -207.939 592.396 1250.1 261.402 589.815 1223.36 -237.618 561.14 1145.02 297.921 528.93 1133.16 -272.69 747.959 953.358 268.85 719.28 929.623 323.01 632.771 905.499 -227.195 584.019 894.123 -283.475 290.246 28.5153 194.176 304.96 36.3326 80.9559 972.15 69.9011 -127.864 985.435 80.2052 -25.8321 737.26 1573.29 85.9282 750.145 1575.52 -52.521 747.907 1748.94 24.1045 627.724 1050.94 158.894 652.067 1043.96 -101.057 441.465 1048.36 16.4045 527.089 737.03 205.915 584.661 658.867 123.324 491.845 620.374 198.301 672.227 745.588 -153.174 770.024 740.408 -87.0816 710.636 644.451 -138.098 365.89 477.875 189.134 413.942 406.415 138.354 332.515 398.167 193.501 758.942 442.025 -131.946 815.24 401.806 -76.9823 748.156 396.226 -141.373 104.118 171.035 108.684 230.685 109.052 74.2343 213.45 91.2356 180.397 332.357 36.6065 110.328 739.599 69.6535 -51.1008 905.159 88.4561 -21.8019 892.632 78.8585 -118.872 1019.67 82.2062 -48.5378 667.8 1352.54 0.223192 570.454 1450.46 207.21 600.611 1460.6 -210.817 591.101 1251.18 258.958 593.283 1223 -239.633 558.582 1146.4 295.488 533.283 1132.34 -274.67 740.899 949.639 270.234 710.886 927.254 324.241 636.229 903.962 -228.798 587.555 892.826 -285.255 272.559 31.21 194.791 289.209 38.0646 81.9425 957.274 62.788 -126.451 970.564 72.8073 -24.312 738.915 1572.28 83.4335 752.328 1574.37 -54.927 753.046 1748.65 21.5546 629.931 1052.27 156.594 654.111 1045.71 -103.148 443.7 1049.17 14.4415 534.76 737.371 205.335 594.602 660.065 124.071 502.238 620.118 198.769 674.553 747 -155.199 772.538 741.651 -89.6619 712.369 645.669 -139.651 376.689 480.859 189.741 421.645 406.434 139.593 339.138 402.671 193.925 757.549 442.335 -133.511 811.83 400.185 -77.9325 745.152 397.027 -142.844 100.346 188.955 107.296 222.012 116.812 74.6232 202.441 101.037 179.964 315.597 35.7524 111.532 722.693 72.1825 -51.2325 889.435 84.4847 -21.529 876.781 75.4144 -118.863 1003.71 73.6314 -48.2556 669 1353.76 -2.4579 571.069 1451.96 203.978 602.21 1461.09 -213.811 590.325 1252.8 256.11 596.937 1223.2 -241.616 556.585 1148.39 292.544 537.768 1132.12 -276.457 733.935 946.686 271.217 702.53 925.67 324.918 639.262 902.522 -230.735 590.552 891.869 -287.36 256.099 35.8253 194.724 274.828 41.1834 82.5927 940.662 56.5058 -126.176 954.205 66.1343 -24.0809 740.441 1572.02 80.458 754.225 1573.93 -57.7622 757.32 1748.75 18.5104 632.064 1054.22 153.731 655.984 1047.78 -105.88 445.775 1050.47 12.0222 544.07 738.186 204.42 606.49 662.192 124.481 515.027 620.314 198.975 675.169 748.352 -157.712 773.057 742.123 -92.5259 711.585 646.566 -141.668 390.445 484.682 189.925 432.134 407.131 140.536 348.475 408.142 193.888 753.319 442.257 -135.503 805.756 398.599 -79.3664 739.531 397.422 -144.65 99.1191 208.634 104.813 215.531 125.943 74.5494 193.289 112.793 179.012 300.437 35.701 112.968 705.562 74.5467 -51.7631 872.908 81.5757 -21.553 860.038 73.0645 -119.146 986.652 66.9303 -48.3493 670.084 1355.67 -5.59258 571.403 1454.18 200.27 603.878 1462.16 -217.374 589.059 1255.09 252.839 601.296 1223.86 -243.901 553.936 1151.1 289.088 543.176 1132.21 -278.523 725.736 944.316 271.981 692.822 924.778 325.274 643.326 901.247 -232.91 594.659 891.113 -289.84 241.116 42.3156 194.435 262.182 45.7273 83.2431 923.258 51.8322 -126.238 936.951 61.1575 -24.1713 741.545 1572.93 76.8245 755.65 1574.59 -61.3138 760.416 1749.86 14.6615 634.151 1056.47 150.443 657.8 1050.01 -109.142 447.747 1052.04 9.21281 554.428 739.088 203.142 619.562 664.671 124.45 529.369 620.561 198.88 674.151 749.68 -160.592 771.643 741.905 -95.5617 708.372 647.283 -144.002 406.542 488.722 189.74 444.92 408.327 141.159 360.365 414.071 193.482 746.22 441.849 -137.751 797.047 397 -81.075 731.24 397.4 -146.677 101.916 229.24 101.675 212.549 136.386 74.1506 187.588 126.251 177.741 288.312 37.2808 114.488 687.744 76.016 -52.5992 855.596 79.1817 -21.7048 842.48 71.1218 -119.59 968.873 61.56 -48.5816 671.152 1358.06 -9.11412 571.462 1456.91 196.154 605.683 1463.58 -221.49 587.317 1257.82 249.183 606.392 1224.79 -246.528 550.633 1154.3 285.154 549.582 1132.37 -280.935 716.386 942.236 272.479 681.863 924.266 325.293 648.91 900.376 -235.136 600.419 890.615 -292.459 229.329 50.9074 193.979 252.744 52.1026 83.8422 905.263 48.0518 -126.461 919.029 57.2273 -24.39 742.196 1575 72.6428 756.596 1576.37 -65.4841 761.97 1751.97 10.1072 635.868 1059.07 146.883 659.059 1052.45 -112.766 449.243 1053.96 6.3271 565.836 740.221 201.573 633.892 667.832 124.032 545.399 621.017 198.453 671 751.123 -163.753 767.707 741.056 -98.6727 702.19 647.944 -146.648 425.085 493.15 189.04 460.184 410.05 141.312 374.826 420.49 192.506 735.71 441.257 -140.278 785.312 395.569 -83.259 719.755 397.06 -148.919 108.236 250.524 97.4043 212.86 147.714 73.1626 184.971 141.177 175.849 279.258 39.7154 116.069 669.386 76.3814 -53.854 837.716 77.4685 -22.2785 824.197 69.6525 -120.461 950.576 57.9853 -49.3645 671.851 1360.92 -12.6565 571.092 1460.06 192.074 607.15 1465.43 -225.643 585.096 1260.93 245.553 611.438 1226.09 -249.087 546.833 1157.9 281.16 555.989 1132.84 -283.254 706.481 940.936 272.843 670.366 924.498 325.091 654.691 899.64 -237.365 606.376 890.263 -295.163 220.472 61.2298 193.175 246.374 59.7685 84.311 886.747 45.3571 -127.144 900.693 54.5771 -25.0811 742.189 1578.07 68.2857 756.776 1579.08 -69.8871 762.004 1754.87 5.24846
Out[9]:
In [10]:
# Plot original and reconstructed L.Acromium.X over time
lacro_np = np.array(h2o.as_list(gait["L.Acromium.X"]))
lacro_pred_np = np.array(h2o.as_list(pred["reconstr_L.Acromium.X"]))
line_orig = plt.plot(time_np, lacro_np, '-')
line_imp = plt.plot(time_np, lacro_pred_np, '-')
plt.title("Position of Left Acromium over Time")
plt.xlabel("Time")
plt.ylabel("X-Coordinate of Left Acromium")
blue_patch = mpatches.Patch(color = 'blue', label = 'Original')
green_patch = mpatches.Patch(color = 'green', label='Imputed')
plt.legend([blue_patch, green_patch], ["Original", "Imputed"])
plt.show()
In [11]:
# Import walking gait data with missing values
gait_miss = h2o.upload_file(_locate("smalldata/glrm_test/subject01_walk1_miss15.csv"))
gait_miss.describe()
Parse Progress: [##################################################] 100%
Rows:151 Cols:124
Chunk compression summary:
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chunk_name
count
count_percentage
size
size_percentage C2S
2-Byte Fractions
1
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4-Byte Fractions
123
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Frame distribution summary:
size
number_of_rows
number_of_chunks_per_column
number_of_chunks 192.168.1.106:54321
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Time R.ASIS.X R.ASIS.Y R.ASIS.Z L.ASIS.X L.ASIS.Y L.ASIS.Z V.Sacral.X V.Sacral.Y V.Sacral.Z R.Thigh.Upper.X R.Thigh.Upper.Y R.Thigh.Upper.Z R.Thigh.Front.X R.Thigh.Front.Y R.Thigh.Front.Z R.Thigh.Rear.X R.Thigh.Rear.Y R.Thigh.Rear.Z L.Thigh.Upper.X L.Thigh.Upper.Y L.Thigh.Upper.Z L.Thigh.Front.X L.Thigh.Front.Y L.Thigh.Front.Z L.Thigh.Rear.X L.Thigh.Rear.Y L.Thigh.Rear.Z R.Shank.Upper.X R.Shank.Upper.Y R.Shank.Upper.Z R.Shank.Front.X R.Shank.Front.Y R.Shank.Front.Z R.Shank.Rear.X R.Shank.Rear.Y R.Shank.Rear.Z L.Shank.Upper.X L.Shank.Upper.Y L.Shank.Upper.Z L.Shank.Front.X L.Shank.Front.Y L.Shank.Front.Z L.Shank.Rear.X L.Shank.Rear.Y L.Shank.Rear.Z R.Heel.X R.Heel.Y R.Heel.Z R.Midfoot.Sup.X R.Midfoot.Sup.Y R.Midfoot.Sup.Z R.Midfoot.Lat.X R.Midfoot.Lat.Y R.Midfoot.Lat.Z R.Toe.Tip.X R.Toe.Tip.Y R.Toe.Tip.Z L.Heel.X L.Heel.Y L.Heel.Z L.Midfoot.Sup.X L.Midfoot.Sup.Y L.Midfoot.Sup.Z L.Midfoot.Lat.X L.Midfoot.Lat.Y L.Midfoot.Lat.Z L.Toe.Tip.X L.Toe.Tip.Y L.Toe.Tip.Z Sternum.X Sternum.Y Sternum.Z R.Acromium.X R.Acromium.Y R.Acromium.Z L.Acromium.X L.Acromium.Y L.Acromium.Z R.Bicep.X R.Bicep.Y R.Bicep.Z L.Bicep.X L.Bicep.Y L.Bicep.Z R.Elbow.X R.Elbow.Y R.Elbow.Z L.Elbow.X L.Elbow.Y L.Elbow.Z R.Wrist.Med.X R.Wrist.Med.Y R.Wrist.Med.Z R.Wrist.Lat.X R.Wrist.Lat.Y R.Wrist.Lat.Z L.Wrist.Med.X L.Wrist.Med.Y L.Wrist.Med.Z L.Wrist.Lat.X L.Wrist.Lat.Y L.Wrist.Lat.Z R.Toe.Lat.X R.Toe.Lat.Y R.Toe.Lat.Z R.Toe.Med.X R.Toe.Med.Y R.Toe.Med.Z L.Toe.Lat.X L.Toe.Lat.Y L.Toe.Lat.Z L.Toe.Med.X L.Toe.Med.Y L.Toe.Med.Z R.Temple.X R.Temple.Y R.Temple.Z L.Temple.X L.Temple.Y L.Temple.Z Top.Head.X Top.Head.Y Top.Head.Z type real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real real mins 0.0 588.90717 1042.57324 107.79163 600.01556 1029.25427 -152.53879 399.40009 1034.90125 -21.44083 481.83603 732.70135 169.71159 535.63422 657.21033 74.20708 443.03299 613.54547 168.15961 468.19415 737.72083 -194.25998 550.69415 684.75494 -133.588 435.01773 627.49988 -170.86086 319.34705 445.08429 157.69023 376.44724 403.25574 102.54192 295.04089 368.36661 165.6133 341.2023 438.80435 -172.96315 365.72482 375.95242 -120.97533 304.46347 393.67728 -173.38676 68.60076 56.43383 59.948 190.98845 76.90237 57.86759 157.32503 62.79 159.97461 242.90858 33.52863 102.0894 76.37951 60.01719 -74.0361 211.85968 70.39124 -69.30095 185.39088 48.22646 -140.09074 254.42706 36.65646 -88.18266 627.38177 1342.85413 -35.20795 511.80032 1427.44507 164.48206 551.72424 1453.58936 -249.89265 485.94559 1227.90454 216.05853 531.12134 1217.64429 -266.60974 424.32767 1129.49243 242.4415 460.20703 1123.80298 -304.79358 535.87439 889.81964 262.1105 486.99316 876.53882 304.71069 554.35272 895.92426 -240.59163 503.10611 886.58942 -300.87775 179.7708 33.33099 181.24631 218.04131 36.96362 71.79319 202.74066 36.02512 -153.13719 228.04898 42.9706 -54.88903 675.97009 1562.28418 44.15432 683.50897 1567.27209 -94.07465 614.13971 1740.38916 -19.48838 mean 1.25 614.521937381 1065.67421107 147.703810859 621.468577752 1053.88708992 -113.122046299 419.961478582 1058.93961659 21.1173823529 602.023772652 751.727318268 198.126564524 676.998435725 698.116475255 107.988446202 607.493851145 634.098869191 191.194278051 589.7071056 756.634831575 -164.439363308 676.351652422 728.968314375 -105.687799286 598.001710242 651.426971145 -150.982097813 543.651496589 476.831541692 177.902406439 612.248566296 427.129153607 128.558000234 550.95748125 395.283420826 183.200654918 578.969913643 453.857565448 -144.91755189 613.901491364 398.723144921 -94.282770315 548.710087308 418.688882632 -151.060904697 418.619440076 121.180163701 90.9976358462 545.774982636 110.411220308 69.7803931852 524.563115041 93.9240401481 173.773202619 654.156492222 66.8884640769 120.134765312 431.875431429 129.842342879 -51.2799509756 574.977815625 103.838779764 -30.0915743411 566.120252698 96.7959412605 -123.583813759 678.850758647 66.4413544355 -58.1608756 643.77072488 1367.91781435 7.47555930233 541.600241496 1458.34269906 215.231620662 578.89798065 1481.99186786 -202.491409055 547.47776 1259.51176984 262.389468295 596.567747218 1244.48827078 -229.600702602 503.465348926 1157.80938348 293.643441875 545.959992063 1147.66211244 -268.395942261 657.229595769 944.06776352 282.972861818 617.135221221 928.325214803 331.347985231 673.973280074 938.227669084 -215.020891417 628.216717937 921.965815116 -273.340353333 592.733126692 61.2529552713 194.700779394 616.123127803 67.72312864 86.2080589256 610.74992041 64.8094222764 -131.935055308 652.881504884 74.2817251181 -32.4495277206 708.096513 1597.33403922 92.7947677273 718.288894141 1603.7745607 -44.2737168421 698.76248313 1773.21534205 34.8947876033 maxs 2.5 641.12048 1091.26807 180.07411 661.46918 1078.02356 -80.82956 451.5914 1077.77014 55.29718 692.89514 788.11365 216.86717 766.44531 750.72375 136.25021 726.57483 672.42242 209.89946 674.53168 781.90839 -138.11635 772.35175 780.81445 -66.30186 713.16107 681.38623 -123.1844 719.69702 531.05676 200.56787 799.47015 457.5513 154.56749 751.88885 458.64368 202.59061 764.30676 494.35605 -116.46951 821.66901 425.57733 -63.825 750.77588 472.92294 -125.0268 812.50183 320.70309 108.161 935.61414 197.97754 85.62352 934.44775 209.43217 188.70589 1071.77734 179.28133 153.59363 821.7641 321.80249 -34.92287 971.31763 178.00603 -6.83138 955.73096 184.36398 -104.3698 1082.51477 168.6488 -33.04971 673.89301 1393.88806 43.5209 573.64575 1485.37354 262.06827 609.36566 1507.81018 -156.17076 593.20453 1288.58093 305.86801 643.91699 1271.75806 -196.56128 567.0025 1193.14404 339.82635 608.93268 1186.43945 -230.94901 771.56329 1003.08368 312.96448 750.302 969.89471 362.03549 793.86859 998.83923 -188.33229 768.91589 958.34167 -249.44443 1022.32318 136.89597 218.5173 1029.85803 153.3546 113.4589 1024.06946 132.61819 -111.9407 1039.38684 146.49858 -9.44173 740.63611 1640.01184 139.15808 754.62506 1647.88391 0.84904 752.89178 1809.14917 85.29955 sigma 0.72889825536 14.9221530809 14.1118800605 25.4320668986 15.1985087313 14.1627886941 24.2429348729 14.4347102075 12.1006665421 24.0349655413 67.1042685894 14.2055227243 15.6879027907 74.6813145799 26.3890165553 18.4568665408 96.4225733009 15.0677784035 12.5084264088 66.3462443984 11.2649580796 17.8424219983 72.2174940573 26.1430363887 21.330821545 92.8419425867 11.5232616805 13.9527415824 134.808765047 25.7438724872 11.1362019486 143.972624737 16.4987109984 11.6710725124 155.376675607 28.587049937 8.38900649533 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In [12]:
# Basic GLRM using quadratic loss and no regularization
model2 = h2o.glrm(x=gait_miss[1:], validation_x=gait[1:], k=10, init="SVD", svd_method = "GramSVD", loss="Quadratic", regularization_x="None", regularization_y="None", max_iterations=2000, min_step_size=1e-6)
model2.show()
glrm Model Build Progress: [##################################################] 100%
Model Details
=============
H2OEstimator : Beta - Generalized Low Rank Model
Model Key: GLRM_model_python_1446185816814_11
Model Summary:
/Library/Python/2.7/site-packages/IPython/kernel/__main__.py:2: DeprecationWarning: `h2o.glrm` is deprecated. Use the estimators sub module to build an H2OGeneralizedLowRankEstimator.
from IPython.kernel.zmq import kernelapp as app
number_of_iterations
final_step_size
final_objective_value 2000.0
0.0
122299.7
ModelMetricsGLRM: glrm
** Reported on train data. **
MSE: NaN
Sum of Squared Error (Numeric): 122299.726469
Misclassification Error (Categorical): 0.0
ModelMetricsGLRM: glrm
** Reported on validation data. **
MSE: NaN
Sum of Squared Error (Numeric): 153530.207952
Misclassification Error (Categorical): 0.0
Scoring History:
timestamp
duration
iteration
step_size
objective 2015-10-29 23:30:10
0.704 sec
0.0
0.7
4709528.9 2015-10-29 23:30:10
0.713 sec
1.0
0.4
4709528.9 2015-10-29 23:30:10
0.722 sec
2.0
0.2
4709528.9 2015-10-29 23:30:10
0.731 sec
3.0
0.1
4709528.9 2015-10-29 23:30:10
0.740 sec
4.0
0.0
4709528.9 ---
---
---
---
---
--- 2015-10-29 23:30:47
37.411 sec
1995.0
0.0
122316.1 2015-10-29 23:30:47
37.438 sec
1996.0
0.0
122310.5 2015-10-29 23:30:47
37.466 sec
1997.0
0.0
122306.5 2015-10-29 23:30:47
37.493 sec
1998.0
0.0
122303.0 2015-10-29 23:30:47
37.521 sec
1999.0
0.0
122299.7
In [13]:
# Plot objective function value each iteration
model2_score = model2.score_history()
plt.xlabel("Iteration")
plt.ylabel("Objective")
plt.title("Objective Function Value per Iteration")
plt.plot(model2_score["iteration"], model2_score["objective"])
plt.show()
In [14]:
# Impute missing data from X and Y
pred2 = model2.predict(gait_miss)
pred2.head()
reconstr_R.ASIS.X reconstr_R.ASIS.Y reconstr_R.ASIS.Z reconstr_L.ASIS.X reconstr_L.ASIS.Y reconstr_L.ASIS.Z reconstr_V.Sacral.X reconstr_V.Sacral.Y reconstr_V.Sacral.Z reconstr_R.Thigh.Upper.X reconstr_R.Thigh.Upper.Y reconstr_R.Thigh.Upper.Z reconstr_R.Thigh.Front.X reconstr_R.Thigh.Front.Y reconstr_R.Thigh.Front.Z reconstr_R.Thigh.Rear.X reconstr_R.Thigh.Rear.Y reconstr_R.Thigh.Rear.Z reconstr_L.Thigh.Upper.X reconstr_L.Thigh.Upper.Y reconstr_L.Thigh.Upper.Z reconstr_L.Thigh.Front.X reconstr_L.Thigh.Front.Y reconstr_L.Thigh.Front.Z reconstr_L.Thigh.Rear.X reconstr_L.Thigh.Rear.Y reconstr_L.Thigh.Rear.Z reconstr_R.Shank.Upper.X reconstr_R.Shank.Upper.Y reconstr_R.Shank.Upper.Z reconstr_R.Shank.Front.X reconstr_R.Shank.Front.Y reconstr_R.Shank.Front.Z reconstr_R.Shank.Rear.X reconstr_R.Shank.Rear.Y reconstr_R.Shank.Rear.Z reconstr_L.Shank.Upper.X reconstr_L.Shank.Upper.Y reconstr_L.Shank.Upper.Z reconstr_L.Shank.Front.X reconstr_L.Shank.Front.Y reconstr_L.Shank.Front.Z reconstr_L.Shank.Rear.X reconstr_L.Shank.Rear.Y reconstr_L.Shank.Rear.Z reconstr_R.Heel.X reconstr_R.Heel.Y reconstr_R.Heel.Z reconstr_R.Midfoot.Sup.X reconstr_R.Midfoot.Sup.Y reconstr_R.Midfoot.Sup.Z reconstr_R.Midfoot.Lat.X reconstr_R.Midfoot.Lat.Y reconstr_R.Midfoot.Lat.Z reconstr_R.Toe.Tip.X reconstr_R.Toe.Tip.Y reconstr_R.Toe.Tip.Z reconstr_L.Heel.X reconstr_L.Heel.Y reconstr_L.Heel.Z reconstr_L.Midfoot.Sup.X reconstr_L.Midfoot.Sup.Y reconstr_L.Midfoot.Sup.Z reconstr_L.Midfoot.Lat.X reconstr_L.Midfoot.Lat.Y reconstr_L.Midfoot.Lat.Z reconstr_L.Toe.Tip.X reconstr_L.Toe.Tip.Y reconstr_L.Toe.Tip.Z reconstr_Sternum.X reconstr_Sternum.Y reconstr_Sternum.Z reconstr_R.Acromium.X reconstr_R.Acromium.Y reconstr_R.Acromium.Z reconstr_L.Acromium.X reconstr_L.Acromium.Y reconstr_L.Acromium.Z reconstr_R.Bicep.X reconstr_R.Bicep.Y reconstr_R.Bicep.Z reconstr_L.Bicep.X reconstr_L.Bicep.Y reconstr_L.Bicep.Z reconstr_R.Elbow.X reconstr_R.Elbow.Y reconstr_R.Elbow.Z reconstr_L.Elbow.X reconstr_L.Elbow.Y reconstr_L.Elbow.Z reconstr_R.Wrist.Med.X reconstr_R.Wrist.Med.Y reconstr_R.Wrist.Med.Z reconstr_R.Wrist.Lat.X reconstr_R.Wrist.Lat.Y reconstr_R.Wrist.Lat.Z reconstr_L.Wrist.Med.X reconstr_L.Wrist.Med.Y reconstr_L.Wrist.Med.Z reconstr_L.Wrist.Lat.X reconstr_L.Wrist.Lat.Y reconstr_L.Wrist.Lat.Z reconstr_R.Toe.Lat.X reconstr_R.Toe.Lat.Y reconstr_R.Toe.Lat.Z reconstr_R.Toe.Med.X reconstr_R.Toe.Med.Y reconstr_R.Toe.Med.Z reconstr_L.Toe.Lat.X reconstr_L.Toe.Lat.Y reconstr_L.Toe.Lat.Z reconstr_L.Toe.Med.X reconstr_L.Toe.Med.Y reconstr_L.Toe.Med.Z reconstr_R.Temple.X reconstr_R.Temple.Y reconstr_R.Temple.Z reconstr_L.Temple.X reconstr_L.Temple.Y reconstr_L.Temple.Z reconstr_Top.Head.X reconstr_Top.Head.Y reconstr_Top.Head.Z 615.559 1055.73 165.388 637.654 1045.15 -96.0784 428.02 1054.55 22.8896 512.613 741.997 206.036 564.202 666.081 117.102 474.533 626.147 193.928 651.983 744.595 -149.962 746.053 735.381 -80.6366 688.606 641.683 -138.661 353.674 472.64 180.223 413.667 413.357 128.641 335.142 386.419 184.697 747 444.138 -133.872 812.433 414.986 -84.1447 743.488 397.159 -141.853 154.454 108.204 95.9431 297.535 86.9001 63.2528 284.25 69.9924 170.862 427.156 43.8712 107.702 811.693 69.8626 -56.3249 965.355 123.517 -32.5535 947.231 112.867 -128.449 1073.88 139.013 -65.6209 659.525 1359.28 9.66988 566.976 1455.4 221.453 589.473 1469.07 -199.445 596.172 1254.9 271.338 574.958 1232.06 -230.383 570.092 1148.59 307.779 509.184 1143.01 -264.36 775.01 982.204 265.071 750.704 950.31 319.456 612.686 910.631 -225.125 563.264 900.858 -281.744 362.933 32.5927 188.765 374.367 38.7506 77.4304 1015.61 110.629 -139.965 1030.26 122.944 -38.8223 725.718 1590.34 91.6554 734.235 1594.64 -48.2221 714.538 1761.9 28.8296 617.952 1054.93 163.786 640.732 1045.72 -98.3779 430.438 1054.91 19.9749 510.595 741.643 205.86 563.425 663.92 118.709 471.564 625.616 194.772 652.541 745.948 -151.738 746.897 736.507 -83.1013 688.155 643.316 -138.989 348.758 473.583 182.08 407.631 412.342 131.558 328.304 387.981 186.962 744.408 443.922 -133.87 809.349 413.009 -83.5218 740.044 396.697 -142.306 142.313 117.334 99.1604 283.247 89.6501 67.3383 268.023 71.5465 174.856 407.755 43.3005 111.584 797.683 66.6039 -55.4427 955.032 114.496 -31.3253 938.234 104.551 -127.146 1065.82 128.796 -62.5455 662.397 1357.39 6.22569 570.866 1455.3 217.867 593.926 1468.28 -203.449 597.095 1255.41 268.727 577.671 1230.97 -234.181 569.227 1149.25 306.243 511.844 1141.72 -268.311 771.591 976.833 266.482 746.115 946.254 321.46 615.788 909.982 -227.826 566.263 899.733 -284.489 343.42 30.4286 192.892 356.973 37.693 81.1018 1006.78 100.47 -137.79 1020.71 112.609 -36.1812 736.18 1580.56 88.9966 746.244 1584.18 -50.7589 742.811 1755.07 26.8157 619.331 1053.2 162.319 643.075 1044.81 -99.2862 432.456 1052.75 17.5004 511.083 740.128 205.327 564.759 661.461 119.587 471.886 623.874 195.048 659.549 746.05 -152.224 755.205 738.921 -84.6006 697.197 644.083 -138.415 347.514 473.337 183.243 404.457 410.142 133.223 324.521 388.592 188.155 752.21 444.073 -133.105 814.673 410.419 -81.5072 746.1 397.311 -141.977 130.852 126.728 101.409 268.896 92.1654 69.2291 252.653 73.2936 176.187 388.159 41.3084 111.796 784.137 68.565 -54.1473 943.902 107.26 -28.3448 928.761 97.5935 -124.364 1056.22 114.606 -58.1591 663.208 1355.56 2.94591 570.504 1453.82 213.303 594.751 1464.95 -207.338 595.896 1254.51 264.478 580.153 1227.66 -237.067 567.136 1148.61 302.4 515.462 1137.88 -271.013 765.283 970.441 266.274 738.333 941.586 321.188 619.932 907.999 -229.103 570.674 897.114 -285.538 324.9 28.11 193.501 339.329 36.3404 81.505 996.278 89.5438 -134.347 1009.3 101.164 -32.3752 735.759 1578.26 85.2653 746.567 1581.72 -54.1357 742.543 1752.76 22.8269 620.81 1052.34 160.813 644.977 1044.68 -100.468 434.245 1051.55 15.7015 513.979 739.304 204.915 569.07 660.469 120.529 475.711 622.761 195.375 663.395 746.644 -153.025 759.681 740.462 -86.1264 701.641 645.043 -138.372 350.406 474.426 184.231 404.998 408.723 134.58 324.254 390.683 189.038 754.665 443.961 -132.908 815.342 408.105 -80.4876 747.076 397.431 -142.098 121.071 139.201 102.286 255.827 96.1617 70.4216 238.065 77.6429 176.824 369.121 38.935 112.099 769.791 68.4251 -53.5431 932.129 100.466 -26.4864 917.993 90.7288 -122.747 1045.83 102.986 -55.2708 663.954 1354.61 0.478683 570.302 1453.1 209.889 595.675 1462.97 -210.268 594.651 1254.23 261.411 582.52 1225.58 -239.183 564.935 1148.58 299.556 518.726 1135.4 -273.043 759.166 965.416 266.784 730.959 938.065 321.554 623.082 905.873 -230.451 573.787 894.778 -286.817 306.39 27.6793 193.781 322.158 35.8806 81.858 984.8 79.7017 -132.072 997.674 91.0645 -29.8956 736.18 1576.32 82.4625 747.59 1579.5 -56.6942 744.716 1751.07 19.8625 622.925 1051.29 159.145 647.549 1044.15 -101.797 436.668 1049.89 13.7646 518.083 738.511 204.395 574.588 659.632 121.307 480.896 621.724 195.495 667.398 746.74 -153.851 764.396 741.341 -87.7755 706.113 645.467 -138.324 354.673 475.577 185.152 406.73 407.17 135.637 325.187 392.737 189.826 756.792 443.42 -132.822 815.269 405.312 -79.3963 747.679 397.316 -142.385 111.191 151.736 103.32 242.884 99.6372 71.3428 223.713 81.4129 177.254 350.342 35.6338 111.728 753.767 69.4136 -53.3119 917.999 93.945 -24.4009 905.034 83.8968 -120.978 1032.63 91.0177 -51.7876 665.176 1353.59 -2.08174 570.112 1452.17 206.266 597.118 1460.73 -213.462 593.372 1253.68 258.038 586.001 1223.16 -241.46 562.608 1148.24 296.28 523.353 1132.42 -275.337 752.52 959.661 267.128 722.901 933.881 321.676 627.743 903.128 -232.002 578.44 891.819 -288.34 288.184 26.2618 193.655 305.152 34.4774 81.6845 970.729 69.695 -129.425 983.368 80.8198 -26.9832 736.193 1575.12 79.4261 748.18 1578.08 -59.5241 744.862 1749.92 16.5364 625.365 1051.53 157.466 650.359 1045.12 -103.573 439.144 1049.75 11.8299 522.912 737.667 203.989 581.059 658.711 122.137 487.183 620.349 196.018 669.765 747.608 -155.203 767.079 742.048 -89.6214 707.829 646.332 -138.888 361.202 477.002 186.344 410.262 406.412 137.054 328.524 395.97 190.868 755.66 443.144 -133.261 812.224 403.153 -78.8445 745.213 397.364 -143.049 106.747 168.07 103.852 233.304 107.232 72.4075 212.645 90.1863 177.902 332.898 36.8049 112.317 737.523 69.9351 -53.0865 903.526 88.7592 -22.5074 891.327 78.8377 -119.602 1018.91 81.7406 -48.977 666.704 1354.29 -4.70835 570.295 1453.22 202.982 599.014 1460.46 -216.953 592.302 1254.75 255.203 590.28 1222.32 -243.959 560.266 1149.48 293.516 528.845 1130.9 -277.87 745.426 955.018 268.163 714.345 930.885 322.607 633.064 901.612 -233.634 583.884 890.181 -290.2 271.973 30.6623 194.041 290.234 38.1287 82.154 956.392 62.0122 -127.325 968.77 72.9838 -24.5783 737.133 1575.65 76.4884 749.752 1578.32 -62.473 746.843 1750.89 13.2234 628.915 1052.54 155.326 653.697 1046.38 -105.594 442.594 1050.04 10.051 531.546 737.957 203.405 591.745 659.801 122.739 498.236 620.125 196.174 673.083 748.661 -157.111 770.748 742.804 -92.2683 710.61 647.194 -140.341 372.202 479.913 186.981 417.911 405.965 137.74 335.158 400.121 191.249 755.194 443.104 -134.914 809.522 401.146 -79.8507 743.135 397.969 -144.782 100.503 185.518 102.982 222.804 113.731 72.3328 200.232 98.503 177.241 315.03 34.1304 112.038 720.464 73.007 -54.0485 887.203 84.6231 -22.2352 875.12 74.8694 -119.781 1002.06 72.6453 -48.2342 669.089 1355.46 -7.08964 571.635 1454.43 200.028 601.7 1460.78 -219.824 592.552 1255.99 252.455 595.122 1222.17 -245.977 559.404 1150.89 290.65 534.583 1130.26 -279.881 739.961 951.342 268.999 707.489 928.596 323.104 637.295 899.078 -236.079 587.824 888.164 -292.887 254.475 33.1003 193.247 274.304 39.2562 81.7657 938.909 54.9909 -126.941 951.754 65.6537 -24.0771 738.991 1576.24 73.6723 751.914 1578.66 -65.2265 749.809 1751.64 10.1666 631.109 1054.21 152.098 655.786 1047.98 -108.529 444.839 1050.79 7.2448 541.285 738.57 202.294 603.968 661.768 122.943 511.564 620.262 196.297 674.008 749.572 -159.632 771.647 742.909 -95.0632 710.17 647.672 -142.273 386.63 483.741 187.332 428.929 406.678 138.693 345.191 405.676 191.446 751.452 442.594 -136.693 803.921 399.174 -80.9242 738.099 397.901 -146.436 99.7076 205.485 101.161 216.709 123.388 72.4438 191.867 110.428 176.485 300.419 34.6713 113.04 703.837 74.8759 -54.5117 871.128 81.4745 -21.7119 859.147 72.3251 -119.634 985.708 65.5215 -47.6927 670.156 1357.03 -10.6396 571.469 1456.28 195.582 603.513 1461.25 -223.915 590.692 1257.97 248.443 600.413 1222.29 -248.656 556.016 1153.38 286.399 541.443 1129.63 -282.386 730.328 948.138 269.327 696.202 927.135 322.94 643.506 898.032 -238.047 594.311 887.286 -295.234 240.392 39.7727 192.894 262.17 44.2717 82.2302 922.305 50.1115 -126.533 935.105 60.45 -23.6335 739.312 1577.48 69.4493 752.596 1579.58 -69.32 750.724 1752.87 5.61663 633.024 1056.49 149.247 657.287 1050.27 -111.296 446.556 1052.26 5.19222 551.616 739.395 201.499 616.977 664.232 123.348 525.945 620.512 196.703 673.062 750.915 -162.068 770.38 742.797 -97.6261 707.162 648.432 -144.265 402.79 487.832 187.813 441.635 407.804 139.693 357.096 411.71 191.69 744.598 442.237 -138.519 795.406 397.539 -82.2129 729.994 397.926 -148.056 101.658 226.441 98.8641 212.955 134.085 72.3957 185.743 123.923 175.641 287.811 36.1102 114.311 685.703 76.2323 -54.9236 853.563 78.9023 -21.4091 841.349 70.3116 -119.76 967.716 59.9293 -47.6085 670.785 1359.41 -13.3498 570.939 1458.81 192.244 604.838 1462.8 -227.122 588.471 1260.47 245.563 605.155 1223.38 -250.624 552.277 1156.34 283.183 547.652 1130.04 -284.264 720.572 945.708 270.445 684.916 926.359 323.578 648.772 897.439 -239.632 599.783 887.051 -297.31 228.227 48.2282 192.621 252.074 50.5969 82.8595 904.011 46.1829 -126.425 917.085 56.2784 -23.5423 739.482 1579.55 66.2642 753.087 1581.31 -72.4774 751.908 1755.14 2.14528 635.437 1058.81 145.656 659.061 1052.4 -114.722 448.768 1053.74 2.70909 564.143 740.174 200.047 632.344 667.181 122.94 543.234 620.724 196.448 670.945 752.216 -165.19 767.532 741.89 -100.764 702.196 649.018 -147.097 422.686 492.2 187.563 457.859 409.336 139.89 372.67 418.202 191.205 735.277 441.634 -141.267 784.845 395.97 -84.7241 719.588 397.62 -150.514 107.825 248.462 95.4936 212.91 145.85 71.5258 183.368 139.119 173.867 278.628 38.3398 115.097 667.702 76.5172 -56.3822 836.119 76.8301 -22.3816 823.209 68.6211 -121.142 949.683 55.6579 -49.1613 671.995 1361.73 -16.4883 571.072 1461.29 188.516 606.901 1464.28 -230.628 586.805 1262.89 242.176 610.859 1224.45 -252.828 549.026 1159.31 279.274 554.862 1130.41 -286.331 711.162 943.872 270.864 674.032 926.028 323.36 655.157 896.584 -241.695 606.304 886.594 -299.874 219.564 58.5618 191.549 245.377 58.3082 82.9515 885.593 43.0205 -127.708 899.36 53.0504 -24.9762 740.165 1581.67 62.4251 753.887 1583.08 -76.273 753.056 1757.16 -2.01401
Out[14]:
In [16]:
# Plot original and imputed L.Acromium.X over time
lacro_pred_np2 = np.array(h2o.as_list(pred2["reconstr_L.Acromium.X"]))
plt.plot(time_np, lacro_np, 'b-')
plt.plot(time_np, lacro_pred_np2, 'g-')
# Mark points where training data contains missing values
idx_miss = zip(*gait_miss["L.Acromium.X"].isna().which().as_data_frame(True).values.tolist())
plt.plot(time_np[idx_miss], lacro_np[idx_miss], "o", marker = "x", ms = 8, mew = 1.5, mec = "r")
plt.title("Position of Left Acromium over Time")
plt.xlabel("Time")
plt.ylabel("X-Coordinate of Left Acromium")
blue_patch = mpatches.Patch(color = 'blue', label = 'Original')
green_patch = mpatches.Patch(color = 'green', label = 'Imputed')
red_patch = mpatches.Patch(color = 'red', label = "Missing")
plt.legend([blue_patch, green_patch, red_patch], ["Original", "Imputed", "Missing"])
plt.show()
Content source: madmax983/h2o-3
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