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How do I fix the Python code errors output by the JMP Pro 13.1 Formula Depot?

tjs

New Contributor

Joined:

Jul 22, 2017

Hello, 

I am attempting to publish the Probability Forumulas from my Discriminant analysis using JMP Pro 13.1's Forumla Depot. When I select "Publish Python Code" I receive the following dialog of errors shown in the image.


Screen Shot 2017-07-22 at 5.18.25 PM.jpg

Python code is still output, however I'd prefer not to use erroneous code and I am wondering how to debug this code or what I am doing wrong. I am unsure what exactly "Vec Quadratic" or "The formula uses an unsupported operator, type 2" refer to in terms of Python. I am assuming "Vec Quadratic" refers to my use of the "Quadratic". I am completely unaware of what the software means by "type 2" operator. 

 

From my knowledge of python, Matricies and Lists are basic data containers, often implemented using the numpy or pandas modules. I've inluded the output python code below, but I am unaware how to completely debug the script without understanding what the error dialog is attempting to communicate. There is little use in providing an option to publish code in python if it fails to consider fundament aspects of the language, thus I am confused as to why I am recieving these errors.

 

How do I fix the code? What does the dialog mean by "Vec Quadratic" or "type 2" operator?

 

Thanks in advance!

-tjs

 
from __future__ import division
from math import *
import jmp_score as jmp


""" ==================================================================
 Copyright(C) 2016 SAS Institute Inc.All rights reserved.
 
 Notice:
 The following permissions are granted provided that the
 above copyright and this notice appear in the score code and
 any related documentation.Permission to copy, modify
 and distribute the score code generated using
 JMP(R) software is limited to customers of SAS Institute Inc. ("SAS")
 and successive third parties, all without any warranty, express or
 implied, or any other obligation by SAS.SAS and all other SAS
 Institute.Inc.product and service names are registered
 trademarks or trademarks of SAS Institute Inc.in the USA
 and other countries.Except as contained in this notice,
 the name of the SAS Institute Inc. and JMP shall not be used in
 the advertising or promotion of products or services without
 prior written authorization from SAS Institute Inc.
 ================================================================== """

""" Python code generated by JMP v13.1.0 """

def getModelMetadata():
	return {"creator": "Discriminant", "modelName": "", "predicted": "Group", "table": "CVA-EFA_Invariant_2-11siny 2", "version": "13.1.0", "timestamp": "2017-07-23T00:13:30Z"}


def getInputMetadata():
    return {
        "siny 1": "float",
        "cosx 2": "float",
        "sinx 2": "float",
        "cosy 2": "float",
        "siny 2": "float",
        "cosx 3": "float",
        "sinx 3": "float",
        "cosy 3": "float",
        "siny 3": "float",
        "cosx 4": "float",
        "sinx 4": "float",
        "cosy 4": "float",
        "siny 4": "float",
        "cosx 5": "float",
        "sinx 5": "float",
        "cosy 5": "float",
        "siny 5": "float",
        "cosx 6": "float",
        "sinx 6": "float",
        "cosy 6": "float",
        "siny 6": "float",
        "cosx 7": "float",
        "sinx 7": "float",
        "cosy 7": "float",
        "siny 7": "float",
        "cosx 8": "float",
        "sinx 8": "float",
        "cosy 8": "float",
        "siny 8": "float",
        "cosx 9": "float",
        "sinx 9": "float",
        "cosy 9": "float",
        "siny 9": "float",
        "cosx 10": "float",
        "sinx 10": "float",
        "cosy 10": "float",
        "siny 10": "float",
        "cosx 11": "float",
        "sinx 11": "float",
        "cosy 11": "float",
        "siny 11": "float"
	}


def getOutputMetadata():
    return {
        "Prob[Ash-Flow]": "float",
        "Prob[Basaltic Shield]": "float",
        "Prob[Io Patera]": "float",
        "Prob[Lunar Impact Crater]": "float",
        "Prob[Martian Caldera]": "float",
        "Pred Group": "str"
	}


def score(indata, outdata):
    # SqDist_Ash_Flow_
    # SqDist_Basaltic_Shield_
    # SqDist_Io_Patera_
    # SqDist_Lunar_Impact_Crater_
    # SqDist_Martian_Caldera_
    _temp0 = 1
    _temp1 = 1
    _temp2 = 1
    _temp3 = 1
    _temp4 = 1
    # _temp5
    _temp6 = [0 for i in range(5)]
    _temp7 = ""

    SqDist_Ash_Flow_ = placeholder_Vec_Quadratic("""
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	 1427.08897484238 -2385.45764209956 -3914.04650453936 5605.86145377789 4123.81947489635 1231.5333997689 6774.03420943606 7746.2097254439 -1852.93952146761 -6456.87449613712 3688.9747306406 8728.08262091278
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	 90339.896718047 -2467.43052804586 151153.21008584 65854.7228569993 302585.516730375]
"""
, (placeholder_Matrix(placeholder_List(indata['siny 1'], indata['cosx 2'], indata['sinx 2'], indata['cosy 2'], indata['siny 2'], indata['cosx 3'], indata['sinx 3'], indata['cosy 3'], indata['siny 3'], indata['cosx 4'], indata['sinx 4'], indata['cosy 4'], indata['siny 4'], indata['cosx 5'], indata['sinx 5'], indata['cosy 5'], indata['siny 5'], indata['cosx 6'], indata['sinx 6'], indata['cosy 6'], indata['siny 6'], indata['cosx 7'], indata['sinx 7'], indata['cosy 7'], indata['siny 7'], indata['cosx 8'], indata['sinx 8'], indata['cosy 8'], indata['siny 8'], indata['cosx 9'], indata['sinx 9'], indata['cosy 9'], indata['siny 9'], indata['cosx 10'], indata['sinx 10'], indata['cosy 10'], indata['siny 10'], indata['cosx 11'], indata['sinx 11'], indata['cosy 11'], indata['siny 11'])) - """
[-0.784913794871795, -0.000830563333333333, 0.00584296692307692, 0.00477162435897436, -0.00443089615384615, 0.0367847625641026, -0.00402905687179487, 0.000251019051282051, -0.0347147594871795, 0.001634847
	, -0.00101164392307692, 0.001604759, 0.00224805102564102, 0.00497423584615385, -0.00335020748717949, -0.00405844438461539, -0.00597616286923077, 0.00232975319487179, 0.00172794907692308, -0.00222922928205128
	, -0.00260087287179487, 0.00081534682051282, -0.00169913268205128, -0.00185881902564103, 0.000451847512820513, -0.00112038967692308, 0.00321866992051282, 0.00113230992307692, -0.0000655279743589742, 0.000880897282051282
	, -0.0002644763, 0.000431016487179487, -0.000926707871794872, 0.0000358902076923078, 0.00151305825384615, 0.00136959019230769, 0.000808805246153847, 0.000702492097435897, -0.000609273, -0.000203190025641026
	, 0.000185177823076923]
"""
)) + -408.098218104361

    SqDist_Basaltic_Shield_ = placeholder_Vec_Quadratic("""
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	 69605.2036001228 6601.20654114144 -4175.99455383824 -157268.969853992 49444.0115130672 -11979.2685844687 327623.958614479 113169.991574224 176913.839557958 311917.655651012 -182085.152156522 -114288.930038256
	 346808.582880432 57070.0999962321 -195073.811718164 53505.8127084766 201784.741813269 -104962.369793516 137061.09929875 160067.381337892 130063.44980635 -82051.8914581203 295926.800491872 51992.3260157594
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	22703.4365983679 82249.7052407062 -28701.4826493989 -17867.9426360616 -43284.5049496698 -93415.3750996256 -59180.361068453 -1462.321288878 51838.6302249751 -104161.275876583 239785.77984826 -173018.656248638
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	 232430.571725483 -314737.256977856 -538757.944966084 208322.318920964 237095.838107127,
	5298.73353878439 -38918.3824882449 14874.2925236382 -20908.4770867969 51055.4865880753 -19591.7913582273 435.894631615392 28051.1614176252 477.246845670747 -28039.6618871231 -121606.615006476 24324.7646089263
	 38594.8326036267 -22366.6960043195 115588.667578788 -28553.1373159521 -25828.2955123743 46661.4899524356 91237.4380758584 79216.5771587016 -13398.3792654128 -9846.63363328813 -119831.895016882 50165.1100481312
	 53505.8127084766 -209293.096548963 -225589.801492566 317608.84340803 -97416.3117838509 171888.966037664 -40973.8554659799 188286.77645774 80792.5753036371 301352.080513587 149871.335466636 86201.759288784
	 59271.3059609286 -262726.79573194 30902.6175618514 81501.1106298262 -28151.5822039158,
	-7380.29214135619 -82412.1816682757 41418.9900105907 11046.0230681978 11305.3712909452 52691.404763297 70559.6419697466 -26854.7915340766 12379.315051304 139106.426024335 -198198.098984251 91564.2706415482
	 13487.254925575 -97907.0049936996 55207.4907129118 -150920.892941352 18090.3215456647 162985.477264855 489940.111105215 77254.7045899515 196998.245568567 304513.78024487 -342972.270079949 -47283.2801334446
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	30481.4075682582 13633.5406929522 13603.2816804382 -62034.3178673961 42126.1487786009 -106680.806281258 -26900.7287402008 8415.77118282015 79709.5156053268 -194977.218688346 -137775.21225935 -57004.4179888421
	 44930.43116099 -57686.5292642401 311055.882456245 -45762.9491899202 -43185.4403644234 237951.586468913 -105712.781663777 147698.94833916 14262.9564587022 -197409.828597193 -254915.478335493 166296.12663543
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	 490651.62019345 -890769.58941863 -492187.982815701 143840.275530104 292383.173644154,
	17814.5739775016 -47839.3972563854 40012.6154980269 -41240.3008257427 33892.9152424594 -22842.7140900431 59247.4899696791 -9588.15537831141 71287.674509359 29741.3820186349 -170565.071967047 8297.70896996502
	 86374.9299746571 -107344.089464749 210262.325577739 -160943.052388067 3732.20313026541 69529.6933039358 101994.739541171 157691.661793782 138678.426870023 245665.493498679 -380075.066351048 -1120.66372493487
	 137061.09929875 -42458.1859678265 224168.08121998 -40973.8554659799 250196.718284067 379276.206247946 649234.270408174 51348.5478827761 649930.576096602 -478.58991163833 -354277.845876142 -12640.5176416819
	 460982.318350704 -702303.510511447 -380731.853306592 -161168.181159652 182062.110097471,
	-11867.9643864095 -73555.9400582417 44829.095432888 -5515.81785946496 26836.2295260991 62924.9851437864 69046.7654037879 12492.241801066 -27786.4156122985 56008.1375325309 -240357.104897793 102164.924367542
	 1045.28185797764 -116704.625494887 70717.932419693 -122551.533878534 -38522.7244573317 145203.191158008 460477.669030848 92444.3078237512 -111.688140239073 259521.014966705 -374988.746836906 19865.4352206417
	 160067.381337892 -72144.5473868249 -404061.725662878 188286.77645774 169179.158303191 -49931.8685904874 51348.5478827761 415228.073394514 -103392.240184173 188593.107543597 498749.06587884 12084.4692414153
	 131673.429448475 629.651898079479 180888.385819716 -98196.3821836459 -174980.330280915,
	40345.8351231146 -36317.528293998 48442.2230261357 -41479.9072411565 62055.0756116863 -119309.082093547 30601.665427581 6428.9338344435 134293.949967283 -13995.1688546398 -126382.946082218 -84504.1113574487
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	 130063.44980635 -256968.883032802 480723.317335154 80792.5753036371 159712.204147679 730496.772186366 649930.576096602 -103392.240184173 1275713.0835982 27819.1814153934 -767980.716339401 101839.739974206
	 644047.708303509 -1276848.63530193 -709019.709937694 148493.491369715 521554.921063346,
	12226.3384454486 20575.5955307266 -2254.20096007291 -53430.0355096285 59551.6622307286 -54152.2977955069 -72895.5417220747 69768.7875318055 293.533777731769 -243263.402148913 -78714.2992895618 -49375.7991850539
	 10467.3205048483 -23287.4555040391 205362.148200405 119394.423188617 -59298.9122206204 97545.9851725886 -112554.758366542 2441.23358709145 -163559.249822191 -204038.976066058 -63926.325994864 227719.460960609
	 -82051.8914581203 -404336.270357351 -145507.030460319 301352.080513587 -238838.649216824 236993.374488006 -478.58991163833 188593.107543597 27819.1814153934 667218.623240433 -2850.11359162784 34769.1632928259
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	 295926.800491872 250577.312059419 -1045557.43437234 149871.335466636 196143.692278739 -615755.137282739 -354277.845876142 498749.06587884 -767980.716339401 -2850.11359162784 1749807.83265757 27427.774555554
	 -462847.141288901 640270.681996347 809547.393682816 -471940.228749076 -448333.110933803,
	847.283701745286 -9662.15267213998 335.41876467179 -6424.22105550048 7904.4992391105 7567.70948734359 29564.8763465651 -11919.1375071455 4165.24939910597 21057.6450225746 -70589.2361523178 37802.8890526653
	 24638.8297893745 39946.497781725 7462.16438438701 -86353.224389323 21403.3687696025 47025.0486400196 45066.7507988004 77527.6691062672 43258.4846061141 10809.7516837187 -20077.0632483233 -80266.7324573465
	 51992.3260157594 -63721.5136444749 -60565.3411961645 86201.759288784 -52220.9772934653 108144.110775694 -12640.5176416819 12084.4692414153 101839.739974206 34769.1632928259 27427.774555554 231857.481352237
	 -14960.4353926716 -263615.731357789 -6997.10903421753 -42087.6092462894 -6525.80428887192,
	15980.3654803886 -49247.709313424 39675.0072593112 -35796.3715890822 29587.2322448506 -43615.3053039962 62224.5986966587 1926.71978217382 47480.4851126091 -32426.3066735589 -197636.940658649 -12596.1777999803
	 38042.7494188025 -79809.5476062574 227814.029007398 -94776.3940067102 -18493.8490060449 161816.192954835 145851.886582203 155045.229254885 51213.2300333214 86310.9589363024 -455738.83785923 244742.125371673
	 86297.8600886723 -67803.7066640835 232430.571725483 59271.3059609286 271180.018234835 490651.62019345 460982.318350704 131673.429448475 644047.708303509 96396.5829943174 -462847.141288901 -14960.4353926716
	 738821.254136548 -697397.283531303 -387227.880938488 8274.19270718297 256798.645664887,
	-36309.4774273026 104706.530539394 -41725.9767025198 65568.6445473614 -89381.9825625779 85884.3944821507 -72586.8826980942 6883.35900550112 -116044.025699381 -84469.4984295871 308933.555670821 -16791.0396341537
	 -196993.045212893 -9625.49941678588 -383892.766013801 237001.364198648 -54399.3880753108 -166691.805593687 -99326.643482944 -365558.289196087 -349200.269406541 -159933.002997483 463246.988831203 -2354.42477374427
	 -286785.398546624 318460.476829406 -314737.256977856 -262726.79573194 -251724.860931129 -890769.58941863 -702303.510511447 629.651898079479 -1276848.63530193 -51752.0819656714 640270.681996347 -263615.731357789
	 -697397.283531303 1874010.8858336 710591.163738764 225388.783321639 -493681.833118558,
	-29324.805454882 -14978.6980251585 -21167.1411996822 24584.1317013674 -13550.9073462976 90901.3909150182 -1187.77728098439 11877.6734369002 -97477.7493648616 45223.6492126256 -31563.4414775375 103324.855484454
	 -83288.3906521514 -9152.92578552919 -164830.285301391 44962.3712919742 -24737.6858049176 -32117.3613160426 289255.147179112 -89154.3591713677 -100649.234567902 126978.877172397 118828.039751544 -75655.5857444451
	 70333.1015677741 121945.381812161 -538757.944966084 30902.6175618514 -31332.8977794001 -492187.982815701 -380731.853306592 180888.385819716 -709019.709937694 96662.3597184524 809547.393682816 -6997.10903421753
	 -387227.880938488 710591.163738764 674038.505756267 -176697.251271489 -305678.262511085,
	20150.875030273 86376.7001672422 7312.51072319821 9592.48762043376 12752.5761172273 -103801.931973262 -152146.525946182 53466.9681864742 45348.9996440982 -253461.797083968 225525.924408146 -185815.840589197
	 -7356.45801494013 103531.814160703 56162.8770658167 285831.005533978 -27385.9723114369 -7746.79675502524 -508419.57368512 -143385.73603276 -83475.1013357013 -520062.26000029 275901.50667633 374271.296069063
	 -270073.981996542 -390297.019517802 208322.318920964 81501.1106298262 -298995.667067915 143840.275530104 -161168.181159652 -98196.3821836459 148493.491369715 290602.075034988 -471940.228749076 -42087.6092462894
	 8274.19270718297 225388.783321639 -176697.251271489 883776.893252824 28917.7383181504,
	19724.6246763757 4600.6701184436 14663.7312967715 -3098.16936617085 23268.1622417002 -77063.4537129329 -17281.6409378042 -8.69821403989151 68754.6748258838 13506.7051352843 -1245.25584882416 -58748.9659252919
	 73936.4255983324 55011.4447256852 94135.3338979634 11690.4169069828 35827.9813694272 -24576.5321397059 -82103.8995557856 27202.2967489454 172411.024631069 -58076.4582442661 1008.9892660667 131982.352612291
	 50486.7822253027 -105566.10206188 237095.838107127 -28151.5822039158 126455.596863313 292383.173644154 182062.110097471 -174980.330280915 521554.921063346 -130736.967383112 -448333.110933803 -6525.80428887192
	 256798.645664887 -493681.833118558 -305678.262511085 28917.7383181504 530678.752018861]
"""
, (placeholder_Matrix(placeholder_List(indata['siny 1'], indata['cosx 2'], indata['sinx 2'], indata['cosy 2'], indata['siny 2'], indata['cosx 3'], indata['sinx 3'], indata['cosy 3'], indata['siny 3'], indata['cosx 4'], indata['sinx 4'], indata['cosy 4'], indata['siny 4'], indata['cosx 5'], indata['sinx 5'], indata['cosy 5'], indata['siny 5'], indata['cosx 6'], indata['sinx 6'], indata['cosy 6'], indata['siny 6'], indata['cosx 7'], indata['sinx 7'], indata['cosy 7'], indata['siny 7'], indata['cosx 8'], indata['sinx 8'], indata['cosy 8'], indata['siny 8'], indata['cosx 9'], indata['sinx 9'], indata['cosy 9'], indata['siny 9'], indata['cosx 10'], indata['sinx 10'], indata['cosy 10'], indata['siny 10'], indata['cosx 11'], indata['sinx 11'], indata['cosy 11'], indata['siny 11'])) - """
[-0.82362227027027, -0.00180719567567568, -0.00322261508108108, 0.000165569486486487, 0.00312910170270271, 0.0319072227027027, -0.00271743421621622, -0.00110696297297297, -0.0217278083964865, 0.000666033135135135
	, -0.00171761767567568, -0.00260860108108108, -0.00125872740540541, 0.00768729524324324, -0.000440350864864864, -0.00218607478378378, -0.00253213940540541, 0.000886425513513514, -0.000422598540540541, -0.00139670923648649
	, 0.000854998162162162, 0.00329187556756757, -0.000104621818918919, 0.000738066535135135, -0.00330624217567568, 0.000439376162162162, 0.000433695324324325, 0.000582144586486487, -0.000357406405405406, 0.000789170973783784
	, 0.000416542810810811, 0.00115090678378378, -0.000520458108108108, 0.000385679540540541, -0.000112824327027027, 0.000281507618918919, 0.000103902283783784, 0.000433307108108108, -0.000351023991891892, -0.000143763172972973
	, 0.000346124321621622]
"""
)) + -425.642694239497

    SqDist_Io_Patera_ = placeholder_Vec_Quadratic("""
[	882.390283688564 477.215016725583 43.9916929238605 -487.606975788395 426.830241825454 -1930.09581547517 725.484274227374 162.111116945249 2527.25840122792 -1360.75897956499 -321.160285543767 -995.728334896864
	 1105.2045173345 -1557.83822233891 520.532439344714 -785.766523514433 2414.7527760276 1228.09605588111 287.423220983003 -1893.71659769663 597.636822101033 -757.530418974229 -1638.41669771748 -213.78415077169
	 1922.28958896896 -637.766836291818 -2382.81249712193 -1295.98487175117 2708.47010014075 1139.61493319809 1313.63788782589 -251.215795894813 1703.07695369349 -32.4506319343914 663.69617068433 -2245.52126948458
	 1597.82807153357 -3311.05200309589 -168.296872457201 123.742359338332 -312.801462925531,
	477.215016725583 9495.42657838523 -1071.27692258704 27.0907880011791 1299.38542897754 -1560.20583625953 2016.20801302361 763.312499043437 1439.76763139154 -7986.55125111627 -1770.01290386542 2048.83427438478
	 7638.35129447827 -1756.02712340214 -2472.9475051125 -759.338659088856 2291.71062888031 -4437.94283422547 3669.82953185987 -473.331634612876 1256.88708754062 -1078.70117590478 1694.4546475115 4089.86578669347
	 290.005936202973 1554.10018288338 -11315.930930237 3960.82281197632 4512.47431962051 8589.4230619568 4215.80296808445 -3660.03045834497 6153.54193029993 1592.00949114198 9354.99239918965 6745.83289579847
	 5044.59354631899 -9915.35128716381 -6929.0995950561 -4736.47095941924 8850.31013177797,
	43.9916929238605 -1071.27692258704 4852.72962961613 -1113.42485126085 352.721533113572 -91.9699638181109 -139.98120871855 -300.591962903302 577.461689147604 1604.139052558 -4038.93120247975 -4847.6649531186
	 1100.7230082529 -1571.75578900626 -225.098439832291 -1733.52822834779 -1493.78529076614 -2698.65569048509 -1235.18370643042 -3420.50215220625 2121.58950120685 1527.05227506668 297.66063951188 313.032015691003
	 -2551.78133798829 -2880.46703833343 1278.49768035705 -4052.10117563741 2080.44684586302 -249.314933387125 -3069.36563327274 2728.734562208 969.658100153694 2470.38881943628 -5179.68809777289 -2507.19032153271
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	 -159.549584840225 1699.0352476208 -155.346080889505 4264.44234706268 -785.710578389763 1732.2995091074 1111.2209226797 4190.79913137108 1713.37730424828 -851.215421090419 2928.38507123826 3814.69436626415
	 -727.471635207205 -2051.55718212607 -422.53795653578 3769.79886138347 -2112.23843460405 -3002.78044482234 -2420.15236965392 3447.63169568817 -1154.03920706582 -2766.52627140932 7744.7824452253 3711.59666491437
	 -568.767264471519 9375.31950785803 3372.87089686161 2358.62583830168 -998.45016619085,
	426.830241825454 1299.38542897754 352.721533113572 -133.854998941525 4593.31738444177 1109.78428896078 589.825569037268 -1526.1403412732 2590.56374407987 -3064.33551341609 -1327.71501511086 179.038196348249
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	 29381.6222128898 -13716.4715858556 -17260.0405066477 -16194.2960851561 22560.1109928813 -7215.7114896834 -2276.54000190015 -618.647142633122 26736.9704701732 11679.9065595006 -17017.3719137847 12875.8553474928
	 24782.0968750681 26760.8990680851 18096.9760532985 13520.6034384149 56656.3975225026 112832.820738998 19298.10444974 -8830.88861604622 96519.2275777004 -57795.5676878502 -33324.2510860604 23054.9804323627
	 68193.9614580665 -105645.901672266 19146.7783683523 -51054.1167623334 232386.229167606]
"""
, (placeholder_Matrix(placeholder_List(indata['siny 1'], indata['cosx 2'], indata['sinx 2'], indata['cosy 2'], indata['siny 2'], indata['cosx 3'], indata['sinx 3'], indata['cosy 3'], indata['siny 3'], indata['cosx 4'], indata['sinx 4'], indata['cosy 4'], indata['siny 4'], indata['cosx 5'], indata['sinx 5'], indata['cosy 5'], indata['siny 5'], indata['cosx 6'], indata['sinx 6'], indata['cosy 6'], indata['siny 6'], indata['cosx 7'], indata['sinx 7'], indata['cosy 7'], indata['siny 7'], indata['cosx 8'], indata['sinx 8'], indata['cosy 8'], indata['siny 8'], indata['cosx 9'], indata['sinx 9'], indata['cosy 9'], indata['siny 9'], indata['cosx 10'], indata['sinx 10'], indata['cosy 10'], indata['siny 10'], indata['cosx 11'], indata['sinx 11'], indata['cosy 11'], indata['siny 11'])) - """
[-0.732483012987013, -0.00195957101298701, -0.00563664053928572, 0.0116471565850649, -0.00809235887012987, 0.0422766338961039, -0.00184994231558442, -0.000372163837662338, -0.0425562291558441, -0.00189569357792208
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	, 0.000233672727272727, -0.000205639303896104, 0.00002714714537013, 0.0000632502175324676, 0.0000560057616883117, 0.00054231489935065, 0.000271358872727273, 0.000246427507487013, -0.000222587856493506, 0.000195539427272727
	, -0.000133439277922078, 0.000199271775324675]
"""
)) + -408.294484386449

    SqDist_Lunar_Impact_Crater_ = placeholder_Vec_Quadratic("""
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	 -20032.1600626272 -1489741.00246032 -229058.789626013 -60308.093837863 1982965.29463707]
"""
, (placeholder_Matrix(placeholder_List(indata['siny 1'], indata['cosx 2'], indata['sinx 2'], indata['cosy 2'], indata['siny 2'], indata['cosx 3'], indata['sinx 3'], indata['cosy 3'], indata['siny 3'], indata['cosx 4'], indata['sinx 4'], indata['cosy 4'], indata['siny 4'], indata['cosx 5'], indata['sinx 5'], indata['cosy 5'], indata['siny 5'], indata['cosx 6'], indata['sinx 6'], indata['cosy 6'], indata['siny 6'], indata['cosx 7'], indata['sinx 7'], indata['cosy 7'], indata['siny 7'], indata['cosx 8'], indata['sinx 8'], indata['cosy 8'], indata['siny 8'], indata['cosx 9'], indata['sinx 9'], indata['cosy 9'], indata['siny 9'], indata['cosx 10'], indata['sinx 10'], indata['cosy 10'], indata['siny 10'], indata['cosx 11'], indata['sinx 11'], indata['cosy 11'], indata['siny 11'])) - """
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	, 0.000143012487581699, -0.0000527462432026143, 0.000066368418627451, -0.000230854256993464]
"""
)) + -491.823360509978

    SqDist_Martian_Caldera_ = placeholder_Vec_Quadratic("""
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	 66727.1481840666 -20383.6506864314 170656.257328082 -2610.68255112341 -58522.1897461315 -325407.218683854 51941.6604988107 162139.69347176 -61012.3355936477 -79091.2891885751 -408706.783271222 345100.679463607
	 41917.9180049783 1080902.49972583 163982.749461612 381676.753055382 401950.830802598 -94216.6761402745 838698.381206232 -117864.80189484 31592.6877354031 -75994.2747222566 236336.674143276 809057.385688389
	 1380125.69107842 479489.064878248 204053.771767203 33823.4820737728 381594.087875095,
	-2161.89424863369 -21284.3515702027 -80914.4379317126 -20536.5546536404 8600.48046483938 36342.482818885 8489.63888253195 105178.998202453 -21573.6086767188 106846.285480943 -29638.51635002 37180.0976124836
	 15803.2851725276 -47250.4145736541 47390.8989569492 -7838.28228993608 48677.931288808 633.231080087488 -44380.1076393288 9430.75018960447 4965.8643113511 -274927.736128089 -76843.3060787114 318483.199577826
	 -196344.168116005 -95461.0504233443 14293.2557970837 87995.2632871979 55813.523825487 -237737.834535595 2576.09267674892 -129387.752756472 -257530.11508715 62727.9432344085 -330383.049501495 358978.794598747
	 479489.064878248 966963.278607678 291346.542685696 65674.1089069312 -69902.6092387882,
	1096.45357869053 -1345.04309617817 -27875.6283413534 -72.1786761586734 -3913.27780808969 26254.4347460863 -2169.65782696037 21429.7534035898 -2015.61202710996 95908.1759264965 13146.7351297313 -4325.40535310648
	 36398.1127284865 -7929.13618359894 -39438.6997305786 -28502.6571702272 70296.797010183 -51491.2750664938 -27251.2684676563 -38701.0053058776 -1866.24385484363 -129027.714162896 -143591.78227744 164715.116055015
	 -141734.906396427 -10623.4128594612 8909.58353155752 28395.1140455423 -62294.9804098305 38876.165648755 -181515.753346104 75251.6586567567 -147176.738994376 196831.079540633 -36343.5729803995 170225.768963603
	 204053.771767203 291346.542685696 535406.910022764 223255.95095784 23696.0730940998,
	-4315.23631366384 -24161.5789121783 19669.2990064963 27740.0539942909 -22035.5943739107 18840.8483859722 -17338.3132168235 18342.8176564307 21244.4105142704 151751.922737494 -2685.25076594987 -24711.451025209
	 49703.4837370894 34183.5214273081 -47604.194292396 124049.063564684 97597.5557794207 -148864.679037879 -85684.5836942713 -42858.5769567575 35965.5241264518 -236371.927669843 -187035.801355652 105271.525805627
	 -113599.539709503 13034.2524714239 -85124.3803219802 -7532.03664623398 -135769.702393434 78010.4333942134 -372881.843625009 459999.431719372 -279539.394554388 177958.163574634 -96786.7289574992 149557.274830877
	 33823.4820737728 65674.1089069312 223255.95095784 767666.806805352 -32369.7335856946,
	1776.76430300505 -6979.1630437667 -6861.89457595565 -2689.09143535965 17217.9440185257 -16153.3699131271 3409.82368880899 31082.0129842535 -11792.5688281153 -9905.92491870065 -13402.9532345733 25583.4512751478
	 -3438.33205112777 -28440.8051850943 78819.3974907477 -64447.2729258949 -81051.4786632485 -100783.340312085 104786.644466374 64919.6545722302 -15564.5412695499 149381.27321686 -76675.2432534653 -19791.6959058307
	 74880.1783596436 447674.120347404 37613.6681022477 113628.00081243 156253.857641503 56780.5335768229 348415.401086554 -110830.00013802 228950.158533177 -72816.1420063055 172085.168195919 242953.114656294
	 381594.087875095 -69902.6092387882 23696.0730940998 -32369.7335856946 340811.97007268]
"""
, (placeholder_Matrix(placeholder_List(indata['siny 1'], indata['cosx 2'], indata['sinx 2'], indata['cosy 2'], indata['siny 2'], indata['cosx 3'], indata['sinx 3'], indata['cosy 3'], indata['siny 3'], indata['cosx 4'], indata['sinx 4'], indata['cosy 4'], indata['siny 4'], indata['cosx 5'], indata['sinx 5'], indata['cosy 5'], indata['siny 5'], indata['cosx 6'], indata['sinx 6'], indata['cosy 6'], indata['siny 6'], indata['cosx 7'], indata['sinx 7'], indata['cosy 7'], indata['siny 7'], indata['cosx 8'], indata['sinx 8'], indata['cosy 8'], indata['siny 8'], indata['cosx 9'], indata['sinx 9'], indata['cosy 9'], indata['siny 9'], indata['cosx 10'], indata['sinx 10'], indata['cosy 10'], indata['siny 10'], indata['cosx 11'], indata['sinx 11'], indata['cosy 11'], indata['siny 11'])) - """
[-0.867988419354839, -0.00176070883870968, -0.000777676225806453, -0.000126754516129031, -0.00141140806451613, 0.0238110822580645, 0.000905635612903226, -0.00374933209677419, -0.0208806961290323, -0.00101861903225806
	, -0.0000240449677419354, 0.0000661158516129026, 0.000196959451612902, 0.00159653993548387, 0.0012283464516129, 0.00278650377419355, -0.00260049570967742, -0.00103042780645161, 0.0000926208709677421, 0.000699005806451613
	, 0.000389492967741935, -0.00123956939677419, 0.00169688941935484, -0.00184529774193548, -0.00070859, -0.00110065318387097, 0.000115045161290323, -0.00114691541935484, -0.00228352416129032, -0.000254185193548387
	, 0.000573568967741936, 0.000580014703225807, 0.00042068, -0.00105904861290323, 0.000608956551612903, 0.000838163612903226, 0.000755284290322581, 0.000370447774193548, -0.000220430835483871, 0.000180732277419355
	, -0.0000710762419354838]
"""
)) + -407.949033120277

    _temp0 += jmp.exp((0.5 * SqDist_Ash_Flow_ + -0.5 * SqDist_Basaltic_Shield_))
    _temp0 += jmp.exp((0.5 * SqDist_Ash_Flow_ + -0.5 * SqDist_Io_Patera_))
    _temp0 += jmp.exp((0.5 * SqDist_Ash_Flow_ + -0.5 * SqDist_Lunar_Impact_Crater_))
    _temp0 += jmp.exp((0.5 * SqDist_Ash_Flow_ + -0.5 * SqDist_Martian_Caldera_))
    outdata['Prob[Ash-Flow]'] = 1 / _temp0

    _temp1 += jmp.exp((-0.5 * SqDist_Ash_Flow_ + 0.5 * SqDist_Basaltic_Shield_))
    _temp1 += jmp.exp((0.5 * SqDist_Basaltic_Shield_ + -0.5 * SqDist_Io_Patera_))
    _temp1 += jmp.exp((0.5 * SqDist_Basaltic_Shield_ + -0.5 * SqDist_Lunar_Impact_Crater_))
    _temp1 += jmp.exp((0.5 * SqDist_Basaltic_Shield_ + -0.5 * SqDist_Martian_Caldera_))
    outdata['Prob[Basaltic Shield]'] = 1 / _temp1

    _temp2 += jmp.exp((-0.5 * SqDist_Ash_Flow_ + 0.5 * SqDist_Io_Patera_))
    _temp2 += jmp.exp((-0.5 * SqDist_Basaltic_Shield_ + 0.5 * SqDist_Io_Patera_))
    _temp2 += jmp.exp((0.5 * SqDist_Io_Patera_ + -0.5 * SqDist_Lunar_Impact_Crater_))
    _temp2 += jmp.exp((0.5 * SqDist_Io_Patera_ + -0.5 * SqDist_Martian_Caldera_))
    outdata['Prob[Io Patera]'] = 1 / _temp2

    _temp3 += jmp.exp((-0.5 * SqDist_Ash_Flow_ + 0.5 * SqDist_Lunar_Impact_Crater_))
    _temp3 += jmp.exp((-0.5 * SqDist_Basaltic_Shield_ + 0.5 * SqDist_Lunar_Impact_Crater_))
    _temp3 += jmp.exp((-0.5 * SqDist_Io_Patera_ + 0.5 * SqDist_Lunar_Impact_Crater_))
    _temp3 += jmp.exp((0.5 * SqDist_Lunar_Impact_Crater_ + -0.5 * SqDist_Martian_Caldera_))
    outdata['Prob[Lunar Impact Crater]'] = 1 / _temp3

    _temp4 += jmp.exp((-0.5 * SqDist_Ash_Flow_ + 0.5 * SqDist_Martian_Caldera_))
    _temp4 += jmp.exp((-0.5 * SqDist_Basaltic_Shield_ + 0.5 * SqDist_Martian_Caldera_))
    _temp4 += jmp.exp((-0.5 * SqDist_Io_Patera_ + 0.5 * SqDist_Martian_Caldera_))
    _temp4 += jmp.exp((-0.5 * SqDist_Lunar_Impact_Crater_ + 0.5 * SqDist_Martian_Caldera_))
    outdata['Prob[Martian Caldera]'] = 1 / _temp4

    _temp6[0] = outdata['Prob[Ash-Flow]']
    _temp6[1] = outdata['Prob[Basaltic Shield]']
    _temp6[2] = outdata['Prob[Io Patera]']
    _temp6[3] = outdata['Prob[Lunar Impact Crater]']
    _temp6[4] = outdata['Prob[Martian Caldera]']
    _temp5 = jmp.max_array(5, _temp6)
    if (_temp5 == 0):
        _temp7 = "Ash-Flow"
    elif (_temp5 == 1):
        _temp7 = "Basaltic Shield"
    elif (_temp5 == 2):
        _temp7 = "Io Patera"
    elif (_temp5 == 3):
        _temp7 = "Lunar Impact Crater"
    elif (_temp5 == 4):
        _temp7 = "Martian Caldera"
    else:
        _temp7 = ""
    outdata['Pred Group'] = _temp7

    return outdata['Pred Group']

1 ACCEPTED SOLUTION

Accepted Solutions
tjs

New Contributor

Joined:

Jul 22, 2017

Solution

I figured it out, you can do it all in Python with numpy/numpy.linalg. It's just going to take a while to work through the whole script. It's odd that the python code output assumes the user doesn't have numpy dependency. I'm unsure what you could even do with the output in python without numpy or some other assumed equivalent, but I guess that's a proprietary attempt at open-source.

Thanks anyway!

-tjs

 

If anyone sees this post with the same problem and wants to know the workarounds, message me!

3 REPLIES
markbailey

Staff

Joined:

Jun 23, 2011

There are several sources of the answer to your question, "What does the dialog mean by "Vec Quadratic"?" I used Help > Books > Scripting Guide. There I found this explanation:

Untitled.jpeg

This function is unique to JMP and is used for efficiency. It returns quantities that are used in the computation of the conditional standard errors.

I don't think that you did anything wrong but the mechanism of publishing this formula doesn't not include the conversion of Vec Quadratic() to simpler forms that are available in Python. You could try replacing this function with other equivalent but less efficient functions that are translatable.

Learn it once, use it forever!
tjs

New Contributor

Joined:

Jul 22, 2017

Solution

I figured it out, you can do it all in Python with numpy/numpy.linalg. It's just going to take a while to work through the whole script. It's odd that the python code output assumes the user doesn't have numpy dependency. I'm unsure what you could even do with the output in python without numpy or some other assumed equivalent, but I guess that's a proprietary attempt at open-source.

Thanks anyway!

-tjs

 

If anyone sees this post with the same problem and wants to know the workarounds, message me!

nascif_jmp

Staff

Joined:

Jul 30, 2015

Hi @tjs,

 

Sorry for the inconvenience. This was indeed an attempt; our first pass at producing equivalent code for JMP models not just for Python but also for C and JavaScript. In our first pass, we focused on models that used only primitive operations that required no external libraries. At the same time, we wanted to help customers that were manually translating models (sometimes very large ones) from JSL to their target deployment languages. Therefore the compromise of still generating code with placeholders for unsupported operations. Given that you were eventually able to convert your model, I think it was the right decision given our constraints.

 

JMP supports a rich set of models, which make use of a very large set of operators. It will be an ongoing effort on our part to translate them all for all the target languages. We also want to be careful when introducing dependencies on external libraries as they add complexity to the model deployment. 

 

Your feedback helps us to prioritize our efforts and fine-tune our roadmap. Thanks for sharing it and for offering to help the community!