Python equivalent of Wolfram Language ParametricPlot3D?












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The Wolfram Language as a ParametricPlot3D that can be used to interactively examine parametric functions in 3D. I have several series of data that I would like to represent as categorical curves in an interactive 3D plot.



As a minimal example on a set of 10 series with 20 observations in each, in Wolfram Language I can



SeedRandom[987]
obs = RandomVariate[StudentTDistribution[3, 1, 5], {10, 20}];
foos = PDF@*SmoothKernelDistribution /@ obs;

ParametricPlot3D[
MapIndexed[{First@#2, u, v #1[u]} &]@foos, {u, -5, 10}, {v, 0, 1},
BoxRatios -> {5, 1, 1},
PlotRange -> Full,
ColorFunction -> ColorData["SunsetColors"],
Background -> Lighter@Purple,
AxesStyle -> White,
TicksStyle -> White,
Boxed -> False,
AxesEdge -> {{0, 0}, {1, 0}, {1, 1}},
ViewPoint -> {3, -2, 1.5},
ImageSize -> Large,
Mesh -> None,
PlotLegends -> Automatic,
PlotPoints -> {80, 15},
Ticks -> {{#, IntegerName@#} & /@ Range@10, Automatic, Automatic}]



enter image description here




How is this done with JSON in Python?









share









$endgroup$

















    0












    $begingroup$


    The Wolfram Language as a ParametricPlot3D that can be used to interactively examine parametric functions in 3D. I have several series of data that I would like to represent as categorical curves in an interactive 3D plot.



    As a minimal example on a set of 10 series with 20 observations in each, in Wolfram Language I can



    SeedRandom[987]
    obs = RandomVariate[StudentTDistribution[3, 1, 5], {10, 20}];
    foos = PDF@*SmoothKernelDistribution /@ obs;

    ParametricPlot3D[
    MapIndexed[{First@#2, u, v #1[u]} &]@foos, {u, -5, 10}, {v, 0, 1},
    BoxRatios -> {5, 1, 1},
    PlotRange -> Full,
    ColorFunction -> ColorData["SunsetColors"],
    Background -> Lighter@Purple,
    AxesStyle -> White,
    TicksStyle -> White,
    Boxed -> False,
    AxesEdge -> {{0, 0}, {1, 0}, {1, 1}},
    ViewPoint -> {3, -2, 1.5},
    ImageSize -> Large,
    Mesh -> None,
    PlotLegends -> Automatic,
    PlotPoints -> {80, 15},
    Ticks -> {{#, IntegerName@#} & /@ Range@10, Automatic, Automatic}]



    enter image description here




    How is this done with JSON in Python?









    share









    $endgroup$















      0












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      0





      $begingroup$


      The Wolfram Language as a ParametricPlot3D that can be used to interactively examine parametric functions in 3D. I have several series of data that I would like to represent as categorical curves in an interactive 3D plot.



      As a minimal example on a set of 10 series with 20 observations in each, in Wolfram Language I can



      SeedRandom[987]
      obs = RandomVariate[StudentTDistribution[3, 1, 5], {10, 20}];
      foos = PDF@*SmoothKernelDistribution /@ obs;

      ParametricPlot3D[
      MapIndexed[{First@#2, u, v #1[u]} &]@foos, {u, -5, 10}, {v, 0, 1},
      BoxRatios -> {5, 1, 1},
      PlotRange -> Full,
      ColorFunction -> ColorData["SunsetColors"],
      Background -> Lighter@Purple,
      AxesStyle -> White,
      TicksStyle -> White,
      Boxed -> False,
      AxesEdge -> {{0, 0}, {1, 0}, {1, 1}},
      ViewPoint -> {3, -2, 1.5},
      ImageSize -> Large,
      Mesh -> None,
      PlotLegends -> Automatic,
      PlotPoints -> {80, 15},
      Ticks -> {{#, IntegerName@#} & /@ Range@10, Automatic, Automatic}]



      enter image description here




      How is this done with JSON in Python?









      share









      $endgroup$




      The Wolfram Language as a ParametricPlot3D that can be used to interactively examine parametric functions in 3D. I have several series of data that I would like to represent as categorical curves in an interactive 3D plot.



      As a minimal example on a set of 10 series with 20 observations in each, in Wolfram Language I can



      SeedRandom[987]
      obs = RandomVariate[StudentTDistribution[3, 1, 5], {10, 20}];
      foos = PDF@*SmoothKernelDistribution /@ obs;

      ParametricPlot3D[
      MapIndexed[{First@#2, u, v #1[u]} &]@foos, {u, -5, 10}, {v, 0, 1},
      BoxRatios -> {5, 1, 1},
      PlotRange -> Full,
      ColorFunction -> ColorData["SunsetColors"],
      Background -> Lighter@Purple,
      AxesStyle -> White,
      TicksStyle -> White,
      Boxed -> False,
      AxesEdge -> {{0, 0}, {1, 0}, {1, 1}},
      ViewPoint -> {3, -2, 1.5},
      ImageSize -> Large,
      Mesh -> None,
      PlotLegends -> Automatic,
      PlotPoints -> {80, 15},
      Ticks -> {{#, IntegerName@#} & /@ Range@10, Automatic, Automatic}]



      enter image description here




      How is this done with JSON in Python?







      visualization matplotlib wolfram-language





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      asked 5 mins ago









      EdmundEdmund

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