[Paraview] Assemble Variables into Tensor

[Utkarsh Ayachit]

Nick,

You can use the *Programmable Filter* instead with something like the
following script as the *Script*:


from paraview.vtk.numpy_interface import dataset_adapter as dsa

import numpy

def make_tensor(xx,yy,zz, xy, yz, xz):

  t = numpy.vstack([xx,yy,zz,xy, yz, xz]).transpose().view(dsa.VTKArray)

  t.DataSet = xx.DataSet

  t.Association = xx.Association

  return t


xx = inputs[0].PointData["sigma_xx"]

yy = inputs[0].PointData["sigma_yy"]

zz = inputs[0].PointData["sigma_zz"]

xy = inputs[0].PointData["sigma_xy"]

yz = inputs[0].PointData["sigma_yz"]

xz = inputs[0].PointData["sigma_xz"]

output.PointData.append(make_tensor(xx,yy,zz,xy,yz,xz), "tensor")


Utkarsh

On Wed, Nov 29, 2017 at 5:01 PM, Nicholas Richmond <
nicholas.richmond at maine.edu> wrote:

> Greetings,
>
> I have a vtk Polygonal Mesh with six separate arrays (sigma_xx, sigma_yy,
> sigma_zz, sigma_xy, sigma_yz, sigma_xz). I'd like to assemble these into a
> tensor so that I may apply the Tensor Glyph filter.
>
> After reading that the paraview.simple.TensorGlyph
> <https://www.paraview.org/ParaView/Doc/Nightly/www/py-doc/paraview.simple.TensorGlyph.html>
>  expects a symmetric tensor with the order XX, YY, ZZ, XY, YZ, XZ, I
> tried to assemble the six separate arrays into a single array with the
> Python Calculator, but have been unsuccessful.
>
> I've tried a variety of approaches, including:
>
> *Expression:* np.array([sigma_xx, sigma_yy, sigma_zz, sigma_xy, sigma_yz,
> sigma_xz])
> *Array Association:* Point Data
>
> I can make a vector of the normal stresses using the "make_vector"
> function from paraview.vtk.numpy_interface.algorithms, but there is no
> "make_tensor" function to assemble both normal and shear stresses into a
> single symmetric tensor.
>
> Any guidance would be most appreciated.
> Many thanks,
> Nick Richmond
>
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