[Paraview] ParaView numpy interface question

[Dean, Kevin]

Hey all,

I have a quick question about setting scalar values with the python macro
inside paraview.

So I have two images that I want to do scalar manipulation with.

*example code:*

from paraview import simple

from vtk.util import numpy_support as npvtk


import vtk.numpy_interface.dataset_adapter as dsa
import pandas as pd

import vtk


scaling_vti = simple.XMLImageDataReader(FileName=[scaling_filename])

scaling_rawData = simple.servermanager.Fetch(scaling_vti)

scaling_data = dsa.WrapDataObject(scaling_rawData)

scaling_array =
pd.DataFrame(npvtk.vtk_to_numpy(data.GetPointData().GetScalars()),
columns=
['scaling_error'])

humans_vti = simple.FindSource(humans_filename)
humans_vti.PointArrayStatus = ['Scattering Density']
humans_rawData = simple.servermanager.Fetch(humans_vti)
humans_data = dsa.WrapDataObject(humans_rawData)
humans_array = pd.DataFrame(npvtk.vtk_to_numpy(humans_data.GetPointData().GetScalars()),
columns=['scalar_intensity'])

new_scalars = pd.DataFrame(humans_array.scalar_intensity * scaling_array.
scaling_error)

data.GetPointData().SetScalars(npvtk.numpy_to_vtk(new_scalars))


After I do this, I can bypass the pipeline (because I haven't figure
out how to use it yet) by

writing this image to a new file then load it again to render it.

Is there a way I can set the paraview image with the new scalar values
and have it render without
having to write it to a file first?

Or, is there a way to convert the
vtk.numpy_interface.dataset_adapter.DataSetAttributes type back
to paraview.servermanager.FieldDataInformation?

Thanks,

Kevin E. Dean

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