On 08/06/2012 10:27 AM, Janusz Michalik wrote:
Hi Hal. I'm trying to use this filter that you attached but I get errors. This
is what I'm doing and I'm not sure what is wrong:
1) Take the GradientOfUnstructuredData in the Paraview filters which gives me
the velocity tensor with components numbered from 0 to 8.
2) I modified your tensor components matrix to have
tensor_components = [
'G_0', 'G_1', 'G_2',
'G_3', 'G_4', 'G_5',
'G_6', 'G_7', 'G_8']
where G is the result array name obtained from the Gradient Filter.
3) I run the your eig filter but I get errors:
My input was six separate one-component scalar arrays. If you have a
nine-component array, we can deal with that slightly differently:
input_array = numpy.array(pd['G'])
N = input_array.shape[0]
assert (input_array.shape[1] == 9)
Tensors = input_array.reshape((N,3,3))
eigenvalues = numpy.empty((N,3), dtype=numpy.float32)
eigenvectors = numpy.empty((N,3,3), dtype=numpy.float32)
for i in xrange(N):
eigenvalues[i,:], eigenvectors[i,:,:] = (
numpy.linalg.eig(Tensors[i,:,:]))
for i in xrange(3):
pd.AddArray(
paraview.vtk.dataset_adapter.numpyTovtkDataArray(
eigenvalues[:,i],
name=('EigVal_%d' % (i+1))))
pd.AddArray(
paraview.vtk.dataset_adapter.numpyTovtkDataArray(
eigenvectors[:,:,i],
name=('EigVec_%d' % (i+1))))
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