[Paraview] What is the "numpy way"?

[Cory Quammen]

Hi Adam,

There are some utilities in VTK for converting back and forth from VTK
arrays to numpy arrays. Here is an example of usage from within
pvpython that should work:

>>> import numpy as np
>>> d = np.genfromtxt('/home/cory/sample.csv', skip_header=1, delimiter=',')
>>> d
array([[ 1.,  2.,  3.],
       [ 4.,  5.,  6.],
       [ 7.,  8.,  9.]])
>>> import vtk
>>> import vtk.util.numpy_support as ns
>>> vtk_array = ns.numpy_to_vtk(d, 1, vtk.VTK_FLOAT)
>>> vtk_array
(vtkFloatArray)0x7f76a9b92410
>>> vtk_array.GetNumberOfComponents()
3
>>> vtk_array.GetNumberOfTuples()
3L
>>> vtk_array.GetTuple(0)
(1.0, 2.0, 3.0)

vtk_array is a vtkDoubleArray holding the values in the numpy array d.
The 1 in the second argument means that the data should be deep copied
into the VTK array - this is usually what you want unless you hold a
reference to the numpy array d somewhere else in your code.

I hope that helps.

Best regards,
Cory

On Fri, Jun 19, 2015 at 12:26 PM, Adam Lyon <lyon at fnal.gov> wrote:
> Hi all, I've been debugging a simulation of particle physics experiment -- I
> usually have the program make a csv file of some data to visualize (for
> example, x,y,z,time,Bx,By,Bz) where, e.g., Bx is a component of a magnetic
> field. I can read that file straight into ParaView with its text file
> reader, but I find it more convenient to run the csv file through a python
> script that makes a vtp file and I load that into ParaView. These files tend
> to be big, and having a compressed binary vtp file means that ParaView can
> read it very quickly (e.g. I parse csv file once with my script instead of
> loading it into ParaView to parse each time I open it).
>
> The examples in the documentation show how to use the vtk-numpy interface to
> make a vector of points and "dump" them into a vtkPoints object. For
> example,
>
> d = np.genfromtxt(fname, ...)  # more arguments not shown for brevity
>
> coord = algs.make_vector(d["x"], d["y"], d["z"])
> pts = vtk.vtkPoints()
> pts.SetData(dsa.numpyTovtkDataArray(coord, "Points"))
>
> That looks very nice and must be very efficient.
>
> I don't see an obvious way to do the same thing with point or cell data. So,
> for example, I have...
>
> numPts = pts.GetNumberOfPoints()
> bfield = vtk.vtkFloatArray()
> bfield.SetNumberOfComponents(3)
> bfield.SetNumberOfTuples(numPts)
> bfield.SetName("BField")
>
> for a in xrange(numPts):
>    bfield.InsertTuple(a, [ d["Bx"][a], d["By"][a], d["Bz"][a] ])
>
> polyData.GetPointData().AddArray(bfield)  # polyData is a vtkPolyData object
>
> That loop and explicitly decomposing the "d" array to get at the magnetic
> field components looks "old fashioned" to me.
>
> What would be the "numpy way" to make that work? Thanks! -- Adam
>
> ------
>
> Adam L. Lyon
> Scientist; Associate Division Head for Systems for Scientific Applications
>
> Scientific Computing Division & Muon g-2 Experiment
> Fermi National Accelerator Laboratory
> 630 840 5522 office
> www.fnal.gov
> lyon at fnal.gov
>
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-- 
Cory Quammen
R&D Engineer
Kitware, Inc.