Postprocessing using pythonFlu + Matplotlib +Scipy
 

Hi all,

I would like to try using pythonFlu + Matplotlib + Scipy/Numpy to do some postprocessing.
I'm able to export some data in raw format (x,y,z, field1, field2, ...) on surfaces (patches or plane defined in sampleDict) and read them with a simple python script.

I've got some difficulties to use the Numpy meshgrid and Matplotlib contour in my script even in my mesh is block structured.

I first try to plot a scalar field on a patch. The mesh obtained from blockMesh is structured (in fact block-structured). My major problem is automatically obtain the size of the x (Nx) and y (Ny) data on this particular patche to use meshgrid and contour in my script.

meshgrid(x, y)
For vectors x, y with lengths Nx=len(x) and Ny=len(y), return X, Y
where X and Y are (Ny, Nx) shaped arrays with the elements of x
and y repeated to fill the matrix

Does pythonFlu have some magic tool with it to do those kind of postprocessing ? :D
Did you manage to postprocess your openfoam data only with matplotlib+numpy+scipy ?

Thanks for shearing your experiences.
Cheers ;)

Francois

May I add that I would like to preserve the original mesh structure (near wall refinement, etc ..) over interpolating the data on a new equally spaced grid.

Hi Francois,

Once you can generate the data and import them in Python it should be pretty easy to find out the metrics you are looking for.
Am I wrong? May be you could attach the whole example to demonstrate your point?

pythonFlu is focused completely on OpenFOAM wrapping.
Nevertheless, we could start to develop third-party OpenFOAM related post-processing tools based on Python.
Integration with pythonFlu better be optional, to make this tools valuable by themselves.

Best regards,
Alexey