Hello,
I have written a python script that loads in an Ensight data file which has multiple solution times associated with it and performs a set of fairly simple operations on it. It is running very slow, and I'm wondering if there are any experts who use Python to control Paraview that could help me to optimize the script. In a nutshell the script does the following. 1.) Go to a timestep 2.) Generate a series of 2D slices in the 3D domain 3.) Compute some values of the solution variables on those slices 4.) Write data to a file 5.) Delete the entire pipeline except the original data 6.) Go back to 1.) This process is painfully slow(2+days just to run the script on a modest size data set). I believe that the script having to delete the pipeline and then re-create it for every timestep is contributing to the slowdown. My trouble is that I do not know how to selectively activate certain elements in the pipeline if I want to extract information from them, so I have to add them sequentially so that the newest one is the active one. The script may also be rendering each step, which is unnecessary for me, but I do not know how to disable that as well. I have attached a copy of the script. I have a minimal working example that contains the data set with only 3 timesteps worth of data. I am even willing to pay $100 for an expert to help me out with this. Thank you, Christopher R. Neal Graduate Student Center for Compressible Multiphase Turbulence Mechanical and Aerospace Engineering Department University of Florida Cell: (863)-697-1958 E-mail: [email protected]
SliceAverages.py
Description: SliceAverages.py
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