pyVorpal

PyVorpal-1.2.2

  • Uses VorpalDom
  • Extracts all or some blocks which can be plotted
  • Creates a Visit friendly .h5 file
  • There must be a .in file
  • VorpalComposer/VisIt can’t plot meshs with 0 or 1 cells in any dimension (at least on windows). As a workaround these are set to have 2 cells for plotting. It’s better than nothing for now.

With VorpalComposer you can integrate block plotting with the inbuilt visualisation. As the blocks are saved to an .h5 file as a mesh VorpalComposer lists the blocks as mesh’s and is able to plot them.

Plot the blocks as well as the fields in VorpalComposer

If you “Enable VisIt Context Menu” under “Visualisation Options” in Tools/Settings you can right click on the visualization pane and open the visit GUI. This lets you edit the colours and opacity of the plot.

You can run it in one of two ways.

From txpp.py (the preprocessor)

You can run it from within VorpalComposer by editing txpp.py. Ever ytime you press “Save and Process Setup” it will update the blocks file and enable visualisation. To do this change the end of txpp.py to read:

  if options.checkVars:
    VarsPyFileNameString=filename.replace('.pre','Vars.py')
    if os.path.isfile(VarsPyFileNameString): checkVarsPyFile(VarsPyFileNameString,filename)

  from pyvorpal import *
  vFile = VorpalDOM(filename.replace('.pre','.in'))
  extractor = BlockExtractor(vFile)
  extractor.plotNamedBlock('*')
  extractor.close()

#-- entry point
if __name__ == '__main__':
  main()
As Vorpal’s internal python build is quite restricted, if you want to do this you need to install the pyVorpal package and the elementtree package into Vorpal’s python.  Download both pyVorpal and elementtree and extract them. Then from within both package directories run: “/path/to/vorpal/bin/python setup.py install”

From any.py

If you don’t want to edit txpp.py and install packaged into Vorpal’s python  (or can’t)  then you can run it separately using a file that looks like this. You must install pyVorpal into your system python.

  from pyvorpal import *
  vFile = VorpalDOM("yourinfile.in")
  extractor = BlockExtractor(vFile)
  extractor.plotNamedBlock('*')
  extractor.close()

 

Leave a Reply