[Paraview] Newbie question on Python Programmable Filters

Wed Sep 5 16:42:02 EDT 2012

OK, the 30,000 foot view:

I have a time series of about 20 slices (currently) of values of each component (3 components total) of a vector displacement 3d spatial field from an elastic wave propagation simulation. At the moment, I'm simply trying to visualise the vector length to see the propagating phases of the wavefield. Because my upstream codes and scripts only write individual components of the vector field, I need to combine the components and then calculate the vector lengths *somewhere*.  The programmable filter seemed like a good place to try that, since once I am past the learning curve for it, I'll have the full flexibilty of numpy for doing almost anything else I want with these and similar data from my upstream simulation codes.

Now the 10,000 foot view:
I've been trying to simply calculate the sqrt(x*x + y*y + z*z) scalar field (where x, y, and z are the respective components as a function of position)  and let that flow on down the pipeline as a new spatial field to be visualised. I assumed (correctly if I'm interpreting your answer correctly) that if I built the filter to deal with the spatial aspects of the calculation, the time series would be taken care of by paraview iterating over all files pointed to by inputs[0] (a set of files containing timesteps of the x components), inputs[1] (ditto for the y components), and inputs[2] (ditto for the z components).  The set of *.vtu files for each component have filenames specifying component and time step (e.g.: x001, x002, x003, etc., y001, y002, y003, etc., and z001, z002, z003 etc.). 

Now the close-up:
As far as I can tell, after compiling from source from the git "release" branch (on an up-to-date Linux Mint distro -- which tracks Ubuntu Precise), my approach will work for a set of 3 single timestep arrays fed into the "ports" (or whatever paraview's terminology is for the inputs to a filter in the pipeline). In other words, a single timeslice (x001,y001,z001) appears on inputs[0:3] (numpy slice notation) and is processed correctly. (I'll go away and verify that shortly.)  I *think* the "hangs/race-conditions/whatever" start when there are multiple timesteps presented to each input port.  I was unsure whether the 'inputs[0], inputs[1], inputs[2]' syntax needed to be extended to deal with time series as above, and could not find documentation on the inputs[] array after extensive searching -- just a few snippets of example code that were all consistent with paraview dealing with the time series on its own.

I'm inexperienced enough with paraview to not know if I have a conceptual error with the way I'm approaching this problem, or if I have simply stumbled over a bug. That's why I've posted to the mailing list!

As always, your (and the rest of the list's) help is greatly appreciated!

Cheers,
	Frank

On 05/09/2012, at 4:01 PM, Andy Bauer wrote:

> I'm not sure I completely understand about your inputs[0]. As for iterating
> over time with the python programmable filter, inside the filter it will
> only have access to values from a single time step at each invocation of
> RequestData(). You can think of the order of operations if you have 5 time
> steps as:
> 1) iterate over each of the 5 time steps (i.e. load a file and update the
> pipeline with that data set)
> 2) update the python programmable filter output for the current data set
> resulting from the loaded file
> 
> If you want time statistics for your variables I think you probably want to
> use the calculator filter to square the value at each point and then use
> the temporal statistics filter to get an average of those values. After
> that you can just multiply the results by the number of time steps.
> 
> If I'm misunderstanding what you're trying to do, I'd suggest giving a
> description of what you're trying to do and maybe there's a simpler way of
> doing it.
> 
> Andy
> 
> On Wed, Sep 5, 2012 at 2:56 PM, Frank Horowitz
> <frank.horowitz at cornell.edu>wrote:
> 
>> OK Andy,
>> 
>> Thanks for that!
>> 
>> I've compiled and installed Paraview from git's release branch, and (a
>> slight modification) of your code runs correctly. I think that means that
>> my paraview/python integration is semi-sane.
>> 
>> However, my problem still occurs. Recall that I have a time series of .vtu
>> files (indexed by integers built-in to their filenames) being fed into
>> inputs[0] (at least as I understand it).
>> 
>> In my original code snippet, I assumed that the "m = x*x" statement would
>> iterate not only over the point values of the spatial array, but also over
>> all timeslices.  Is that a correct assumption? Is that the source of my
>> problems???
>> 
>> Thanks again for your help,
>>    Frank Horowitz
>> 
>> ------------------------------
>> *From:* Andy Bauer [andy.bauer at kitware.com]
>> *Sent:* Tuesday, September 04, 2012 7:57 PM
>> *To:* Frank Horowitz
>> *Cc:* paraview at paraview.org
>> *Subject:* Re: [Paraview] Newbie question on Python Programmable Filters
>> 
>> Hi Frank,
>> 
>> I didn't have a problem with the following on my windows machine using the
>> ParaView 3.14.1 installer.
>> =======
>> try: paraview.simple
>> 
>> except: from paraview.simple import *
>> 
>> paraview.simple._DisableFirstRenderCameraReset()
>> 
>> Wavelet1 = Wavelet()
>> 
>> RenderView1 = GetRenderView()
>> 
>> ProgrammableFilter1 = ProgrammableFilter()
>> 
>> ProgrammableFilter1.PythonPath = ''
>> 
>> ProgrammableFilter1.RequestInformationScript = ''
>> 
>> ProgrammableFilter1.Script = 'x = inputs[0].PointData[\'RTData\']\nprint
>> "x shape =",x.shape\n\nm = x*x # I _thought_ this should run at numpy
>> speeds?\nprint "m shape=",m.shape\n\n# more debugging code to finish
>> computation of the norm omitted\n\noutput.PointData.append(m,"Displacement
>> Norm")'
>> 
>> Show()
>> 
>> Render()
>> 
>> =============
>> 
>> Does this work for you?  If it doesn't, I wonder if it's an issue with
>> having multiple pythons and numpy or system environments causing problems.
>> What version of paraview are you using and how did you get it
>> built/installed on your machine?
>> 
>> Andy
>> 
>> On Tue, Sep 4, 2012 at 6:04 PM, Frank Horowitz <frank.horowitz at cornell.edu
>>> wrote:
>> 
>>> Hal Canary wrote on Tue Sep 4 15:22:01 EDT 2012:
>>>> On 09/04/2012 02:20 PM, Frank Horowitz wrote:
>>>>> 
>>>> x = inputs[0].PointData['Scalars_']
>>>> 
>>>> 
>>>> 
>>>> I thought one needs to convert a vtkarray to a numpy array with
>>>> 
>>>>      x = numpy.array(inputs[0].PointData['Scalars_'])
>>>> 
>>>> before doing anything with it.
>>> 
>>> 
>>> Computations after that style of construction hang too.  To my eye, the
>>> results of such an expression should be 100% standard numpy, obeying 100%
>>> standard numpy semantics.
>>> 
>>> It appears that there is a bug in numpy integration to the Python
>>> Programmable Filter.
>>> 
>>> I'll re-compile from source and report back on the results.  Is the bug
>>> tracking system evident from the homepage?
>>> 
>>> Cheers,
>>>        Frank Horowitz
>>> 
>>> 
>>> 
>>> 
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>> 
>> 