I don't think there's a way to speed it up too much, at least on a single core. It's likely that most of the cost is in building the index (this implicitly happens when you do "ds.slice"). This requires parsing the AMR hierarchy, detecting which fields are available on disk and inferring which derived fields yt can construct out of those, parsing parameters, etc. One way to verify that this is where the time is going is to run your analysis script under a profiler: $ python -m cProfile -o prof.out You can then postprocess the prof.out file to get things like hotspot statistics and call graphs. I like to use pyprof2html for this: https://pypi.python.org/pypi/pyprof2html/ (despite the docs on pypi, you should probably install it with "pip install pyprof2html") If you have access to a cluster, another option would be to take advantage of the fact that your workflow is embarrassingly parallel (i.e. the act of producing a single image is completely independent of the other images in the time series). yt provides a function called parallel_objects which makes it easy to construct embarrassingly parallel analysis pipelines that can be managed using an MPI-parallel cluster. More detail on yt's parallelism and parallel_objects is available here: http://yt-project.org/doc/analyzing/parallel_computation.html http://yt-project.org/doc/reference/api/generated/yt.utilities.parallel_tool... I've seen substantial speedups for generating movies in the past using this machinery, so I think this may really help. Hope that helps, Nathan On Wed, Feb 3, 2016 at 9:04 AM, Slavin, Jonathan <jslavin@cfa.harvard.edu> wrote:

Hi all,

I've been using yt to handle FLASH AMR data stored in HDF5 files. I want to cycle through a series of images generated, plotting each as I go using matplotlib. To do this I have (somewhat simplified): for f in files: ds = yt.load(f) slc = ds.slice(2,0) # its 2D r-z data frb = slc.to_frb(width=(Rmax,'pc'), height=(Zmax, 'pc'), resolution=(NX,NY)) image = np.array(frb['temp']) imshow(img) etc.

This works the way I want it to, but is very slow. Is there a way to speed it up?

Thanks, Jon

-- ________________________________________________________ Jonathan D. Slavin Harvard-Smithsonian CfA jslavin@cfa.harvard.edu 60 Garden Street, MS 83 phone: (617) 496-7981 Cambridge, MA 02138-1516 cell: (781) 363-0035 USA ________________________________________________________

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