Hi Casey, You might try adding a gaussian filter from scipy: http://docs.scipy.org/doc/scipy/reference/generated/scipy.ndimage.filters.ga... Once you make the projection, you can get N^2 image data by creating a FixedResolutionBuffer like this: frb = FixedResolutionBuffer(projection, (x_left, x_right, y_left, y_right), (N, N), antialias=False) where projection is your projection object (like pc.plots[-1]) The actual data for a field can be accessed by frb[field]. You should be able to take that NxN array and apply whatever filter you like. Britton On Mon, Jun 27, 2011 at 11:59 PM, Casey W. Stark <caseywstark@gmail.com>wrote:
Hello yt.
I'm trying to generate plots like the ones in Frenk 1999, the Santa Barbara Cluster Comparison Project. I would like to reproduce the plots of projections of the dark matter density, gas density, and temperature at z = 0.
The first step is pretty easy - just make a plotcollection and add a projection. The part I'm not sure about is the smoothing. I need to apply Gaussian smoothing to this 256^3 data. I figure I do something like what is in AMRSmoothedCoveringGridBase, but I'm really not sure.
Has anyone done anything similar with yt?
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