Hi Casey,

You might try adding a gaussian filter from scipy:
http://docs.scipy.org/doc/scipy/reference/generated/scipy.ndimage.filters.gaussian_filter.html
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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