Date: Tue, 11 Aug 2015 13:17:50 -0500
From: Nathan Goldbaum <nathan12343@gmail.com>
To: Discussion of the yt analysis package
        <yt-users@lists.spacepope.org>
Subject: Re: [yt-users] getting slice array
Message-ID:
        <CAJXewOmiymap0uUBy0hL=zo0Ltf0kG7UErXYFy9dqZseXoapsg@mail.gmail.com>
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On Tue, Aug 11, 2015 at 1:10 PM, Slavin, Jonathan <jslavin@cfa.harvard.edu>
wrote:

> Hi all,
>
> I'm new to using yt, though I'm an experienced python and matplotlib
> user.  I've been doing runs with FLASH and would like to be able to plot
> the results with matplotlib.  I've used yt "interactively" in an ipython
> notebook and found it a bit cumbersome - e.g. you can't pan and zoom like
> you can with matplotlib.  On the other hand yt has some nice facilities for
> accessing the data.  So my question is, how do I get a slice, such as is
> plotted using the yt.SlicePlot function, in an array that I can then
> manipulate, plot, etc.?  If I do:
> ds = yt.load(file)
> slc = ds.slice(2,0.)
> d = slc['density']
> I have a YTArray that's apparently 1-D:
> d.shape
> (138496,)
> I should mention that this is a 2-D, cylindrically symmetric (r-z) run.
> Thanks in advance for any help you can offer.
>

If you have a yt plot object (e.g. a SlicePlot or a ProjectionPlot), you
can do:

slc = yt.SlicePlot(...)
densit_image = slc.frb['density']

"frb" here is a FixedResolutionBuffer object which translates the
multiresolution 1-D array you ran into above into a 2D pixelized
representation of your data.

You can also create a FixedResolutionBuffer object directly:
http://yt-project.org/docs/dev/analyzing/generating_processed_data.html#d-image-arrays

The image arrays you get back from a FixedResolutionBuffer object can be
passed directly to e.g. matplotlib's imshow command.

By the way, Matt Turk has an open pull request to add the interactive
panning and zooming you were looking for:

http://yt-project.org/docs/dev/analyzing/generating_processed_data.html#d-image-arrays

I'm hoping to finish up that pull request soon, since having interactive
plots both in the notebook and using matplotlib's interactive backends is a
common feature request.