[AstroPy] all-sky map

[Matthew Turk]

Hi Eric,

On Wed, Apr 6, 2011 at 8:49 AM, Erik Tollerud <erik.tollerud at gmail.com> wrote:
>> If anybody knows why the figure size has to be 2:1 to avoid a blank
>> image, I'd really appreciate a tip.
>
> Maybe this is a version problem? If I do the following with matplotlib 1.0.1:
>
> import matplotlib
> matplotlib.use('agg') #I tried a few other backends and got the same result
>
> from matplotlib.pyplot import figure,axes,imshow,savefig
> from numpy.random import randn
> from math import pi
>
> img = randn(100,100)
>
> figure(figsize=(10,5))
> imshow(img,extent=(-pi,pi,-pi/2,pi/2))
> savefig('filename.png')
>
> I get this result: http://dl.dropbox.com/u/8683962/moll-agg1.png
>
> And if I add aspect=.5 to the imshow call, I get
> http://dl.dropbox.com/u/8683962/moll-agg12.png
>
> Clearly it is not blank in either case, although the second case is
> presumably is what you want.

Yup, that works for me, but it doesn't apply the Mollweide projection.
 I put up a paste here:

http://dpaste.com/hold/529372/

I run this, and allsky1.png has the image.  allsky2.png and
allsky3.png both have empty ovals, and it's not clear to me what's
causing that.

-Matt

>
>
>
> On Tue, Apr 5, 2011 at 3:56 PM, Matthew Turk <matthewturk at gmail.com> wrote:
>> Hi Marsall,
>>
>> On Tue, Apr 5, 2011 at 2:50 PM, Marshall Perrin <mperrin at stsci.edu> wrote:
>>> On Apr 5, 2011, at 12:32 PM, Jonathan Slavin wrote:
>>>> I'm looking for a way to plot an all-sky map of modeled data using a
>>>> Hammer-Aitoff projection.  The way I've done this in IDL is to create a
>>>> uniform x-y grid, translate that l, b using the proper conversion for an
>>>> Aitoff projection and generate the data on that grid.  I then display
>>>> the image and overlay an Aitoff grid (which I also generate).  So the
>>>> image is rectangular and extends beyond the plot edges.  That is fine,
>>>> but then all the labeling, etc. has to be done by hand.  Is there an
>>>> easier way?  Any help would be appreciated.
>>>
>>>
>>> Check out the matplotlib mpl_toolkits.basemap module.   The Basemap class implements a user-selectable map projection, and yields a callable object which handles the translation between projection coordinate systems and x,y positions for plotting.   Here is some code I recently wrote to do a similar task, plotting positions of objects on an all-sky Mollweide projection:
>>
>> In theory one should be able to get this going with just the standard
>> Matplotlib projections, without basemap, which has a huge dependency
>> set.  There seems to be a bug if you don't set the figure to have
>> aspect ratio 2:1, but this code works for me, where img is a square
>> array.
>>
>> import matplotlib.figure
>> import matplotlib.backends.backend_agg
>>
>> fig = matplotlib.figure.Figure((10, 5))
>> ax = fig.add_subplot(1,1,1,projection='mollweide')
>> image = ax.imshow(img, extent=(-pi,pi,-pi/2,pi/2), clip_on=False, aspect=0.5)
>> cb = fig.colorbar(image, orientation='horizontal')
>>
>> cb.set_label(r"$\mathrm{Column}\/\mathrm{Density}\/[\mathrm{g}/\mathrm{cm}^2]$")
>> canvas = matplotlib.backends.backend_agg.FigureCanvasAgg(fig)
>> canvas.print_figure("allsky.png")
>>
>> (a bit more discussion:
>> http://blog.enzotools.org/yt-development-all-sky-column-density-calcula
>> )
>>
>> If anybody knows why the figure size has to be 2:1 to avoid a blank
>> image, I'd really appreciate a tip.
>>
>> -Matt
>>
>>>
>>>        # define base map class.
>>>        map = Basemap(projection='moll', lat_0 = 0, lon_0 = 0,
>>>                              resolution = None)  # do *NOT* draw Earth continents at any resolution!
>>>        map.drawmapboundary()
>>>        p.title("Equatorial coordinates J2000")
>>>
>>>        # draw and label ra/dec grid lines every 30 degrees.
>>>        degtoralabel = lambda deg : "%+d$^h$" % int(deg/15)
>>>        degtodeclabel = lambda deg : "%+d$^\circ$" % deg
>>>        map.drawparallels(n.arange(-90, 90, 30), fmt=degtodeclabel, labels=[1,0,0,0])
>>>        map.drawmeridians(n.arange(0, 360, 30) )  # label these manually since I don't like the default label positions:
>>>                                                                                        # this also demonstrates how to overplot text on map coordinates...
>>>        for h in [0,6,12,18]:
>>>            x,y = map(h*15,0)
>>>            p.text(x,y, degtoralabel(h*15))
>>>
>>>        # draw data points
>>>        px, py = map(data.radeg, data.dedeg)
>>>        map.plot(px, py, "o", color="red")
>>>
>>>
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>
>
>
> --
> Erik Tollerud
>