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Asked: 2026-05-25T14:44:26+00:00

I am trying to make a density all-sky plot which is complete in RA

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I am trying to make a density “all-sky” plot which is complete in RA (i.e 0 to 360 deg) but incomplete in DEC (let’s say from -45 to 90 deg). If I plot this without any projection it is ok, but when I try to plot using the ‘mollweide’ projection I am not recovering the input, but if I do a little change in the code I do recover the expected behavior (however, I don’t have a coherent explanation for this change as you’ll see in the example).

Let’s see a self-contained example with its outputs to be clearer:

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.backends.backend_agg
from math import pi

#array between 0 and 360 deg
RA = np.random.random(10000)*360
#array between -45 and 90 degrees. By construction!
DEC= np.random.random(10000)*135-45

fig = plt.Figure((10, 4.5))
ax = fig.add_subplot(111,projection='mollweide')
ax.grid(True)
ax.set_xlabel('RA')
ax.set_ylabel('DEC')

ax.set_xticklabels(np.arange(30,331,30))
hist,xedges,yedges = np.histogram2d(DEC,RA,bins=[90,180],range=[[-90,90],[0,360]])
#TO RECOVER THE EXPECTED BEHAVIOUR, I HAVE TO CHANGE -90 FOR -80 IN THE PREVIOUS LINE:
#hist,xedges,yedges = np.histogram2d(DEC,RA,bins=[90,180],range=[[-80,90],[0,360]])
#I DO NOT WHY!

extent = (-pi,pi,-pi/2.,pi/2.)
image = ax.imshow(hist,extent=extent,clip_on=False,aspect=0.5,origin='lower')

cb = fig.colorbar(image, orientation='horizontal')
canvas = matplotlib.backends.backend_agg.FigureCanvasAgg(fig)

fig.canvas.print_figure("image1.png")

And the output image is:
[As I am new here I am not allowed to post images, so I will post a link, if it does not work, please write me an email and I can share a Dropbox folder with the images ;)]

Output Image that I am getting

Where you can see clearly that the RA is OK so it ranges between 0 and 360, BUT the DEC ranges from -35 to 90 instead of -45 to 90. So far I do not understand why I am missing 10 deg.

However, if I do a little change in the code, replacing the line

hist,xedges,yedges = np.histogram2d(DEC,RA,bins=[90,180],range=[[-90,90],[0,360]]

for

hist,xedges,yedges = np.histogram2d(DEC,RA,bins=[90,180],range=[[-80,90],[0,360]]

I get what I think I should get, which is this plot:

Output Image 2

[Again, if the link does not work, let me know and I can share a Dropbox folder with you]

where DEC now ranges from -45 to 90 as expected because I created DEC in that way.

However the change of -90 for -80 doesn’t make sense (I think).
So probably I am doing something wrong that I can’t notice now, or I am misunderstanding something in the code or there is a curious bug in matplotlib??

Please any help/hint/correction would be greatly appreciate it

Eduardo

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1 Answer

  1. Editorial Team

    If this is useful for someone else, this is the “corrected version” of my code, which gives as output this image. The main change is to use pcolormesh instead of imshow (as @Joe suggested):

    import numpy as np
import matplotlib.pyplot as plt
import matplotlib.backends.backend_agg

#array between 0 and 360 deg
#CAVEAT: it seems that is needed an array from -180 to 180, so is just a
#shift in the coordinates
RA = np.random.random(10000)*360-180
#array between -45 and 90 degrees
DEC= np.random.random(10000)*135-45

fig = plt.Figure((10, 5))
ax = fig.add_subplot(111,projection='mollweide')

ax.set_xlabel('RA')
ax.set_ylabel('DEC')
ax.set_xticklabels(np.arange(30,331,30))

hist,xedges,yedges = np.histogram2d(DEC,RA,bins=[60,40],range=[[-90,90],[-180,180]])

X,Y = np.meshgrid(np.radians(yedges),np.radians(xedges))

image = ax.pcolormesh(X,Y,hist)
ax.grid(True)
cb = fig.colorbar(image, orientation='horizontal')
canvas = matplotlib.backends.backend_agg.FigureCanvasAgg(fig)
fig.canvas.print_figure("image4.png")
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