Extent and aspect; square pixels in an image with shared axis in matplotlib

Question

I am stuck in a rather complicated situation. I am plotting some data as an image with imshow(). Unfortunately my script is long and a little messy, so it is difficult to make a working example, but I am showing the key steps. This is how I get the data for my image from a bigger array, written in a file:

data = np.tril(np.loadtxt('IC-heatmap-20K.mtx'), 1)
#
#Here goes lot's of other stuff, where I define start and end
#
chrdata = data[start:end, start:end]
chrdata = ndimage.rotate(chrdata, 45, order=0, reshape=True, 
                         prefilter=False, cval=0)
ax1 = host_subplot(111) 
#I don't really need host_subplot() in this case, I could use something more common;
#It is just divider.append_axes("bottom", ...) is really convenient.
plt.imshow(chrdata, origin='lower', interpolation='none',
           extent=[0, length*resolution, 0, length*resolution]) #resolution=20000

So the values I am interested in are all in a triangle with the top angle in the middle of the top side of a square. At the same time I plot some data (lot's of coloured lines in this case) along with the image near it's bottom.

So at first this looks OK, but is actually is not: all pixels in the image are not square, but elongated with their height being bigger, than their width. This is how they look if I zoom in:

This doesn't happen, If I don't set extent when calling imshow(), but I need it so that coordinates in the image and other plots (coloured lines at the bottom in this case), where identical (see Converting coordinates of a picture in matplotlib?). I tried to fix it using aspect. I tried to do that and it fixed the pixels' shape, but I got a really weird picture:

The thing is, later in the code I explicitly set this:

ax1.set_ylim(0*resolution, length*resolution) #resolution=20000

But after setting aspect I get absolutely different y limits. And the worst thing: ax1 is now wider, than axes of another plot at the bottom, so that their coordinates do not match anymore! I add it in this way:

axPlotx = divider.append_axes("bottom", size=0.1, pad=0, sharex=ax1)

I would really appreciate help with getting it fixed: square pixels, identical coordinates in two (or more, in other cases) plots. As I see it, the axes of the image need to become wider (as aspect does), the ylims should apply and the width of the second axes should be identical to the image's. Thanks for reading this probably unclear explanation, please, let me know, if I should clarify anything.

UPDATE

As suggested in the comments, I tried to use

ax1.set(adjustable='box-forced')

And it did help with the image itself, but it caused two axes to get separated by white space. Is there any way to keep them close to each other?

Answer 1

Re-edited my entire answer as I found the solution to your problem. I solved it using the set_adjustable("box_forced") option as suggested by the comment of tcaswell.

import numpy
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import host_subplot, make_axes_locatable


#Calculate aspect ratio
def determine_aspect(shape, extent):
    dx = (extent[1] - extent[0]) / float(shape[1])
    dy = (extent[3] - extent[2]) / float(shape[0])
    return dx / dy

data = numpy.random.random((30,60))

shape = data.shape
extent = [-10, 10, -20, 20]
x_size, y_size = 6, 6

fig = plt.figure(figsize = (x_size, y_size))
ax = host_subplot(1, 1, 1)
ax.imshow(data, extent = extent, interpolation = "None", aspect = determine_aspect(shape, extent))

#Determine width and height of the subplot frame
bbox = ax.get_window_extent().transformed(fig.dpi_scale_trans.inverted())
width, height = bbox.width, bbox.height

#Calculate distance, the second plot needs to be elevated by
padding = (y_size - (height - width)) / float(1 / (2. * determine_aspect(shape, extent)))

#Create second image in subplot with shared x-axis
divider = make_axes_locatable(ax)
axPlotx = divider.append_axes("bottom", size = 0.1, pad = -padding, sharex = ax)

#Turn off yticks for axPlotx and xticks for ax 
axPlotx.set_yticks([])
plt.setp(ax.get_xticklabels(), visible=False)

#Make the plot obey the frame
ax.set_adjustable("box-forced")

fig.savefig("test.png", dpi=300, bbox_inches = "tight")

plt.show()

This results in the following image where the x-axis is shared:

Hope that helps!