multi_image.py

#!/usr/bin/env python
'''
Make a set of images with a single colormap, norm, and colorbar.

It also illustrates colorbar tick labelling with a multiplier.
'''

import pylab
from matplotlib import cm, colors
from matplotlib.font_manager import FontProperties
from matplotlib.numerix.mlab import amin, amax

Nr = 3
Nc = 2

fig = pylab.gcf()
cmap = cm.cool

figtitle = 'Multiple images'
t = pylab.gcf().text(0.5, 0.95, figtitle,
               horizontalalignment='center',
               fontproperties=FontProperties(size=16))

cax = fig.add_axes([0.2, 0.08, 0.6, 0.04])

w = 0.4
h = 0.22
ax = []
images = []
vmin = 1e40
vmax = -1e40
for i in range(Nr):
    for j in range(Nc):
        pos = [0.075 + j*1.1*w, 0.18 + i*1.2*h, w, h]
        a = fig.add_axes(pos)
        if i > 0:
            a.set_xticklabels([])
        # Make some fake data with a range that varies
        # somewhat from one plot to the next.
        data =((1+i+j)/10.0)*pylab.rand(10,20)*1e-6
        dd = pylab.ravel(data)
        # Manually find the min and max of all colors for
        # use in setting the color scale.
        vmin = min(vmin, amin(dd))
        vmax = max(vmax, amax(dd))
        images.append(a.imshow(data, cmap=cmap))

        ax.append(a)

# Set the first image as the master, with all the others
# observing it for changes in cmap or norm.
norm = colors.Normalize(vmin=vmin, vmax=vmax)
for i, im in enumerate(images):
    im.set_norm(norm)
    if i > 0:
        images[0].add_observer(im)

# The colorbar is also based on this master image.
fig.colorbar(images[0], cax, orientation='horizontal')

# We need the following only if we want to run this
# script interactively and be able to change the colormap.
pylab.sci(images[0])

pylab.show()