<jupyter_start><jupyter_text>Demo Axes Grid2Grid of images with shared xaxis and yaxis.<jupyter_code>import numpy as np

import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import ImageGrid
import matplotlib.colors


plt.rcParams["mpl_toolkits.legacy_colorbar"] = False


def get_demo_image():
    from matplotlib.cbook import get_sample_data
    f = get_sample_data("axes_grid/bivariate_normal.npy", asfileobj=False)
    z = np.load(f)
    # z is a numpy array of 15x15
    return z, (-3, 4, -4, 3)


def add_inner_title(ax, title, loc, **kwargs):
    from matplotlib.offsetbox import AnchoredText
    from matplotlib.patheffects import withStroke
    prop = dict(path_effects=[withStroke(foreground='w', linewidth=3)],
                size=plt.rcParams['legend.fontsize'])
    at = AnchoredText(title, loc=loc, prop=prop,
                      pad=0., borderpad=0.5,
                      frameon=False, **kwargs)
    ax.add_artist(at)
    return at


fig = plt.figure(figsize=(6, 6))

# Prepare images
Z, extent = get_demo_image()
ZS = [Z[i::3, :] for i in range(3)]
extent = extent[0], extent[1]/3., extent[2], extent[3]

# *** Demo 1: colorbar at each axes ***
grid = ImageGrid(fig, 211,  # similar to subplot(211)
                 nrows_ncols=(1, 3),
                 direction="row",
                 axes_pad=0.05,
                 add_all=True,
                 label_mode="1",
                 share_all=True,
                 cbar_location="top",
                 cbar_mode="each",
                 cbar_size="7%",
                 cbar_pad="1%",
                 )

for i, (ax, z) in enumerate(zip(grid, ZS)):
    im = ax.imshow(
        z, origin="lower", extent=extent, interpolation="nearest")
    cb = ax.cax.colorbar(im)
    # Changing the colorbar ticks
    if i in [1, 2]:
        cb.set_ticks([-1, 0, 1])

for ax, im_title in zip(grid, ["Image 1", "Image 2", "Image 3"]):
    t = add_inner_title(ax, im_title, loc='lower left')
    t.patch.set_alpha(0.5)

for ax, z in zip(grid, ZS):
    ax.cax.toggle_label(True)
    #axis = ax.cax.axis[ax.cax.orientation]
    #axis.label.set_text("counts s$^{-1}$")
    #axis.label.set_size(10)
    #axis.major_ticklabels.set_size(6)

grid[0].set_xticks([-2, 0])
grid[0].set_yticks([-2, 0, 2])

# *** Demo 2: shared colorbar ***
grid2 = ImageGrid(fig, 212,
                  nrows_ncols=(1, 3),
                  direction="row",
                  axes_pad=0.05,
                  add_all=True,
                  label_mode="1",
                  share_all=True,
                  cbar_location="right",
                  cbar_mode="single",
                  cbar_size="10%",
                  cbar_pad=0.05,
                  )

grid2[0].set_xlabel("X")
grid2[0].set_ylabel("Y")

vmax, vmin = np.max(ZS), np.min(ZS)
norm = matplotlib.colors.Normalize(vmax=vmax, vmin=vmin)

for ax, z in zip(grid2, ZS):
    im = ax.imshow(z, norm=norm,
                   origin="lower", extent=extent,
                   interpolation="nearest")

# With cbar_mode="single", cax attribute of all axes are identical.
ax.cax.colorbar(im)
ax.cax.toggle_label(True)

for ax, im_title in zip(grid2, ["(a)", "(b)", "(c)"]):
    t = add_inner_title(ax, im_title, loc='upper left')
    t.patch.set_ec("none")
    t.patch.set_alpha(0.5)

grid2[0].set_xticks([-2, 0])
grid2[0].set_yticks([-2, 0, 2])

plt.show()<jupyter_output><empty_output>
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