import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import AxesGrid

def get_demo_image():
    import numpy as np
    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 demo_grid_with_each_cbar(fig):
    """
    A grid of 2x2 images. Each image has its own colorbar.
    """

    grid = AxesGrid(F, 111, # similar to subplot(122)
                    nrows_ncols = (2, 2),
                    axes_pad = 0.1,
                    label_mode = "1",
                    share_all = True,
                    cbar_location="right",
                    cbar_mode="each",
                    cbar_size="7%",
                    cbar_pad="2%",
                    )
    Z, extent = get_demo_image()
    for i in range(4):
        im = grid[i].imshow(Z, extent=extent, interpolation="nearest")
        grid.cbar_axes[i].colorbar(im)
    grid[2].set_ylabel('Long y label')
    grid.cbar_axes[3].set_ylabel('Long Cbar label')


    # This affects all axes because we set share_all = True.
    grid.axes_llc.set_xticks([-2, 0, 2])
    grid.axes_llc.set_yticks([-2, 0, 2])



F = plt.figure(1, (5.5, 2.5))

F.subplots_adjust(left=0.05, right=0.98)

demo_grid_with_each_cbar(F)

plt.draw()
plt.show()