I propose you incorporate you plot in a fig and get inspiration from this sample using the colorbar
data = np.tile(np.arange(4), 2)
fig = plt.figure()
ax = fig.add_subplot(121)
cax = fig.add_subplot(122)
cmap = colors.ListedColormap(['b','g','y','r'])
bounds=[0,1,2,3,4]
norm = colors.BoundaryNorm(bounds, cmap.N)
im=ax.imshow(data[None], aspect='auto',cmap=cmap, norm=norm)
cbar = fig.colorbar(im, cax=cax, cmap=cmap, norm=norm, boundaries=bounds,
ticks=[0.5,1.5,2.5,3.5],)
plt.show()
you see that you can set bounds
for the colors in colorbar and ticks.
it is not rigourously what you want to achieve, but the hint to fig could help.
This other one uses ticks
as well to define the scale of colorbar.
import numpy as np
import matplotlib.pyplot as plt
xi = np.array([0., 0.5, 1.0])
yi = np.array([0., 0.5, 1.0])
zi = np.array([[0., 1.0, 2.0],
[0., 1.0, 2.0],
[-0.1, 1.0, 2.0]])
v = np.linspace(-.1, 2.0, 15, endpoint=True)
plt.contour(xi, yi, zi, v, linewidths=0.5, colors='k')
plt.contourf(xi, yi, zi, v, cmap=plt.cm.jet)
x = plt.colorbar(ticks=v)
print x
plt.show()