How do you control the colorbar after it is created automatically with the iris.quickplot module?

From matplotlib v1.3 onwards, the return value from contouring/pcolormeshing should have a "colorbar" attribute, which allows us to get hold of the colorbar artist created for that contour/mesh (aka. a "ScalarMappable").

Let's get some data to try it out with:

In [1]:

import iris

temp = iris.load_cube(iris.sample_data_path('air_temp.pp'))
print temp.summary(shorten=True)

air_temperature / (K)               (latitude: 73; longitude: 96)

Let's look at the default quickplot:

In [2]:

import iris.quickplot as qplt
import matplotlib.pyplot as plt

plt.figure(figsize=(10, 10))
qplt.contourf(temp)
plt.gca().coastlines()
plt.show()

So, supposing we wanted to control some aspect of the colorbar, we currently don't have a reference to the colorbar Artist, but we can get it by storing the result of contourf and accessing its colorbar attribute:

cs = qplt.contourf(temp)
cbar = cs.colorbar

For instance, let's change the ticks of the colorbar:

In [3]:

import iris.quickplot as qplt
import matplotlib.pyplot as plt

plt.figure(figsize=(11, 11))

cs = qplt.contourf(temp)
cbar = cs.colorbar

cbar.set_ticks([250, 270, 290])

plt.gca().coastlines()

plt.show()