Customizing matplotlib's parameters in code

As we already said, matplotlib configuration is read from a configuration file. This file provides a place to set up permanent default values for certain matplotlib properties, well, for almost everything in matplotlib.

There are two ways to change parameters during code execution: using the dictionary of parameters (rcParams) or calling the matplotlib.rc() command. The former enables us to load an already existing dictionary into rcParams, while the latter enables a call to a function using a tuple of keyword arguments.

If we want to restore the dynamically changed parameters, we can use matplotlib.rcdefaults() call to restore the standard matplotlib settings.

The following two code samples illustrate previously explained behaviors:

Both examples are semantically the same. In the second sample, we define that all subsequent plots will have lines with line width of 2 points. The last statement of the previous code defines that the color of every line following this statement will be red, unless we override it by local settings. See the following example:

import matplotlib.pyplot as plt
import numpy as np

t = np.arange(0.0, 1.0, 0.01)

s = np.sin(2 * np.pi * t)
# make line red
plt.rcParams['lines.color'] = 'r'
plt.plot(t,s)

c = np.cos(2 * np.pi * t)
# make line thick
plt.rcParams['lines.linewidth'] = '3'
plt.plot(t,c)

plt.show()

First, we import matplotlib.pyplot and NumPy to allow us to draw sine and cosine graphs. Before plotting the first graph, we explicitly set the line color to red using the plt.rcParams['lines.color'] = 'r' command.

Next, we go to the second graph (cosine function) and explicitly set the line width to three points using the plt.rcParams['lines.linewidth'] = '3' command.

If we want to reset specific settings, we should call matplotlib.rcdefaults().

In this recipe, we have seen how to customize the style of a matplotlib chart dynamically changing its configuration parameters. The matplotlib.rcParams object is the interface that we used to modify the parameters. It's global to the matplotlib packages and any change that we apply to it affects all the charts that we draw after.