Matplotlib is an amazing visualization library in Python for 2D plots of arrays. Matplotlib is a multi-platform data visualization library built on NumPy arrays and designed to work with the broader SciPy stack.
matplotlib.pyplot.rc()
matplotlib.pyplot.rc() function is used to the rc params. Grouping in rc is done through the ‘group'(eg, for lines). For lines in axes the group is linewidth. The group for axes is facecolor and so on. A list or tuple can also act as a group name(eg, xtick, ytick). Kwargs act as a name value pair which broadly is a dictionary, eg:
Syntax:
rc(‘lines’, linewidth=3, color=’g’)
It sets the current rc params and is same as
rcParams[‘lines.linewidth’] = 3
rcParams[‘lines.color’] = ‘g’
To save typing for interactive users the following aliases are available:
| Alias | Property |
|---|---|
| ‘lw’ | ‘linewidth’ |
| ‘ls’ | ‘linestyle’ |
| ‘c’ | ‘color’ |
| ‘fc’ | ‘facecolor’ |
| ‘ec’ | ‘edgecolor’ |
| ‘mew’ | ‘markeredgewidth’ |
| ‘aa’ | ‘antialiased’ |
Therefore once could abbreviate the above rc commands as follows
rc(‘lines’, lw=3, c=’g’)
Note: One can use the pythons kwargs dictionary to store dictionaries of its default parameters. For example,
font = {‘family’ : ‘monospace’,
‘weight’ : ‘italic’,
‘size’ : ‘medium’}
# pass in the font dict as kwargs
rc(‘font’, **font)
This helps in easily switching among different configurations. you can also use matplotlib.style.use(‘default’) or rcdefaults() to restore back the rc params after change.
Example 1:
from cycler import cycler import numpy as np import matplotlib.pyplot as plt # setting up a custom cycler sample_cycler = (cycler(color =['r', 'g', 'b', 'y']) + cycler(lw =[1, 2, 3, 4])) # using the rc function plt.rc('lines', linewidth = 4) plt.rc('axes', prop_cycle = sample_cycler) A = np.linspace(0, 2 * np.pi, 50) line_offsets = np.linspace(0, 2 * np.pi, 4, endpoint = False) B = np.transpose([np.sin(A + phi) for phi in line_offsets]) figure, (axes0, axes1) = plt.subplots(nrows = 2) axes0.plot(B) axes0.set_title('Set default color cycle to 1st plot') axes1.set_prop_cycle(sample_cycler) axes1.plot(B) axes1.set_title('Set axes color cycle to 2nd plot') # Adding space between the two plots. figure.subplots_adjust(hspace = 0.4) plt.show() |
Output:
Example 2:
import matplotlib.pyplot as plt plt.subplot(332) plt.plot([1, 2, 3, 4]) # setting the axes attributes # before the call to subplot plt.rc('font', weight ='bold') plt.rc('xtick.major', size = 5, pad = 7) plt.rc('xtick', labelsize = 15) # setting aliases for color, linestyle # and linewidth; gray, solid, thick plt.rc('grid', c ='0.3', ls ='-', lw = 4) plt.rc('lines', lw = 2, color ='g') plt.subplot(312) plt.plot([1, 2, 3, 4]) plt.grid(True) # set changes to default value plt.rcdefaults() plt.subplot(313) plt.plot([1, 2, 3, 4]) plt.grid(True) plt.show() |
Output:
