Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. The Axes Class contains most of the figure elements: Axis, Tick, Line2D, Text, Polygon, etc., and sets the coordinate system. And the instances of Axes supports callbacks through a callbacks attribute.
matplotlib.axes.Axes.set_prop_cycle() Function
The Axes.set_prop_cycle() function in axes module of matplotlib library is used to set the property cycle of the Axes.
Syntax: Axes.set_prop_cycle(self, *args, **kwargs)
Parameters: This method accepts the following parameters.
- cycler : This parameter is used to set the given Cycler.
- label : This parameter is the property key.
- values : This parameter is the finite-length iterable of the property values.
Returns:This method does not returns any values.
Below examples illustrate the matplotlib.axes.Axes.set_prop_cycle() function in matplotlib.axes:
Example 1:
# Implementation of matplotlib function from cycler import cycler import numpy as np import matplotlib.pyplot as plt x = np.linspace(0, 200, 10) yy = np.transpose([2 * np.sin(x + phi) for phi in x]) fig, ax1 = plt.subplots() ax1.set_prop_cycle(color =['magenta', 'g', 'y', 'k'], lw =[1, 2, 3, 4]) ax1.plot(yy) ax1.set_title(' matplotlib.axes.Axes.set_prop_cycle() \ Example\n', fontsize = 12, fontweight ='bold') plt.show() |
Output:
Example 2:
# Implementation of matplotlib function from cycler import cycler import numpy as np import matplotlib.pyplot as plt x = np.linspace(0, 3 * np.pi) offsets = np.linspace(0, 3 * np.pi, 8, endpoint = False) yy = np.transpose([2 * np.sin(x + phi) for phi in offsets]) plt.rc('lines', linewidth = 4) plt.rc('axes', prop_cycle =(cycler(color =['r', 'g', 'purple', 'orange']) + cycler(linestyle =['-', '--', ':', '-.']))) fig, (ax0, ax1) = plt.subplots(nrows = 2) ax0.plot(yy) ax0.set_title('Above example with set_prop_cycle() \ function\n\nSet default color cycle to rgby', fontsize = 12, fontweight ='bold') ax1.set_prop_cycle(color =['magenta', 'g', 'y', 'k'], lw =[1, 2, 3, 4]) ax1.plot(yy) ax1.set_title('Set axes color cycle to cmyk', fontsize = 12, fontweight ='bold') plt.show() |
Output:
