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.axvspan() Function
The Axes.axvspan() function in axes module of matplotlib library is used to add a vertical span (rectangle) across the axis.
Syntax:
Axes.axvspan(self, xmin, xmax, ymin=0, ymax=1, **kwargs)Parameters: This method accept the following parameters that are described below:
- xmin: This parameter indicates the first X-axis coordinate of the vertical span rectangle in data units.
- xmax: This parameter indicates the second X-axis coordinate of the vertical span rectangle in data units.
- ymin: This parameter indicates the first Y-axis coordinate of the vertical span rectangle in relative Y-axis units .
- ymax: This parameter indicates the second Y-axis coordinate of the vertical span rectangle in relative Y-axis units.
Returns: This returns the vertical span (rectangle) from (xmin, ymin) to (xmax, ymax).
Below examples illustrate the matplotlib.axes.Axes.axhspan() function in matplotlib.axes:
Example-1:
# Implementation of matplotlib function import matplotlib.pyplot as plt import numpy as np fig, ax = plt.subplots() ax.axvspan(1.5, 2.5, facecolor ='g', alpha = 0.7) ax.set_title('matplotlib.axes.Axes.axvspan() Example') plt.show() |
Output:
Example-2:
# Implementation of matplotlib function import numpy as np import matplotlib.pyplot as plt t = np.arange(-3, 4, .1) s = np.sin(np.pi * t) fig, ax = plt.subplots() ax.plot(t, s, color ='black') ax.axhline(y = 1, color ='black') ax.axvline(x = 1, color ='black') ax.axvline(x = 0, ymin = 0.75, linewidth = 8, color ='green') ax.axhline(y =.5, xmin = 0.25, xmax = 0.75, color ='black') ax.axhspan(0.25, 0.75, facecolor ='green', alpha = 0.7) ax.axvspan(1.25, 1.55, facecolor ='0.5', alpha = 0.5) ax.set_title('matplotlib.axes.Axes.axvspan() Example') plt.show() |
Output:
