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.has_data() Function
The Axes.has_data() function in axes module of matplotlib library is used to check if any artists have been added to axes.
Syntax: Axes.has_data(self)
Parameters: This method does not accepts any parameter.
Returns: This method return True if any artists have been added to axes.
Below examples illustrate the matplotlib.axes.Axes.has_data() function in matplotlib.axes:
Example 1:
# ImpleIn Reviewtation of matplotlib function import matplotlib.pyplot as plt fig, ax1 = plt.subplots( ) ax1.set_xscale("log") ax1.set_yscale("log") ax1.set_adjustable("datalim") ax1.plot([1, 3, 34, 4, 46, 3, 7, 45, 10], [1, 9, 27, 8, 29, 84, 78, 19, 48], "o-", color ="green") ax1.set_xlim(1e-1, 1e2) ax1.set_ylim(1, 1e2) w = ax1.has_data() print("Value Return by has_data() :", w) fig.suptitle('matplotlib.axes.Axes.has_data()\ function Example\n\n', fontweight ="bold") fig.canvas.draw() plt.show() |
Output:
Value Return by has_data() : True
Example 2:
# ImpleIn Reviewtation of matplotlib function import matplotlib.pyplot as plt import matplotlib.tri as tri import numpy as np n_angles = 36n_radii = 10min_radius = 2radii = np.linspace(min_radius, 0.95, n_radii) angles = np.linspace(0, 2 * np.pi, n_angles, endpoint = False) angles = np.repeat(angles[..., np.newaxis], n_radii, axis = 1) angles[:, 1::2] += 2 * np.pi / n_angles x = (radii * np.cos(angles)).flatten() y = (radii * np.sin(angles)).flatten() triang = tri.Triangulation(x, y) triang.set_mask(np.hypot(x[triang.triangles].mean(axis = 1), y[triang.triangles].mean(axis = 1)) < min_radius) fig, ax = plt.subplots() ax.triplot(triang, 'bo-', lw = 1, color = "green") w = ax.has_data() print("Value Return by has_data() :", w) fig.suptitle('matplotlib.axes.Axes.has_data() function\ Example\n\n', fontweight ="bold") fig.canvas.draw() plt.show() |
Output:
Value Return by has_data() : True
