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.get_lines() Function
The Axes.get_lines() function in axes module of matplotlib library is used to return a list of lines contained by the Axes
Syntax: Axes.get_lines(self)
Parameters: This method does not accept any parameters.
Returns: This method return a list of lines contained by the Axes.
Below examples illustrate the matplotlib.axes.Axes.get_lines() function in matplotlib.axes:
Example 1:
# Implementation of matplotlib function from matplotlib import colors from matplotlib.ticker import PercentFormatter import numpy as np import matplotlib.pyplot as plt N_points = 100000x = np.random.randn(N_points) y = .4 * x + np.random.randn(100000) + 5 fig, ax = plt.subplots() ax.hist2d(x, y, bins = 100, norm = colors.LogNorm(), cmap ="Greens") w = list(ax.get_lines()) if len(w)== 0: ax.text(-2, 8.5, "No line contained by the Axes \n") else: ax.text(-3, 8.5, "List of the lines contained by the Axes \n") x = 8.5 for i in w: ax.text(-3, x-0.5, str(i)) x-= 0.5 fig.suptitle('matplotlib.axes.Axes.get_lines() \ function Example', fontweight ="bold") plt.show() |
Output:
Example 2:
# Implementation of matplotlib function import numpy as np import matplotlib.pyplot as plt import matplotlib.patches as mpatches fig, ax = plt.subplots() x, y = 10 * np.random.rand(2, 1000) ax.plot(x, y, 'go', alpha = 0.2) circ = mpatches.Circle((0.5, 0.5), 0.25, transform = ax.transAxes, facecolor ='blue', alpha = 0.75) ax.add_patch(circ) w = list(ax.get_lines()) if len(w)== 0: ax.text(1, 8.5, "No line contained by the Axes \n") else: ax.text(1, 8.5, "List of the lines contained by the Axes \n") x = 8.5 for i in w: ax.text(1, x-0.5, str(i)) x-= 0.5 fig.suptitle('matplotlib.axes.Axes.get_lines() \ function Example', fontweight ="bold") plt.show() |
Output:
