Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. The figure module provides the top-level Artist, the Figure, which contains all the plot elements. This module is used to control the default spacing of the subplots and top level container for all plot elements.
matplotlib.figure.Figure.align_xlabels() function
The align_xlabels() method figure module of matplotlib library is used to Align the xlabels of subplots with the same subplots row or column if label alignment is being done automatically.
Syntax: align_xlabels(self, axs=None)
Parameters: This accept the following parameters that are described below:
- axs : This parameter is the list of Axes to align the xlabels.
Returns: This method does not return any value.
Below examples illustrate the matplotlib.figure.Figure.align_xlabels() function in matplotlib.figure:
Example 1:
# Implementation of matplotlib function import matplotlib.pyplot as plt import numpy as np import matplotlib.gridspec as gridspec fig = plt.figure() gs = gridspec.GridSpec(2, 2) for i in range(2): ax = fig.add_subplot(gs[1, i]) ax.set_ylabel('Y label') ax.set_xlabel('X label') if i == 0: for tick in ax.get_xticklabels(): tick.set_rotation(45) fig.align_xlabels() fig.suptitle('matplotlib.figure.Figure.align_xlabels() \ function Example\n\n', fontweight ="bold") plt.show() |
Output:
Example 2:
# Implementation of matplotlib function import matplotlib.pyplot as plt import numpy as np import matplotlib.gridspec as gridspec fig = plt.figure(tight_layout = True) gs = gridspec.GridSpec(2, 2) ax = fig.add_subplot(gs[0, :]) ax.plot(np.arange(0, 1e6, 1000)) ax.set_ylabel('YLabel0') ax.set_xlabel('XLabel0') for i in range(2): ax = fig.add_subplot(gs[1, i]) ax.plot(np.arange(1., 0., -0.1) * 2000., np.arange(1., 0., -0.1)) ax.set_ylabel('YLabel1 % d' % i) ax.set_xlabel('XLabel1 % d' % i) if i == 0: for tick in ax.get_xticklabels(): tick.set_rotation(55) fig.align_xlabels() fig.suptitle('matplotlib.figure.Figure.align_xlabels() \ function Example\n\n', fontweight ="bold") plt.show() |
Output:
