Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. Pyplot is a state-based interface to a Matplotlib module which provides a MATLAB-like interface. There are various plots which can be used in Pyplot are Line Plot, Contour, Histogram, Scatter, 3D Plot, etc.
Sample Code
# sample code import matplotlib.pyplot as plt plt.plot([1, 2, 3, 4], [16, 4, 1, 8]) plt.show() |
Output:
matplotlib.pyplot.tight_layout() Function
The tight_layout() function in pyplot module of matplotlib library is used to automatically adjust subplot parameters to give specified padding.
Syntax: matplotlib.pyplot.tight_layout(pad=1.08, h_pad=None, w_pad=None, rect=None)
Parameters: This method accept the following parameters that are described below:
- pad: This parameter is used for padding between the figure edge and the edges of subplots, as a fraction of the font size.
- h_pad, w_pad: These parameter are used for padding (height/width) between edges of adjacent subplots, as a fraction of the font size.
- rect: This parameter is rectangle in the normalized figure coordinate that the whole subplots area will fit into.
Returns: This method does not return any value.
Below examples illustrate the matplotlib.pyplot.tight_layout() function in matplotlib.pyplot :
Example-1:
import numpy as np import matplotlib.pyplot as plt fig, axs = plt.subplots(1, 2) x = np.arange(0.0, 2.0, 0.02) y1 = np.sin(2 * np.pi * x) y2 = np.exp(-x) l1, = axs[0].plot(x, y1) l2, = axs[0].plot(x, y2, marker ='o') y3 = np.sin(4 * np.pi * x) y4 = np.exp(-2 * x) l3, = axs[1].plot(x, y3, color ='tab:green') l4, = axs[1].plot(x, y4, color ='tab:red', marker ='o') fig.legend((l1, l2), ('Line 1', 'Line 2'), 'upper left') fig.legend((l3, l4), ('Line 3', 'Line 4'), 'upper right') fig.suptitle('matplotlib.pyplot.tight_layout() Example') plt.tight_layout() plt.show() |
Output:
Example-2:
import matplotlib.pyplot as plt import numpy as np from matplotlib.ticker import EngFormatter prng = np.random.RandomState(19680801) xs = np.logspace(1, 9, 100) ys = (0.8 + 0.4 * prng.uniform(size = 100)) * np.log10(xs)**2 plt.xscale('log') formatter0 = EngFormatter(unit ='Hz') plt.plot(xs, ys) plt.xlabel('Frequency') plt.title('matplotlib.pyplot.tight_layout() Example') plt.tight_layout() plt.show() |
Output:
