Matplotlib.pyplot.close() in Python

Matplotlib close() function in pyplot module of the matplotlib library is used to close a figure window. This function is designed to close a figure window or a set of figure windows. When called without any arguments, it closes the currently active figure. Alternatively, we can pass a figure number or a reference to a figure object as an argument to close a specific figure.

Matplotlib.pyplot.close() Syntax in Python

Syntax: matplotlib.pyplot.close(fig=None)

Parameters: This method accept only one parameters.

1. fig: This parameter accepts the following values:
2. None: This value will close the current figure
3. Figure: This value will close the given Figure instance
4. int: This value will close a figure number
5. str: This value will close a figure name
6. ‘all’:This value will close all figures

Returns: This method does not return any values.

Python matplotlib.pyplot.close() Function Example

Below are the examples by which we can understand about how to close Matplotlib figure in Python using Matplotlib.pyplot.close() function:

Closing PyPlot Windows Using matplotlib.pyplot.close() Function

In this example, the code uses Matplotlib to create a 2D plot with two overlaid images. The first image (`Z1`) represents a checkerboard pattern, displayed in binary colors. The second image (`Z2`) is generated using a custom function (`geeks`) and displayed in green with partial transparency. Then using close() function, windows are closed.

Python3

# Implementation of matplotlib function
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.colors import LogNorm

dx, dy = 0.015, 0.05
x = np.arange(-4.0, 4.0, dx)
y = np.arange(-4.0, 4.0, dy)
X, Y = np.meshgrid(x, y)

extent = np.min(x), np.max(x), np.min(y), np.max(y)

Z1 = np.add.outer(range(8), range(8)) % 2
plt.imshow(Z1, cmap="binary_r",
           interpolation='nearest',
           extent=extent,
           alpha=1)

def geeks(x, y):
    return (1 - x / 2 + x**5 + y**6) * np.exp(-(x**2 + y**2))

Z2 = geeks(X, Y)

x = plt.imshow(Z2, cmap="Greens",
               alpha=0.7,
               interpolation='bilinear',
               extent=extent)
plt.close()
plt.title('matplotlib.pyplot.close Example')
plt.show()

Output:

Close Matplotlib Figure Using Triangular Mesh and close() Function

In this example, the code utilizes Matplotlib to generate a triangular mesh plot with two overlaid images. The first image (Z1) displays a checkerboard pattern, and the second image (Z2) is generated using a custom function. The code also includes a call to plt.close(1) to close the default figure, and it proceeds to create a triangular mesh plot with a color bar using the matplotlib.tri module.

Python3

# Implementation of matplotlib function
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.colors import LogNorm
import matplotlib.tri as tri

dx, dy = 0.015, 0.05
x = np.arange(-4.0, 4.0, dx)
y = np.arange(-4.0, 4.0, dy)
X, Y = np.meshgrid(x, y)

extent = np.min(x), np.max(x), np.min(y), np.max(y)

Z1 = np.add.outer(range(8), range(8)) % 2
plt.imshow(Z1, cmap ="binary_r",
           interpolation ='nearest',
           extent = extent,
           alpha = 1)

def geeks(x, y):
    return (1 - x / 2 + x**5 + y**6) * np.exp(-(x**2 + y**2))

Z2 = geeks(X, Y)

x = plt.imshow(Z2, cmap ="Greens",
               alpha = 0.7,
               interpolation ='bilinear',
               extent = extent)
plt.close(1)
ang = 40
rad = 10
radm = 0.35
radii = np.linspace(radm, 0.95, rad)

angles = np.linspace(0, 0.5 * np.pi, ang)
angles = np.repeat(angles[...,
                          np.newaxis],
                   rad, axis = 1)

angles[:, 1::2] += np.pi / ang

x = (radii * np.cos(angles)).flatten()
y = (radii * np.sin(angles)).flatten()
z = (np.sin(4 * radii) * np.cos(4 * angles)).flatten()

triang = tri.Triangulation(x, y)
triang.set_mask(np.hypot(x[triang.triangles].mean(axis = 1),
                         y[triang.triangles].mean(axis = 1))
                < radm)

tpc = plt.tripcolor(triang, z,
                    shading ='flat')

plt.colorbar(tpc)
plt.plasma()

plt.title('matplotlib.pyplot.close() Example')
plt.show()

Output: