Matplotlib.pyplot.autumn() in Python

Last Updated : 12 Jul, 2025

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.

matplotlib.pyplot.autumn() Function

The autumn() function in pyplot module of matplotlib library is used to set the colormap to "autumn". Syntax:

matplotlib.pyplot.autumn()

Below examples illustrate the matplotlib.pyplot.autumn() function in matplotlib.pyplot: Example 1:

Python3 1==

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

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.autumn()

plt.title('matplotlib.pyplot.autumn() function\
Example\n\n', fontweight ="bold")
plt.show()

Output:

Example 2:

Python3 1==

# 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)
  
plt.imshow(Z2, alpha = 0.7, 
           interpolation ='bilinear',
           extent = extent)

plt.set_cmap("gist_rainbow")
plt.autumn()
plt.title('matplotlib.pyplot.autumn() function \
Example\n\n', fontweight ="bold")
plt.show()