Matplotlib.pyplot.autumn() in Python

# 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()

# 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()