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Matplotlib.pyplot.gray() in Python

  • Last Updated : 21 Apr, 2020

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.

Matplotlib.pyplot.gray() Function

The gray() function in pyplot module of matplotlib library is used to set the colormap to “gray”.

Syntax:

matplotlib.pyplot.gray()

Below examples illustrate the matplotlib.pyplot.gray() function in matplotlib.pyplot:

Example #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, 3 * 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.gray()
plt.title('matplotlib.pyplot.gray() function\
Example\n\n', fontweight ="bold")
  
plt.show()

Output:

Example #2:




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

Output:




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