Matplotlib.colors.hsv_to_rgb() in Python

Last Updated : 21 Apr, 2020

Matplotlib is an amazing visualization library in Python for 2D plots of arrays. Matplotlib is a multi-platform data visualization library built on NumPy arrays and designed to work with the broader SciPy stack.

matplotlib.colors.hsv_to_rgb()

The matplotlib.colors.hsv_to_rgb() function is used to convert hsv values to rgb.

Syntax: matplotlib.colors.hsv_to_rgb(hsv)

Parameters:

hsv: It is an array-like argument in the form of (…, 3) where all values are assumed to be in the range of 0 to 1.

Returns:

rgb: It returns an ndarray in the form of (…, 3) that comprises of colors converted to RGB values within the range of 0 to 1.

Example 1:

import matplotlib.pyplot as plt 
import matplotlib.colors 
import numpy as np 
   
  
# helper function to find  
# mid-points 
def helper(z): 
      
    k = () 
    for i in range(z.ndim): 
        z = (z[k + np.index_exp[:-1]] + z[k + np.index_exp[1:]]) / 2.0
        k += np.index_exp[:] 
          
    return z 
   
# dummy coordinates with  rgb  
# values attached with each 
s, alpha, x = np.mgrid[0:1:11j, 
                       0:np.pi*2:25j, 
                       -0.5:0.5:11j] 
a = s*np.cos(alpha) 
b = s*np.sin(alpha) 
   
sc, alphac, xc = helper(s), helper(alpha), helper(x) 
   
# wobbly torus about [0.7, *, 0] 
sphere = (sc - 0.7)**2 + (xc + 0.2*np.cos(alphac*2))**2 < 0.2**2
   
# combining the color components 
hsv = np.zeros(sphere.shape + (3,)) 
hsv[..., 0] = alphac / (np.pi*2) 
hsv[..., 1] = sc 
hsv[..., 2] = xc + 0.5
   
#the hsv to rgb function 
plot_colors = matplotlib.colors.hsv_to_rgb(hsv) 
   
# and plot everything 
figure = plt.figure() 
axes = figure.gca(projection='3d') 
  
axes.voxels(a, b, x, sphere, 
          facecolors=plot_colors, 
          edgecolors=np.clip(2*plot_colors - 0.5, 0, 1),  
          linewidth=0.5) 
   
plt.show() 

Output:

Example 2:

from matplotlib.colors import hsv_to_rgb 
  
# sample squares for example 
first_square = np.full((50, 50, 3), 
                       fill_value ='698',  
                       dtype = np.uint8) / 255.0
  
second_square = np.full((50, 50, 3), 
                        fill_value ='385', 
                        dtype = np.uint8) / 255.0
  
plt.subplot(1, 2, 1) 
plt.imshow(hsv_to_rgb(first_square)) 
  
plt.subplot(1, 2, 2) 
plt.imshow(hsv_to_rgb(second_square)) 
  
plt.show() 