Matplotlib.colors.to_hex() in Python

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.to_hex()

The matplotlib.colors.to_hex() function is used to convert numbers between 0 to 1 into hex color code. It uses the #rrggbb format if keep_alpha is set to False(its also the default) else it uses #rrggbbaa.

Syntax: matplotlib.colors.to_hex(c, keep_alpha=False)

Parameters:

1. c: This represents an array of color sequence between 0 to 1.
2. keep_alpha: If set True uses #rrggbbaa format else uses #rrggbb format and it only accepts boolean values.

Example 1:

import matplotlib.pyplot as plt
from matplotlib import colors
import numpy as np

# dummy data to build the grid
data = np.random.rand(10, 10) * 20

# converting into hex color code
hex_color=matplotlib.colors.to_hex([ 0.47,
                                    0.0,
                                    1.0 ])

# create discrete colormap
cmap = colors.ListedColormap([hex_color,
                              'green'])

bounds = [0,10,20]
norm = colors.BoundaryNorm(bounds, cmap.N)

fig, ax = plt.subplots()
ax.imshow(data, cmap=cmap, norm=norm)

# draw gridlines
ax.grid(which='major', axis='both',
        linestyle='-', color='k',
        linewidth=2)

ax.set_xticks(np.arange(-.5, 10, 1));
ax.set_yticks(np.arange(-.5, 10, 1));

plt.show()

Output:

Example 2:

import matplotlib.pyplot as plt
from matplotlib import colors
import numpy as np

# dummy data to build the grid
data = np.random.rand(10, 10) * 20

# converting into hex color
# code with alpha set to True
hex_color = matplotlib.colors.to_hex([ 0.47,
                                      0.0,
                                      1.0,
                                      0.5 ],
                                     keep_alpha = True)

# create discrete colormap
cmap = colors.ListedColormap([hex_color,
                              'red'])

bounds = [0, 10, 20]
norm = colors.BoundaryNorm(bounds, cmap.N)

fig, ax = plt.subplots()
ax.imshow(data, cmap = cmap, norm = norm)

# draw gridlines
ax.grid(which ='major', axis ='both',
        linestyle ='-', color ='k',
        linewidth = 2)

ax.set_xticks(np.arange(-.5, 10, 1));
ax.set_yticks(np.arange(-.5, 10, 1));

plt.show()

Output: