Matplotlib.colors.to_rgba() 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_rgba()

The matplotlib.colors.to_rgba() function is used convert c(color) to an RGBA color. It converts the color name into an array of RGBA encoded colors. It returns an RGBA tuple of four floats from 0-1.

Syntax: matplotlib.colors.to_rgba(c, alpha=None)
Parameters:

• c: It is a matplotlib color or a np.ma.masked color. 
  
• alpha: It is an optional parameter that accepts a scalar. It forces the alpha value if alpha is not None. But if c is “none”(case-sensitive) it maps to (0, 0, 0, 0). 
  

Returns: It returns a tuple of scalars in the form of (r, g, b, a). 

Example 1:

Python3

import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection
from matplotlib import colors as mcolors
import numpy as np

# simple example showing many
# lines in a single set of axes
x_axis = np.arange(100)

# Here are different sets of
# y to plot vs x
y_axis = x_axis[:50, np.newaxis] + x_axis[np.newaxis, :]

segments = np.zeros((50, 100, 2))
segments[:, :, 1] = y_axis
segments[:, :, 0] = x_axis

#some supported values to test
# masked array :
segments = np.ma.masked_where((segments > 50) & (segments < 60),
                               segments)

# setting the plot limits.
figure, axes = plt.subplots()
axes.set_xlim(x_axis.min(), x_axis.max())
axes.set_ylim(y_axis.min(), y_axis.max())

# colors is sequence of rgba
# tuples and .rgba implementation
colors = [mcolors.to_rgba(c)
          for c in plt.rcParams['axes.prop_cycle'].by_key()['color']]

line_segments = LineCollection(segments,
                               linewidths = (0.5, 1, 1.5, 2),
                               colors = colors,
                               linestyle = 'solid')

axes.add_collection(line_segments)
axes.set_title(' With masked arrays')
plt.show()

Output:

Example 2:

Python3

import matplotlib.pyplot as plt
import matplotlib.colors as mcolors


# helper function to plot a color table
def colortable(colors, title,
               colors_sort = True,
               emptycols = 0):

    # cell dimensions
    width = 212
    height = 22
    swatch_width = 48
    margin = 12
    topmargin = 40

    # Sorting colors based on hue,
    # saturation, value and name.
    # implementation of to_rgb
    if colors_sort is True:
        to_hsv = sorted((tuple(mcolors.rgb_to_hsv(mcolors.to_rgba(color)[:3])),
                         name)
                        for name, color in colors.items())
        names = [name for hsv, name in to_hsv]
    else:
        names = list(colors)

    length_of_names = len(names)
    length_cols = 4 - emptycols
    length_rows = length_of_names // length_cols + int(length_of_names % length_cols > 0)

    width2 = width * 4 + 2 * margin
    height2 = height * length_rows + margin + topmargin
    dpi = 72

    figure, axes = plt.subplots(figsize =(width2 / dpi, height2 / dpi), dpi = dpi)
    figure.subplots_adjust(margin / width2, margin / height2,
                           (width2-margin)/width2,
                           (height2-topmargin)/height2)

    axes.set_xlim(0, width * 4)
    axes.set_ylim(height * (length_rows-0.5), -height / 2.)
    axes.yaxis.set_visible(False)
    axes.xaxis.set_visible(False)
    axes.set_axis_off()
    axes.set_title(title, fontsize = 24, loc ="left", pad = 10)

    for i, name in enumerate(names):
        rows = i % length_rows
        cols = i // length_rows
        y = rows * height

        swatch_start_x = width * cols
        swatch_end_x = width * cols + swatch_width
        text_pos_x = width * cols + swatch_width + 7

        axes.text(text_pos_x, y, name, fontsize = 14,
                horizontalalignment ='left',
                verticalalignment ='center')

        axes.hlines(y, swatch_start_x, swatch_end_x,
                  color = colors[name], linewidth = 18)

    return figure

colortable(mcolors.BASE_COLORS, "Base Colors",
                colors_sort = False, emptycols = 1)
colortable(mcolors.TABLEAU_COLORS, "Tableau Palette",
                colors_sort = False, emptycols = 2)
colortable(mcolors.CSS4_COLORS, "CSS Colors")

plt.show()

Output: