The road to Visualization （ 11、 ... and ）matplotlib Color details

One . Preface

matplotlib Library is the most popular data visualization library at present , He supports quite a number of color choices , Next, I will introduce in detail matplotlib Various color input supported by the library .

Two . Supported colors

1. 2.1 Closed interval [0, 1] Floating point values in RGB or RGBA（ red 、 green 、 blue 、alpha） Tuples .

   give an example ：(0.1, 0.2, 0.54),(0.1, 0.5, 0.2, 0.6)

2. Case insensitive hexadecimal RGB or RGBA character string .

   give an example ：’#0f0f0f’ perhaps ’#0f0f0f80’

3. Case insensitive RGB or RGBA A string is a hexadecimal shorthand equivalent to a repeating character .

   give an example ：’#abc’ As ‘#aabbcc’ and ’#fb1’ As ‘#ffbb11’

4. A string representation of a closed interval floating-point value of a grayscale value .

   • 0 ： As black
   • 1： As white
   • 0.8 ： As light gray

5. Some basic colors of single character shorthand symbols .

   • 'b' Like blue
   • 'g' As green
   • 'r' As red
   • 'c' As cyan
   • 'm' Magenta
   • 'y' As yellow
   • 'k' As black
   • 'w' As white

6. Case insensitive X11/CSS4 Color name ,（ No spaces ）

   give an example ：'aquamarine' and 'mediumseagreen'

7. come from xkcd Case insensitive color names , with 'xkcd:' Prefix .

   give an example ：'xkcd:sky blue' and 'xkcd:eggshell'

8. come from “T10” The classification palette is case insensitive Tableau Color .

   • 'tab:blue'
   • 'tab:orange'
   • 'tab:green'
   • 'tab:red'
   • 'tab:purple'
   • 'tab:brown'
   • 'tab:pink'
   • 'tab:gray'
   • 'tab:olive'
   • 'tab:cyan'

9. “CN” Color specification .

   • 'C0'
   • 'C1'

matplotlib Formula for calculating transparency ：

$RG{B}_{new}=RG{B}_{below}\ast (1-\alpha )+RG{B}_{artist}\ast \alpha$

3、 ... and . example

3.1X11/CSS4 And xkcd Color contrast

Complete code ：

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

overlap = {
    name for name in mcolors.CSS4_COLORS
           if f'xkcd:{
      name}' in mcolors.XKCD_COLORS}

fig = plt.figure(figsize=[9, 5])
ax = fig.add_axes([0, 0, 1, 1])

n_groups = 3
n_rows = len(overlap) // n_groups + 1

for j, color_name in enumerate(sorted(overlap)):
    css4 = mcolors.CSS4_COLORS[color_name]
    xkcd = mcolors.XKCD_COLORS[f'xkcd:{
      color_name}'].upper()

    # Pick text colour based on perceived luminance.
    rgba = mcolors.to_rgba_array([css4, xkcd])
    luma = 0.299 * rgba[:, 0] + 0.587 * rgba[:, 1] + 0.114 * rgba[:, 2]
    css4_text_color = 'k' if luma[0] > 0.5 else 'w'
    xkcd_text_color = 'k' if luma[1] > 0.5 else 'w'

    col_shift = (j // n_rows) * 3
    y_pos = j % n_rows
    text_args = dict(fontsize=10, weight='bold' if css4 == xkcd else None)
    ax.add_patch(mpatch.Rectangle((0 + col_shift, y_pos), 1, 1, color=css4))
    ax.add_patch(mpatch.Rectangle((1 + col_shift, y_pos), 1, 1, color=xkcd))
    ax.text(0.5 + col_shift, y_pos + .7, css4,
            color=css4_text_color, ha='center', **text_args)
    ax.text(1.5 + col_shift, y_pos + .7, xkcd,
            color=xkcd_text_color, ha='center', **text_args)
    ax.text(2 + col_shift, y_pos + .7, f' {
      color_name}', **text_args)

for g in range(n_groups):
    ax.hlines(range(n_rows), 3*g, 3*g + 2.8, color='0.7', linewidth=1)
    ax.text(0.5 + 3*g, -0.3, 'X11/CSS4', ha='center')
    ax.text(1.5 + 3*g, -0.3, 'xkcd', ha='center')

ax.set_xlim(0, 3 * n_groups)
ax.set_ylim(n_rows, -1)
ax.axis('off')

plt.show()

The effect is as follows ：

3.2CN Color choices

Matplotlib When drawing, the “CN” The color changes to RGBA. The complete code is as follows ：

import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl

th = np.linspace(0, 2*np.pi, 128)


def demo(sty):
    mpl.style.use(sty)
    fig, ax = plt.subplots(figsize=(3, 3))

    ax.set_title('style: {!r}'.format(sty), color='C0')

    ax.plot(th, np.cos(th), 'C1', label='C1')
    ax.plot(th, np.sin(th), 'C2', label='C2')
    ax.legend()


demo('default')
demo('seaborn')

​ The effect is as follows ：

Four . Reference resources

1. Detailed explanation of visual basic classes

2. bar Function details

3. plot Function details

4. Line2D Class explanation

5. Rectangle Class explanation

6. Patch Class explanation

7. Circle Class explanation

8. Ellipse Class explanation

9. Arrow Class explanation

10. Detailed explanation of split canvas function