A deep dive into matplotlib’s colormap

In-depth study of matplotlib color table requires specific code examples

1. Introduction
matplotlib is a powerful Python drawing library that provides rich drawings Functions and tools can be used to create various types of charts. The color map (color map) is an important concept in matplotlib, which determines the color scheme of the chart. An in-depth study of the matplotlib color table will help us better master matplotlib's drawing functions and make the drawing results more beautiful and orderly. This article will introduce the concept of color tables and give some specific code examples to help readers better understand and apply them.

2. What is a color table
A color table is a color mapping table that maps a continuous data range to intervals of different colors. It is usually used to express the degree of change in data. The color table in matplotlib is a function that receives data with a value range between 0 and 1 and returns the corresponding RGB color value. matplotlib provides many default color tables, such as 'viridis', 'hot', etc., and you can also customize a color table that meets your needs.

3. Use the default color table
In matplotlib, you can use the plt.colormaps() function to view all available default color tables. The following sample code will display thumbnails of all default color tables:

import matplotlib.pyplot as plt

cmaps = plt.colormaps()

for cmap in cmaps:
    fig, ax = plt.subplots(figsize=(0.25, 0.25))
    ax.imshow([[0, 1]], cmap=cmap)
    ax.axis('off')
    ax.set_title(cmap, fontsize=4)
    plt.show()

This code will draw thumbnails of all default color tables one by one and display the name of the color table in the title of each thumbnail, So that we can better understand the characteristics of each color table.

4. Customized color table
In addition to using the default color table, we can also customize the color table to meet specific needs. The following is a sample code that shows how to customize a ladder-shaped color table:

import numpy as np
import matplotlib.pyplot as plt

def custom_cmap(x):
    colors = ['red', 'green', 'blue', 'yellow']
    return colors[int(x * 4)]

x = np.linspace(0, 1, 100)
y = np.ones_like(x)

plt.scatter(x, y, c=x, cmap=custom_cmap)
plt.colorbar()
plt.show()

In this example, we define a custom color table custom_cmap, consisting of red, Composed of four colors: green, blue and yellow. Depending on the value of the data, the c parameter will determine the color of the plotted points. By setting the cmap parameter to a custom color table, we can color the data points according to a custom color scheme.

5. Application of color tables
Color tables are widely used in various types of charts, such as heat maps, contour maps, and color maps. The following is a sample code for drawing a heat map:

import numpy as np
import matplotlib.pyplot as plt

data = np.random.rand(10, 10)

plt.imshow(data, cmap='rainbow')
plt.colorbar()
plt.show()

This code first generates a matrix of random data, and then uses the imshow function to draw the heat map. By setting the cmap parameter to 'rainbow', we use a default color table to express the degree of change in the data. Finally, use the colorbar function to add a color-represented ruler.

6. Summary
This article introduces the concept of matplotlib color table and gives some specific code examples. By in-depth study of the matplotlib color table, we can more flexibly control the color matching of drawings, making the drawing results more beautiful and orderly. At the same time, mastering the use of color tables also provides convenience for us to apply color tables in various charts. I hope this article can help readers learn and apply the matplotlib color table.

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