What is the matplotlib color table?

The matplotlib color table is a mapping relationship used to map data values ​​to colors. Data values ​​can be mapped to colors for visualizing data. In matplotlib, there are many built-in color tables to choose from. The built-in color tables of matplotlib include viridis, plasma, inferno, magma, cividis, Turbo, etc. matplotlib can create your own colormaps and save them as .json files or define them directly in code.

# Operating system for this tutorial: Windows 10 system, Dell G3 computer.

The colormap (colormap) in matplotlib is a mapping relationship used to map data values ​​to colors. It can be used to visualize data by mapping data values ​​to colors. In matplotlib, there are many built-in color tables to choose from, and you can also customize the color table.

matplotlib has many built-in color tables:

viridis: A popular color table with a gradient from dark yellow to dark green, suitable for visualizing dynamic data.

plasma: A color table based on red, green and blue, suitable for visualizing multi-dimensional data.

inferno: A gradient from dark red to bright red, suitable for visualizing heat maps.

magma: A gradient from dark purple to bright purple, suitable for visualizing surfaces of three-dimensional data.

cividis: A gradient from light green to dark green, suitable for visualizing ecological data.

Turbo: A highly contrasting color table, ranging from blue to yellow to red, suitable for visualizing categorical data.

In addition, there are many other built-in color tables, you can get a complete list by checking the official matplotlib documentation.

How to use matplotlib's color table

Using matplotlib's color table can be very simple. For example, if you want to use the 'viridis' colormap to draw a heat map, you can use the following code:

import matplotlib.pyplot as plt  
import numpy as np  
  
# 生成一些随机数据  
data = np.random.rand(10, 10)  
  
# 使用viridis颜色表绘制热力图  
plt.imshow(data, cmap='viridis')  
plt.colorbar()  
plt.show()

Can I customize matplotlib's colormap?

You can customize matplotlib's color table. You can create your own colormap and save it as a .json file or define it directly in code. For example, here's an example of how to create and use a custom colormap:

import matplotlib.pyplot as plt  
import numpy as np  
from matplotlib.colors import ListedColormap  
  
# 定义自己的颜色表，这里使用了一些常见的颜色  
colors = ['red', 'green', 'blue']  
cmap = ListedColormap(colors)  
  
# 生成一些随机数据  
data = np.random.rand(10, 10)  
  
# 使用自定义颜色表绘制热力图  
plt.imshow(data, cmap=cmap)  
plt.colorbar()  
plt.show()

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