Creating a Custom Colormap and Incorporating a Color Scale

To create your own colormap, one approach is to utilize the LinearSegmentedColormap function from the matplotlib.colors module. This approach is simpler and produces a continuous color scale.

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

# Generate random data points
x, y, c = zip(*np.random.rand(30, 3) * 4 - 2)

# Define lower and upper bounds for normalization
norm = plt.Normalize(-2, 2)

# Create a list of tuples representing the values and corresponding colors
tuples = [(norm(-2.), 'red'), (norm(-1.), 'violet'), (norm(2.), 'blue')]

# Generate the colormap from the list of tuples
cmap = matplotlib.colors.LinearSegmentedColormap.from_list('', tuples)

# Plot the data points using the custom colormap
plt.scatter(x, y, c=c, cmap=cmap, norm=norm)

# Add a color scale to the plot
plt.colorbar()
plt.show()

This code snippet successfully creates a colormap with a smooth transition from red to violet to blue, ranging from -2 to 2. The color scale is also incorporated to the right of the plot, allowing for easy color interpretation.