How to Generate a Custom Colormap Blending Red, Violet, and Blue for Plotting Values Between -2 and 2?

Custom Colormap Creation and Color Scale Enhancement

In this technical inquiry, the challenge lies in generating a custom colormap that smoothly blends red, violet, and blue, mapping to values between -2 and 2. The ultimate goal is to use this colormap to color coordinates in a plot and include a color scale for reference.

Colormap Generation

To achieve this, a LinearSegmentedColormap is employed. Unlike the ListedColormap mentioned in the initial approach, the LinearSegmentedColormap allows for a smooth and continuous color gradient. To create the colormap, we utilize the LinearSegmentedColormap.from_list method, specifying the desired colors as a list.

Color Mapping and Plotting

The next step involves mapping the colors to the data values. Here, the Normalize function is used to normalize the values within the range of -2 to 2. The scatter plot is then utilized to display the coordinates, using the custom colormap and the normalized values.

Color Scale Addition

To enhance the readability of the plot, a color scale is essential. The colorbar function is utilized to add a color scale to the plot, providing a visual representation of the colormap and the corresponding value range.

Example Implementation

To illustrate the process, the following code snippet demonstrates the creation of a custom colormap and its application to a plot:

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

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

norm = plt.Normalize(-2, 2)
cmap = matplotlib.colors.LinearSegmentedColormap.from_list("", ["red", "violet", "blue"])

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

By following these steps, one can effectively create a smooth and continuous custom colormap, map colors to data values, and incorporate a color scale for better understanding of the plot and its values.

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