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pythonmatplotlibcolormap

How to create a custom colormap with three colors?

I want to create a custom colormap with three colors, red-white-blue, using Matplotlib.

I know how to create a custom colormap with two colors. Here from red to blue:

import numpy as np
from matplotlib.colors import ListedColormap
N = 1024
vals = np.zeros((N, 4))
vals[:, 0] = np.linspace(1.0, 0.0, N) # red
vals[:, 2] = np.linspace(0.0, 1.0, N) # blue
vals[:, 3] = 1.0
my_cmap = ListedColormap(vals)

But how do I add the color white between red and blue?

Solution

  • I used this adapted code from the matplotlib documentation

    import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib.colors import ListedColormap

def plot_examples(colormaps):
    """
    Helper function to plot data with associated colormap.
    """
    np.random.seed(19680801)
    data = np.random.randn(30, 30)
    n = len(colormaps)
    fig, axs = plt.subplots(1, n, figsize=(n * 2 + 2, 3),
                            constrained_layout=True, squeeze=False)
    for [ax, cmap] in zip(axs.flat, colormaps):
        psm = ax.pcolormesh(data, cmap=cmap, rasterized=True, vmin=-4, vmax=4)
        fig.colorbar(psm, ax=ax)
    plt.show()

# Red, Green, Blue
N = 256
vals = np.ones((N, 4))
# Red stays constant until middle of colormap all other channels increas
# to result in white
# from middle of colormap we decrease to 0, 0, 255 which is blue
vals[:, 0] = np.concatenate((np.linspace(1, 1, N//2), np.linspace(1, 0, N//2)), axis=None)
vals[:, 1] = np.concatenate((np.linspace(0, 1, N//2), np.linspace(1, 0, N//2)), axis=None)
vals[:, 2] = np.concatenate((np.linspace(0, 1, N//2), np.linspace(1, 1, N//2)), axis=None)
newcmp = ListedColormap(vals)

plot_examples([newcmp])

    The output of this script looks similar to this custom colormap