colormap testing using sine-wave comb data.

cmap_comb.py

"""
This function produces an image that can be used to
quickly determine the perceptual linearity of a colormap.
The idea behind this came from Peter Kovesi and
explained very well on his website:

http://peterkovesi.com/projects/colourmaps/

CET Perceptually Uniform Colour Maps

Peter Kovesi 
Geophysics & Image Analysis Group 
Centre for Exploration Targeting 
School of Earth and Environment 
The University of Western Australia 
peter.kovesi@uwa.edu.au

and also on the paper arXiv:1509.03700 found here:

https://arxiv.org/abs/1509.03700
"""

def cmap_comb(ax, cmap):
    nperiods, npoints, amplitude = 80, 50, 70
    x = np.linspace(0, nperiods * 2 * np.pi, npoints * nperiods)
    y = np.linspace(0, amplitude, npoints * 10)
    X, Y = np.meshgrid(x, y)
    img = X +  Y * np.sin(X) * (Y**2 / Y.max()**2)
    ax.imshow(img, cmap=cmap, aspect=2, origin='lower', vmin=x[0], vmax=x[-1])
    ax.set_title(cmap.name)
    ax.set_axis_off()

fig, ax = pyplot.subplots(3, figsize=(12,4*3))
cmap_comb(ax[0], cm.viridis)
cmap_comb(ax[1], cm.jet)
cmap_comb(ax[2], cm.seismic)

This is a convenient way to test the perceptual-linearity of a colormap. The comb structure should fade out at the same horizontal level throughout the colormap's range. The depth of the comb is less important than the uniformity of where it gets washed out.