Plot complex functions in perceptually-uniform color space

This generates a bivariate color map that adjusts both lightness and hue, for plotting complex functions, the magnitude and phase of signals, etc.

Magnitude is mapped to lightness and phase angle is mapped to hue in a perceptually-uniform color space (previously LCh, now CIECAM02's JCh).

Since matplotlib doesn't handle 2D colormaps natively, it's currently implemented as a cplot function that adds to an axes object, which you can then apply further MPL features to:

ax_cplot = fig.add_subplot()
cplot(splane_eval, re=(-r, r), im=(-r, r), axes=ax_cplot)
ax_cplot.set_xlabel('$\sigma$')
ax_cplot.axis('equal')
…

See the example script.

There are currently two ways to handle the chroma information:

For each lightness J, find the maximum chroma that can be represented in RGB for any hue, and then use that for every other hue. This produces images with perceptually accurate magnitude variation, but the colors are muted and more difficult to perceive.

For each lightness J and hue h, find the maximum chroma that can be represented in RGB. This produces vivid images, but the chroma variation produces misleading streaks as it makes sharp angles around the RGB edges.

analog_filter.py uses a constant-chroma map to visualize the poles and zeros of an analog bandpass filter, with accompanying magnitude and phase plots along jω axis, and a log-dB plot of magnitude for comparison:

To create a new release

1. bump the __version__ number,

2. publish to PyPi and GitHub:

   $ make publish
   

complex_colormap is published under the MIT license.