A while ago I wrote a post on my blog with code on how to import in Python a colour palette in an ASCII file and convert it to a Matplotlib colormap:
mycarta.wordpress.com/2014/04/25/convert-color-palettes-to-python-matplotlib-colormaps/

Following that post I wrote a tutorial on a geoscience magazine on how to evaluate and compare colormaps using Python:
wiki.seg.org/wiki/How_to_evaluate_and_compare_color_maps

In the accompanying notebook I show how to convert a 256x3 RGB colormap to a 256x256x3 RGB image, then convert it to CIELAB using scikit-image's rgb2lab, then plot the 256x1 lightness (L) array to evaluate the colormaps perceptually.
You can read the relevant extract of the notebook using this nbviewer link:
http://nbviewer.ipython.org/urls/dl.dropbox.com/s/54zoax2qesb71wn/evaluate_colormaps_skimage_test.ipynb?dl=0
In that case scikit-image worked really well for me.

Now I am trying to follow up with a new tutorial and I run into problems with the color space conversions.
You can follow what I am trying to do in this other notebook extract:
http://nbviewer.ipython.org/urls/dl.dropbox.com/s/noli66nzrlk0676/make_colormap_skimage_test.ipynb?dl=0

The goal of this new tutorial is to show how to build colormaps from scratch using perceptual principles. I design a color palette in LCH (polar version of CIELAB) by keeping Chroma and Lightness fixed and interpolating Hue around the circle, then convert to LAB, then to RGB.
As far as I know the code I wrote should work, but the result is a black colormap. I am thinking I got wrong one or more of the ranges for the LCH coordinates. I assumed L between (0,1), Ch between (0,1), and H between (0, 2*pi).
Is that wrong, and if that's the case, what are the ranges? Many of them are not stated clearly in the documentation in here: http://scikit-image.org/docs/dev/api/skimage.color.html