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A tool for visualizing and designing colormaps using colorspacious and matplotlib

viscm

This is a little tool for analyzing colormaps and creating new colormaps.

Downloads:

  • https://pypi.python.org/pypi/viscm/
  • https://anaconda.org/conda-forge/viscm/

Code and bug tracker: https://github.com/matplotlib/viscm

Contact: Nathaniel J. Smith [email protected] and Stéfan van der Walt [email protected]

Dependencies:

  • Python 3.9+
  • colorspacious <https://pypi.python.org/pypi/colorspacious>_ 1.1+
  • Matplotlib 3.5+
  • NumPy 1.22+
  • SciPy 1.8+
  • one of PyQt6, PySide6

License: MIT, see LICENSE <LICENSE>__ for details.

Installation

This is a GUI application, and requires Qt Python bindings. They can be provided by PyQt (GPL) or PySide (LGPL)::

$ pip install viscm[PySide]

...or::

$ pip install viscm[PyQt]

Usage

::

$ viscm view jet $ viscm edit

There is some information available about how to interpret the resulting visualizations and use the editor tool on this website <https://bids.github.io/colormap/>_.

Reproducing viridis ^^^^^^^^^^^^^^^^^^^

Load viridis AKA option_d.py <https://github.com/BIDS/colormap/>__ using::

viscm --uniform-space buggy-CAM02-UCS -m Bezier edit /tmp/option_d.py

Note that there was a small bug in the assumed sRGB viewing conditions while designing viridis. It does not affect the outcome by much. Also see :code:viscm --help.