Custom colormaps#

MintPy support the following colormaps:

  • Matplotlib colormaps
  • Custom colormaps: cmy, dismph, and romanian
  • Custom colormaps in .cpt (color palette tables) format. To add your own colormap, drop the corresponding .cpt file in $MINTPY/mintpy/data/colormaps.

We recommend to use cyclic colormap cmy for wrapped phase/displacement measurement.

To use colormap cmy in velocity.h5 -c cmy

To use colormap cmy in python:

from mintpy.colors import ColormapExt
cmap = ColormapExt('cmy').colromap

Colormaps from GMT#

All GMT cpt files, e.g. the 20 built-in colormaps shown below, can be recognized by setting the variable GMT_CPT_DIR in $MINTPY_HOME/src/mintpy/objects/ The default hardwired value is /opt/local/share/gmt/cpt for macOS users with GMT installed using MacPorts.

Colormaps from cpt-city#

The following colormaps is included by default:

  • BlueWhiteOrangeRed
  • DEM_print
  • differences
  • GMT_haxby
  • GMT_no_green
  • seminf-haxby
  • temp-c
  • temperature
  • wiki-2.0
  • wiki-schwarzwald-d050
  • wiki-scotland
  • More at cpt-city

Colormaps from Scientific Color-Maps by Fabio Crameri#

The following colormaps is included by default:

  • batlow (the scientific rainbow)
  • hawaii
  • oleron (surface topography)
  • roma (seismic tomography)
  • vik (diverging)
  • vikO (cyclic diverging)
  • More at Scientific Color-Maps (Crameri, 2018)

Interactive web tool to generate custom colormaps by Jon Herman#

This web tool creates a custom colormap (for Matplotlib/Matlab) by dragging points on the RGB intensity curves.

  • Choose output as plaintext style and RGB format.
  • Copy and save the RGB table to a text file
  • Use this script to convert the RGB table to 8-column CPT file with heading, overrule background, foreground, and NaN colors.