Welcome to colorstamps’s documentation!

Colorstamps is a package containting 2d colormaps and helper functions to use the colormaps. Most included colormaps are based on the ‘CAM02-LCD’ colorspace as defined in the package colorspacious (https://pypi.org/project/colorspacious/)

Installation

pip install colorstamps

Use

import matplotlib.pyplot as plt
import colorstamps
# img = (100,200,2) example data
img = colorstamps.helpers.get_random_data()
# map data to colormap
rgb, stamp = colorstamps.apply_stamp(img[:,:,0], img[:,:,1], 'peak',
                                   vmin_0 = -1.2, vmax_0 = 1.2,
                                   vmin_1 = -1, vmax_1 = 1,
                                 )
fig, axes = plt.subplots(1,2,figsize=(10,3), dpi = 100)
axes[0].imshow(rgb)
# show colormap as overlay
overlaid_ax = stamp.overlay_ax(axes[0],
                lower_left_corner = [0.7,0.85], width = 0.2)
overlaid_ax.set_ylabel(r'$\phi$')
overlaid_ax.set_xlabel(r'$\omega$')
# also show colormap as in separate ax to illustrate functionality
stamp.show_in_ax(axes[1])
axes[1].set_ylabel(r'$\phi$')
axes[1].set_xlabel(r'$\omega$')

Contents

The colormaps are encoded as numpy arrays of shape (l,l,3) with rgb color values in the range 0 to 1.

Table of contents:

• colorstamps.stamps module
• colorstamps.helpers module
• using 2d colormap for line plots

colorstamps.stamps contain functions that generate colormaps, and the documentation also shows how they can be customized.

colorstamps.helpers contain functions for applying the colormaps to a dataset, visualizing the colormap with the data in a matplotlib figure, and evaluating the colormap.

Quick reference

This is a quick reference of the default colormaps in colorstamps.stamps

see colorstamps.stamps for additional colormaps