Artists

The artists module contains a variety of data visualizaton tools.

Artist objects

artist description gallery links
mpl_1D() generic 1D slice(s) 1
mpl_2D() generic 2D slice(s) 1
absorbance() absorbance spectra 1, 2
difference_2D() 2D difference slice(s) 1

Colors

Two-dimensional data is often represented using “heatmaps”. Your choice of colormap is a crucial part of how your data is perceived. WrightTools has a few choice colormaps built-in.

(Source code, png, pdf)

_images/artists-1.png

All of these are held in the colormaps dictionary.

>>> wt.artists.colormaps['default']
<matplotlib.colors.LinearSegmentedColormap at 0x7f6d8b658d30>

Throughout WrightTools you can refer to colormaps by their name. By default, WrightTools will use the default (signed) colormap when plotting un(signed) channels.

There are many great resources on how to choose the best colormap. Choosing Colormaps is a great place to start reading. WrightTools tries to use perceptual colormaps wherever possible. When a large dynamic range is needed, the data can always be scaled to accommodate.

The default colormap is based on the wonderful cubehelix color scheme. [1] The cubehelix parameters have been fine-tuned to roughly mimic the colors of the historically popular “jet” colormap.

The isoluminant series are instances of the color scheme proposed by Kindlmann et al. [2]

The skyebar series were designed by Schuyler (Skye) Kain for use in his instrumental software package COLORS.

wright and signed_old are kept for legacy purposes.

Custom figures

WrightTools offers specialized tools for custom figure generation. It is often difficult to

Layout

Layout documentation coming soon.

Plot

Plot documentation coming soon.

Beautify

Beautify documentation coming soon.

Save

Save documentation coming soon.

[1]A colour scheme for the display of astronomical intensity images Dave Green Bulletin of the Astronomical Society of India 2011 arXiv:1108.5083
[2]Face-based luminace matching for perceptual colormap generation G. Kindlmann, E. Reinhard, and S Creem IEEE Visualization 2002 doi:10.1109/visual.2002.1183788