High-contrast Imaging Plotting library
Project description
hciplot
HCIplot
-- High-contrast Imaging Plotting library. The goal of this
library is to be the "Swiss army" solution for plotting and visualizing
multi-dimensional high-contrast imaging datacubes on Jupyter lab
.
While visualizing FITS files is straightforward with SaoImage DS9 or any
other FITS viewer, exploring the content of an HCI datacube as an
in-memory numpy
array (for example when running your Jupyter session
on a remote machine) is far from easy.
HCIplot
contains two functions, plot_frames
and plot_cubes
,
and relies on the matplotlib
and HoloViews
libraries and
ImageMagick
. With HCIplot
you can:
- plot a single 2d array or create a mosaic of several 2d arrays,
- annotate save publication ready images,
- visualize 2d arrays as surface plots,
- create interactive plots when handling 3d or 4d arrays (thanks to
HoloViews
, - save to disk a 3d array as an animation (gif or mp4).
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.