SkyProj: Sky Projections with matplotlib and PROJ
SkyProj provides an astronomically oriented interface to plotting sky maps based on matplotlib and PROJ. The primary goal of SkyProj is to create publication quality projected visualizations of healsparse and HEALPix maps. In addition, SkyProj can be an interactive tool that allows you to dynamically zoom in on healsparse maps showing the full resolution of the map.
The SkyProj package addresses multiple issues in the default healpy plotting routines:
healpy supports a limited set of sky projections (cartview, mollview, and gnomview)
healpy converts sparse HEALPix maps to full maps to plot; this is memory intensive for large nside.
healpy is best at plotting full-sky and not partial-sky maps.
The code is hosted in GitHub. Please use the issue tracker to let us know about any problems or questions with the code. The list of released versions of this package can be found here, with the main branch including the most recent (non-released) development.
The SkyProj code was written by Eli Rykoff based on work by Alex Drlica-Wagner, and matplotlib/projection integrations derived from the cartopy package. This software was developed under the Rubin Observatory Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC) using LSST DESC resources. The DESC acknowledges ongoing support from the Institut National de Physique Nucléaire et de Physique des Particules in France; the Science & Technology Facilities Council in the United Kingdom; and the Department of Energy, the National Science Foundation, and the LSST Corporation in the United States. DESC uses resources of the IN2P3 Computing Center (CC-IN2P3–Lyon/Villeurbanne - France) funded by the Centre National de la Recherche Scientifique; the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231; STFC DiRAC HPC Facilities, funded by UK BIS National E-infrastructure capital grants; and the UK particle physics grid, supported by the GridPP Collaboration. This work was performed in part under DOE Contract DE-AC02-76SF00515.