This page lists some capabilities of SpacePy and, in some cases, of other packages that might be of interest to SpacePy users. It is organized by topic; searching within this page is recommended. See the module reference for every class/function available in SpacePy, organized by module.
toolbox functions are useful in manipulating
datamanager also contains many functions
for indexing arrays and manipulating them in ways that do not depend
on the interpretation of their contents.
coordinates provides a class for transforming among
most coordinate systems used in Earth magnetospheric and
It also provides generalized coordinate transforms via quaternions.
pycdf provides reading and writing of NASA CDF files,
with additional functionality for those with ISTP-compliant metadata.
numpy.loadtxt() and related functions are helpful for reading
various “plain-text” files into numerical arrays.
scipy.io.readsav() reads IDL savesets.
astropy.io.fits supports FITS files.
ae9ap9 supports import and visualization of data from
the AE9/AP9 empirical radiation belt model.
empiricals implements several simple empirical and/or
analytic models for magnetospheric and solar wind phenomena, including
the plasmapause location, the Shue magnetopause model, and solar wind
pybats supports output analysis and visualization of
many models compatible with the Space Weather Modeling Framework,
including the BATS-R-US global MHD model and the RAM-SCB ring current
poppysupports determining confidence intervals on
population metrics using the non-parametric bootstrap method.
time contains a class that easily allows time to be
represented in, and converted among, many representations, including
Python datetimes, ISO time strings, GPS time, TAI, etc.
poppy implements association analysis to determine the
relationship between point-in-time events.
seapy implements superposed epoch analysis, the
statistical evaluation of the time evolution of a system relative
to a set of starting epochs.