Metadata-Version: 2.1
Name: toast
Version: 2.3.14
Summary: Time Ordered Astrophysics Scalable Tools
Home-page: https://github.com/hpc4cmb/toast
Author: Theodore Kisner, Reijo Keskitalo
Author-email: tskisner.public@gmail.com
License: BSD
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Console
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: POSIX
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering :: Astronomy
Requires-Python: >=3.7.0
Description-Content-Type: text/markdown
License-File: LICENSE
License-File: AUTHORS
Requires-Dist: cmake
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: healpy
Requires-Dist: matplotlib
Requires-Dist: ephem
Requires-Dist: h5py
Provides-Extra: mpi
Requires-Dist: mpi4py (>=3.0) ; extra == 'mpi'

# Time Ordered Astrophysics Scalable Tools

![Build Status](https://github.com/hpc4cmb/toast/workflows/Run%20Test%20Suite/badge.svg?branch=master)

[![DOI](https://zenodo.org/badge/33680104.svg)](https://zenodo.org/badge/latestdoi/33680104)

## Description

TOAST is a [software framework](https://en.wikipedia.org/wiki/Software_framework) for
simulating and processing timestream data collected by telescopes. Telescopes which
collect data as timestreams rather than images give us a unique set of analysis
challenges. Detector data usually contains noise which is correlated in time as well as
sources of correlated signal from the instrument and the environment. Large pieces of
data must often be analyzed simultaneously to extract an estimate of the sky signal.

## Documentation

See the full documentation here:

https://toast-cmb.readthedocs.io/en/latest/


