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ci | ||
docs | ||
toasty | ||
.coveragerc | ||
.gitignore | ||
.readthedocs.yaml | ||
CHANGELOG.md | ||
LICENSE | ||
MANIFEST.in | ||
README.md | ||
pyproject.toml | ||
setup.py |
README.md
toasty
toasty is a Python library that helps you create “tile pyramids” from astronomical image data as used in the TOAST format. These multi-resolution maps can be viewed in software such as WorldWide Telescope.
toasty was originally written by Chris Beaumont, benefited from contributions by Clara Brasseur (Space Telescope Science Institute), and is currently maintained as part of the WorldWide Telescope project.
Installation
The easiest way to install toasty is through pip:
pip install toasty
For more information, please see the full toasty installation instructions.
Documentation, Examples, etc.
For documentation and examples, go to:
https://toasty.readthedocs.io/
Contributions
Contributions to toasty are welcome! See the WorldWide Telescope contributors’ guide for applicable information. We use a standard workflow with issues and pull requests. All participants in toasty and the WWT communities must abide by the WWT Code of Conduct.
Release History
Releases of toasty are logged in the file
CHANGELOG.md
on the release
branch of this repository, as well as release listings
maintained by GitHub
and PyPI.
Dependencies
toasty is a Python package so, yes, Python is required.
- astropy if using FITS files or WCS coordinates
- azure-storage-blob >= 12.0 if using the Azure storage backend for pipeline processing
- cython
- filelock
- healpy if using HEALPix maps
- numpy
- pillow
- pyavm if using Astronomy Visualization Metadata tags
- pytest to run the test suite
- PyYAML
- tqdm
- wwt_data_formats >= 0.15
Legalities
toasty is copyright Chris Beaumont, Clara Brasseur, and the WorldWide Telescope Team. It is licensed under the MIT License.
Acknowledgments
toasty is part of the WorldWide Telescope system, a .NET Foundation project managed by the non-profit American Astronomical Society (AAS). Work on WWT has been supported by the AAS, the US National Science Foundation (grants 1550701, 1642446, and 2004840), the Gordon and Betty Moore Foundation, and Microsoft.