torchfits
FITS I/O for PyTorch: read and write FITS as tensors and tables — cutouts, predicate filters, and a shell CLI (C++ engine, vendored CFITSIO).
Prebuilt binary wheels for Python 3.10–3.14 on PyTorch 2.13.x (the wheel ABI lane) — Linux (x86_64, aarch64) and macOS (Apple Silicon arm64), with vendored CFITSIO.
Docs: stable · edge (main tip)
Install
pip install torchfits
Prebuilt wheels automatically enable GPU acceleration (CUDA on Linux, MPS on macOS) when available, or fall back to CPU. For CPU-only installs, custom CUDA builds, or other PyTorch versions, see the Installation guide.
At a glance
| Task | API |
|---|---|
| Image → tensor | torchfits.read_tensor("img.fits", device="cuda") |
| Write a tensor | torchfits.write("out.fits", tensor) |
| Filter a catalog | torchfits.table.read(..., where="MAG < 20") |
| Columns as tensors | torchfits.table.read_torch(..., where=...) |
| Open a MEF | with torchfits.open("mef.fits") as hdul: … |
| Train | FitsImageDataset + make_loader(..., num_workers=4) |
| Shell | torchfits info / header / convert / cutout / … |
Quick start
import torchfits
tensor = torchfits.read_tensor("image.fits", hdu=0, device="cpu")
table = torchfits.table.read(
"catalog.fits",
columns=["RA", "DEC", "MAG_G"],
where="MAG_G < 20.0",
)
torchfits info science.fits
torchfits convert catalog.fits out.parquet --hdu 1
torchfits cutout 'science.fits[100:256,100:256]' cutout.fits
Learn more
| Documentation | Quick start, Python workflows, API, CLI |
| Python workflows | Which API for images, tables, cutouts, training |
| Examples | Runnable scripts + transform plots |
| Benchmarks | Methodology and scorecards |
| Changelog | Release notes |
Develop
Pixi-first (do not use bare python for project work):
git clone https://github.com/astroai/torchfits.git
cd torchfits
pixi install
pixi run preflight-push # fast gate while editing
pixi run test # full unit suite
pixi run ci-local # pre-push parity
Agent conventions: AGENTS.md. Release process: docs/release.md.
License
1 maintainer
Release files for torchfits 1.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distributions (wheels)
Total release size: 16.7 MB
Release files / torchfits-1.1.0-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
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| Size | 1.2 MB |
| Tags | CPython 3.14 Linux glibc 2.27+ x86-64 Linux glibc 2.28+ x86-64 |
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