---
id: reproject
version: "0.21.0"
license: BSD 3-Clause
license_treatment: permissive
maintenance: active
---

# reproject — Reproject astronomical images

License: permissive · Maintenance: active · Downloads: 162.2K/mo

## What it is and what it does

Reproject is a Python package for re-gridding astronomical images from one world coordinate system to another—changing pixel resolution, orientation, or coordinate frame. It implements three distinct reprojection techniques: simple interpolation (similar to SWARP), the adaptive anti-aliased algorithm from DeForest (2004), and exact pixel overlap calculation on the celestial sphere (similar to Montage). It also supports reprojection to and from HEALPIX projections via astropy-healpix.

The package depends on a substantial stack of scientific Python libraries (numpy, scipy, astropy, astropy-healpix) and integrates with dask, dask-image, zarr, and fsspec for handling larger datasets. It is actively maintained, requires Python 3.11 or later, and is distributed under a permissive BSD 3-Clause license. Installation involves pre-built wheels for standard platforms, though the compiled dependencies add moderate friction.

Use it for:

- Align multiple astronomical survey images to a common pixel grid and coordinate system before stacking or analysis.
- Convert celestial observations between different projections (e.g., tangent-plane to HEALPIX) for survey-wide processing.
- Resample high-resolution imaging data to match lower-resolution reference frames while preserving flux.
- Prepare multi-wavelength observations from different telescopes for joint analysis by harmonizing their coordinate systems.
- Generate footprint maps showing valid data coverage after reprojection to a target coordinate frame.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Reproject astronomical images between different world coordinate systems and pixel grids using interpolation, adaptive anti-aliasing, or exact pixel overlap methods, with support for HEALPIX projections.

Yes, if you work with astronomical images and need to align them across different coordinate systems or resolutions. The package offers a well-maintained, permissive-licensed solution with multiple reprojection algorithms and HEALPIX support. Medium install friction is acceptable for scientific workflows. No known security vulnerabilities.

## Install

pip install reproject
uv add reproject
poetry add reproject

## Installing reproject

Before you install: Medium install friction due to 10 runtime dependencies including compiled packages (numpy, scipy, astropy). Pre-built wheels available for current Python versions on major platforms. Active maintenance with recent release.

License in practice: BSD 3-Clause is permissive; you can use, modify, and distribute this package freely in commercial and private projects provided you include the license notice.

Quickstart:

pip install reproject

from reproject import reproject_interp
from astropy.io import fits

data, header = fits.getdata('input.fits', header=True)
output_data, footprint = reproject_interp((data, header), target_header)

Requires Python >= 3.11. Compiled dependencies (numpy, scipy, astropy) must be installed; pre-built wheels handle this on standard platforms.

Verify before relying:

- Whether the package handles large datasets efficiently with dask and zarr integration beyond basic reprojection.
- Performance characteristics and memory requirements for typical astronomical survey data sizes.
- Specific accuracy or speed trade-offs between the three implemented reprojection algorithms.

## Package facts

- License: BSD 3-Clause (permissive)
- Python support: supports_current
- Install friction: medium
- Maintenance: active
- Downloads: 162.2K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

astronomical image reprojection, world coordinate system transformation, celestial image regridding, HEALPIX projection, image coordinate remapping, astronomical coordinate conversion, pixel grid alignment, astronomy, image-processing, coordinate-systems

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