Welcome to dfreproject’s documentation!¶
dfreproject is a Python package for reprojecting astronomical images. The code runs using torch in order to speed up calculations.
The idea behind this package was to make a stripped down version of the reproject package affiliated with astropy in order to reduce computational time. We achieve approximately 20X faster computations with this package using the GPU and 10X using the CPU for images taken by the Dragonfly Telephoto Array. Take a look at the demos for an example. We note that the only projection we currently support is the Tangential Gnomonic projection which is the most popular in optical astronomy. If you have need for this package to work with another projection geometry, please open a GitHub ticket.
For the sake of transparency of the calculations dfreproject performs, we’ve written out the computations at each step in the methodology section file.
You can quickly run dfreproject with the following:
from astropy.io import fits
from astropy.wcs import WCS
from dfreproject import calculate_reprojection
# Load source and target images
source_hdu = fits.open('source_image.fits')[0]
target_hdu = fits.open('target_grid.fits')[0]
target_wcs = WCS(target_hdu.header)
# Perform dfreproject with bilinear interpolation
reprojected = calculate_reprojection(
source_hdus=source_hdu,
target_wcs=target_wcs,
shape_out=target_hdu.data.shape,
order='bilinear'
)
# Save as FITS
output_hdu = fits.PrimaryHDU(data=reprojected)
output_hdu.header.update(target_wcs.to_header())
output_hdu.writeto('reprojected_image.fits', overwrite=True)
If you use this package, please cite our Zenodo DOI:
Performance Tips¶
If you are running this for several frames, you can pass them as a batched pytorch tensor.
If you have access to a GPU set device=’cuda’.
The ‘bilinear’ option for the interpolation algorithm is typically more than sufficient.
Note: Claude.ai was used in preparing the docstrings for the functions.