reproject.mosaicking.reproject_and_coadd(input_data, output_projection, shape_out=None, input_weights=None, hdu_in=None, reproject_function=None, hdu_weights=None, combine_function='mean', match_background=False, background_reference=None, **kwargs)[source]

Given a set of input images, reproject and co-add these to a single final image.

This currently only works with 2-d images with celestial WCS.


One or more input datasets to reproject and co-add. This should be an iterable containing one entry for each dataset, where a single dataset is one of:

  • The name of a FITS file

  • An HDUList object

  • An image HDU object such as a PrimaryHDU, ImageHDU, or CompImageHDU instance

  • A tuple where the first element is an ndarray and the second element is either a WCS or a Header object

  • An NDData object from which the .data and .wcs attributes will be used as the input data.

output_projectionWCS or Header

The output projection, which can be either a WCS or a Header instance.

shape_outtuple, optional

If output_projection is a WCS instance, the shape of the output data should be specified separately.


If specified, this should be an iterable with the same length as input_data, where each item is one of:

hdu_inint or str, optional

If one or more items in input_data is a FITS file or an HDUList instance, specifies the HDU to use.


The function to use for the reprojection

combine_function{ ‘mean’, ‘sum’, ‘median’ }

The type of function to use for combining the values into the final image.


Whether to match the backgrounds of the images.

background_referenceNone or int

If None, the background matching will make it so that the average of the corrections for all images is zero. If an integer, this specifies the index of the image to use as a reference.


Keyword arguments to be passed to the reprojection function.