grid_from_epsfs#
- photutils.psf.grid_from_epsfs(epsfs, grid_xypos=None, meta=None)[source]#
Create a GriddedPSFModel from a list of ImagePSF models.
Given a list of
ImagePSF
models, this function will return aGriddedPSFModel
. The fiducial points for each input ImagePSF can either be set on each individual model by setting the ‘x_0’ and ‘y_0’ attributes, or provided as a list of tuples (grid_xypos
). If agrid_xypos
list is provided, it must match the length of input EPSFs. In either case, the fiducial points must be on a grid.Optionally, a
meta
dictionary may be provided for the output GriddedPSFModel. If this dictionary contains the keys ‘grid_xypos’, ‘oversampling’, or ‘fill_value’, they will be overridden.Note: If set on the input ImagePSF (x_0, y_0), then
origin
must be the same for each input EPSF. Additionally data units and dimensions must be for each input EPSF, and values forflux
andoversampling
, andfill_value
must match as well.- Parameters:
- epsfslist of
photutils.psf.ImagePSF
A list of ImagePSF models representing the individual PSFs.
- grid_xyposlist, optional
A list of fiducial points (x_0, y_0) for each PSF. If not provided, the x_0 and y_0 of each input EPSF will be considered the fiducial point for that PSF. Default is None.
- metadict, optional
Additional metadata for the GriddedPSFModel. Note that, if they exist in the supplied
meta
, any values under the keysgrid_xypos
,oversampling
, orfill_value
will be overridden. Default is None.
- epsfslist of
- Returns:
- GriddedPSFModel:
photutils.psf.GriddedPSFModel
The gridded PSF model created from the input EPSFs.
- GriddedPSFModel: