CellPointSpreadFunction#

class lsst.images.cells.CellPointSpreadFunction(array, bounds, resampling_kernel='lanczos5')#

Bases: PointSpreadFunction

A PSF model that is at least approximately constant over cells.

Parameters:

array (ndarray) – A 4-d array of PSF kernel images with with shape (n_cells_y, n_cells_x, psf_shape_y, psf_shape_x).
bounds (CellGridBounds) – Description of the cell grid and any missing cells. Array entries for missing cells should be NaN.
resampling_kernel (Literal['lanczos3', 'lanczos5'], default: 'lanczos5') – Name of the resampling kernel to use when shifting the kernel image into the stellar image.

Notes

Unlike most PSF model types, CellPointSpreadFunction can be subset via slicing:

a bounding Box for a subimage, which returns a new PSF with only the cells that cover that subimage;
a CellIJ index, which returns the kernel image for that cell.

Attributes Summary

`bounds`	The bounds where the PSF can be evaluated (`CellGridBounds`).
`grid`	The grid that defines the PSF's cells (`CellGrid`).
`kernel_bbox`	Bounding box of all images returned by `compute_kernel_image`.

Methods Summary

`compute_kernel_image`(*, x, y)	Evaluate the PSF model into an image suitable for convolution.
`compute_stellar_bbox`(*, x, y)	Return the bounding box of the image that would be returned by `compute_stellar_image`.
`compute_stellar_image`(*, x, y)	Evaluate the PSF model into an image suitable for comparison with the image of an astrophysical point source.
`from_legacy`(legacy_psf[, bounds])	Make a PSF object from a legacy `lsst.afw.detection.Psf` instance.
`serialize`(archive)
`to_legacy`()	Convert to a legacy `lsst.cell_coadds.StitchedPsf` object.

Attributes Documentation

bounds#: The bounds where the PSF can be evaluated (CellGridBounds).

grid#

The grid that defines the PSF’s cells (CellGrid).

Notes

This is usually (but is not guaranteed to be) the grid for a full patch, even when the PSF only covers a subimage.

kernel_bbox#

Methods Documentation

compute_kernel_image(*, x, y)#

Evaluate the PSF model into an image suitable for convolution.

Parameters:

x (float) – Column position coordinate to evaluate at.
y (float) – Row position coordinate to evaluate at.

Returns:

An image of the PSF, centered on the center of the center pixel, which is defined to be (0, 0) by the image’s origin.

Return type:

Image

compute_stellar_bbox(*, x, y)#

Return the bounding box of the image that would be returned by compute_stellar_image.

Parameters:

x (float) – Column position coordinate to evaluate at.
y (float) – Row position coordinate to evaluate at.

Returns:

The bounding box of the image that would be returned by compute_stellar_image at the given point.

Return type:

Box

compute_stellar_image(*, x, y)#

Evaluate the PSF model into an image suitable for comparison with the image of an astrophysical point source.

Parameters:

x (float) – Column position coordinate to evaluate at.
y (float) – Row position coordinate to evaluate at.

Returns:

An image of the PSF, centered on the given coordinates, just like the postage stamp of a star would be.

Return type:

Image

classmethod from_legacy(legacy_psf, bounds=None)#

Make a PSF object from a legacy lsst.afw.detection.Psf instance.

Parameters:

legacy_psf (TypeAliasType) – Legacy PSF object.
bounds (Bounds | None, default: None) – The region where this PSF model is valid.

Returns:

The converted PSF object.

Return type:

PointSpreadFunction

Notes

This base class method is a factory dispatch function that automatically selects the right PointSpreadFunction subclass to use. When that is already known, a subclass from_legacy method can be called instead.

serialize(archive)#

Parameters:: archive (OutputArchive[Any])
Return type:: CellPointSpreadFunctionSerializationModel

to_legacy()#

Convert to a legacy lsst.cell_coadds.StitchedPsf object.

Return type:: TypeAliasType