DonutStamp¶
- class lsst.ts.wep.task.DonutStamp(stamp_im: ~lsst.afw.image._maskedImage.MaskedImageF, sky_position: ~lsst.geom.SpherePoint, centroid_position: ~lsst.geom.Point2D, blend_centroid_positions: ~numpy.ndarray, defocal_type: str, defocal_distance: float, detector_name: str, cam_name: str, bandpass: str, archive_element: ~typing.Optional[~lsst.afw.table.io.Persistable] = None, comp_im: ~lsst.ts.wep.cwfs.compensableImage.CompensableImage = <factory>)¶
Bases:
AbstractStampSingle donut stamp
- Parameters:
- stamp_im
lsst.afw.image.MaskedImageF The actual pixel values for the postage stamp
- sky_position
lsst.geom.SpherePoint Position of the center of the stamp. Note the user must keep track of the coordinate system
- centroid_position
lsst.geom.Point2D Position of the center of the stamp in pixels
- blend_centroid_positions
numpy.ndarray Positions of the centroids (in pixels) for sources blended with the central source
- defocal_type
str Defocal state of the stamp. “extra” or “intra” are allowed values.
- defocal_distance
float Defocal offset of the instrument in mm.
- detector_name
str CCD where the donut is found
- cam_name
str Camera name for the stamp image. “LSSTCam” or “LSSTComCam” are available camera names currently.
- bandpass
str The bandpass for the stamp image.
- archive_element
afwTable.io.Persistable, optional Archive element (e.g. Transform or WCS) associated with this stamp. (the default is None.)
- comp_im
CompensableImage, init=False CompensableImage object to create masks for the stamp. This is initialized in the __post_init__ stage of the dataclass.
- mask_comp
afwImage.Mask, init=False Padded Mask for use at the offset planes. This is initialized in the __post_init__ stage of the dataclass.
- mask_pupil
afwImage.Mask, init=False Non-padded mask corresponding to aperture. This is initialized in the __post_init__ stage of the dataclass.
- stamp_im
Attributes Summary
Methods Summary
Calculate the X, Y field position of the centroid in degrees.
factory(stamp_im, metadata, index[, ...])This method is needed to service the FITS reader.
Get the proper camera object for the donuts.
makeMasks(inst, model, boundaryT, ...)Get the binary mask which considers the obscuration and off-axis correction.
Attributes Documentation
Methods Documentation
- calcFieldXY()¶
Calculate the X, Y field position of the centroid in degrees.
- classmethod factory(stamp_im, metadata, index, archive_element=None)¶
This method is needed to service the FITS reader. We need a standard interface to construct objects like this. Parameters needed to construct this object are passed in via a metadata dictionary and then passed to the constructor of this class. They should each point to lists of values.
- Parameters:
- stamp_im
lsst.afw.image.MaskedImage Pixel data to pass to the constructor
- metadata
lsst.daf.base.PropertyList PropertyList containing the information needed by the constructor.
- index
int Index into the lists in
metadata- archive_element
afwTable.io.Persistable, optional Archive element (e.g. Transform or WCS) associated with this stamp. (the default is None.)
- stamp_im
- Returns:
- DonutStamp
An instance of this class
- getCamera()¶
Get the proper camera object for the donuts.
- Returns:
lsst.afw.cameraGeom.CameraCamera object for the exposures.
- Raises:
ValueErrorThe camera is not supported.
- makeMasks(inst, model, boundaryT, maskScalingFactorLocal)¶
Get the binary mask which considers the obscuration and off-axis correction.
- Parameters:
- inst
Instrument Instrument to use.
- model
str Optical model. It can be “paraxial”, “onAxis”, or “offAxis”.
- boundaryT
int Extended boundary in pixel. It defines how far the computation mask extends beyond the pupil mask. And, in fft, it is also the width of Neuman boundary where the derivative of the wavefront is set to zero.
- maskScalingFactorLocal
float Mask scaling factor (for fast beam) for local correction.
- inst
- Returns:
- mask_pupil
afwImage.Mask Non-padded mask for use at the offset planes.
- mask_comp
afwImage.Mask Padded mask for use at the offset planes.
- mask_pupil