InstallGaussianPsfTask¶

InstallGaussianPsfTask installs a Gaussian PSF model in an exposure.

Processing summary¶

InstallGaussianPsfTask installs a Gaussian PSF model in an exposure, creating a new PSF with the same sigma and width if a PSF already exists for the exposure. If there is not a PSF model for the exposure, the sigma and width are taken from the config.

Python API summary¶

from lsst.meas.algorithms.installGaussianPsf import InstallGaussianPsfTask

classInstallGaussianPsfTask(config=None, name=None, parentTask=None, log=None): Install a Gaussian PSF model in an exposure...

attributeconfig: Access configuration fields and retargetable subtasks.

methodrun(exposure): Set exposure’s PSF to a simple PSF model...

See also

See the InstallGaussianPsfTask API reference for complete details.

Retargetable subtasks¶

No subtasks.

Configuration fields¶

fwhm¶

Default: 3.5322300675464238
Field type: float Field

Estimated FWHM of simple Gaussian PSF model, in pixels. Ignored if input exposure has a PSF model.

width¶

Default: 11
Field type: int RangeField
Range: [1,inf)

Width and height of PSF model, in pixels. Must be odd.

Examples¶

from lsst.afw.image import ExposureF
from lsst.meas.algorithms.installGaussianPsf import InstallGaussianPsfTask, FwhmPerSigma

exposure = ExposureF(100, 100)
task = InstallGaussianPsfTask()
task.run(exposure=exposure)

 # This particular exposure had no PSF model to begin with, so the new PSF model
 # uses the config's FWHM. However, measured FWHM is based on the truncated
 # PSF image, so it does not exactly match the input
 center = exposure.getBBox().getCenter()
 measFwhm = exposure.getPsf().computeShape(center).getDeterminantRadius() * FwhmPerSigma
 assert abs(measFwhm - task.config.fwhm) < 1e-3