lsst.scarlet.lite gee10cc3b42+585e252eca
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Public Member Functions | Public Attributes | Protected Member Functions | List of all members
lsst.scarlet.lite.models.fit_psf.FittedPsfBlend Class Reference
Inheritance diagram for lsst.scarlet.lite.models.fit_psf.FittedPsfBlend:
lsst.scarlet.lite.blend.Blend

Public Member Functions

tuple[int, float] fit (self, int max_iter, float e_rel=1e-4, int min_iter=1, int resize=10)
 
- Public Member Functions inherited from lsst.scarlet.lite.blend.Blend
 __init__ (self, Sequence[Source] sources, Observation observation)
 
tuple[int, int, int] shape (self)
 
Box bbox (self)
 
list[Componentcomponents (self)
 
Image get_model (self, bool convolve=False, bool use_flux=False)
 
float log_likelihood (self)
 
Blend fit_spectra (self, bool clip=False)
 
 parameterize (self, Callable parameterization)
 
None conserve_flux (self, bool mask_footprint=True)
 

Public Attributes

 bbox
 
 observation
 
 it
 
- Public Attributes inherited from lsst.scarlet.lite.blend.Blend
 sources
 
 observation
 
 it
 
 shape
 
 bbox
 

Protected Member Functions

Image _grad_log_likelihood (self)
 

Detailed Description

A blend that attempts to fit the PSF along with the source models.

Member Function Documentation

◆ _grad_log_likelihood()

Image lsst.scarlet.lite.models.fit_psf.FittedPsfBlend._grad_log_likelihood ( self)
protected
Gradient of the likelihood wrt the unconvolved model

Reimplemented from lsst.scarlet.lite.blend.Blend.

◆ fit()

tuple[int, float] lsst.scarlet.lite.models.fit_psf.FittedPsfBlend.fit ( self,
int max_iter,
float e_rel = 1e-4,
int min_iter = 1,
int resize = 10 )
Fit all of the parameters

Parameters
----------
max_iter: int
    The maximum number of iterations
e_rel: float
    The relative error to use for determining convergence.
min_iter: int
    The minimum number of iterations.
resize: int
    Number of iterations before attempting to resize the
    resizable components. If `resize` is `None` then
    no resizing is ever attempted.

Reimplemented from lsst.scarlet.lite.blend.Blend.


The documentation for this class was generated from the following file: