BasicModelInitializer

class lsst.meas.extensions.multiprofit.fit_coadd_multiband.BasicModelInitializer(*, inputs: dict[str, ~typing.Any] = <factory>, priors_shape_mag: dict = <factory>)

Bases: ModelInitializer

A generic model initializer that should work on most kinds of models with a single source.

Attributes Summary

model_config

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

Methods Summary

get_centroid_and_shape(source, catexps, ...)	Get the centroid and shape for a source.
get_params_init(model)	Return the free and/or centroid parameters for a model.
get_priors_type(model)	Return the list of priors of known type, by type.
initialize_model(model, source, catexps, ...)	Initialize a MultiProFit model for a single object corresponding to a row in a catalog.

Attributes Documentation

model_config: ClassVar[pydantic.ConfigDict] = {'arbitrary_types_allowed': True, 'extra': 'forbid', 'frozen': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

Methods Documentation

get_centroid_and_shape(source: Mapping[str, Any], catexps: list[CatalogExposureSourcesABC], config_data: CatalogSourceFitterConfigData, values_init: Mapping[ParameterD, float] | None = None) → tuple[tuple[float, float], tuple[float, float, float]]

Get the centroid and shape for a source.

Parameters

source

A mapping with fields expected to be populated in the corresponding source catalog for initialization.

catexps

A list of (source and psf) catalog-exposure pairs.

config_data

Configuration settings and data for fitting and output.

values_init

Initial parameter values from the model configuration.

Returns

centroid

The x- and y-axis centroid values.

sig_x, sig_y, rho

The x- and y-axis Gaussian sigma and rho values defining the estimated elliptical shape of the source.

get_params_init(model: ModelD | ModelF) → tuple[ParameterD]

Return the free and/or centroid parameters for a model.

Parameters

model

The model to return parameters for.

Returns

parameters

The ordered list of parameters for the model.

get_priors_type(model: ModelD | ModelF) → tuple[tuple[GaussianPrior], tuple[ShapePrior]]

Return the list of priors of known type, by type.

Parameters

model

The model to return priors for.

Returns

priors_gauss

A list of all of the Gaussian priors, in the order they occurred.

priors_shape

A list of all of the shape priors, in the order they occurred.

initialize_model(model: ModelD | ModelF, source: Mapping[str, Any], catexps: list[CatalogExposureSourcesABC], config_data: CatalogSourceFitterConfigData, values_init: Mapping[ParameterD, float] | None = None, **kwargs)

Initialize a MultiProFit model for a single object corresponding to a row in a catalog.

Parameters

model

The model to initialize parameter values for.

source

A mapping with fields expected to be populated in the corresponding source catalog for initialization.

catexps

Per-band catalog-exposure pairs.

config_data

Fitter configuration and data.

values_init

Default initial values for parameters.

**kwargs

Additional keyword arguments for any purpose.