ModelInitializer

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

Bases: ABC, BaseModel

An interface for a configurable model initializer based on priors and optional external data.

Attributes Summary

model_config

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

Methods Summary

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[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

abstract 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.