pysersic.multiband

Classes

`BaseMultiBandFitter`	Base class for multi-band fitter, for new classes only need to add a sample_param_at_bands function specifying the linking of parameters between bands.
`FitMultiBandPoly`	Base class for multi-band fitter, for new classes only need to add a sample_param_at_bands function specifying the linking of parameters between bands.
`FitMultiBandBSpline`	Base class for multi-band fitter, for new classes only need to add a sample_param_at_bands function specifying the linking of parameters between bands.

Module Contents

class pysersic.multiband.BaseMultiBandFitter(fitter_list: List[pysersic.pysersic.FitSingle] | List[pysersic.pysersic.FitMulti], wavelengths: jax.Array, linked_params: List[str], const_params: List[str] | None = [], band_names: List[str] | None = None, linked_params_range: dict | None = {}, wv_to_save: jax.Array | None = None, rescale_unlinked_priors: bool | None = False)

Bases: pysersic.pysersic.BaseFitter

Base class for multi-band fitter, for new classes only need to add a sample_param_at_bands function specifying the linking of parameters between bands.

fitter_list

n_bands

wavelengths

param_names

wv_av

wv_range

wv_normed

wv_to_save = None

linked_params

const_params = []

unlinked_params

reparam_dict

linked_params_mean

linked_params_scale

linked_params_range

const_prior_dict

data

rms

psf

mask

loss_func

renderer

prior

abstract sample_param_at_bands(name: str) → jax.Array

Function used to sample linked parameters at each band

Parameters:: name (str) – parameter name
Returns:: params_at_bands – parameter values sampled at bands
Return type:: jax.Array

build_model(return_model: bool = False) → callable

build numpyro model for multi-band inference

Parameters:: return_model (bool, optional) – wether or not to save and return observed images, by default False
Returns:: numpyro model
Return type:: callable

class pysersic.multiband.FitMultiBandPoly(fitter_list: List[pysersic.pysersic.FitSingle], wavelengths: jax.Array, linked_params: List[str], const_params: List[str] | None = [], band_names: List[str] | None = None, linked_params_range: dict | None = {}, wv_to_save: jax.Array | None = None, rescale_unlinked_priors: bool | None = False, poly_order: int | None = 2)

Bases: BaseMultiBandFitter

Base class for multi-band fitter, for new classes only need to add a sample_param_at_bands function specifying the linking of parameters between bands.

poly_order = 3

restrict_func(x, hi, low)

sample_param_at_bands(name)

Function used to sample linked parameters at each band

Parameters:: name (str) – parameter name
Returns:: params_at_bands – parameter values sampled at bands
Return type:: jax.Array

class pysersic.multiband.FitMultiBandBSpline(fitter_list: List[pysersic.pysersic.FitSingle], wavelengths: jax.Array, linked_params: List[str], const_params: List[str] | None = [], band_names: List[str] | None = None, linked_params_range: dict | None = {}, wv_to_save: jax.Array | None = None, rescale_unlinked_priors: bool | None = False, N_knots: int | None = 4, spline_k: int | None = 2, pad_knots: bool | None = True)

Bases: BaseMultiBandFitter

Base class for multi-band fitter, for new classes only need to add a sample_param_at_bands function specifying the linking of parameters between bands.

N_knots = 4

spline_k = 2

dmat_bands

dmat_save

sample_param_at_bands(name)

Function used to sample linked parameters at each band

Parameters:: name (str) – parameter name
Returns:: params_at_bands – parameter values sampled at bands
Return type:: jax.Array