ModelF

class lsst.gauss2d.fit.ModelF

Bases: ParametricModel

Attributes Summary

data

mode

outputs

priors

psfmodels

sources

Methods Summary

compute_hessian(self[, transformed, ...])

compute_loglike_grad(self[, include_prior, ...])

evaluate(self[, print, normalize_loglike])

gaussians(self, channel)

offsets_parameters(self)

parameters(self, parameters, paramfilter)

setup_evaluators(self, evaluatormode, ...)

verify_jacobian(self[, findiff_frac, ...])

Attributes Documentation

data
mode
outputs
priors
psfmodels
sources

Methods Documentation

compute_hessian(self: lsst.gauss2d.fit._gauss2d_fit.ModelF, transformed: bool = False, include_prior: bool = True, options: lsst.gauss2d.fit._gauss2d_fit.HessianOptions | None = None, print: bool = False) lsst.gauss2d._gauss2d.ImageF
compute_loglike_grad(self: lsst.gauss2d.fit._gauss2d_fit.ModelF, include_prior: bool = False, print: bool = False, verify: bool = False, findiff_frac: float = 0.0001, findiff_add: float = 0.0001, rtol: float = 0.001, atol: float = 0.001) list[float]
evaluate(self: lsst.gauss2d.fit._gauss2d_fit.ModelF, print: bool = False, normalize_loglike: bool = False) list[float]
gaussians(self: lsst.gauss2d.fit._gauss2d_fit.ModelF, channel: lsst.gauss2d.fit._gauss2d_fit.Channel) lsst.gauss2d._gauss2d.Gaussians
offsets_parameters(self: lsst.gauss2d.fit._gauss2d_fit.ModelF) list[tuple[lsst::modelfit::parameters::ParameterBase<double>, int]]
parameters(self: lsst.gauss2d.fit._gauss2d_fit.ModelF, parameters: list[lsst::modelfit::parameters::ParameterBase<double>] = [], paramfilter: lsst::gauss2d::fit::ParamFilter = None) list[lsst::modelfit::parameters::ParameterBase<double>]
setup_evaluators(self: lsst.gauss2d.fit._gauss2d_fit.ModelF, evaluatormode: lsst.gauss2d.fit._gauss2d_fit.EvaluatorMode = <EvaluatorMode.image: 0>, outputs: list[list[lsst.gauss2d._gauss2d.ImageF]] = [], residuals: list[lsst.gauss2d._gauss2d.ImageF] = [], outputs_prior: list[lsst.gauss2d._gauss2d.ImageF] = [], residuals_prior: lsst.gauss2d._gauss2d.ImageF = None, force: bool = False, print: bool = False) None
verify_jacobian(self: lsst.gauss2d.fit._gauss2d_fit.ModelF, findiff_frac: float = 0.0001, findiff_add: float = 0.0001, rtol: float = 0.001, atol: float = 0.001, max_diff_ll: float = 0) list[str]