VariableArgsFitter#

class stellarphot.transit_fitting.VariableArgsFitter[source]#

Bases: LevMarLSQFitter

A callable class that can be used to fit functions with arbitrary number of positional parameters. This is a modified version of the astropy.modeling.fitting.LevMarLSQFitter fitter.

Methods Summary

__call__(model, *args[, weights, maxiter, ...])

Fit data to this model.

Methods Documentation

__call__(model, *args, weights=None, maxiter=100, acc=1e-07, epsilon=1.4901161193847656e-08, estimate_jacobian=False)[source]#

Fit data to this model.

Parameters:

modelFittableModel: model to fit to x, y, z
xarray: input coordinates
yarray: input coordinates
zarray, optional: input coordinates
weightsarray, optional: Weights for fitting. For data with Gaussian uncertainties, the weights should be 1/sigma.

Changed in version 5.3: Calculate parameter covariances while accounting for weights as “absolute” inverse uncertainties. To recover the old behavior, choose weights=None.
maxiterint: maximum number of iterations
accfloat: Relative error desired in the approximate solution
epsilonfloat: A suitable step length for the forward-difference approximation of the Jacobian (if model.fjac=None). If epsfcn is less than the machine precision, it is assumed that the relative errors in the functions are of the order of the machine precision.
estimate_jacobianbool: If False (default) and if the model has a fit_deriv method, it will be used. Otherwise the Jacobian will be estimated. If True, the Jacobian will be estimated in any case.
equivalencieslist or None, optional, keyword-only: List of additional equivalencies that are should be applied in case x, y and/or z have units. Default is None.
filter_non_finitebool, optional: Whether or not to filter data with non-finite values. Default is False
inplacebool, optional: If False (the default), a copy of the model with the fitted parameters set will be returned. If True, the returned model will be the same instance as the model passed in, and the parameter values will be changed inplace.

Returns:

fitted_modelFittableModel: If inplace is False (the default), this is a copy of the input model with parameters set by the fitter. If inplace is True, this is the same model as the input model, with parameters updated to be those set by the fitter.