VariableArgsFitter

class stellarphot.transit_fitting.VariableArgsFitter

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)

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

Returns:

model_copyFittableModel

a copy of the input model with parameters set by the fitter