class astropy.modeling.fitting.SLSQPLSQFitter[source]

Bases: astropy.modeling.fitting.Fitter

SLSQP optimization algorithm and least squares statistic.


A linear model is passed to a nonlinear fitter

Attributes Summary


Methods Summary

__call__(self, model, x, y[, z, weights]) Fit data to this model.

Attributes Documentation

supported_constraints = ['bounds', 'eqcons', 'ineqcons', 'fixed', 'tied']

Methods Documentation

__call__(self, model, x, y, z=None, weights=None, **kwargs)[source]

Fit data to this model.

model : FittableModel

model to fit to x, y, z

x : array

input coordinates

y : array

input coordinates

z : array (optional)

input coordinates

weights : array (optional)

Weights for fitting. For data with Gaussian uncertainties, the weights should be 1/sigma.

kwargs : dict

optional keyword arguments to be passed to the optimizer or the statistic

verblevel : int

0-silent 1-print summary upon completion, 2-print summary after each iteration

maxiter : int

maximum number of iterations

epsilon : float

the step size for finite-difference derivative estimates

acc : float

Requested accuracy

equivalencies : list or None, optional and keyword-only argument

List of additional equivalencies that are should be applied in case x, y and/or z have units. Default is None.

model_copy : FittableModel

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