FittingWithOutlierRemoval

class astropy.modeling.fitting.FittingWithOutlierRemoval(fitter, outlier_func, niter=3, **outlier_kwargs)

Bases: object

This class combines an outlier removal technique with a fitting procedure. Basically, given a number of iterations niter, outliers are removed and fitting is performed for each iteration.

Parameters:

fitter : An Astropy fitter

An instance of any Astropy fitter, i.e., LinearLSQFitter, LevMarLSQFitter, SLSQPLSQFitter, SimplexLSQFitter, JointFitter.

outlier_func : function

A function for outlier removal.

niter : int (optional)

Number of iterations.

outlier_kwargs : dict (optional)

Keyword arguments for outlier_func.

Methods Summary

__call__(model, x, y[, z, weights])

Parameters:

Methods Documentation

__call__(model, x, y, z=None, weights=None, **kwargs)

Parameters:

model : FittableModel

An analytic model which will be fit to the provided data. This also contains the initial guess for an optimization algorithm.

x : array-like

Input coordinates.

y : array-like

Data measurements (1D case) or input coordinates (2D case).

z : array-like (optional)

Data measurements (2D case).

weights : array-like (optional)

Weights to be passed to the fitter.

kwargs : dict (optional)

Keyword arguments to be passed to the fitter.

Returns:

filtered_data : numpy.ma.core.MaskedArray

Data used to perform the fitting after outlier removal.

fitted_model : FittableModel

Fitted model after outlier removal.