LinearLSQFitter#
- class astropy.modeling.fitting.LinearLSQFitter(calc_uncertainties=False)[source]#
Bases:
object
A class performing a linear least square fitting. Uses
numpy.linalg.lstsq
to do the fitting. Given a model and data, fits the model to the data and changes the model’s parameters. Keeps a dictionary of auxiliary fitting information.Notes
Note that currently LinearLSQFitter does not support compound models.
Attributes Summary
Methods Summary
__call__
(model, x, y[, z, weights, rcond])Fit data to this model.
Attributes Documentation
- supported_constraints = ['fixed']#
- supports_masked_input = True#
Methods Documentation
- __call__(model, x, y, z=None, weights=None, rcond=None)[source]#
Fit data to this model.
- Parameters:
- model
FittableModel
model to fit to x, y, z
- x
array
Input coordinates
- yarray_like
Input coordinates
- zarray_like, optional
Input coordinates. If the dependent (
y
orz
) coordinate values are provided as anumpy.ma.MaskedArray
, any masked points are ignored when fitting. Note that model set fitting is significantly slower when there are masked points (not just an empty mask), as the matrix equation has to be solved for each model separately when their coordinate grids differ.- weights
array
, optional Weights for fitting. For data with Gaussian uncertainties, the weights should be 1/sigma.
- rcond
float
, optional Cut-off ratio for small singular values of
a
. Singular values are set to zero if they are smaller thanrcond
times the largest singular value ofa
.- equivalencies
list
orNone
, optional, keyword-only List of additional equivalencies that are should be applied in case x, y and/or z have units. Default is None.
- model
- Returns:
- model_copy
FittableModel
a copy of the input model with parameters set by the fitter
- model_copy