InitialGuessIterativeNonlinearLSTSQPSF.fit_lstsq¶
giant.point_spread_functions.psf_meta:
- classmethod InitialGuessIterativeNonlinearLSTSQPSF.fit_lstsq(x, y, z)[source]¶
This fits a PSF to a surface using iterative non-linear least squares estimation.
The estimation in this function is performed iteratively. First, a non-iterative fit is performed using the super class’s fit method. This initial fit is then refined using iterative non-linear least squares to remove biases that might have been introduced in the non-iterative fit..
If the fit is unsuccessful due to a rank deficient matrix then
update_states()will be called which will likely result in the state parameters being set to NaN.- Parameters:
x (Sequence | ndarray) – The x values underlying the surface the PSF is to be fit to
y (Sequence | ndarray) – The y values underlying the surface the PSF is to be fit to
z (Sequence | ndarray) – The z or “height” values of the surface the PSF is to be fit to
- Returns:
The initialized PSF with values according to the fit
- Return type: