nectarchain.trr_verification_package.flatfield_source_characterization.optimize_with_outlier_rejection_variance#
- optimize_with_outlier_rejection_variance(sigma, data, minuit, camera)[source]#
Fit a 2D Gaussian with an additional intrinsic variance term V_int, using iterative outlier rejection.
- Parameters:
- sigmanumpy.ma.MaskedArray
Uncertainty on the data.
- datanumpy.ma.MaskedArray
Illumination data.
- minuitiminuit.Minuit or list
Initial parameter values for the fit.
- cameractapipe.instrument.CameraGeometry
Camera geometry in the EngineeringCameraFrame.
- Returns:
- n_pe_varnumpy.ma.MaskedArray
Outlier-masked illumination data.
- modelnumpy.ndarray
Best-fit 2D Gaussian model.
- minuit_newiminuit.Minuit
Minuit fit result including V_int.
- residualsnumpy.ndarray
Normalised residuals.