lightkurve.correctors.RegressionCorrector.correct#
- RegressionCorrector.correct(design_matrix_collection, cadence_mask=None, sigma=5, niters=5, propagate_errors=False)[source]#
Find the best fit correction for the light curve.
- Parameters
- design_matrix_collection
DesignMatrixorDesignMatrixCollection One or more design matrices. Each matrix must have a shape of (time, regressors). The columns contained in each matrix must be known to correlate with additive noise components we want to remove from the light curve.
- cadence_masknp.ndarray of bools (optional)
Mask, where True indicates a cadence that should be used.
- sigmaint (default 5)
Standard deviation at which to remove outliers from fitting
- nitersint (default 5)
Number of iterations to fit and remove outliers
- propagate_errorsbool (default False)
Whether to propagate the uncertainties from the regression. Default is False. Setting to True will increase run time, but will sample from multivariate normal distribution of weights.
- design_matrix_collection
- Returns
- corrected_lc
LightCurve Corrected light curve, with noise removed.
- corrected_lc