lightkurve.correctors.corrector.Corrector.correct#

abstract Corrector.correct(cadence_mask: numpy.array = None, optimize: bool = False) → lightkurve.lightcurve.LightCurve[source]#

Returns a LightCurve from which systematic noise has been removed.

This method shall:

  • accept meaningful parameters that can be used to tune the correction, including:

    • optimize: should an optimizer be used to tune the parameters?

    • cadence_mask: flags cadences to be used to fit the noise model.

  • store all parameters as object attributes (e.g. self.optimize, self.cadence_mask);

  • store helpful diagnostic information as object attributes;

  • store the result in the self.corrected_lc attribute;

  • return self.corrected_lc.

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