- SFFCorrector.correct(centroid_col=None, centroid_row=None, windows=20, bins=5, timescale=1.5, breakindex=None, degree=3, restore_trend=False, additional_design_matrix=None, polyorder=None, sparse=False, **kwargs)¶
Find the best fit correction for the light curve.
- centroid_colnp.ndarray of floats (optional)
Array of centroid column positions. If
None, will use the
centroid_colattribute of the input light curve by default.
- centroid_rownp.ndarray of floats (optional)
Array of centroid row positions. If
None, will use the
centroid_rowattribute of the input light curve by default.
Number of windows to split the data into to perform the correction. Default 20.
Number of “knots” to place on the arclength spline. More bins will increase the number of knots, making the spline smoother in arclength. Default 10.
- timescale: float
Time scale of the b-spline fit to the light curve in time, in units of input light curve time.
- breakindexNone, int or list of ints (optional)
Optionally the user can break the light curve into sections. Set break index to either an index at which to break, or list of indicies.
The degree of polynomials in the splines in time and arclength. Higher values will create smoother splines. Default 3.
- 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
- restore_trendbool (default False)
Whether to restore the long term spline trend to the light curve
- 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.
Additional design matrix to remove, e.g. containing background vectors.
Deprecated as of Lightkurve v1.4. Use
Corrected light curve, with noise removed.