SFFCorrector¶

class
lightkurve.correctors.
SFFCorrector
(lc)¶ Bases:
lightkurve.correctors.regressioncorrector.RegressionCorrector
Special case of
RegressionCorrector
where theDesignMatrix
includes the target’s centroid positions.The design matrix also contains columns representing a spline in time design to capture the intrinsic, longterm variability of the target.
 Parameters
 lc
LightCurve
The light curve that needs to be corrected.
 lc
Attributes Summary
Shorthand for self.design_matrix_collection.
Methods Summary
correct
(self[, centroid_col, centroid_row, …])Find the best fit correction for the light curve.
diagnose
(self)Returns a diagnostic plot which visualizes what happened during the most recent call to
correct()
.diagnose_arclength
(self)Returns a diagnostic plot which visualizes arclength vs flux from most recent call to
correct()
.diagnose_priors
(self)Returns a diagnostic plot visualizing how the bestfit coefficients compare against the priors.
Attributes Documentation

X
¶ Shorthand for self.design_matrix_collection.
Methods Documentation

correct
(self, 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, **kwargs)¶ Find the best fit correction for the light curve.
 Parameters
 centroid_colnp.ndarray of floats (optional)
Array of centroid column positions. If
None
, will use thecentroid_col
attribute of the input light curve by default. centroid_rownp.ndarray of floats (optional)
Array of centroid row positions. If
None
, will use thecentroid_row
attribute of the input light curve by default. windowsint
Number of windows to split the data into to perform the correction. Default 20.
 binsint
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 bspline 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.
 degreeint
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
DesignMatrix
(optional) Additional design matrix to remove, e.g. containing background vectors.
 polyorderint
Deprecated as of Lightkurve v1.4. Use
degree
instead.
 Returns
 corrected_lc
LightCurve
Corrected light curve, with noise removed.
 corrected_lc

diagnose
(self)¶ Returns a diagnostic plot which visualizes what happened during the most recent call to
correct()
.

diagnose_arclength
(self)¶ Returns a diagnostic plot which visualizes arclength vs flux from most recent call to
correct()
.

diagnose_priors
(self)¶ Returns a diagnostic plot visualizing how the bestfit coefficients compare against the priors.
The method will show the results obtained during the most recent call to
correct()
. Ifcorrect()
has not yet been called, aValueError
will be raised. Returns
Axes
The matplotlib axes object.