Minimum component filter for Gts.
minimum_component(self, mask_period=, p=1, fcut=None, Q=None, in_place=False, verbose=True)¶
Minimum component filtering for Gts.
Minimum component filtering is useful for determining the background component of a signal in the presence of spikes
mask_periods – periods (list or list of lists) which should be ignored for smoothing
p – integer (optional). polynomial degree to be used for the fit (default = 1)
fcut – float (optional). the cutoff frequency for the low-pass filter. Default value is f_nyq / sqrt(N)
Q – float (optional). the strength of the low-pass filter. Larger Q means a steeper cutoff. default value is 0.1 * fcut
in_place – if True then replace the current time series
verbose – boolean, verbose mode
the filtered time series
This code follows the procedure explained in the book “Practical Statistics for Astronomers” by Wall & Jenkins book, as well as in Wall, J, A&A 122:371, 1997