11.9.3. astroML.filters.min_component_filter¶
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astroML.filters.min_component_filter(x, y, feature_mask, p=1, fcut=None, Q=None)[source]¶ Minimum component filtering
Minimum component filtering is useful for determining the background component of a signal in the presence of spikes
- Parameters
- xarray_like
1D array of evenly spaced x values
- yarray_like
1D array of y values corresponding to x
- feature_maskarray_like
1D mask array giving the locations of features in the data which should be ignored for smoothing
- pinteger (optional)
polynomial degree to be used for the fit (default = 1)
- fcutfloat (optional)
the cutoff frequency for the low-pass filter. Default value is f_nyq / sqrt(N)
- Qfloat (optional)
the strength of the low-pass filter. Larger Q means a steeper cutoff default value is 0.1 * fcut
- Returns
- y_filteredndarray
The filtered version of y.
Notes
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