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[ascl:1601.012] SavGolFilterCov: Savitzky Golay filter for data with error covariance

A Savitzky–Golay filter is often applied to data to smooth the data without greatly distorting the signal; however, almost all data inherently comes with noise, and the noise properties can differ from point to point. This python script improves upon the traditional Savitzky-Golay filter by accounting for error covariance in the data. The inputs and arguments are modeled after scipy.signal.savgol_filter.

Code site:
https://github.com/surhudm/savitzky_golay_with_errors
Used in:
http://adsabs.harvard.edu/abs/2016arXiv160106063M
Bibcode:
2016ascl.soft01012M

Views: 2403

ascl:1601.012
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