savitzkygolay

Package savitzkygolay provides a filter on a set of data which provides an effective way of smoothing data that generally follows curves found in polynomials.

Download:

go get github.com/pconstantinou/savitzkygolay

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Package savitzkygolay provides a filter on a set of data which provides an effective way of smoothing data that generally follows curves found in polynomials. It is particularly good alternative to a moving average since it does not introduce a delay proportial to about half the window length.

Example:

noise := 15.0
xs := make([]float64, testSize, testSize)
ys := make([]float64, testSize, testSize)
for i := range xs {
	ys[i] = 20 * math.Sin(float64(i)/math.Pi/6) +
				(rand.Float64() * noise) - noise/2.0)
	xs[i] = float64(i)
}

filter, err := savitzkygolay.NewFilterWindow(11)
sgy, err := filter.Process(ys, xs)

Filter interface may be retained to avoid the overhead of pre-computing the polynomials however the size is proportial to the square of the window size.

The filter run on O(number of elements * size of window)

Project unit tests generate outputs which illustrate the filter.

The Go implementation was based on the JavaScript implementation:

https://github.com/mljs/savitzky-golay

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Automatically generated by autoreadme on 2020.05.13