This library provides an implementation of the Whittaker-Eilers smoothing algorithm in Go. It is designed to smooth time series data or other sequences, offering support for both equally and non-equally spaced data. The library is particularly useful for reducing noise in data while preserving important signals.

• Whittaker-Eilers smoothing for sequences of float64.
• Support for both equally and non-equally spaced data.
• Customizable smoothing parameters.

To use this library, first ensure you have Go installed on your system. Then, you can install the library using go get:

go get -u github.com/njern/wte

package main

import (
    "fmt"
    "github.com/njern/wte"
)

func main() {
    data := []float64{1, 2, 3, 4, 5, 6, 7, 8, 9, 10}
    lambda := 10.0
    order := 2

    // For equally spaced data, pass nil for spacing
    smoothed, err := wte.Smooth(data, lambda, order, nil)
    if err != nil {
        panic(err)
    }

    fmt.Println("Smoothed data:", smoothed)
}

Contributions to improve this library are welcome. Feel free to fork the repository, make your changes, and submit a pull request.

This library is licensed under the MIT License.

• I was inspired to develop this library after reading The perfect way to smooth your noisy data by Andrew Bowell and used his (excellent) Rust library to generate the test cases.
• This library was developed using the gonum package for Go matrix operations. Special thanks to the Gonum contributors.