hampel

Sequential outlier detection and removal using Hampel identifiers.

It supports f32 and f64.

Usage

Add this to your Cargo.toml:

[dependencies]
hampel = "0.2"
#features = ["extrapolation"]  <-- At your option

extrapolation feature

When this feature is enabled, linear extrapolated values are returned when outliers are detected. If not enabled, the median value of the window is returned.

Example

use hampel::Window;

fn main() {
    // Window size: 5 (>= 3)
    // Initialization value of window: 0.0
    // Threshold: Median of the window ±3σ.
    let mut filter = Window::<f64, 5>::new(0.0, 3.0);
    
    let input_vals = [0.0; 100];  // <- Containing outliers
    let mut filtered_vals = [0.0; 100];
    for (i, val) in input_vals.iter().enumerate() {
        filtered_vals[i] = filter.update(*val);
    }
    // filtered_vals <-- Outliers have been removed
}

Sample images

License

Licensed under either of Apache License, Version 2.0 or MIT License at your option.

Contribution

Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.