Module quality_benchmarking

Module to perform quality benchmarking of augmenters This module provides functionality to evaluate and compare the quality of different data augmentation techniques. Currently, it includes using the Dynamic Time Warping (DTW) algorithm to measure the similarity between original and augmented time series data.

Examples

use fraug::quality_benchmarking::dtw;
use fraug::augmenters::{Jittering, Augmenter};
use fraug::Dataset;

let original_series = vec![1.0, 2.0, 3.0, 4.0, 5.0];
let original_reference = original_series.clone();

let augmenter = Jittering::new(0.1);
augmenter.augment_one(&original_series);
 
let (distance, path) = dtw(&original_series, &original_reference);

Functions

dtw

Implementation of Dynamic Time Warping (DTW) algorithm. This function computes the DTW distance between two sequences and returns the distance along with the optimal path.