Crates.io | kneed |
lib.rs | kneed |
version | 1.0.0 |
source | src |
created_at | 2024-06-29 08:29:54.20457 |
updated_at | 2024-08-24 23:23:39.32664 |
description | Pure rust implementation of Knee-point detection |
homepage | https://github.com/vihu/kneed |
repository | https://github.com/vihu/kneed |
max_upload_size | |
id | 1287221 |
size | 59,231 |
This is a pure rust implementation of Knee-point detection.
The code here aims to be a 1:1 match of kneed.
General usage:
// Provide your x: Vec<f64> and y: Vec<f64>
let x = [1.0, 2.0, 3.0];
let y = [10.0, 20.0, 30.0];
let params = KneeLocatorParams::new(
ValidCurve::Concave,
ValidDirection::Increasing,
InterpMethod::Interp1d,
);
// Instantiate KneeLocator
let kl = KneeLocator::new(x.to_vec(), y.to_vec(), 1.0, params);
// After instantiation, you can invoke the following:
// kl.knee
// kl.knee_y
// kl.norm_knee
// kl.norm_knee_y
// kl.elbow()
// kl.norm_elbow()
// kl.elbow_y()
// kl.norm_elbow_y()
// kl.all_elbows()
// kl.all_norm_elbows()
// kl.all_elbows_y()
// kl.all_norm_elbows_y()
Example from the paper:
let (x, y) = DataGenerator::figure2();
let params = KneeLocatorParams::new(
ValidCurve::Concave,
ValidDirection::Increasing,
InterpMethod::Interp1d,
);
let kneedle = KneeLocator::new(x.to_vec(), y.to_vec(), 1.0, params);
assert_relative_eq!(0.222222222222222, kneedle.knee.unwrap());
assert_relative_eq!(1.8965517241379306, kneedle.knee_y.unwrap());
All credit for the python implementation goes to Kevin Arvai.