allan - variance and deviation tools for stability analysis

A Rust implementation of Allan variance and deviation calculations for analyzing the stability and noise characteristics of time-series data. This is particularly useful for characterizing frequency standards, oscillators, gyroscopes, and other precision measurement instruments.

Overview

Allan variance is a method of representing frequency stability in oscillators and other time-series data. Unlike standard deviation, Allan variance converges for most types of noise commonly found in physical systems and can distinguish between different noise types.

This library provides:

• Overlapping Allan variance (AVAR) and Allan deviation (ADEV) calculations
• Modified Allan variance (MVAR) and Modified Allan deviation (MDEV) calculations
• Overlapping Hadamard variance (HVAR) and Hadamard deviation (HDEV) calculations
• Configurable tau (averaging time) ranges with multiple spacing options
• Streaming calculation with efficient circular buffer implementation
• Support for real-time analysis of continuous data streams
• SIMD optimizations (enabled by default) for 3x faster Modified Allan calculations

Example

use allan::{Allan, ModifiedAllan, Hadamard};

// Allan variance/deviation
let mut allan = Allan::new();
for sample in measurements.iter() {
    allan.record(*sample);
}

let tau_1 = allan.get(1).unwrap();
println!("Allan deviation at τ=1: {}", tau_1.deviation().unwrap());
println!("Allan variance at τ=1: {}", tau_1.variance().unwrap());

// Modified Allan variance/deviation (better white PM noise rejection)
let mut modified = ModifiedAllan::new();
for sample in measurements.iter() {
    modified.record(*sample);
}

let tau_1 = modified.get(1).unwrap();
println!("Modified Allan deviation at τ=1: {}", tau_1.deviation().unwrap());
println!("Modified Allan variance at τ=1: {}", tau_1.variance().unwrap());

// Hadamard variance/deviation (3rd difference, better drift rejection)
let mut hadamard = Hadamard::new();
for sample in measurements.iter() {
    hadamard.record(*sample);
}

let tau_1 = hadamard.get(1).unwrap();
println!("Hadamard deviation at τ=1: {}", tau_1.deviation().unwrap());
println!("Hadamard variance at τ=1: {}", tau_1.variance().unwrap());

Documentation

API documentation is available at docs.rs/allan.

License

Licensed under either of

• Apache License, Version 2.0, (LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)
• MIT license (LICENSE-MIT or http://opensource.org/licenses/MIT)

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.