jeenalee / tv1d

Total variation denoising algorithms for 1D data.

tv1d

Total variation denoising algorithms for 1d data.

Total Variation Denoising

Total variation (TV) denoising removes fine, potentially spurious noise from a discrete signal while preserving its sharp edges. The technique is well-suited for recovering piecewise constant signals and is often favored for denoising images over alternatives that would smooth edges.

Install

Add this to your Cargo.toml:

[dependencies]
tv1d = "0.1.0"

Example Usage

extern crate tv1d

fn main() {
    let input = vec![13.0, 24.3, 63.41, 13.6];
    let lambda = 3.0;

    let output = tv1d::condat(&input, lambda);
}

Documentation

Read the documentation on Docs.rs.

License

This crate is licensed under MIT license (LICENSE).

Using Rust crate from other languages

Please check out the Rust Book's chapter "Rust Inside Other Languages".

Contribution

See CONTRIBUTING.md!

Denoising Example

Following is a visualization of tv1d::condat with varying lambda applied to Human Death-associated protein 6 (DAXX) transcript variant 1 expression data from UCSC Human Genome database.

"base pair" denotes the position at the transcript. "expression value" denotes the level of expression at a given "base pair" after denoising. "lambda" is the degree of denoising applied to the signals, and 0 is the raw signals.

The plots were generated with ggpy.