big_o 0.1.4

Infers asymptotic computational complexity
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# big_o

[gh-image]: https://github.com/maksym-arutyunyan/big_o/workflows/Rust/badge.svg
[gh-checks]: https://github.com/maksym-arutyunyan/big_o/actions/workflows/rust.yml
[cratesio-image]: https://img.shields.io/crates/v/big_o.svg
[cratesio]: https://crates.io/crates/big_o
[docsrs-image]: https://docs.rs/big_o/badge.svg
[docsrs]: https://docs.rs/big_o

[![big_o GitHub Actions][gh-image]][gh-checks]
[![big_o on crates.io][cratesio-image]][cratesio]
[![big_o on docs.rs][docsrs-image]][docsrs]

Infers asymptotic computational complexity.

`big_o` helps to estimate computational complexity of algorithms by inspecting measurement data (eg. execution time, memory consumption, etc). Users are expected to provide measurement data, `big_o` will try to fit a set of complexity models and return the best fit.

## Example

```rust
use assert_approx_eq::assert_approx_eq;

// f(x) = gain * x ^ 2 + offset
let data = vec![(1., 1.), (2., 4.), (3., 9.), (4., 16.)];

let (complexity, _all) = big_o::infer_complexity(data).unwrap();

assert_eq!(complexity.name, big_o::Name::Quadratic);
assert_eq!(complexity.notation, "O(n^2)");
assert_approx_eq!(complexity.params.gain.unwrap(), 1.0, 1e-6);
assert_approx_eq!(complexity.params.offset.unwrap(), 0.0, 1e-6);
assert!(complexity.rank < big_o::complexity("O(n^3)").unwrap().rank);
```