big_o

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.

Examples

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

let (best, all) = bigo::infer_complexity(data).unwrap();

asserteq!(best.name, bigo::Name::Quadratic); asserteq!(best.notation, "O(n^2)"); assertapproxeq::assertapproxeq!(best.params.gain.unwrap(), 1.0, 1e-6); assertapproxeq::assertapprox_eq!(best.params.offset.unwrap(), 0.0, 1e-6); ```