Crates.io | statrs-fork |
lib.rs | statrs-fork |
version | 0.17.0 |
source | src |
created_at | 2022-09-17 14:31:54.517234 |
updated_at | 2022-09-17 14:31:54.517234 |
description | Statistical computing library for Rust |
homepage | https://github.com/EgorDm/statrs |
repository | https://github.com/EgorDm/statrs |
max_upload_size | |
id | 668192 |
size | 758,410 |
Should work for both nightly and stable Rust.
NOTE: While I will try to maintain backwards compatibility as much as possible, since this is still a 0.x.x project the API is not considered stable and thus subject to possible breaking changes up until v1.0.0
Statrs provides a host of statistical utilities for Rust scientific computing. Included are a number of common distributions that can be sampled (i.e. Normal, Exponential, Student's T, Gamma, Uniform, etc.) plus common statistical functions like the gamma function, beta function, and error function.
This library is a work-in-progress port of the statistical capabilities in the C# Math.NET library. All unit tests in the library borrowed from Math.NET when possible and filled-in when not.
This library is a work-in-progress and not complete. Planned for future releases are continued implementations of distributions as well as porting over more statistical utilities
Please check out the documentation here
Add the most recent release to your Cargo.toml
[dependencies]
statrs = "0.16"
Statrs comes with a number of commonly used distributions including Normal, Gamma, Student's T, Exponential, Weibull, etc.
The common use case is to set up the distributions and sample from them which depends on the Rand
crate for random number generation
use statrs::distribution::Exp;
use rand::distributions::Distribution;
let mut r = rand::rngs::OsRng;
let n = Exp::new(0.5).unwrap();
print!("{}", n.sample(&mut r));
Statrs also comes with a number of useful utility traits for more detailed introspection of distributions
use statrs::distribution::{Exp, Continuous, ContinuousCDF};
use statrs::statistics::Distribution;
let n = Exp::new(1.0).unwrap();
assert_eq!(n.mean(), Some(1.0));
assert_eq!(n.variance(), Some(1.0));
assert_eq!(n.entropy(), Some(1.0));
assert_eq!(n.skewness(), Some(2.0));
assert_eq!(n.cdf(1.0), 0.6321205588285576784045);
assert_eq!(n.pdf(1.0), 0.3678794411714423215955);
as well as utility functions including erf
, gamma
, ln_gamma
, beta
, etc.
use statrs::statistics::Distribution;
use statrs::distribution::FisherSnedecor;
let n = FisherSnedecor::new(1.0, 1.0).unwrap();
assert!(n.variance().is_none());
Want to contribute? Check out some of the issues marked help wanted
Clone the repo:
git clone https://github.com/statrs-dev/statrs
Create a feature branch:
git checkout -b <feature_branch> master
After commiting your code:
git push -u origin <feature_branch>
Then submit a PR, preferably referencing the relevant issue.
This repo makes use of rustfmt
with the configuration specified in rustfmt.toml
.
See https://github.com/rust-lang-nursery/rustfmt for instructions on installation
and usage and run the formatter using rustfmt --write-mode overwrite *.rs
in
the src
directory before committing.
Please be explicit and and purposeful with commit messages.
Modify test code
test: Update statrs::distribution::Normal test_cdf