# StreamHist
[![ci-badge](https://github.com/jettify/streamhist/workflows/CI/badge.svg)](https://github.com/jettify/streamhist/actions?query=workflow%3ACI)
[![Crates.io](https://img.shields.io/crates/v/streamhist.svg)](https://crates.io/crates/streamhist)
[![Documentation](https://docs.rs/streamhist/badge.svg)](https://docs.rs/streamhist/)
A rust implementation of a streaming centroid histogram algorithm found in
[Streaming Parallel Decision Trees](http://jmlr.org/papers/volume11/ben-haim10a/ben-haim10a.pdf)
paper by Ben-Haim/Tom-Tov.
# Example
```rust
use rand::SeedableRng;
use rand_distr::{Distribution, Normal};
use rand_isaac::Isaac64Rng;
use streamhist::StreamingHistogram;
fn main() {
let mut rng = Isaac64Rng::seed_from_u64(42);
let dist = Normal::new(2.0, 3.0).unwrap();
let mut hist = StreamingHistogram::new(32);
let maxn = 10000;
let vals: Vec<f64> = (0..maxn).map(|_| dist.sample(&mut rng)).collect();
for v in vals.iter() {
hist.insert_one(*v);
}
println!("------------------------------------------------");
println!("Est Mean {:?}", hist.mean().unwrap());
println!("Est Var {:?}", hist.var().unwrap());
println!("Est Median {:?}", hist.median().unwrap());
println!("Est Count vals <= 2.0 {:?}", hist.count_less_then_eq(2.0));
println!("Est quantile {:?}", hist.quantile(0.75).unwrap());
println!("Min {:?}", hist.min().unwrap());
println!("Max {:?}", hist.max().unwrap());
println!("Count {:?}", hist.count());
println!("------------------------------------------------");
assert_eq!(hist.count(), maxn);
}
```
# Lincese
Licensed under the Apache License, Version 2.0