| Crates.io | online-statistics |
| lib.rs | online-statistics |
| version | 0.2.6 |
| created_at | 2022-07-23 14:02:11.390389+00 |
| updated_at | 2022-09-10 09:51:32.202738+00 |
| description | Blazingly fast, generic, and serializable online statistics. |
| homepage | |
| repository | https://github.com/online-ml/online-statistics.rs |
| max_upload_size | |
| id | 631417 |
| size | 75,234 |
online-statistics is crate 🦀 for Blazingly fast, generic and serializable online statistics.
Let's compute the online median and then serialize it:
use online_statistics::quantile::Quantile;
use online_statistics::stats::Univariate;
let data: Vec<f64> = vec![9., 7., 3., 2., 6., 1., 8., 5., 4.];
let mut running_median: Quantile<f64> = Quantile::new(0.5_f64).unwrap();
for x in data.into_iter() {
running_median.update(x); // update the current statistics
println!("The actual median value is: {}", running_median.get());
}
assert_eq!(running_median.get(), 5.0);
// Convert the statistic to a JSON string.
let serialized = serde_json::to_string(&running_median).unwrap();
// Convert the JSON string back to a statistic.
let deserialized: Quantile<f64> = serde_json::from_str(&serialized).unwrap();
Now let's compute the online sum using the iterators:
use online_statistics::iter::IterStatisticsExtend;
let data: Vec<f64> = vec![1., 2., 3.];
let vec_true: Vec<f64> = vec![1., 3., 6.];
for (d, t) in data.into_iter().online_sum().zip(vec_true.into_iter()) {
assert_eq!(d, t); // ^^^^^^^^^^
}
You can also compute rolling statistics; in the following example let's compute the rolling sum on 2 previous data:
use online_statistics::rolling::Rolling;
use online_statistics::stats::Univariate;
use online_statistics::variance::Variance;
let data: Vec<f64> = vec![9., 7., 3., 2., 6., 1., 8., 5., 4.];
let mut running_var: Variance<f64> = Variance::default();
// We wrap `running_var` inside the `Rolling` struct.
let mut rolling_var: Rolling<f64> = Rolling::new(&mut running_var, 2).unwrap();
for x in data.into_iter() {
rolling_var.update(x);
}
assert_eq!(rolling_var.get(), 0.5);
Add the following line to your cargo.toml:
[dependencies]
online-statistics = "0.2.6"
| Statistics | Rollable ? |
|---|---|
| Mean | ✅ |
| Variance | ✅ |
| Sum | ✅ |
| Min | ✅ |
| Max | ✅ |
| Count | ❌ |
| Quantile | ✅ |
| Peak to peak | ✅ |
| Exponentially weighted mean | ❌ |
| Exponentially weighted variance | ❌ |
| Interquartile range | ✅ |
| Kurtosis | ❌ |
| Skewness | ❌ |
| Covariance | ❌ |
The stats module of the river library in Python greatly inspired this crate.