中文
devexamples

Sliding Window Statistics with Iterators

Compute rolling sums and averages over fixed-size windows with slice iterators, avoiding index loops and extra allocations.

RustData Integrity

Code

snippet
fn rolling_average(values: &[f64], window: usize) -> Vec<f64> {
    if window == 0 || window > values.len() {
        return Vec::new();
    }
    values
        .windows(window)
        .map(|chunk| chunk.iter().sum::<f64>() / window as f64)
        .collect()
}

fn rolling_max(values: &[i64], window: usize) -> Vec<i64> {
    if window == 0 || window > values.len() {
        return Vec::new();
    }
    values
        .windows(window)
        .map(|chunk| chunk.iter().copied().max().unwrap_or_default())
        .collect()
}

fn main() {
    let samples = [3.0, 5.0, 7.0, 9.0, 11.0];
    let averages = rolling_average(&samples, 3);
    let maxima = rolling_max(&[4, 1, 7, 3, 9, 2], 2);
    println!("averages: {averages:?}");
    println!("maxima: {maxima:?}");
}

Related Examples