numeric_statistics/f32/
average.rs

1//! Statistics module for calculating various statistical measures.
2//! 
3//! These are simple naive implementations, just enough to work for
4//! this crate's purpose of network monitoring, such as for latency.
5
6/// Calculate statistical average for values.
7///
8/// Return NaN if the values are empty.
9/// 
10/// Filter NaN values in the stream.
11/// 
12pub fn average<T: AsRef<[f32]>>(values: T) -> f32 {
13    let values = values.as_ref();
14    if values.is_empty() { return f32::NAN; }
15    let mut sum: f32 = 0.0;
16    let mut len: usize = 0;
17    values.iter().for_each(|x|
18        if !x.is_nan() {
19            sum += *x;
20            len += 1;
21        }
22    );
23    sum / len as f32
24}
25
26#[cfg(test)]
27mod test {
28    use super::*;
29
30    #[test]
31    fn test_empty() {
32        let x: &[f32] = &[];
33        assert!(average(x).is_nan());
34    }
35
36    #[test]
37    fn test_nan() {
38        let x: &[f32] = &[f32::NAN];
39        assert!(average(x).is_nan());
40    }
41
42    #[test]
43    fn test_value() {
44        let x: &[f32] = &[1.0];
45        assert_eq_float!(average(x), 1.0);
46    }
47
48    #[test]
49    fn test_values_ascending() {
50        let x = &[1.0, 2.0, 4.0];
51        assert_eq_float!(average(x), 2.3333333);
52    }
53
54    #[test]
55    fn test_values_ascending_and_nans() {
56        let x = &[1.0, f32::NAN, 2.0, f32::NAN, 4.0];
57        assert_eq_float!(average(x), 2.3333333);
58    }
59
60    #[test]
61    fn test_values_descending() {
62        let x = &[4.0, 2.0, 1.0];
63        assert_eq_float!(average(x), 2.3333333);
64    }
65
66    #[test]
67    fn test_values_descending_and_nans() {
68        let x = &[4.0, f32::NAN, 2.0, f32::NAN, 1.0];
69        assert_eq_float!(average(x), 2.3333333);
70    }
71
72}
73
numeric_statistics/f32/average.rs

numeric_statistics/f32/
average.rs
