Struct inc_stats::Percentiles

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pub struct Percentiles { /* private fields */ }

Expand description

Data percentile struct

This struct stores data to allow efficient computation of percentiles. This struct takes linear space. It implements FromIterator to allow collection.

Examples

let nums = [2.0, 4.0, 8.0];
let mut percs = inc_stats::Percentiles::new();
for num in nums.iter() {
    percs.add(num.clone());
}
assert_eq!(3, percs.count());

let nums = [2.0, 4.0, 8.0];
let percs: inc_stats::Percentiles = nums.iter().cloned().collect();
assert_eq!(3, percs.count());

Implementations

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impl Percentiles

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pub fn new() -> Self

Create a new Percentiles object with no data

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pub fn add(&mut self, val: f64)

Add a data point

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pub fn count(&self) -> i64

Get the number of data points

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pub fn percentiles(&mut self, percentiles: I) -> Option<Vec<f64>>where
I: Iterator<Item = f64>,

Get a number of percentiles

This takes linear time in the number of added data points, and log linear in the number of percentiles. This will be marginally more efficient than calling percentile repeatedly in a bad order.

Examples:

let nums = [1.0, 3.0, 7.0];
let mut percs: inc_stats::Percentiles = nums.iter().cloned().collect();
let quarts = percs.percentiles([0.75, 0.25, 0.5].iter().cloned()).unwrap();
assert!((5.0 - quarts[0]).abs() < 1.0e-6);
assert!((2.0 - quarts[1]).abs() < 1.0e-6);
assert!((3.0 - quarts[2]).abs() < 1.0e-6);

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pub fn percentile(&mut self, percentile: &f64) -> Option<f64>

Get a percentile

Linear time.

Examples:

let nums = [1.0, 5.0];
let mut percs: inc_stats::Percentiles = nums.iter().cloned().collect();
let quart = percs.percentile(&0.25).unwrap();
assert!((2.0 - quart).abs() < 1.0e-6);

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pub fn median(&mut self) -> Option<f64>

Get the median

Linear time.

Examples:

let nums = [1.0, 5.0, 100.0];
let mut percs: inc_stats::Percentiles = nums.iter().cloned().collect();
let med = percs.median().unwrap();
assert!((5.0 - med).abs() < 1.0e-6);