Struct average::Mean

pub struct Mean { /* fields omitted */ }

Estimate the arithmetic mean of a sequence of numbers ("population").

Example

use average::Mean;

let a: Mean = (1..6).map(f64::from).collect();
println!("The mean is {}.", a.mean());

Implementations

impl Mean

pub fn new() -> Mean

Create a new mean estimator.

pub fn is_empty(&self) -> bool

Determine whether the sample is empty.

pub fn mean(&self) -> f64

Estimate the mean of the population.

Returns 0 for an empty sample.

pub fn len(&self) -> u64

Return the sample size.

Trait Implementations

impl Clone for Mean

fn clone(&self) -> Mean

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for Mean

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for Mean

fn default() -> Mean

Returns the "default value" for a type.

impl Estimate for Mean

fn add(&mut self, sample: f64)

Add an observation sampled from the population.

fn estimate(&self) -> f64

Estimate the statistic of the population.

impl<'a> FromIterator<&'a f64> for Mean

fn from_iter<T>(iter: T) -> Mean where
    T: IntoIterator<Item = &'a f64>, 

Creates a value from an iterator.

impl FromIterator<f64> for Mean

fn from_iter<T>(iter: T) -> Mean where
    T: IntoIterator<Item = f64>, 

Creates a value from an iterator.

impl Merge for Mean

fn merge(&mut self, other: &Mean)

Merge another sample into this one.

Example

use average::{Mean, Merge};

let sequence: &[f64] = &[1., 2., 3., 4., 5., 6., 7., 8., 9.];
let (left, right) = sequence.split_at(3);
let avg_total: Mean = sequence.iter().collect();
let mut avg_left: Mean = left.iter().collect();
let avg_right: Mean = right.iter().collect();
avg_left.merge(&avg_right);
assert_eq!(avg_total.mean(), avg_left.mean());