Struct WeightedMean

pub struct WeightedMean<T = f64, W = f64, O = f64, C = u32> { /* private fields */ }

ndhistogram bin value computes the mean of the data samples provided when filling.

Mean has 4 type parameters:

• the type that is being averaged,
• the type of the weights that are being filled,
• the type of the output when calculating the mean and its uncertainty,
• the type that counts the number of fills.

This allows, for example, integers to be used when filling or counting, but a floating point type to compute the mean. In most cases, you will only need to specify the first two type parameters as sensible defaults are set for the second two type parameters.

Example

use ndhistogram::{ndhistogram, Histogram, axis::Uniform, value::WeightedMean};

// create a histogram and fill it with some values
let mut hist = ndhistogram!(Uniform::new(10, 0.0, 10.0)?; WeightedMean<i32, i32>);
hist.fill_with_weighted(&0.0, 2, 1);
hist.fill_with_weighted(&0.0, 2, 2);
hist.fill_with_weighted(&0.0, 4, 3);

let weightedmean = hist.value(&0.0);
assert_eq!(weightedmean.unwrap().get(), 3.0);

Implementations

impl<T, W, O, C> WeightedMean<T, W, O, C>

where T: Copy, W: Copy, O: From<T> + From<W> + From<C> + NumOps + Signed + Copy, C: Copy,

pub fn new<I>(values: I) -> Self

where I: IntoIterator<Item = (T, W)>, Self: FillWithWeighted<T, W> + Default,

Factory method to create a Mean from a set of values.

Usually this will not be used as a Histogram will be responsible for creating and filling values.

pub fn get(&self) -> O

Get the current value of the mean.

pub fn mean(&self) -> <O as Div>::Output

Get the current value of the mean.

pub fn num_samples(&self) -> C

Get the number of times the mean value has been filled.

pub fn variance_of_samples(&self) -> O

Compute the variance of the samples.

pub fn standard_deviation_of_samples(&self) -> O

where O: Float,

The square root of the variance of the samples.

pub fn variance_of_mean(&self) -> O

The square of the standard error of the mean.

pub fn standard_error_of_mean(&self) -> O

where O: Float,

Compute the standard error of the mean.

Trait Implementations

impl<T: Clone, W: Clone, O: Clone, C: Clone> Clone for WeightedMean<T, W, O, C>

fn clone(&self) -> WeightedMean<T, W, O, C>

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<T: Debug, W: Debug, O: Debug, C: Debug> Debug for WeightedMean<T, W, O, C>

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

Formats the value using the given formatter.

impl<T: Default, W: Default, O: Default, C: Default> Default for WeightedMean<T, W, O, C>

fn default() -> WeightedMean<T, W, O, C>

Returns the “default value” for a type.

impl<T, W, O, C> FillWithWeighted<T, W> for WeightedMean<T, W, O, C>

where T: Copy + AddAssign + Mul<W, Output = T> + Mul<T, Output = T>, W: Copy + AddAssign + Mul<W, Output = W>, C: AddAssign + One,

fn fill_with_weighted(&mut self, value: T, weight: W)

Fill a histogram with some weighted value.

impl<T: Hash, W: Hash, O: Hash, C: Hash> Hash for WeightedMean<T, W, O, C>

fn hash<__H: Hasher>(&self, state: &mut __H)

Feeds this value into the given Hasher.

fn hash_slice<H>(data: &[Self], state: &mut H)

where H: Hasher, Self: Sized,

Feeds a slice of this type into the given Hasher.

impl<T: Ord, W: Ord, O: Ord, C: Ord> Ord for WeightedMean<T, W, O, C>

fn cmp(&self, other: &WeightedMean<T, W, O, C>) -> Ordering

This method returns an Ordering between self and other.

fn max(self, other: Self) -> Self

where Self: Sized,

Compares and returns the maximum of two values.

fn min(self, other: Self) -> Self

where Self: Sized,

Compares and returns the minimum of two values.

fn clamp(self, min: Self, max: Self) -> Self

where Self: Sized,

Restrict a value to a certain interval.

impl<T: PartialEq, W: PartialEq, O: PartialEq, C: PartialEq> PartialEq for WeightedMean<T, W, O, C>

fn eq(&self, other: &WeightedMean<T, W, O, C>) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl<T: PartialOrd, W: PartialOrd, O: PartialOrd, C: PartialOrd> PartialOrd for WeightedMean<T, W, O, C>

fn partial_cmp(&self, other: &WeightedMean<T, W, O, C>) -> Option<Ordering>

This method returns an ordering between self and other values if one exists.

fn lt(&self, other: &Rhs) -> bool

Tests less than (for self and other) and is used by the < operator.

fn le(&self, other: &Rhs) -> bool

Tests less than or equal to (for self and other) and is used by the <= operator.

fn gt(&self, other: &Rhs) -> bool

Tests greater than (for self and other) and is used by the > operator.

fn ge(&self, other: &Rhs) -> bool

Tests greater than or equal to (for self and other) and is used by the >= operator.

impl<T: Copy, W: Copy, O: Copy, C: Copy> Copy for WeightedMean<T, W, O, C>

impl<T: Eq, W: Eq, O: Eq, C: Eq> Eq for WeightedMean<T, W, O, C>

impl<T, W, O, C> StructuralPartialEq for WeightedMean<T, W, O, C>