Struct ndhistogram::value::WeightedMean

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

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>

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

Returns a copy of the value.

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

Performs copy-assignment from source.

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

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

pub 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>

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

Returns the "default value" for a type.

impl<'de, T, W, O, C> Deserialize<'de> for WeightedMean<T, W, O, C> where
    T: Deserialize<'de>,
    W: Deserialize<'de>,
    C: Deserialize<'de>, 

pub fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
    __D: Deserializer<'de>, 

Deserialize this value from the given Serde deserializer.

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

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, 

pub 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>

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

Feeds this value into the given Hasher.

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

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>

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

This method returns an Ordering between self and other.

#[must_use]pub fn max(self, other: Self) -> Self

Compares and returns the maximum of two values.

#[must_use]pub fn min(self, other: Self) -> Self

Compares and returns the minimum of two values.

#[must_use]pub fn clamp(self, min: Self, max: Self) -> Self

Restrict a value to a certain interval.

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

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

This method tests for self and other values to be equal, and is used by ==.

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

This method tests for !=.

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

pub 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.

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

This method tests less than (for self and other) and is used by the < operator.

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

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

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

This method tests greater than (for self and other) and is used by the > operator.

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

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

impl<T, W, O, C> Serialize for WeightedMean<T, W, O, C> where
    T: Serialize,
    W: Serialize,
    C: Serialize, 

pub fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error> where
    __S: Serializer, 

Serialize this value into the given Serde serializer.

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

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