[−][src]Trait ndarray_stats::DeviationExt

pub trait DeviationExt<A, S, D> where
    S: Data<Elem = A>,
    D: Dimension, {
    pub fn count_eq<T>(
        &self, 
        other: &ArrayBase<T, D>
    ) -> Result<usize, MultiInputError>
    where
        A: PartialEq,
        T: Data<Elem = A>;

    pub fn count_neq<T>(
        &self, 
        other: &ArrayBase<T, D>
    ) -> Result<usize, MultiInputError>
    where
        A: PartialEq,
        T: Data<Elem = A>;

    pub fn sq_l2_dist<T>(
        &self, 
        other: &ArrayBase<T, D>
    ) -> Result<A, MultiInputError>
    where
        A: AddAssign + Clone + Signed,
        T: Data<Elem = A>;

    pub fn l2_dist<T>(
        &self, 
        other: &ArrayBase<T, D>
    ) -> Result<f64, MultiInputError>
    where
        A: AddAssign + Clone + Signed + ToPrimitive,
        T: Data<Elem = A>;

    pub fn l1_dist<T>(
        &self, 
        other: &ArrayBase<T, D>
    ) -> Result<A, MultiInputError>
    where
        A: AddAssign + Clone + Signed,
        T: Data<Elem = A>;

    pub fn linf_dist<T>(
        &self, 
        other: &ArrayBase<T, D>
    ) -> Result<A, MultiInputError>
    where
        A: Clone + PartialOrd + Signed,
        T: Data<Elem = A>;

    pub fn mean_abs_err<T>(
        &self, 
        other: &ArrayBase<T, D>
    ) -> Result<f64, MultiInputError>
    where
        A: AddAssign + Clone + Signed + ToPrimitive,
        T: Data<Elem = A>;

    pub fn mean_sq_err<T>(
        &self, 
        other: &ArrayBase<T, D>
    ) -> Result<f64, MultiInputError>
    where
        A: AddAssign + Clone + Signed + ToPrimitive,
        T: Data<Elem = A>;

    pub fn root_mean_sq_err<T>(
        &self, 
        other: &ArrayBase<T, D>
    ) -> Result<f64, MultiInputError>
    where
        A: AddAssign + Clone + Signed + ToPrimitive,
        T: Data<Elem = A>;

    pub fn peak_signal_to_noise_ratio<T>(
        &self, 
        other: &ArrayBase<T, D>, 
        maxv: A
    ) -> Result<f64, MultiInputError>
    where
        A: AddAssign + Clone + Signed + ToPrimitive,
        T: Data<Elem = A>;

    pub fn __private__(&self, _: PrivateMarker);
}

An extension trait for ArrayBase providing functions to compute different deviation measures.

Required methods

pub fn count_eq<T>(
    &self,
    other: &ArrayBase<T, D>
) -> Result<usize, MultiInputError> where
    A: PartialEq,
    T: Data<Elem = A>, [src]

Counts the number of indices at which the elements of the arrays self and other are equal.

The following errors may be returned:

  • MultiInputError::EmptyInput if self is empty
  • MultiInputError::ShapeMismatch if self and other don't have the same shape

pub fn count_neq<T>(
    &self,
    other: &ArrayBase<T, D>
) -> Result<usize, MultiInputError> where
    A: PartialEq,
    T: Data<Elem = A>, [src]

Counts the number of indices at which the elements of the arrays self and other are not equal.

The following errors may be returned:

  • MultiInputError::EmptyInput if self is empty
  • MultiInputError::ShapeMismatch if self and other don't have the same shape

pub fn sq_l2_dist<T>(
    &self,
    other: &ArrayBase<T, D>
) -> Result<A, MultiInputError> where
    A: AddAssign + Clone + Signed,
    T: Data<Elem = A>, [src]

Computes the squared L2 distance between self and other.

 n
 ∑  |aᵢ - bᵢ|²
i=1

where self is a and other is b.

The following errors may be returned:

  • MultiInputError::EmptyInput if self is empty
  • MultiInputError::ShapeMismatch if self and other don't have the same shape

pub fn l2_dist<T>(
    &self,
    other: &ArrayBase<T, D>
) -> Result<f64, MultiInputError> where
    A: AddAssign + Clone + Signed + ToPrimitive,
    T: Data<Elem = A>, [src]

Computes the L2 distance between self and other.

     n
√ (  ∑  |aᵢ - bᵢ|² )
    i=1

where self is a and other is b.

The following errors may be returned:

  • MultiInputError::EmptyInput if self is empty
  • MultiInputError::ShapeMismatch if self and other don't have the same shape

Panics if the type cast from A to f64 fails.

pub fn l1_dist<T>(&self, other: &ArrayBase<T, D>) -> Result<A, MultiInputError> where
    A: AddAssign + Clone + Signed,
    T: Data<Elem = A>, [src]

Computes the L1 distance between self and other.

 n
 ∑  |aᵢ - bᵢ|
i=1

where self is a and other is b.

The following errors may be returned:

  • MultiInputError::EmptyInput if self is empty
  • MultiInputError::ShapeMismatch if self and other don't have the same shape

pub fn linf_dist<T>(
    &self,
    other: &ArrayBase<T, D>
) -> Result<A, MultiInputError> where
    A: Clone + PartialOrd + Signed,
    T: Data<Elem = A>, [src]

Computes the L∞ distance between self and other.

max(|aᵢ - bᵢ|)
 ᵢ

where self is a and other is b.

The following errors may be returned:

  • MultiInputError::EmptyInput if self is empty
  • MultiInputError::ShapeMismatch if self and other don't have the same shape

pub fn mean_abs_err<T>(
    &self,
    other: &ArrayBase<T, D>
) -> Result<f64, MultiInputError> where
    A: AddAssign + Clone + Signed + ToPrimitive,
    T: Data<Elem = A>, [src]

Computes the mean absolute error between self and other.

       n
1/n *  ∑  |aᵢ - bᵢ|
      i=1

where self is a and other is b.

The following errors may be returned:

  • MultiInputError::EmptyInput if self is empty
  • MultiInputError::ShapeMismatch if self and other don't have the same shape

Panics if the type cast from A to f64 fails.

pub fn mean_sq_err<T>(
    &self,
    other: &ArrayBase<T, D>
) -> Result<f64, MultiInputError> where
    A: AddAssign + Clone + Signed + ToPrimitive,
    T: Data<Elem = A>, [src]

Computes the mean squared error between self and other.

       n
1/n *  ∑  |aᵢ - bᵢ|²
      i=1

where self is a and other is b.

The following errors may be returned:

  • MultiInputError::EmptyInput if self is empty
  • MultiInputError::ShapeMismatch if self and other don't have the same shape

Panics if the type cast from A to f64 fails.

pub fn root_mean_sq_err<T>(
    &self,
    other: &ArrayBase<T, D>
) -> Result<f64, MultiInputError> where
    A: AddAssign + Clone + Signed + ToPrimitive,
    T: Data<Elem = A>, [src]

Computes the unnormalized root-mean-square error between self and other.

√ mse(a, b)

where self is a, other is b and mse is the mean-squared-error.

The following errors may be returned:

  • MultiInputError::EmptyInput if self is empty
  • MultiInputError::ShapeMismatch if self and other don't have the same shape

Panics if the type cast from A to f64 fails.

pub fn peak_signal_to_noise_ratio<T>(
    &self,
    other: &ArrayBase<T, D>,
    maxv: A
) -> Result<f64, MultiInputError> where
    A: AddAssign + Clone + Signed + ToPrimitive,
    T: Data<Elem = A>, [src]

Computes the peak signal-to-noise ratio between self and other.

10 * log10(maxv^2 / mse(a, b))

where self is a, other is b, mse is the mean-squared-error and maxv is the maximum possible value either array can take.

The following errors may be returned:

  • MultiInputError::EmptyInput if self is empty
  • MultiInputError::ShapeMismatch if self and other don't have the same shape

Panics if the type cast from A to f64 fails.

pub fn __private__(&self, _: PrivateMarker)[src]

This method makes this trait impossible to implement outside of ndarray-stats so that we can freely add new methods, etc., to this trait without breaking changes.

We don't anticipate any other crates needing to implement this trait, but if you do have such a use-case, please let us know.

Warning This method is not considered part of the public API, and client code should not rely on it being present. It may be removed in a non-breaking release.

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Implementations on Foreign Types

impl<A, S, D> DeviationExt<A, S, D> for ArrayBase<S, D> where
    S: Data<Elem = A>,
    D: Dimension, [src]

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Implementors

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