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//! Summary statistics (e.g. mean, variance, etc.). use crate::errors::EmptyInput; use ndarray::{Data, Dimension}; use num_traits::{Float, FromPrimitive, Zero}; use std::ops::{Add, Div}; /// Extension trait for `ArrayBase` providing methods /// to compute several summary statistics (e.g. mean, variance, etc.). pub trait SummaryStatisticsExt<A, S, D> where S: Data<Elem = A>, D: Dimension, { /// Returns the [`arithmetic mean`] x̅ of all elements in the array: /// /// ```text /// 1 n /// x̅ = ― ∑ xᵢ /// n i=1 /// ``` /// /// If the array is empty, `Err(EmptyInput)` is returned. /// /// **Panics** if `A::from_usize()` fails to convert the number of elements in the array. /// /// [`arithmetic mean`]: https://en.wikipedia.org/wiki/Arithmetic_mean fn mean(&self) -> Result<A, EmptyInput> where A: Clone + FromPrimitive + Add<Output = A> + Div<Output = A> + Zero; /// Returns the [`harmonic mean`] `HM(X)` of all elements in the array: /// /// ```text /// ⎛ n ⎞⁻¹ /// HM(X) = n ⎜ ∑ xᵢ⁻¹⎟ /// ⎝i=1 ⎠ /// ``` /// /// If the array is empty, `Err(EmptyInput)` is returned. /// /// **Panics** if `A::from_usize()` fails to convert the number of elements in the array. /// /// [`harmonic mean`]: https://en.wikipedia.org/wiki/Harmonic_mean fn harmonic_mean(&self) -> Result<A, EmptyInput> where A: Float + FromPrimitive; /// Returns the [`geometric mean`] `GM(X)` of all elements in the array: /// /// ```text /// ⎛ n ⎞¹⁄ₙ /// GM(X) = ⎜ ∏ xᵢ⎟ /// ⎝i=1 ⎠ /// ``` /// /// If the array is empty, `Err(EmptyInput)` is returned. /// /// **Panics** if `A::from_usize()` fails to convert the number of elements in the array. /// /// [`geometric mean`]: https://en.wikipedia.org/wiki/Geometric_mean fn geometric_mean(&self) -> Result<A, EmptyInput> where A: Float + FromPrimitive; /// Returns the [kurtosis] `Kurt[X]` of all elements in the array: /// /// ```text /// Kurt[X] = μ₄ / σ⁴ /// ``` /// /// where μ₄ is the fourth central moment and σ is the standard deviation of /// the elements in the array. /// /// This is sometimes referred to as _Pearson's kurtosis_. Fisher's kurtosis can be /// computed by subtracting 3 from Pearson's kurtosis. /// /// If the array is empty, `Err(EmptyInput)` is returned. /// /// **Panics** if `A::from_usize()` fails to convert the number of elements in the array. /// /// [kurtosis]: https://en.wikipedia.org/wiki/Kurtosis fn kurtosis(&self) -> Result<A, EmptyInput> where A: Float + FromPrimitive; /// Returns the [Pearson's moment coefficient of skewness] γ₁ of all elements in the array: /// /// ```text /// γ₁ = μ₃ / σ³ /// ``` /// /// where μ₃ is the third central moment and σ is the standard deviation of /// the elements in the array. /// /// If the array is empty, `Err(EmptyInput)` is returned. /// /// **Panics** if `A::from_usize()` fails to convert the number of elements in the array. /// /// [Pearson's moment coefficient of skewness]: https://en.wikipedia.org/wiki/Skewness fn skewness(&self) -> Result<A, EmptyInput> where A: Float + FromPrimitive; /// Returns the *p*-th [central moment] of all elements in the array, μₚ: /// /// ```text /// 1 n /// μₚ = ― ∑ (xᵢ-x̅)ᵖ /// n i=1 /// ``` /// /// If the array is empty, `Err(EmptyInput)` is returned. /// /// The *p*-th central moment is computed using a corrected two-pass algorithm (see Section 3.5 /// in [Pébay et al., 2016]). Complexity is *O(np)* when *n >> p*, *p > 1*. /// /// **Panics** if `A::from_usize()` fails to convert the number of elements /// in the array or if `order` overflows `i32`. /// /// [central moment]: https://en.wikipedia.org/wiki/Central_moment /// [Pébay et al., 2016]: https://www.osti.gov/pages/servlets/purl/1427275 fn central_moment(&self, order: u16) -> Result<A, EmptyInput> where A: Float + FromPrimitive; /// Returns the first *p* [central moments] of all elements in the array, see [central moment] /// for more details. /// /// If the array is empty, `Err(EmptyInput)` is returned. /// /// This method reuses the intermediate steps for the *k*-th moment to compute the *(k+1)*-th, /// being thus more efficient than repeated calls to [central moment] if the computation /// of central moments of multiple orders is required. /// /// **Panics** if `A::from_usize()` fails to convert the number of elements /// in the array or if `order` overflows `i32`. /// /// [central moments]: https://en.wikipedia.org/wiki/Central_moment /// [central moment]: #tymethod.central_moment fn central_moments(&self, order: u16) -> Result<Vec<A>, EmptyInput> where A: Float + FromPrimitive; private_decl! {} } mod means;