Struct nalgebra_lapack::SVD

pub struct SVD<T: Scalar, R: DimMin<C>, C: Dim>where
    DefaultAllocator: Allocator<T, R, R> + Allocator<T, DimMinimum<R, C>> + Allocator<T, C, C>,{
    pub u: OMatrix<T, R, R>,
    pub vt: OMatrix<T, C, C>,
    pub singular_values: OVector<T, DimMinimum<R, C>>,
}

The SVD decomposition of a general matrix.

Fields

u: OMatrix<T, R, R>

The left-singular vectors U of this SVD.

vt: OMatrix<T, C, C>

The right-singular vectors V^t of this SVD.

singular_values: OVector<T, DimMinimum<R, C>>

The singular values of this SVD.

Implementations

impl<T: SVDScalar<R, C>, R: DimMin<C>, C: Dim> SVD<T, R, C>where
    DefaultAllocator: Allocator<T, R, R> + Allocator<T, R, C> + Allocator<T, DimMinimum<R, C>> + Allocator<T, C, C>,

pub fn new(m: OMatrix<T, R, C>) -> Option<Self>

Computes the Singular Value Decomposition of matrix.

impl<R: DimMin<C>, C: Dim> SVD<f32, R, C>where
    DefaultAllocator: Allocator<f32, R, C> + Allocator<f32, C, R> + Allocator<f32, U1, R> + Allocator<f32, U1, C> + Allocator<f32, R, R> + Allocator<f32, DimMinimum<R, C>> + Allocator<f32, DimMinimum<R, C>, R> + Allocator<f32, DimMinimum<R, C>, C> + Allocator<f32, R, DimMinimum<R, C>> + Allocator<f32, C, C>,

pub fn recompose(self) -> OMatrix<f32, R, C>

Reconstructs the matrix from its decomposition.

Useful if some components (e.g. some singular values) of this decomposition have been manually changed by the user.

pub fn pseudo_inverse(&self, epsilon: f32) -> OMatrix<f32, C, R>

Computes the pseudo-inverse of the decomposed matrix.

All singular value below epsilon will be set to zero instead of being inverted.

pub fn rank(&self, epsilon: f32) -> usize

The rank of the decomposed matrix.

This is the number of singular values that are not too small (i.e. greater than the given epsilon).

impl<R: DimMin<C>, C: Dim> SVD<f64, R, C>where
    DefaultAllocator: Allocator<f64, R, C> + Allocator<f64, C, R> + Allocator<f64, U1, R> + Allocator<f64, U1, C> + Allocator<f64, R, R> + Allocator<f64, DimMinimum<R, C>> + Allocator<f64, DimMinimum<R, C>, R> + Allocator<f64, DimMinimum<R, C>, C> + Allocator<f64, R, DimMinimum<R, C>> + Allocator<f64, C, C>,

pub fn recompose(self) -> OMatrix<f64, R, C>

Reconstructs the matrix from its decomposition.

Useful if some components (e.g. some singular values) of this decomposition have been manually changed by the user.

pub fn pseudo_inverse(&self, epsilon: f64) -> OMatrix<f64, C, R>

Computes the pseudo-inverse of the decomposed matrix.

All singular value below epsilon will be set to zero instead of being inverted.

pub fn rank(&self, epsilon: f64) -> usize

The rank of the decomposed matrix.

This is the number of singular values that are not too small (i.e. greater than the given epsilon).

Trait Implementations

impl<T: Clone + Scalar, R: Clone + DimMin<C>, C: Clone + Dim> Clone for SVD<T, R, C>where
    DefaultAllocator: Allocator<T, R, R> + Allocator<T, DimMinimum<R, C>> + Allocator<T, C, C>,

fn clone(&self) -> SVD<T, R, C>

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<T: Debug + Scalar, R: Debug + DimMin<C>, C: Debug + Dim> Debug for SVD<T, R, C>where
    DefaultAllocator: Allocator<T, R, R> + Allocator<T, DimMinimum<R, C>> + Allocator<T, C, C>,

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

Formats the value using the given formatter.

impl<T: Scalar + Copy, R: DimMin<C>, C: Dim> Copy for SVD<T, R, C>where
    DefaultAllocator: Allocator<T, C, C> + Allocator<T, R, R> + Allocator<T, DimMinimum<R, C>>,
    OMatrix<T, R, R>: Copy,
    OMatrix<T, C, C>: Copy,
    OVector<T, DimMinimum<R, C>>: Copy,