Trait linxal::svd::general::SVD
[−]
[src]
pub trait SVD<SV: SingularValue>: Sized + Clone {
fn compute_into<D>(mat: ArrayBase<D, Ix2>, compute_u: bool, compute_vt: bool) -> Result<SVDSolution<Self, SV>, SVDError> where D: DataMut<Elem=Self> + DataOwned<Elem=Self>;
fn compute<D>(mat: &ArrayBase<D, Ix2>, compute_u: bool, compute_vt: bool) -> Result<SVDSolution<Self, SV>, SVDError> where D: Data<Elem=Self> { ... }
}Trait for scalars that can implement SVD.
Required Methods
fn compute_into<D>(mat: ArrayBase<D, Ix2>, compute_u: bool, compute_vt: bool) -> Result<SVDSolution<Self, SV>, SVDError> where D: DataMut<Elem=Self> + DataOwned<Elem=Self>
Compute the singular value decomposition of a matrix.
Use Self::compute when you don't wnat to consume the input
matrix.
On success, returns an SVDSolution, which always contains the
singular values and optionally contains the left and right
singular vectors. The left vectors (via the matrix u) are
returned iff compute_u is true, and similarly for vt and
compute_vt.
Provided Methods
fn compute<D>(mat: &ArrayBase<D, Ix2>, compute_u: bool, compute_vt: bool) -> Result<SVDSolution<Self, SV>, SVDError> where D: Data<Elem=Self>
Comptue the singular value decomposition of a matrix.
Similar to SVD::compute_into, but
the values are copied beforehand. leaving the original matrix
un-modified.