Struct nalgebra::linalg::Hessenberg [−][src]
pub struct Hessenberg<T: ComplexField, D: DimSub<U1>> where
DefaultAllocator: Allocator<T, D, D> + Allocator<T, DimDiff<D, U1>>, { /* fields omitted */ }Expand description
Hessenberg decomposition of a general matrix.
Implementations
impl<T: ComplexField, D: DimSub<U1>> Hessenberg<T, D> where
DefaultAllocator: Allocator<T, D, D> + Allocator<T, D> + Allocator<T, DimDiff<D, U1>>,
impl<T: ComplexField, D: DimSub<U1>> Hessenberg<T, D> where
DefaultAllocator: Allocator<T, D, D> + Allocator<T, D> + Allocator<T, DimDiff<D, U1>>,
Computes the Hessenberg decomposition using householder reflections.
Computes the Hessenberg decomposition using householder reflections.
The workspace containing D elements must be provided but its content does not have to be
initialized.
Retrieves (q, h) with q the orthogonal matrix of this decomposition and h the
hessenberg matrix.
Retrieves the upper trapezoidal submatrix H of this decomposition.
Retrieves the upper trapezoidal submatrix H of this decomposition.
This is less efficient than .unpack_h() as it allocates a new matrix.
Trait Implementations
impl<T: Clone + ComplexField, D: Clone + DimSub<U1>> Clone for Hessenberg<T, D> where
DefaultAllocator: Allocator<T, D, D> + Allocator<T, DimDiff<D, U1>>,
impl<T: Clone + ComplexField, D: Clone + DimSub<U1>> Clone for Hessenberg<T, D> where
DefaultAllocator: Allocator<T, D, D> + Allocator<T, DimDiff<D, U1>>,
impl<T: Debug + ComplexField, D: Debug + DimSub<U1>> Debug for Hessenberg<T, D> where
DefaultAllocator: Allocator<T, D, D> + Allocator<T, DimDiff<D, U1>>,
impl<T: Debug + ComplexField, D: Debug + DimSub<U1>> Debug for Hessenberg<T, D> where
DefaultAllocator: Allocator<T, D, D> + Allocator<T, DimDiff<D, U1>>,
Auto Trait Implementations
impl<T, D> !RefUnwindSafe for Hessenberg<T, D>
impl<T, D> !Send for Hessenberg<T, D>
impl<T, D> !Sync for Hessenberg<T, D>
impl<T, D> !Unpin for Hessenberg<T, D>
impl<T, D> !UnwindSafe for Hessenberg<T, D>
Blanket Implementations
Mutably borrows from an owned value. Read more
The inverse inclusion map: attempts to construct self from the equivalent element of its
superset. Read more
Checks if self is actually part of its subset T (and can be converted to it).
Use with care! Same as self.to_subset but without any property checks. Always succeeds.
The inclusion map: converts self to the equivalent element of its superset.