Struct nalgebra::linalg::Hessenberg [−][src]
pub struct Hessenberg<N: ComplexField, D: DimSub<U1>> where
DefaultAllocator: Allocator<N, D, D> + Allocator<N, DimDiff<D, U1>>, { /* fields omitted */ }
Expand description
Hessenberg decomposition of a general matrix.
Implementations
impl<N: ComplexField, D: DimSub<U1>> Hessenberg<N, D> where
DefaultAllocator: Allocator<N, D, D> + Allocator<N, D> + Allocator<N, DimDiff<D, U1>>,
impl<N: ComplexField, D: DimSub<U1>> Hessenberg<N, D> where
DefaultAllocator: Allocator<N, D, D> + Allocator<N, D> + Allocator<N, 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<N: Clone + ComplexField, D: Clone + DimSub<U1>> Clone for Hessenberg<N, D> where
DefaultAllocator: Allocator<N, D, D> + Allocator<N, DimDiff<D, U1>>,
impl<N: Clone + ComplexField, D: Clone + DimSub<U1>> Clone for Hessenberg<N, D> where
DefaultAllocator: Allocator<N, D, D> + Allocator<N, DimDiff<D, U1>>,
impl<N: Debug + ComplexField, D: Debug + DimSub<U1>> Debug for Hessenberg<N, D> where
DefaultAllocator: Allocator<N, D, D> + Allocator<N, DimDiff<D, U1>>,
impl<N: Debug + ComplexField, D: Debug + DimSub<U1>> Debug for Hessenberg<N, D> where
DefaultAllocator: Allocator<N, D, D> + Allocator<N, DimDiff<D, U1>>,
Auto Trait Implementations
impl<N, D> !RefUnwindSafe for Hessenberg<N, D>
impl<N, D> !Send for Hessenberg<N, D>
impl<N, D> !Sync for Hessenberg<N, D>
impl<N, D> !Unpin for Hessenberg<N, D>
impl<N, D> !UnwindSafe for Hessenberg<N, 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.