Struct nalgebra::linalg::Bidiagonal
source · pub struct Bidiagonal<T: ComplexField, R: DimMin<C>, C: Dim>where
DimMinimum<R, C>: DimSub<U1>,
DefaultAllocator: Allocator<T, R, C> + Allocator<T, DimMinimum<R, C>> + Allocator<T, DimDiff<DimMinimum<R, C>, U1>>,{ /* private fields */ }
Expand description
The bidiagonalization of a general matrix.
Implementations§
source§impl<T: ComplexField, R: DimMin<C>, C: Dim> Bidiagonal<T, R, C>where
DimMinimum<R, C>: DimSub<U1>,
DefaultAllocator: Allocator<T, R, C> + Allocator<T, C> + Allocator<T, R> + Allocator<T, DimMinimum<R, C>> + Allocator<T, DimDiff<DimMinimum<R, C>, U1>>,
impl<T: ComplexField, R: DimMin<C>, C: Dim> Bidiagonal<T, R, C>where
DimMinimum<R, C>: DimSub<U1>,
DefaultAllocator: Allocator<T, R, C> + Allocator<T, C> + Allocator<T, R> + Allocator<T, DimMinimum<R, C>> + Allocator<T, DimDiff<DimMinimum<R, C>, U1>>,
sourcepub fn new(matrix: OMatrix<T, R, C>) -> Self
pub fn new(matrix: OMatrix<T, R, C>) -> Self
Computes the Bidiagonal decomposition using householder reflections.
sourcepub fn is_upper_diagonal(&self) -> bool
pub fn is_upper_diagonal(&self) -> bool
Indicates whether this decomposition contains an upper-diagonal matrix.
sourcepub fn unpack(
self
) -> (OMatrix<T, R, DimMinimum<R, C>>, OMatrix<T, DimMinimum<R, C>, DimMinimum<R, C>>, OMatrix<T, DimMinimum<R, C>, C>)where
DefaultAllocator: Allocator<T, DimMinimum<R, C>, DimMinimum<R, C>> + Allocator<T, R, DimMinimum<R, C>> + Allocator<T, DimMinimum<R, C>, C>,
pub fn unpack(
self
) -> (OMatrix<T, R, DimMinimum<R, C>>, OMatrix<T, DimMinimum<R, C>, DimMinimum<R, C>>, OMatrix<T, DimMinimum<R, C>, C>)where
DefaultAllocator: Allocator<T, DimMinimum<R, C>, DimMinimum<R, C>> + Allocator<T, R, DimMinimum<R, C>> + Allocator<T, DimMinimum<R, C>, C>,
Unpacks this decomposition into its three matrix factors (U, D, V^t)
.
The decomposed matrix M
is equal to U * D * V^t
.
sourcepub fn d(&self) -> OMatrix<T, DimMinimum<R, C>, DimMinimum<R, C>>
pub fn d(&self) -> OMatrix<T, DimMinimum<R, C>, DimMinimum<R, C>>
Retrieves the upper trapezoidal submatrix R
of this decomposition.
sourcepub fn u(&self) -> OMatrix<T, R, DimMinimum<R, C>>
pub fn u(&self) -> OMatrix<T, R, DimMinimum<R, C>>
Computes the orthogonal matrix U
of this U * D * V
decomposition.
sourcepub fn v_t(&self) -> OMatrix<T, DimMinimum<R, C>, C>
pub fn v_t(&self) -> OMatrix<T, DimMinimum<R, C>, C>
Computes the orthogonal matrix V_t
of this U * D * V_t
decomposition.
sourcepub fn diagonal(&self) -> OVector<T::RealField, DimMinimum<R, C>>
pub fn diagonal(&self) -> OVector<T::RealField, DimMinimum<R, C>>
The diagonal part of this decomposed matrix.
sourcepub fn off_diagonal(
&self
) -> OVector<T::RealField, DimDiff<DimMinimum<R, C>, U1>>
pub fn off_diagonal( &self ) -> OVector<T::RealField, DimDiff<DimMinimum<R, C>, U1>>
The off-diagonal part of this decomposed matrix.
Trait Implementations§
source§impl<T: Clone + ComplexField, R: Clone + DimMin<C>, C: Clone + Dim> Clone for Bidiagonal<T, R, C>where
DimMinimum<R, C>: DimSub<U1>,
DefaultAllocator: Allocator<T, R, C> + Allocator<T, DimMinimum<R, C>> + Allocator<T, DimDiff<DimMinimum<R, C>, U1>>,
impl<T: Clone + ComplexField, R: Clone + DimMin<C>, C: Clone + Dim> Clone for Bidiagonal<T, R, C>where
DimMinimum<R, C>: DimSub<U1>,
DefaultAllocator: Allocator<T, R, C> + Allocator<T, DimMinimum<R, C>> + Allocator<T, DimDiff<DimMinimum<R, C>, U1>>,
source§fn clone(&self) -> Bidiagonal<T, R, C>
fn clone(&self) -> Bidiagonal<T, R, C>
Returns a copy of the value. Read more
1.0.0 · source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
Performs copy-assignment from
source
. Read moresource§impl<T: Debug + ComplexField, R: Debug + DimMin<C>, C: Debug + Dim> Debug for Bidiagonal<T, R, C>where
DimMinimum<R, C>: DimSub<U1>,
DefaultAllocator: Allocator<T, R, C> + Allocator<T, DimMinimum<R, C>> + Allocator<T, DimDiff<DimMinimum<R, C>, U1>>,
impl<T: Debug + ComplexField, R: Debug + DimMin<C>, C: Debug + Dim> Debug for Bidiagonal<T, R, C>where
DimMinimum<R, C>: DimSub<U1>,
DefaultAllocator: Allocator<T, R, C> + Allocator<T, DimMinimum<R, C>> + Allocator<T, DimDiff<DimMinimum<R, C>, U1>>,
source§impl<'de, T: ComplexField, R: DimMin<C>, C: Dim> Deserialize<'de> for Bidiagonal<T, R, C>where
DimMinimum<R, C>: DimSub<U1>,
DefaultAllocator: Allocator<T, R, C> + Allocator<T, DimMinimum<R, C>> + Allocator<T, DimDiff<DimMinimum<R, C>, U1>>,
OMatrix<T, R, C>: Deserialize<'de>,
OVector<T, DimMinimum<R, C>>: Deserialize<'de>,
OVector<T, DimDiff<DimMinimum<R, C>, U1>>: Deserialize<'de>,
impl<'de, T: ComplexField, R: DimMin<C>, C: Dim> Deserialize<'de> for Bidiagonal<T, R, C>where
DimMinimum<R, C>: DimSub<U1>,
DefaultAllocator: Allocator<T, R, C> + Allocator<T, DimMinimum<R, C>> + Allocator<T, DimDiff<DimMinimum<R, C>, U1>>,
OMatrix<T, R, C>: Deserialize<'de>,
OVector<T, DimMinimum<R, C>>: Deserialize<'de>,
OVector<T, DimDiff<DimMinimum<R, C>, U1>>: Deserialize<'de>,
source§fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>where
__D: Deserializer<'de>,
fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>where
__D: Deserializer<'de>,
Deserialize this value from the given Serde deserializer. Read more
source§impl<T: ComplexField, R: DimMin<C>, C: Dim> Serialize for Bidiagonal<T, R, C>where
DimMinimum<R, C>: DimSub<U1>,
DefaultAllocator: Allocator<T, R, C> + Allocator<T, DimMinimum<R, C>> + Allocator<T, DimDiff<DimMinimum<R, C>, U1>>,
OMatrix<T, R, C>: Serialize,
OVector<T, DimMinimum<R, C>>: Serialize,
OVector<T, DimDiff<DimMinimum<R, C>, U1>>: Serialize,
impl<T: ComplexField, R: DimMin<C>, C: Dim> Serialize for Bidiagonal<T, R, C>where
DimMinimum<R, C>: DimSub<U1>,
DefaultAllocator: Allocator<T, R, C> + Allocator<T, DimMinimum<R, C>> + Allocator<T, DimDiff<DimMinimum<R, C>, U1>>,
OMatrix<T, R, C>: Serialize,
OVector<T, DimMinimum<R, C>>: Serialize,
OVector<T, DimDiff<DimMinimum<R, C>, U1>>: Serialize,
impl<T: ComplexField, R: DimMin<C>, C: Dim> Copy for Bidiagonal<T, R, C>where
DimMinimum<R, C>: DimSub<U1>,
DefaultAllocator: Allocator<T, R, C> + Allocator<T, DimMinimum<R, C>> + Allocator<T, DimDiff<DimMinimum<R, C>, U1>>,
OMatrix<T, R, C>: Copy,
OVector<T, DimMinimum<R, C>>: Copy,
OVector<T, DimDiff<DimMinimum<R, C>, U1>>: Copy,
Auto Trait Implementations§
impl<T, R, C> !Freeze for Bidiagonal<T, R, C>
impl<T, R, C> !RefUnwindSafe for Bidiagonal<T, R, C>
impl<T, R, C> !Send for Bidiagonal<T, R, C>
impl<T, R, C> !Sync for Bidiagonal<T, R, C>
impl<T, R, C> !Unpin for Bidiagonal<T, R, C>
impl<T, R, C> !UnwindSafe for Bidiagonal<T, R, C>
Blanket Implementations§
source§impl<T> BorrowMut<T> for Twhere
T: ?Sized,
impl<T> BorrowMut<T> for Twhere
T: ?Sized,
source§fn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more
source§impl<SS, SP> SupersetOf<SS> for SPwhere
SS: SubsetOf<SP>,
impl<SS, SP> SupersetOf<SS> for SPwhere
SS: SubsetOf<SP>,
source§fn to_subset(&self) -> Option<SS>
fn to_subset(&self) -> Option<SS>
The inverse inclusion map: attempts to construct
self
from the equivalent element of its
superset. Read moresource§fn is_in_subset(&self) -> bool
fn is_in_subset(&self) -> bool
Checks if
self
is actually part of its subset T
(and can be converted to it).source§fn to_subset_unchecked(&self) -> SS
fn to_subset_unchecked(&self) -> SS
Use with care! Same as
self.to_subset
but without any property checks. Always succeeds.source§fn from_subset(element: &SS) -> SP
fn from_subset(element: &SS) -> SP
The inclusion map: converts
self
to the equivalent element of its superset.