Struct nalgebra::linalg::SymmetricTridiagonal [−][src]
pub struct SymmetricTridiagonal<T: ComplexField, D: DimSub<U1>> where
DefaultAllocator: Allocator<T, D, D> + Allocator<T, DimDiff<D, U1>>, { /* fields omitted */ }
Expand description
Tridiagonalization of a symmetric matrix.
Implementations
impl<T: ComplexField, D: DimSub<U1>> SymmetricTridiagonal<T, D> where
DefaultAllocator: Allocator<T, D, D> + Allocator<T, DimDiff<D, U1>>,
impl<T: ComplexField, D: DimSub<U1>> SymmetricTridiagonal<T, D> where
DefaultAllocator: Allocator<T, D, D> + Allocator<T, DimDiff<D, U1>>,
Computes the tridiagonalization of the symmetric matrix m
.
Only the lower-triangular part (including the diagonal) of m
is read.
Retrieve the orthogonal transformation, diagonal, and off diagonal elements of this decomposition.
Retrieve the diagonal, and off diagonal elements of this decomposition.
The diagonal components of this decomposition.
The off-diagonal components of this decomposition.
Trait Implementations
impl<T: Clone + ComplexField, D: Clone + DimSub<U1>> Clone for SymmetricTridiagonal<T, D> where
DefaultAllocator: Allocator<T, D, D> + Allocator<T, DimDiff<D, U1>>,
impl<T: Clone + ComplexField, D: Clone + DimSub<U1>> Clone for SymmetricTridiagonal<T, D> where
DefaultAllocator: Allocator<T, D, D> + Allocator<T, DimDiff<D, U1>>,
impl<T: Debug + ComplexField, D: Debug + DimSub<U1>> Debug for SymmetricTridiagonal<T, D> where
DefaultAllocator: Allocator<T, D, D> + Allocator<T, DimDiff<D, U1>>,
impl<T: Debug + ComplexField, D: Debug + DimSub<U1>> Debug for SymmetricTridiagonal<T, D> where
DefaultAllocator: Allocator<T, D, D> + Allocator<T, DimDiff<D, U1>>,
impl<'de, T: ComplexField, D: DimSub<U1>> Deserialize<'de> for SymmetricTridiagonal<T, D> where
DefaultAllocator: Allocator<T, D, D> + Allocator<T, DimDiff<D, U1>>,
DefaultAllocator: Allocator<T, D, D> + Allocator<T, DimDiff<D, U1>>,
OMatrix<T, D, D>: Deserialize<'de>,
OVector<T, DimDiff<D, U1>>: Deserialize<'de>,
impl<'de, T: ComplexField, D: DimSub<U1>> Deserialize<'de> for SymmetricTridiagonal<T, D> where
DefaultAllocator: Allocator<T, D, D> + Allocator<T, DimDiff<D, U1>>,
DefaultAllocator: Allocator<T, D, D> + Allocator<T, DimDiff<D, U1>>,
OMatrix<T, D, D>: Deserialize<'de>,
OVector<T, DimDiff<D, U1>>: Deserialize<'de>,
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
Auto Trait Implementations
impl<T, D> !RefUnwindSafe for SymmetricTridiagonal<T, D>
impl<T, D> !Send for SymmetricTridiagonal<T, D>
impl<T, D> !Sync for SymmetricTridiagonal<T, D>
impl<T, D> !Unpin for SymmetricTridiagonal<T, D>
impl<T, D> !UnwindSafe for SymmetricTridiagonal<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.