Struct nalgebra::linalg::SymmetricEigen [−][src]
pub struct SymmetricEigen<T: ComplexField, D: Dim> where
DefaultAllocator: Allocator<T, D, D> + Allocator<T::RealField, D>, {
pub eigenvectors: OMatrix<T, D, D>,
pub eigenvalues: OVector<T::RealField, D>,
}
Expand description
Eigendecomposition of a symmetric matrix.
Fields
eigenvectors: OMatrix<T, D, D>
The eigenvectors of the decomposed matrix.
eigenvalues: OVector<T::RealField, D>
The unsorted eigenvalues of the decomposed matrix.
Implementations
impl<T: ComplexField, D: Dim> SymmetricEigen<T, D> where
DefaultAllocator: Allocator<T, D, D> + Allocator<T::RealField, D>,
impl<T: ComplexField, D: Dim> SymmetricEigen<T, D> where
DefaultAllocator: Allocator<T, D, D> + Allocator<T::RealField, D>,
Computes the eigendecomposition of the given symmetric matrix.
Only the lower-triangular parts (including its diagonal) of m
is read.
Computes the eigendecomposition of the given symmetric matrix with user-specified convergence parameters.
Only the lower-triangular part (including its diagonal) of m
is read.
Arguments
eps
− tolerance used to determine when a value converged to 0.max_niter
− maximum total number of iterations performed by the algorithm. If this number of iteration is exceeded,None
is returned. Ifniter == 0
, then the algorithm continues indefinitely until convergence.
Trait Implementations
impl<T: Clone + ComplexField, D: Clone + Dim> Clone for SymmetricEigen<T, D> where
DefaultAllocator: Allocator<T, D, D> + Allocator<T::RealField, D>,
T::RealField: Clone,
impl<T: Clone + ComplexField, D: Clone + Dim> Clone for SymmetricEigen<T, D> where
DefaultAllocator: Allocator<T, D, D> + Allocator<T::RealField, D>,
T::RealField: Clone,
impl<T: Debug + ComplexField, D: Debug + Dim> Debug for SymmetricEigen<T, D> where
DefaultAllocator: Allocator<T, D, D> + Allocator<T::RealField, D>,
T::RealField: Debug,
impl<T: Debug + ComplexField, D: Debug + Dim> Debug for SymmetricEigen<T, D> where
DefaultAllocator: Allocator<T, D, D> + Allocator<T::RealField, D>,
T::RealField: Debug,
impl<'de, T: ComplexField, D: Dim> Deserialize<'de> for SymmetricEigen<T, D> where
DefaultAllocator: Allocator<T, D, D> + Allocator<T::RealField, D>,
DefaultAllocator: Allocator<T, D, D> + Allocator<T::RealField, D>,
OVector<T::RealField, D>: Deserialize<'de>,
OMatrix<T, D, D>: Deserialize<'de>,
impl<'de, T: ComplexField, D: Dim> Deserialize<'de> for SymmetricEigen<T, D> where
DefaultAllocator: Allocator<T, D, D> + Allocator<T::RealField, D>,
DefaultAllocator: Allocator<T, D, D> + Allocator<T::RealField, D>,
OVector<T::RealField, D>: Deserialize<'de>,
OMatrix<T, D, D>: 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
impl<T: ComplexField, D: Dim> Serialize for SymmetricEigen<T, D> where
DefaultAllocator: Allocator<T, D, D> + Allocator<T::RealField, D>,
DefaultAllocator: Allocator<T, D, D> + Allocator<T::RealField, D>,
OVector<T::RealField, D>: Serialize,
OMatrix<T, D, D>: Serialize,
impl<T: ComplexField, D: Dim> Serialize for SymmetricEigen<T, D> where
DefaultAllocator: Allocator<T, D, D> + Allocator<T::RealField, D>,
DefaultAllocator: Allocator<T, D, D> + Allocator<T::RealField, D>,
OVector<T::RealField, D>: Serialize,
OMatrix<T, D, D>: Serialize,
impl<T: ComplexField, D: Dim> Copy for SymmetricEigen<T, D> where
DefaultAllocator: Allocator<T, D, D> + Allocator<T::RealField, D>,
OMatrix<T, D, D>: Copy,
OVector<T::RealField, D>: Copy,
Auto Trait Implementations
impl<T, D> !RefUnwindSafe for SymmetricEigen<T, D>
impl<T, D> !Send for SymmetricEigen<T, D>
impl<T, D> !Sync for SymmetricEigen<T, D>
impl<T, D> !Unpin for SymmetricEigen<T, D>
impl<T, D> !UnwindSafe for SymmetricEigen<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.