Struct nalgebra::linalg::Cholesky [−][src]
pub struct Cholesky<T: SimdComplexField, D: Dim> where
DefaultAllocator: Allocator<T, D, D>, { /* fields omitted */ }
The Cholesky decomposition of a symmetric-definite-positive matrix.
Implementations
impl<T: SimdComplexField, D: Dim> Cholesky<T, D> where
DefaultAllocator: Allocator<T, D, D>,
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impl<T: SimdComplexField, D: Dim> Cholesky<T, D> where
DefaultAllocator: Allocator<T, D, D>,
[src]pub fn new_unchecked(matrix: OMatrix<T, D, D>) -> Self
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Computes the Cholesky decomposition of matrix
without checking that the matrix is definite-positive.
If the input matrix is not definite-positive, the decomposition may contain trash values (Inf, NaN, etc.)
pub fn unpack(self) -> OMatrix<T, D, D>
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Retrieves the lower-triangular factor of the Cholesky decomposition with its strictly upper-triangular part filled with zeros.
pub fn unpack_dirty(self) -> OMatrix<T, D, D>
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Retrieves the lower-triangular factor of the Cholesky decomposition, without zeroing-out its strict upper-triangular part.
The values of the strict upper-triangular part are garbage and should be ignored by further computations.
pub fn l(&self) -> OMatrix<T, D, D>
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Retrieves the lower-triangular factor of the Cholesky decomposition with its strictly uppen-triangular part filled with zeros.
pub fn l_dirty(&self) -> &OMatrix<T, D, D>
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Retrieves the lower-triangular factor of the Cholesky decomposition, without zeroing-out its strict upper-triangular part.
This is an allocation-less version of self.l()
. The values of the strict upper-triangular
part are garbage and should be ignored by further computations.
pub fn solve_mut<R2: Dim, C2: Dim, S2>(&self, b: &mut Matrix<T, R2, C2, S2>) where
S2: StorageMut<T, R2, C2>,
ShapeConstraint: SameNumberOfRows<R2, D>,
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S2: StorageMut<T, R2, C2>,
ShapeConstraint: SameNumberOfRows<R2, D>,
Solves the system self * x = b
where self
is the decomposed matrix and x
the unknown.
The result is stored on b
.
pub fn solve<R2: Dim, C2: Dim, S2>(
&self,
b: &Matrix<T, R2, C2, S2>
) -> OMatrix<T, R2, C2> where
S2: Storage<T, R2, C2>,
DefaultAllocator: Allocator<T, R2, C2>,
ShapeConstraint: SameNumberOfRows<R2, D>,
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&self,
b: &Matrix<T, R2, C2, S2>
) -> OMatrix<T, R2, C2> where
S2: Storage<T, R2, C2>,
DefaultAllocator: Allocator<T, R2, C2>,
ShapeConstraint: SameNumberOfRows<R2, D>,
Returns the solution of the system self * x = b
where self
is the decomposed matrix and
x
the unknown.
pub fn inverse(&self) -> OMatrix<T, D, D>
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Computes the inverse of the decomposed matrix.
pub fn determinant(&self) -> T::SimdRealField
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Computes the determinant of the decomposed matrix.
impl<T: ComplexField, D: Dim> Cholesky<T, D> where
DefaultAllocator: Allocator<T, D, D>,
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impl<T: ComplexField, D: Dim> Cholesky<T, D> where
DefaultAllocator: Allocator<T, D, D>,
[src]pub fn new(matrix: OMatrix<T, D, D>) -> Option<Self>
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Attempts to compute the Cholesky decomposition of matrix
.
Returns None
if the input matrix is not definite-positive. The input matrix is assumed
to be symmetric and only the lower-triangular part is read.
pub fn rank_one_update<R2: Dim, S2>(
&mut self,
x: &Vector<T, R2, S2>,
sigma: T::RealField
) where
S2: Storage<T, R2, U1>,
DefaultAllocator: Allocator<T, R2, U1>,
ShapeConstraint: SameNumberOfRows<R2, D>,
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&mut self,
x: &Vector<T, R2, S2>,
sigma: T::RealField
) where
S2: Storage<T, R2, U1>,
DefaultAllocator: Allocator<T, R2, U1>,
ShapeConstraint: SameNumberOfRows<R2, D>,
Given the Cholesky decomposition of a matrix M
, a scalar sigma
and a vector v
,
performs a rank one update such that we end up with the decomposition of M + sigma * (v * v.adjoint())
.
pub fn insert_column<R2, S2>(
&self,
j: usize,
col: Vector<T, R2, S2>
) -> Cholesky<T, DimSum<D, U1>> where
D: DimAdd<U1>,
R2: Dim,
S2: Storage<T, R2, U1>,
DefaultAllocator: Allocator<T, DimSum<D, U1>, DimSum<D, U1>> + Allocator<T, R2>,
ShapeConstraint: SameNumberOfRows<R2, DimSum<D, U1>>,
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&self,
j: usize,
col: Vector<T, R2, S2>
) -> Cholesky<T, DimSum<D, U1>> where
D: DimAdd<U1>,
R2: Dim,
S2: Storage<T, R2, U1>,
DefaultAllocator: Allocator<T, DimSum<D, U1>, DimSum<D, U1>> + Allocator<T, R2>,
ShapeConstraint: SameNumberOfRows<R2, DimSum<D, U1>>,
Updates the decomposition such that we get the decomposition of a matrix with the given column col
in the j
th position.
Since the matrix is square, an identical row will be added in the j
th row.
pub fn remove_column(&self, j: usize) -> Cholesky<T, DimDiff<D, U1>> where
D: DimSub<U1>,
DefaultAllocator: Allocator<T, DimDiff<D, U1>, DimDiff<D, U1>> + Allocator<T, D>,
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D: DimSub<U1>,
DefaultAllocator: Allocator<T, DimDiff<D, U1>, DimDiff<D, U1>> + Allocator<T, D>,
Updates the decomposition such that we get the decomposition of the factored matrix with its j
th column removed.
Since the matrix is square, the j
th row will also be removed.
Trait Implementations
impl<T: Clone + SimdComplexField, D: Clone + Dim> Clone for Cholesky<T, D> where
DefaultAllocator: Allocator<T, D, D>,
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impl<T: Clone + SimdComplexField, D: Clone + Dim> Clone for Cholesky<T, D> where
DefaultAllocator: Allocator<T, D, D>,
[src]impl<T: SimdComplexField, D: Dim> Copy for Cholesky<T, D> where
DefaultAllocator: Allocator<T, D, D>,
OMatrix<T, D, D>: Copy,
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impl<T: SimdComplexField, D: Dim> Copy for Cholesky<T, D> where
DefaultAllocator: Allocator<T, D, D>,
OMatrix<T, D, D>: Copy,
[src]Auto Trait Implementations
impl<T, D> !RefUnwindSafe for Cholesky<T, D>
impl<T, D> !RefUnwindSafe for Cholesky<T, D>
impl<T, D> !UnwindSafe for Cholesky<T, D>
impl<T, D> !UnwindSafe for Cholesky<T, D>
Blanket Implementations
impl<SS, SP> SupersetOf<SS> for SP where
SS: SubsetOf<SP>,
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impl<SS, SP> SupersetOf<SS> for SP where
SS: SubsetOf<SP>,
[src]pub fn to_subset(&self) -> Option<SS>
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pub fn is_in_subset(&self) -> bool
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pub fn to_subset_unchecked(&self) -> SS
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pub fn from_subset(element: &SS) -> SP
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impl<V, T> VZip<V> for T where
V: MultiLane<T>,
impl<V, T> VZip<V> for T where
V: MultiLane<T>,