Struct nalgebra::linalg::Cholesky [−][src]
pub struct Cholesky<N: SimdComplexField, D: Dim> where
DefaultAllocator: Allocator<N, D, D>, { /* fields omitted */ }
The Cholesky decomposition of a symmetric-definite-positive matrix.
Implementations
impl<N: SimdComplexField, D: Dim> Cholesky<N, D> where
DefaultAllocator: Allocator<N, D, D>,
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impl<N: SimdComplexField, D: Dim> Cholesky<N, D> where
DefaultAllocator: Allocator<N, D, D>,
[src]pub fn new_unchecked(matrix: MatrixN<N, 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) -> MatrixN<N, 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) -> MatrixN<N, 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) -> MatrixN<N, 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) -> &MatrixN<N, 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<N, R2, C2, S2>) where
S2: StorageMut<N, R2, C2>,
ShapeConstraint: SameNumberOfRows<R2, D>,
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S2: StorageMut<N, 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<N, R2, C2, S2>
) -> MatrixMN<N, R2, C2> where
S2: Storage<N, R2, C2>,
DefaultAllocator: Allocator<N, R2, C2>,
ShapeConstraint: SameNumberOfRows<R2, D>,
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&self,
b: &Matrix<N, R2, C2, S2>
) -> MatrixMN<N, R2, C2> where
S2: Storage<N, R2, C2>,
DefaultAllocator: Allocator<N, 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) -> MatrixN<N, D>
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Computes the inverse of the decomposed matrix.
impl<N: ComplexField, D: Dim> Cholesky<N, D> where
DefaultAllocator: Allocator<N, D, D>,
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impl<N: ComplexField, D: Dim> Cholesky<N, D> where
DefaultAllocator: Allocator<N, D, D>,
[src]pub fn new(matrix: MatrixN<N, 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<N, R2, S2>,
sigma: N::RealField
) where
S2: Storage<N, R2, U1>,
DefaultAllocator: Allocator<N, R2, U1>,
ShapeConstraint: SameNumberOfRows<R2, D>,
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&mut self,
x: &Vector<N, R2, S2>,
sigma: N::RealField
) where
S2: Storage<N, R2, U1>,
DefaultAllocator: Allocator<N, 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<N, R2, S2>
) -> Cholesky<N, DimSum<D, U1>> where
D: DimAdd<U1>,
R2: Dim,
S2: Storage<N, R2, U1>,
DefaultAllocator: Allocator<N, DimSum<D, U1>, DimSum<D, U1>> + Allocator<N, R2>,
ShapeConstraint: SameNumberOfRows<R2, DimSum<D, U1>>,
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&self,
j: usize,
col: Vector<N, R2, S2>
) -> Cholesky<N, DimSum<D, U1>> where
D: DimAdd<U1>,
R2: Dim,
S2: Storage<N, R2, U1>,
DefaultAllocator: Allocator<N, DimSum<D, U1>, DimSum<D, U1>> + Allocator<N, 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<N, DimDiff<D, U1>> where
D: DimSub<U1>,
DefaultAllocator: Allocator<N, DimDiff<D, U1>, DimDiff<D, U1>> + Allocator<N, D>,
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D: DimSub<U1>,
DefaultAllocator: Allocator<N, DimDiff<D, U1>, DimDiff<D, U1>> + Allocator<N, 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<N: Clone + SimdComplexField, D: Clone + Dim> Clone for Cholesky<N, D> where
DefaultAllocator: Allocator<N, D, D>,
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impl<N: Clone + SimdComplexField, D: Clone + Dim> Clone for Cholesky<N, D> where
DefaultAllocator: Allocator<N, D, D>,
[src]impl<N: Debug + SimdComplexField, D: Debug + Dim> Debug for Cholesky<N, D> where
DefaultAllocator: Allocator<N, D, D>,
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impl<N: Debug + SimdComplexField, D: Debug + Dim> Debug for Cholesky<N, D> where
DefaultAllocator: Allocator<N, D, D>,
[src]impl<'de, N: SimdComplexField, D: Dim> Deserialize<'de> for Cholesky<N, D> where
DefaultAllocator: Allocator<N, D, D>,
DefaultAllocator: Allocator<N, D>,
MatrixN<N, D>: Deserialize<'de>,
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impl<'de, N: SimdComplexField, D: Dim> Deserialize<'de> for Cholesky<N, D> where
DefaultAllocator: Allocator<N, D, D>,
DefaultAllocator: Allocator<N, D>,
MatrixN<N, D>: Deserialize<'de>,
[src]fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
__D: Deserializer<'de>,
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__D: Deserializer<'de>,
impl<N: SimdComplexField, D: Dim> Serialize for Cholesky<N, D> where
DefaultAllocator: Allocator<N, D, D>,
DefaultAllocator: Allocator<N, D>,
MatrixN<N, D>: Serialize,
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impl<N: SimdComplexField, D: Dim> Serialize for Cholesky<N, D> where
DefaultAllocator: Allocator<N, D, D>,
DefaultAllocator: Allocator<N, D>,
MatrixN<N, D>: Serialize,
[src]impl<N: SimdComplexField, D: Dim> Copy for Cholesky<N, D> where
DefaultAllocator: Allocator<N, D, D>,
MatrixN<N, D>: Copy,
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DefaultAllocator: Allocator<N, D, D>,
MatrixN<N, D>: Copy,
Auto Trait Implementations
impl<N, D> !RefUnwindSafe for Cholesky<N, D>
impl<N, D> !Send for Cholesky<N, D>
impl<N, D> !Sync for Cholesky<N, D>
impl<N, D> !Unpin for Cholesky<N, D>
impl<N, D> !UnwindSafe for Cholesky<N, 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>,
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