98 lines
3.4 KiB
Rust
98 lines
3.4 KiB
Rust
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use alga::general::Real;
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use core::{MatrixN, MatrixMN, VectorN, DefaultAllocator};
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use dimension::{DimSub, DimDiff, Dynamic, U1};
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use storage::Storage;
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use allocator::Allocator;
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use constraint::{ShapeConstraint, DimEq};
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use linalg::householder;
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/// The Hessenberg decomposition of a general matrix.
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pub struct Hessenberg<N: Real, D: DimSub<U1>>
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where DefaultAllocator: Allocator<N, D, D> +
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Allocator<N, DimDiff<D, U1>> {
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hess: MatrixN<N, D>,
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subdiag: VectorN<N, DimDiff<D, U1>>
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}
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impl<N: Real, D: DimSub<U1>> Hessenberg<N, D>
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where DefaultAllocator: Allocator<N, D, D> +
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Allocator<N, D> +
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Allocator<N, DimDiff<D, U1>> {
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/// Computes the Hessenberg decomposition using householder reflections.
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pub fn new(hess: MatrixN<N, D>) -> Self {
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let mut work = unsafe { MatrixMN::new_uninitialized_generic(hess.data.shape().0, U1) };
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Self::new_with_workspace(hess, &mut work)
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}
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/// Computes the Hessenberg decomposition using householder reflections.
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///
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/// The workspace containing `D` elements must be provided and may be uninitialized.
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pub fn new_with_workspace(mut hess: MatrixN<N, D>, work: &mut VectorN<N, D>) -> Self {
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assert!(hess.is_square(), "Cannot compute the hessenberg decomposition of a non-square matrix.");
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let dim = hess.data.shape().0;
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assert!(dim.value() != 0, "Cannot compute the hessenberg decomposition of an empty matrix.");
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assert_eq!(dim.value(), work.len(), "Hessenberg: invalid workspace size.");
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let mut subdiag = unsafe { MatrixMN::new_uninitialized_generic(dim.sub(U1), U1) };
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if dim.value() == 0 {
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return Hessenberg { hess, subdiag };
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}
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for ite in 0 .. dim.value() - 1 {
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householder::clear_column_unchecked(&mut hess, &mut subdiag[ite], ite, 1, Some(work));
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}
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Hessenberg { hess, subdiag }
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}
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/// Retrieves `(q, h)` with `q` the orthogonal matrix of this decomposition and `h` the
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/// hessenberg matrix.
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#[inline]
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pub fn unpack(self) -> (MatrixN<N, D>, MatrixN<N, D>)
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where ShapeConstraint: DimEq<Dynamic, DimDiff<D, U1>> {
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let q = self.q();
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(q, self.unpack_h())
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}
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/// Retrieves the upper trapezoidal submatrix `H` of this decomposition.
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#[inline]
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pub fn unpack_h(mut self) -> MatrixN<N, D>
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where ShapeConstraint: DimEq<Dynamic, DimDiff<D, U1>> {
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let dim = self.hess.nrows();
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self.hess.fill_lower_triangle(N::zero(), 2);
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self.hess.slice_mut((1, 0), (dim - 1, dim - 1)).set_diagonal(&self.subdiag);
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self.hess
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}
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// FIXME: add a h that moves out of self.
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/// Retrieves the upper trapezoidal submatrix `H` of this decomposition.
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///
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/// This is less efficient than `.unpack_h()`.
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#[inline]
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pub fn h(&self) -> MatrixN<N, D>
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where ShapeConstraint: DimEq<Dynamic, DimDiff<D, U1>> {
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let dim = self.hess.nrows();
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let mut res = self.hess.clone();
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res.fill_lower_triangle(N::zero(), 2);
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res.slice_mut((1, 0), (dim - 1, dim - 1)).set_diagonal(&self.subdiag);
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res
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}
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/// Computes the orthogonal matrix `Q` of this decomposition.
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pub fn q(&self) -> MatrixN<N, D> {
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householder::assemble_q(&self.hess)
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}
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#[doc(hidden)]
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pub fn hess_internal(&self) -> &MatrixN<N, D> {
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&self.hess
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}
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}
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