240 lines
6.6 KiB
Rust
240 lines
6.6 KiB
Rust
use num::Zero;
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use num_complex::Complex;
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use crate::ComplexHelper;
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use na::allocator::Allocator;
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use na::dimension::{DimDiff, DimSub, U1};
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use na::storage::Storage;
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use na::{DefaultAllocator, Matrix, MatrixN, Scalar, VectorN};
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use lapack;
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/// The Hessenberg decomposition of a general matrix.
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#[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
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#[cfg_attr(
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feature = "serde-serialize",
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serde(bound(serialize = "DefaultAllocator: Allocator<N, D, D> +
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Allocator<N, DimDiff<D, U1>>,
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MatrixN<N, D>: Serialize,
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VectorN<N, DimDiff<D, U1>>: Serialize"))
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)]
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#[cfg_attr(
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feature = "serde-serialize",
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serde(bound(deserialize = "DefaultAllocator: Allocator<N, D, D> +
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Allocator<N, DimDiff<D, U1>>,
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MatrixN<N, D>: Deserialize<'de>,
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VectorN<N, DimDiff<D, U1>>: Deserialize<'de>"))
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)]
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#[derive(Clone, Debug)]
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pub struct Hessenberg<N: Scalar, D: DimSub<U1>>
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where
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DefaultAllocator: Allocator<N, D, D> + Allocator<N, DimDiff<D, U1>>,
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{
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h: MatrixN<N, D>,
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tau: VectorN<N, DimDiff<D, U1>>,
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}
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impl<N: Scalar + Copy, D: DimSub<U1>> Copy for Hessenberg<N, D>
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where
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DefaultAllocator: Allocator<N, D, D> + Allocator<N, DimDiff<D, U1>>,
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MatrixN<N, D>: Copy,
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VectorN<N, DimDiff<D, U1>>: Copy,
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{
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}
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impl<N: HessenbergScalar + Zero, D: DimSub<U1>> Hessenberg<N, D>
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where
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DefaultAllocator: Allocator<N, D, D> + Allocator<N, DimDiff<D, U1>>,
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{
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/// Computes the hessenberg decomposition of the matrix `m`.
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pub fn new(mut m: MatrixN<N, D>) -> Self {
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let nrows = m.data.shape().0;
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let n = nrows.value() as i32;
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assert!(
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m.is_square(),
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"Unable to compute the hessenberg decomposition of a non-square matrix."
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);
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assert!(
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!m.is_empty(),
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"Unable to compute the hessenberg decomposition of an empty matrix."
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);
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let mut tau = unsafe { Matrix::new_uninitialized_generic(nrows.sub(U1), U1) };
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let mut info = 0;
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let lwork =
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N::xgehrd_work_size(n, 1, n, m.as_mut_slice(), n, tau.as_mut_slice(), &mut info);
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let mut work = unsafe { crate::uninitialized_vec(lwork as usize) };
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lapack_panic!(info);
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N::xgehrd(
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n,
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1,
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n,
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m.as_mut_slice(),
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n,
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tau.as_mut_slice(),
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&mut work,
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lwork,
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&mut info,
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);
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lapack_panic!(info);
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Self { h: m, tau: tau }
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}
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/// Computes the hessenberg matrix of this decomposition.
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#[inline]
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pub fn h(&self) -> MatrixN<N, D> {
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let mut h = self.h.clone_owned();
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h.fill_lower_triangle(N::zero(), 2);
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h
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}
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}
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impl<N: HessenbergReal + Zero, D: DimSub<U1>> Hessenberg<N, D>
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where
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DefaultAllocator: Allocator<N, D, D> + Allocator<N, DimDiff<D, U1>>,
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{
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/// Computes the matrices `(Q, H)` of this decomposition.
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#[inline]
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pub fn unpack(self) -> (MatrixN<N, D>, MatrixN<N, D>) {
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(self.q(), self.h())
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}
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/// Computes the unitary matrix `Q` of this decomposition.
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#[inline]
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pub fn q(&self) -> MatrixN<N, D> {
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let n = self.h.nrows() as i32;
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let mut q = self.h.clone_owned();
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let mut info = 0;
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let lwork =
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N::xorghr_work_size(n, 1, n, q.as_mut_slice(), n, self.tau.as_slice(), &mut info);
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let mut work = vec![N::zero(); lwork as usize];
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N::xorghr(
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n,
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1,
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n,
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q.as_mut_slice(),
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n,
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self.tau.as_slice(),
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&mut work,
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lwork,
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&mut info,
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);
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q
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}
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}
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/*
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*
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* Lapack functions dispatch.
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*
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*/
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pub trait HessenbergScalar: Scalar + Copy {
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fn xgehrd(
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n: i32,
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ilo: i32,
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ihi: i32,
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a: &mut [Self],
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lda: i32,
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tau: &mut [Self],
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work: &mut [Self],
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lwork: i32,
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info: &mut i32,
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);
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fn xgehrd_work_size(
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n: i32,
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ilo: i32,
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ihi: i32,
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a: &mut [Self],
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lda: i32,
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tau: &mut [Self],
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info: &mut i32,
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) -> i32;
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}
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/// Trait implemented by scalars for which Lapack implements the hessenberg decomposition.
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pub trait HessenbergReal: HessenbergScalar {
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#[allow(missing_docs)]
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fn xorghr(
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n: i32,
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ilo: i32,
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ihi: i32,
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a: &mut [Self],
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lda: i32,
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tau: &[Self],
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work: &mut [Self],
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lwork: i32,
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info: &mut i32,
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);
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#[allow(missing_docs)]
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fn xorghr_work_size(
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n: i32,
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ilo: i32,
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ihi: i32,
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a: &mut [Self],
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lda: i32,
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tau: &[Self],
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info: &mut i32,
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) -> i32;
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}
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macro_rules! hessenberg_scalar_impl(
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($N: ty, $xgehrd: path) => (
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impl HessenbergScalar for $N {
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#[inline]
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fn xgehrd(n: i32, ilo: i32, ihi: i32, a: &mut [Self], lda: i32,
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tau: &mut [Self], work: &mut [Self], lwork: i32, info: &mut i32) {
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unsafe { $xgehrd(n, ilo, ihi, a, lda, tau, work, lwork, info) }
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}
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#[inline]
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fn xgehrd_work_size(n: i32, ilo: i32, ihi: i32, a: &mut [Self], lda: i32,
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tau: &mut [Self], info: &mut i32) -> i32 {
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let mut work = [ Zero::zero() ];
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let lwork = -1 as i32;
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unsafe { $xgehrd(n, ilo, ihi, a, lda, tau, &mut work, lwork, info) };
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ComplexHelper::real_part(work[0]) as i32
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}
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}
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)
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);
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macro_rules! hessenberg_real_impl(
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($N: ty, $xorghr: path) => (
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impl HessenbergReal for $N {
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#[inline]
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fn xorghr(n: i32, ilo: i32, ihi: i32, a: &mut [Self], lda: i32, tau: &[Self],
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work: &mut [Self], lwork: i32, info: &mut i32) {
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unsafe { $xorghr(n, ilo, ihi, a, lda, tau, work, lwork, info) }
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}
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#[inline]
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fn xorghr_work_size(n: i32, ilo: i32, ihi: i32, a: &mut [Self], lda: i32,
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tau: &[Self], info: &mut i32) -> i32 {
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let mut work = [ Zero::zero() ];
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let lwork = -1 as i32;
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unsafe { $xorghr(n, ilo, ihi, a, lda, tau, &mut work, lwork, info) };
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ComplexHelper::real_part(work[0]) as i32
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}
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}
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)
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);
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hessenberg_scalar_impl!(f32, lapack::sgehrd);
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hessenberg_scalar_impl!(f64, lapack::dgehrd);
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hessenberg_scalar_impl!(Complex<f32>, lapack::cgehrd);
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hessenberg_scalar_impl!(Complex<f64>, lapack::zgehrd);
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hessenberg_real_impl!(f32, lapack::sorghr);
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hessenberg_real_impl!(f64, lapack::dorghr);
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