nalgebra/nalgebra-lapack/src/eigen.rs

409 lines
14 KiB
Rust

#[cfg(feature = "serde-serialize")]
use serde::{Deserialize, Serialize};
use num::Zero;
use num_complex::Complex;
use simba::scalar::RealField;
use crate::ComplexHelper;
use na::dimension::{Const, Dim};
use na::{allocator::Allocator, DefaultAllocator, Matrix, OMatrix, OVector, Scalar};
use lapack;
/// Eigendecomposition of a real square matrix with real or complex eigenvalues.
#[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
#[cfg_attr(
feature = "serde-serialize",
serde(
bound(serialize = "DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
OVector<T, D>: Serialize,
OMatrix<T, D, D>: Serialize")
)
)]
#[cfg_attr(
feature = "serde-serialize",
serde(
bound(deserialize = "DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
OVector<T, D>: Serialize,
OMatrix<T, D, D>: Deserialize<'de>")
)
)]
#[derive(Clone, Debug)]
pub struct Eigen<T: Scalar, D: Dim>
where
DefaultAllocator: Allocator<T, D> + Allocator<T, D, D>,
{
/// The real parts of eigenvalues of the decomposed matrix.
pub eigenvalues_re: OVector<T, D>,
/// The imaginary parts of the eigenvalues of the decomposed matrix.
pub eigenvalues_im: OVector<T, D>,
/// The (right) eigenvectors of the decomposed matrix.
pub eigenvectors: Option<OMatrix<T, D, D>>,
/// The left eigenvectors of the decomposed matrix.
pub left_eigenvectors: Option<OMatrix<T, D, D>>,
}
impl<T: Scalar + Copy, D: Dim> Copy for Eigen<T, D>
where
DefaultAllocator: Allocator<T, D> + Allocator<T, D, D>,
OVector<T, D>: Copy,
OMatrix<T, D, D>: Copy,
{
}
impl<T: EigenScalar + RealField, D: Dim> Eigen<T, D>
where
DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
{
/// Computes the eigenvalues and eigenvectors of the square matrix `m`.
///
/// If `eigenvectors` is `false` then, the eigenvectors are not computed explicitly.
pub fn new(
mut m: OMatrix<T, D, D>,
left_eigenvectors: bool,
eigenvectors: bool,
) -> Option<Eigen<T, D>> {
assert!(
m.is_square(),
"Unable to compute the eigenvalue decomposition of a non-square matrix."
);
let ljob = if left_eigenvectors { b'V' } else { b'N' };
let rjob = if eigenvectors { b'V' } else { b'N' };
let (nrows, ncols) = m.shape_generic();
let n = nrows.value();
let lda = n as i32;
// TODO: avoid the initialization?
let mut wr = Matrix::zeros_generic(nrows, Const::<1>);
// TODO: Tap into the workspace.
let mut wi = Matrix::zeros_generic(nrows, Const::<1>);
let mut info = 0;
let mut placeholder1 = [T::zero()];
let mut placeholder2 = [T::zero()];
let lwork = T::xgeev_work_size(
ljob,
rjob,
n as i32,
m.as_mut_slice(),
lda,
wr.as_mut_slice(),
wi.as_mut_slice(),
&mut placeholder1,
n as i32,
&mut placeholder2,
n as i32,
&mut info,
);
lapack_check!(info);
let mut work = vec![T::zero(); lwork as usize];
let mut vl = if left_eigenvectors {
Some(Matrix::zeros_generic(nrows, ncols))
} else {
None
};
let mut vr = if eigenvectors {
Some(Matrix::zeros_generic(nrows, ncols))
} else {
None
};
let vl_ref = vl
.as_mut()
.map(|m| m.as_mut_slice())
.unwrap_or(&mut placeholder1);
let vr_ref = vr
.as_mut()
.map(|m| m.as_mut_slice())
.unwrap_or(&mut placeholder2);
T::xgeev(
ljob,
rjob,
n as i32,
m.as_mut_slice(),
lda,
wr.as_mut_slice(),
wi.as_mut_slice(),
vl_ref,
if left_eigenvectors { n as i32 } else { 1 },
vr_ref,
if eigenvectors { n as i32 } else { 1 },
&mut work,
lwork,
&mut info,
);
lapack_check!(info);
Some(Self {
eigenvalues_re: wr,
eigenvalues_im: wi,
left_eigenvectors: vl,
eigenvectors: vr,
})
}
/// Returns `true` if all the eigenvalues are real.
pub fn eigenvalues_are_real(&self) -> bool {
self.eigenvalues_im.iter().all(|e| e.is_zero())
}
/// The determinant of the decomposed matrix.
#[inline]
#[must_use]
pub fn determinant(&self) -> Complex<T> {
let mut det: Complex<T> = na::one();
for (re, im) in self.eigenvalues_re.iter().zip(self.eigenvalues_im.iter()) {
det *= Complex::new(re.clone(), im.clone());
}
det
}
/// Returns a tuple of vectors. The elements of the tuple are the real parts of the eigenvalues, left eigenvectors and right eigenvectors respectively.
pub fn get_real_elements(
&self,
) -> (
Vec<T>,
Option<Vec<OVector<T, D>>>,
Option<Vec<OVector<T, D>>>,
)
where
DefaultAllocator: Allocator<T, D>,
{
let (number_of_elements, _) = self.eigenvalues_re.shape_generic();
let number_of_elements_value = number_of_elements.value();
let mut eigenvalues = Vec::<T>::with_capacity(number_of_elements_value);
let mut eigenvectors = match self.eigenvectors.is_some() {
true => Some(Vec::<OVector<T, D>>::with_capacity(
number_of_elements_value,
)),
false => None,
};
let mut left_eigenvectors = match self.left_eigenvectors.is_some() {
true => Some(Vec::<OVector<T, D>>::with_capacity(
number_of_elements_value,
)),
false => None,
};
let mut c = 0;
while c < number_of_elements_value {
eigenvalues.push(self.eigenvalues_re[c].clone());
if eigenvectors.is_some() {
eigenvectors
.as_mut()
.unwrap()
.push(self.eigenvectors.as_ref().unwrap().column(c).into_owned());
}
if left_eigenvectors.is_some() {
left_eigenvectors.as_mut().unwrap().push(
self.left_eigenvectors
.as_ref()
.unwrap()
.column(c)
.into_owned(),
);
}
if self.eigenvalues_im[c] != T::zero() {
//skip next entry
c += 1;
}
c += 1;
}
(eigenvalues, left_eigenvectors, eigenvectors)
}
/// Returns a tuple of vectors. The elements of the tuple are the complex eigenvalues, complex left eigenvectors and complex right eigenvectors respectively.
/// The elements appear as conjugate pairs within each vector, with the positive of the pair always being first.
pub fn get_complex_elements(
&self,
) -> (
Option<Vec<Complex<T>>>,
Option<Vec<OVector<Complex<T>, D>>>,
Option<Vec<OVector<Complex<T>, D>>>,
)
where
DefaultAllocator: Allocator<Complex<T>, D>,
{
match self.eigenvalues_are_real() {
true => (None, None, None),
false => {
let (number_of_elements, _) = self.eigenvalues_re.shape_generic();
let number_of_elements_value = number_of_elements.value();
let number_of_complex_entries =
self.eigenvalues_im
.iter()
.fold(0, |acc, e| if !e.is_zero() { acc + 1 } else { acc });
let mut eigenvalues = Vec::<Complex<T>>::with_capacity(number_of_complex_entries);
let mut eigenvectors = match self.eigenvectors.is_some() {
true => Some(Vec::<OVector<Complex<T>, D>>::with_capacity(
number_of_complex_entries,
)),
false => None,
};
let mut left_eigenvectors = match self.left_eigenvectors.is_some() {
true => Some(Vec::<OVector<Complex<T>, D>>::with_capacity(
number_of_complex_entries,
)),
false => None,
};
let mut c = 0;
while c < number_of_elements_value {
if self.eigenvalues_im[c] != T::zero() {
//Complex conjugate pairs of eigenvalues appear consecutively with the eigenvalue having the positive imaginary part first.
eigenvalues.push(Complex::<T>::new(
self.eigenvalues_re[c].clone(),
self.eigenvalues_im[c].clone(),
));
eigenvalues.push(Complex::<T>::new(
self.eigenvalues_re[c + 1].clone(),
self.eigenvalues_im[c + 1].clone(),
));
if eigenvectors.is_some() {
let mut vec = OVector::<Complex<T>, D>::zeros_generic(
number_of_elements,
Const::<1>,
);
let mut vec_conj = OVector::<Complex<T>, D>::zeros_generic(
number_of_elements,
Const::<1>,
);
for r in 0..number_of_elements_value {
vec[r] = Complex::<T>::new(
self.eigenvectors.as_ref().unwrap()[(r, c)].clone(),
self.eigenvectors.as_ref().unwrap()[(r, c + 1)].clone(),
);
vec_conj[r] = Complex::<T>::new(
self.eigenvectors.as_ref().unwrap()[(r, c)].clone(),
self.eigenvectors.as_ref().unwrap()[(r, c + 1)].clone(),
);
}
eigenvectors.as_mut().unwrap().push(vec);
eigenvectors.as_mut().unwrap().push(vec_conj);
}
if left_eigenvectors.is_some() {
let mut vec = OVector::<Complex<T>, D>::zeros_generic(
number_of_elements,
Const::<1>,
);
let mut vec_conj = OVector::<Complex<T>, D>::zeros_generic(
number_of_elements,
Const::<1>,
);
for r in 0..number_of_elements_value {
vec[r] = Complex::<T>::new(
self.left_eigenvectors.as_ref().unwrap()[(r, c)].clone(),
self.left_eigenvectors.as_ref().unwrap()[(r, c + 1)].clone(),
);
vec_conj[r] = Complex::<T>::new(
self.left_eigenvectors.as_ref().unwrap()[(r, c)].clone(),
self.left_eigenvectors.as_ref().unwrap()[(r, c + 1)].clone(),
);
}
left_eigenvectors.as_mut().unwrap().push(vec);
left_eigenvectors.as_mut().unwrap().push(vec_conj);
}
//skip next entry
c += 1;
}
c += 1;
}
(Some(eigenvalues), left_eigenvectors, eigenvectors)
}
}
}
}
/*
*
* Lapack functions dispatch.
*
*/
/// Trait implemented by scalar type for which Lapack function exist to compute the
/// eigendecomposition.
pub trait EigenScalar: Scalar {
#[allow(missing_docs)]
fn xgeev(
jobvl: u8,
jobvr: u8,
n: i32,
a: &mut [Self],
lda: i32,
wr: &mut [Self],
wi: &mut [Self],
vl: &mut [Self],
ldvl: i32,
vr: &mut [Self],
ldvr: i32,
work: &mut [Self],
lwork: i32,
info: &mut i32,
);
#[allow(missing_docs)]
fn xgeev_work_size(
jobvl: u8,
jobvr: u8,
n: i32,
a: &mut [Self],
lda: i32,
wr: &mut [Self],
wi: &mut [Self],
vl: &mut [Self],
ldvl: i32,
vr: &mut [Self],
ldvr: i32,
info: &mut i32,
) -> i32;
}
macro_rules! real_eigensystem_scalar_impl (
($N: ty, $xgeev: path) => (
impl EigenScalar for $N {
#[inline]
fn xgeev(jobvl: u8, jobvr: u8, n: i32, a: &mut [Self], lda: i32,
wr: &mut [Self], wi: &mut [Self],
vl: &mut [Self], ldvl: i32, vr: &mut [Self], ldvr: i32,
work: &mut [Self], lwork: i32, info: &mut i32) {
unsafe { $xgeev(jobvl, jobvr, n, a, lda, wr, wi, vl, ldvl, vr, ldvr, work, lwork, info) }
}
#[inline]
fn xgeev_work_size(jobvl: u8, jobvr: u8, n: i32, a: &mut [Self], lda: i32,
wr: &mut [Self], wi: &mut [Self], vl: &mut [Self], ldvl: i32,
vr: &mut [Self], ldvr: i32, info: &mut i32) -> i32 {
let mut work = [ Zero::zero() ];
let lwork = -1 as i32;
unsafe { $xgeev(jobvl, jobvr, n, a, lda, wr, wi, vl, ldvl, vr, ldvr, &mut work, lwork, info) };
ComplexHelper::real_part(work[0]) as i32
}
}
)
);
real_eigensystem_scalar_impl!(f32, lapack::sgeev);
real_eigensystem_scalar_impl!(f64, lapack::dgeev);
//// TODO: decomposition of complex matrix and matrices with complex eigenvalues.
// eigensystem_complex_impl!(f32, lapack::cgeev);
// eigensystem_complex_impl!(f64, lapack::zgeev);