Untested UDU implementation

Pushing to trigger build

Signed-off-by: Christopher Rabotin <christopher.rabotin@gmail.com>
This commit is contained in:
Christopher Rabotin 2020-09-24 23:21:13 -06:00 committed by Crozet Sébastien
parent 21cc428480
commit 8dda6714b5
4 changed files with 139 additions and 0 deletions

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@ -25,6 +25,7 @@ mod solve;
mod svd; mod svd;
mod symmetric_eigen; mod symmetric_eigen;
mod symmetric_tridiagonal; mod symmetric_tridiagonal;
mod udu;
//// TODO: Not complete enough for publishing. //// TODO: Not complete enough for publishing.
//// This handles only cases where each eigenvalue has multiplicity one. //// This handles only cases where each eigenvalue has multiplicity one.
@ -45,3 +46,4 @@ pub use self::schur::*;
pub use self::svd::*; pub use self::svd::*;
pub use self::symmetric_eigen::*; pub use self::symmetric_eigen::*;
pub use self::symmetric_tridiagonal::*; pub use self::symmetric_tridiagonal::*;
pub use self::udu::*;

68
src/linalg/udu.rs Normal file
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@ -0,0 +1,68 @@
#[cfg(feature = "serde-serialize")]
use serde::{Deserialize, Serialize};
use crate::allocator::Allocator;
use crate::base::{DefaultAllocator, MatrixN};
use crate::dimension::DimName;
use simba::scalar::ComplexField;
/// UDU factorization
#[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
#[derive(Clone, Debug)]
pub struct UDU<N: ComplexField, D: DimName>
where
DefaultAllocator: Allocator<N, D, D>,
{
/// The upper triangular matrix resulting from the factorization
pub u: MatrixN<N, D>,
/// The diagonal matrix resulting from the factorization
pub d: MatrixN<N, D>,
}
impl<N: ComplexField, D: DimName> Copy for UDU<N, D>
where
DefaultAllocator: Allocator<N, D, D>,
MatrixN<N, D>: Copy,
{
}
impl<N: ComplexField, D: DimName> UDU<N, D>
where
DefaultAllocator: Allocator<N, D, D>,
{
/// Computes the UDU^T factorization as per NASA's "Navigation Filter Best Practices", NTRS document ID 20180003657
/// section 7.2 page 64.
/// NOTE: The provided matrix MUST be symmetric.
pub fn new(matrix: MatrixN<N, D>) -> Self {
let mut d = MatrixN::<N, D>::zeros();
let mut u = MatrixN::<N, D>::zeros();
let n = matrix.ncols();
d[(n, n)] = matrix[(n, n)];
u[(n, n)] = N::one();
for j in (0..n - 1).rev() {
u[(j, n)] = matrix[(j, n)] / d[(n, n)];
}
for j in (1..n).rev() {
d[(j, j)] = matrix[(j, j)];
for k in (j + 1..n).rev() {
d[(j, j)] = d[(j, j)] + d[(k, k)] * u[(j, k)].powi(2);
}
u[(j, j)] = N::one();
for i in (0..j - 1).rev() {
u[(i, j)] = matrix[(i, j)];
for k in j + 1..n {
u[(i, j)] = u[(i, j)] + d[(k, k)] * u[(i, k)] * u[(j, k)];
}
u[(i, j)] /= d[(j, j)];
}
}
Self { u, d }
}
}

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@ -14,3 +14,4 @@ mod schur;
mod solve; mod solve;
mod svd; mod svd;
mod tridiagonal; mod tridiagonal;
mod udu;

68
tests/linalg/udu.rs Normal file
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@ -0,0 +1,68 @@
use na::Matrix3;
use na::UDU;
#[test]
#[rustfmt::skip]
fn udu_simple() {
let m = Matrix3::new(
2.0, -1.0, 0.0,
-1.0, 2.0, -1.0,
0.0, -1.0, 2.0);
let udu = UDU::new(m);
println!("u = {}", udu.u);
println!("d = {}", udu.d);
// Rebuild
let p = &udu.u * &udu.d * &udu.u.transpose();
println!("{}", p);
assert!(relative_eq!(m, p, epsilon = 1.0e-7));
}
#[cfg(feature = "arbitrary")]
mod quickcheck_tests {
#[allow(unused_imports)]
use crate::core::helper::{RandComplex, RandScalar};
macro_rules! gen_tests(
($module: ident, $scalar: ty) => {
mod $module {
use std::cmp;
use na::{DMatrix, Matrix4};
#[allow(unused_imports)]
use crate::core::helper::{RandScalar, RandComplex};
quickcheck! {
fn udu(m: DMatrix<$scalar>) -> bool {
let mut m = m;
if m.len() == 0 {
m = DMatrix::<$scalar>::new_random(1, 1);
}
let m = m.map(|e| e.0);
let udu = UDU::new(m.clone());
let p = &udu.u * &udu.d * &udu.u.transpose();
relative_eq!(m, p, epsilon = 1.0e-7)
}
fn udu_static(m: Matrix4<$scalar>) -> bool {
let m = m.map(|e| e.0);
let udu = UDU::new(m.clone());
let p = &udu.u * &udu.d * &udu.u.transpose();
relative_eq!(m, p, epsilon = 1.0e-7)
}
}
}
}
);
gen_tests!(complex, RandComplex<f64>);
gen_tests!(f64, RandScalar<f64>);
}