Merge pull request #340 from rust-ndarray/merge-eig-trait-to-lapack

Merge `Eig_` trait into `Lapack` trait

Author: termoshtt

lax/src/eig.rs

@@ -1,4 +1,12 @@
 //! Eigenvalue problem for general matricies
+//!
+//! LAPACK correspondance
+//! ----------------------
+//!
+//! | f32 | f64 | c32 | c64 |
+//! |:------|:------|:------|:------|
+//! | sgeev | dgeev | cgeev | zgeev |
+//!
 
 use crate::{error::*, layout::MatrixLayout, *};
 use cauchy::*;
@@ -40,44 +48,6 @@ use num_traits::{ToPrimitive, Zero};
 /// A^\dagger V = V Λ ⟺ V^\dagger A = Λ V^\dagger
 /// $$
 ///
-pub trait Eig_: Scalar {
- /// Compute right eigenvalue and eigenvectors $Ax = \lambda x$
- ///
- /// LAPACK correspondance
- /// ----------------------
- ///
- /// | f32 | f64 | c32 | c64 |
- /// |:------|:------|:------|:------|
- /// | sgeev | dgeev | cgeev | zgeev |
- ///
- fn eig(
- calc_v: bool,
- l: MatrixLayout,
- a: &mut [Self],
- ) -> Result<(Vec<Self::Complex>, Vec<Self::Complex>)>;
-}
-
-macro_rules! impl_eig {
- ($s:ty) => {
- impl Eig_ for $s {
- fn eig(
- calc_v: bool,
- l: MatrixLayout,
- a: &mut [Self],
- ) -> Result<(Vec<Self::Complex>, Vec<Self::Complex>)> {
- let work = EigWork::<$s>::new(calc_v, l)?;
- let EigOwned { eigs, vr, vl } = work.eval(a)?;
- Ok((eigs, vr.or(vl).unwrap_or_default()))
- }
- }
- };
-}
-impl_eig!(c64);
-impl_eig!(c32);
-impl_eig!(f64);
-impl_eig!(f32);
-
-/// Working memory for [Eig_]
 #[non_exhaustive]
 pub struct EigWork<T: Scalar> {
  /// Problem size

lax/src/lib.rs

@@ -58,7 +58,7 @@
 //! According to the property input metrix,
 //! there are several types of eigenvalue problem API
 //!
-//! - [Eig_] trait provides methods for eigenvalue problem for general matrix.
+//! - [eig] module for eigenvalue problem for general matrix.
 //! - [Eigh_] trait provides methods for eigenvalue problem for symmetric/hermite matrix.
 //!
 //! Singular Value Decomposition
@@ -101,7 +101,6 @@ mod triangular;
 mod tridiagonal;
 
 pub use self::cholesky::*;
-pub use self::eig::Eig_;
 pub use self::eigh::*;
 pub use self::flags::*;
 pub use self::least_squares::*;
@@ -115,7 +114,7 @@ pub use self::svddc::*;
 pub use self::triangular::*;
 pub use self::tridiagonal::*;
 
-use self::alloc::*;
+use self::{alloc::*, error::*, layout::*};
 use cauchy::*;
 use std::mem::MaybeUninit;
 
@@ -130,16 +129,38 @@ pub trait Lapack:
  + Solve_
  + Solveh_
  + Cholesky_
- + Eig_
  + Eigh_
  + Triangular_
  + Tridiagonal_
  + Rcond_
  + LeastSquaresSvdDivideConquer_
 {
+ /// Compute right eigenvalue and eigenvectors
+ fn eig(
+ calc_v: bool,
+ l: MatrixLayout,
+ a: &mut [Self],
+ ) -> Result<(Vec<Self::Complex>, Vec<Self::Complex>)>;
 }
 
-impl Lapack for f32 {}
-impl Lapack for f64 {}
-impl Lapack for c32 {}
-impl Lapack for c64 {}
+macro_rules! impl_lapack {
+ ($s:ty) => {
+ impl Lapack for $s {
+ /// Compute right eigenvalue and eigenvectors
+ fn eig(
+ calc_v: bool,
+ l: MatrixLayout,
+ a: &mut [Self],
+ ) -> Result<(Vec<Self::Complex>, Vec<Self::Complex>)> {
+ use eig::*;
+ let work = EigWork::<$s>::new(calc_v, l)?;
+ let EigOwned { eigs, vr, vl } = work.eval(a)?;
+ Ok((eigs, vr.or(vl).unwrap_or_default()))
+ }
+ }
+ };
+}
+impl_lapack!(c64);
+impl_lapack!(c32);
+impl_lapack!(f64);
+impl_lapack!(f32);