ndarray-linalg 0.5.0

Linear algebra package for rust-ndarray using LAPACK
Documentation
//! Eigenvalue decomposition for Hermite matrices

use ndarray::*;

use super::error::*;
use super::layout::*;

use lapack_traits::LapackScalar;
pub use lapack_traits::UPLO;

pub trait Eigh<EigVal, EigVec> {
    fn eigh(self, UPLO) -> Result<(EigVal, EigVec)>;
}

impl<A, S, Se> Eigh<ArrayBase<Se, Ix1>, ArrayBase<S, Ix2>> for ArrayBase<S, Ix2>
    where A: LapackScalar,
          S: DataMut<Elem = A>,
          Se: DataOwned<Elem = A::Real>
{
    fn eigh(mut self, uplo: UPLO) -> Result<(ArrayBase<Se, Ix1>, ArrayBase<S, Ix2>)> {
        let s = A::eigh(true, self.square_layout()?, uplo, self.as_allocated_mut()?)?;
        Ok((ArrayBase::from_vec(s), self))
    }
}

impl<'a, A, S, Se, So> Eigh<ArrayBase<Se, Ix1>, ArrayBase<So, Ix2>> for &'a ArrayBase<S, Ix2>
    where A: LapackScalar + Copy,
          S: Data<Elem = A>,
          Se: DataOwned<Elem = A::Real>,
          So: DataOwned<Elem = A> + DataMut
{
    fn eigh(self, uplo: UPLO) -> Result<(ArrayBase<Se, Ix1>, ArrayBase<So, Ix2>)> {
        let mut a = replicate(self);
        let s = A::eigh(true, a.square_layout()?, uplo, a.as_allocated_mut()?)?;
        Ok((ArrayBase::from_vec(s), a))
    }
}

impl<'a, A, S, Se> Eigh<ArrayBase<Se, Ix1>, &'a mut ArrayBase<S, Ix2>> for &'a mut ArrayBase<S, Ix2>
    where A: LapackScalar,
          S: DataMut<Elem = A>,
          Se: DataOwned<Elem = A::Real>
{
    fn eigh(mut self, uplo: UPLO) -> Result<(ArrayBase<Se, Ix1>, &'a mut ArrayBase<S, Ix2>)> {
        let s = A::eigh(true, self.square_layout()?, uplo, self.as_allocated_mut()?)?;
        Ok((ArrayBase::from_vec(s), self))
    }
}

pub trait EigValsh<EigVal> {
    fn eigvalsh(self, UPLO) -> Result<EigVal>;
}

impl<A, S, Se> EigValsh<ArrayBase<Se, Ix1>> for ArrayBase<S, Ix2>
    where A: LapackScalar,
          S: DataMut<Elem = A>,
          Se: DataOwned<Elem = A::Real>
{
    fn eigvalsh(mut self, uplo: UPLO) -> Result<ArrayBase<Se, Ix1>> {
        let s = A::eigh(false, self.square_layout()?, uplo, self.as_allocated_mut()?)?;
        Ok(ArrayBase::from_vec(s))
    }
}

impl<'a, A, S, Se> EigValsh<ArrayBase<Se, Ix1>> for &'a ArrayBase<S, Ix2>
    where A: LapackScalar + Copy,
          S: Data<Elem = A>,
          Se: DataOwned<Elem = A::Real>
{
    fn eigvalsh(self, uplo: UPLO) -> Result<ArrayBase<Se, Ix1>> {
        let mut a = self.to_owned();
        let s = A::eigh(false, a.square_layout()?, uplo, a.as_allocated_mut()?)?;
        Ok(ArrayBase::from_vec(s))
    }
}

impl<'a, A, S, Se> EigValsh<ArrayBase<Se, Ix1>> for &'a mut ArrayBase<S, Ix2>
    where A: LapackScalar,
          S: DataMut<Elem = A>,
          Se: DataOwned<Elem = A::Real>
{
    fn eigvalsh(mut self, uplo: UPLO) -> Result<ArrayBase<Se, Ix1>> {
        let s = A::eigh(true, self.square_layout()?, uplo, self.as_allocated_mut()?)?;
        Ok(ArrayBase::from_vec(s))
    }
}