kryst 3.2.1

Krylov subspace and preconditioned iterative solvers for dense and sparse linear systems, with shared and distributed memory parallelism.
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#![cfg(not(feature = "complex"))]
use kryst::algebra::scalar::{KrystScalar, S};
use kryst::matrix::dist_csr::DistCsrOp;
use kryst::matrix::op::LinOp;
use kryst::matrix::sparse::CsrMatrix;
use kryst::parallel::{NoComm, UniverseComm};

#[test]
#[should_panic]
fn dist_matvec_panics_on_bad_dims() {
    // Minimal 1x1 operator with serial communicator
    let local = CsrMatrix::<S>::from_csr(1, 1, vec![0, 1], vec![0], vec![S::from_real(1.0)]);
    let part = vec![0, 1]; // single-rank partition
    let comm = UniverseComm::NoComm(NoComm);
    let op = DistCsrOp::from_local_rows(1, 0, &local, &part, comm).unwrap();

    let x = vec![S::from_real(1.0), S::from_real(2.0)];
    let mut y = vec![S::zero()];
    // Should panic (previously: silently ignored the Err)
    op.matvec(&x, &mut y);
}

#[test]
fn dist_try_matvec_returns_error_on_bad_dims() {
    let local = CsrMatrix::<S>::from_csr(1, 1, vec![0, 1], vec![0], vec![S::from_real(1.0)]);
    let part = vec![0, 1];
    let comm = UniverseComm::NoComm(NoComm);
    let op = DistCsrOp::from_local_rows(1, 0, &local, &part, comm).unwrap();

    let x = vec![S::from_real(1.0), S::from_real(2.0)];
    let mut y = vec![S::zero()];

    let err = op.try_matvec(&x, &mut y).unwrap_err();
    match err {
        kryst::error::KError::InvalidInput(msg) => {
            assert!(msg.to_lowercase().contains("dimension"))
        }
        other => panic!("unexpected error: {:?}", other),
    }
}