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use sprs::errors::LinalgError;
use sprs::{CsStructureI, CsStructureViewI, PermOwnedI, SpIndex};
use suitesparse_camd_sys::*;

// FIXME should be using SuiteSparseInt::MAX but this will not compile
// in rust 1.42 as u32::MAX was introduced in 1.43. This can be changed if
// the MSRV is bumped.
const MAX_INT32: usize = std::u32::MAX as usize;

/// Find a permutation matrix P which reduces the fill-in of the square
/// sparse matrix `mat` in Cholesky factorization (ie, the number of nonzeros
/// of the Cholesky factorization of P A P^T is less than for the Cholesky
/// factorization of A).
///
/// If A is not symmetric, the ordering will be computed for A + A^T
///
/// # Errors
///
/// This function will error if the passed matrix is not square.
pub fn try_camd<I, Iptr>(
    mat: CsStructureViewI<I, Iptr>,
) -> Result<PermOwnedI<I>, LinalgError>
where
    I: SpIndex,
    Iptr: SpIndex,
{
    let n = mat.rows();
    if n != mat.cols() {
        return Err(LinalgError::NonSquareMatrix);
    }
    let mut control = [0.; CAMD_CONTROL];
    let mut info = [0.; CAMD_INFO];
    let (camd_res, perm) = if n <= MAX_INT32 {
        let constraint: *const SuiteSparseInt = std::ptr::null();
        let mat: CsStructureI<SuiteSparseInt, SuiteSparseInt> =
            mat.to_other_types();
        let mut perm: Vec<SuiteSparseInt> = vec![0; n];
        let camd_res = unsafe {
            let indptr_proper = mat.proper_indptr();
            camd_order(
                n as SuiteSparseInt,
                indptr_proper.as_ptr(),
                mat.indices().as_ptr(),
                perm.as_mut_ptr(),
                control.as_mut_ptr(),
                info.as_mut_ptr(),
                constraint as *mut SuiteSparseInt,
            ) as isize
        };
        let perm = perm.iter().map(|&i| I::from_usize(i as usize)).collect();
        (camd_res, perm)
    } else {
        let constraint: *const SuiteSparseLong = std::ptr::null();
        let mat: CsStructureI<SuiteSparseLong, SuiteSparseLong> =
            mat.to_other_types();
        let mut perm: Vec<SuiteSparseLong> = vec![0; n];
        let camd_res = unsafe {
            let indptr_proper = mat.proper_indptr();
            camd_l_order(
                n as SuiteSparseLong,
                indptr_proper.as_ptr(),
                mat.indices().as_ptr(),
                perm.as_mut_ptr(),
                control.as_mut_ptr(),
                info.as_mut_ptr(),
                constraint as *mut SuiteSparseLong,
            )
        } as isize;
        let perm = perm.iter().map(|&i| I::from_usize(i as usize)).collect();
        (camd_res, perm)
    };
    // CsMat invariants guarantee sorted and non duplicate indices so this
    // should not happen.
    if camd_res != CAMD_OK {
        panic!("CsMat invariants have been broken");
    }
    Ok(PermOwnedI::new(perm))
}

/// Find a permutation matrix P which reduces the fill-in of the square
/// sparse matrix `mat` in Cholesky factorization (ie, the number of nonzeros
/// of the Cholesky factorization of P A P^T is less than for the Cholesky
/// factorization of A).
///
/// If A is not symmetric, the ordering will be computed for A + A^T
///
/// # Panics
///
/// This function will panic if the passed matrix is not square.
pub fn camd<I, Iptr>(mat: CsStructureViewI<I, Iptr>) -> PermOwnedI<I>
where
    I: SpIndex,
    Iptr: SpIndex,
{
    try_camd(mat).unwrap()
}

#[cfg(test)]
mod tests {
    use sprs::CsMatI;

    #[test]
    fn try_camd() {
        let mat = CsMatI::new_csc(
            (4, 4),
            vec![0, 2, 4, 6, 8],
            vec![0, 3, 1, 2, 1, 2, 0, 3],
            vec![1., 2., 21., 6., 6., 2., 2., 8.],
        );
        let res = super::try_camd(mat.structure_view());
        assert!(res.is_ok());
    }
}