Vector

Sum of absolute values (BLAS dasum). Sparse vectors sum over stored entries only.

Sum of the entries with Neumaier's compensation, holding to within one rounding of the exact sum whatever the length or the ordering.

aT * b. Sparse operands walk their stored entries only.

Visit each stored entry as (index, value), in ascending index order for any storage. A SparseVector may present numerical zeros as stored, and any other Vector has every index visited.

Zero-based logical index of the first maximum absolute value (BLAS idamax), or -1 when empty. Dense vectors use DenseVectorKernels.iamax; sparse vectors visit only their stored entries. NaNs are ignored by the strict comparison; a later finite or infinite magnitude can therefore win after a leading NaN. All-zero and all-NaN nonempty inputs return 0, as do sparse inputs whose maximum is an implicit zero. Strided views report their logical index rather than a backing-array offset.

Euclidean norm (BLAS dnrm2). Rescales when the sum of squares would overflow or underflow, so any finite input gives the correct norm.

Plain sum of the entries. Distinct from asum, which sums their absolute values.