VectorStorage
The vector storages koblas itself defines, DenseVector and SparseVector.
Inheritors
Properties
Functions
Sum of the entries with Neumaier's compensation, holding to within one rounding of the exact sum whatever the length or the ordering.
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.
Materialise into a fresh dense DoubleArray, independent of the internal storage.