Spadixtype

Spadixtype is a term used in computer science to denote a flexible, parameterizable abstract data type designed to represent sparse multi-dimensional data and related graph-like structures. The central idea is to store only the non-default entries of a high-dimensional grid or network while providing a uniform interface for access and manipulation.

A spadixtype is typically parameterized by a coordinate type C, a value type V, and a dimensionality D. The coordinates form keys that map to values, with the convention that absent entries imply a default value (often zero or null). Implementations aim to balance memory efficiency with access speed, supporting operations such as insert or assign, fetch, delete, and contains. Additional facilities include iteration over non-default entries, range or neighborhood queries, and slicing or projection into lower dimensions.

Common implementations include hash-based sparse maps, tree-based sparse arrays, and compressed storage variants inspired by sparse matrices. Features such as serialization, lazy evaluation, and compatibility with existing numeric or graph frameworks are frequently provided.

Typical use cases include scientific computing on large sparse grids, finite element methods, geographic information systems, machine learning with high-dimensional sparse features, and graph representations where adjacency is sparse.

There is no universal standard for spadixtype; it is described in language-specific libraries and research papers as a concept rather than a fixed specification. See also sparse matrix, sparse array, and multidimensional indexing concepts.