Data Encoders

Data encoders map raw data (a scalar, a feature vector, or a batch) into a Hypervector. Each wraps an Encoding and reuses its generate / normalize_fn / backend, so encoder output works with the existing bundle / bind / similarity / select functions. Everything is dimension-first: a batch of B inputs encodes to a (D, B) hypervector.

Encoder base class

Codebook encoders

A value indexes into a precomputed (D, L) basis. Constructor signature (encoding, levels, low=0.0, high=1.0): levels must be at least 1 and high must exceed low, or the constructor raises ValueError.

Functional encoders

A transform of a feature vector.