`RepEngineOnehot` — One-Hot Sequence Encoder¶

Module: autopeptideml.reps.seq_based
Inherits from: RepEngineBase

Overview¶

RepEngineOnehot encodes canonical amino acid sequences as fixed-length binary one-hot vectors. Each position in the sequence maps to a 21-element binary vector (20 standard amino acids + unknown 'X'). Sequences longer than max_length are truncated; shorter ones are zero-padded.

This encoder is useful as a lightweight baseline representation that requires no third-party dependencies beyond NumPy.

Residue Alphabet¶

The encoder uses a fixed alphabet of 21 characters:

Index	Residue	Index	Residue	Index	Residue
0	V (Val)	7	H (His)	14	T (Thr)
1	I (Ile)	8	W (Trp)	15	M (Met)
2	L (Leu)	9	F (Phe)	16	A (Ala)
3	E (Glu)	10	Y (Tyr)	17	G (Gly)
4	Q (Gln)	11	R (Arg)	18	P (Pro)
5	D (Asp)	12	K (Lys)	19	C (Cys)
6	N (Asn)	13	S (Ser)	20	X (unknown)

Non-canonical residues are not mapped and should be converted to 'X' beforehand using CanonicalCleaner.

Attributes¶

Attribute	Type	Description
`engine`	`str`	Fixed to `'one-hot'`.
`max_length`	`int`	Maximum sequence length. Sequences are truncated to this value.
`name`	`str`	Fixed to `'one-hot'`.

Constructor¶

RepEngineOnehot(max_length: int)

Parameter	Type	Description
`max_length`	`int`	Maximum number of residues per sequence. Determines the output vector length as `max_length × 21`.

Methods¶

`compute_reps` (inherited)¶

compute_reps(
    mols: List[str],
    verbose: bool = False,
    batch_size: int = 12
) -> np.ndarray

Returns an int8 array of shape (n_seqs, max_length × 21).

`dim`¶

dim() -> int

Returns max_length × 21.

`_preprocess_batch`¶

_preprocess_batch(batch: List[str]) -> List[str]

Truncates each sequence to max_length characters.

`_rep_batch`¶

_rep_batch(batch: List[str]) -> np.ndarray

Converts each sequence in the batch into a flattened one-hot matrix of shape (max_length × 21,).
Returns a 2D int8 array of shape (len(batch), max_length × 21).

Example¶

from autopeptideml.reps.seq_based import RepEngineOnehot

engine = RepEngineOnehot(max_length=10)

sequences = ['ACDEFGHIKL', 'MWGY']
X = engine.compute_reps(sequences)

print(X.shape)   # (2, 210)  — 10 × 21
print(engine.dim())  # 210

Notes¶

In AutoPeptideML.build_models, pass reps=['one-hot'] to use this encoder with the default max_length=50.
For variable-length sequences, max_length should be set to the maximum expected length in your dataset to avoid truncation of long sequences.
The encoder operates on canonical sequences. Use the to-sequences preprocessing pipeline to convert SMILES or mixed input to canonical sequences before passing to this engine.

RepEngineOnehot — One-Hot Sequence Encoder¶