Source code for bio_embeddings.embed.one_hot_encoding_embedder

import re

import numpy
from numpy import ndarray

from bio_embeddings.embed import EmbedderInterface


[docs]class OneHotEncodingEmbedder(EmbedderInterface): """Baseline embedder: One hot encoding as per-residue embedding, amino acid composition for per-protein This embedder is meant to be used as naive baseline for comparing different types of inputs or training method. While option such as device aren't used, you may still pass them for consistency. """ number_of_layers = 1 embedding_dimension = len(AMINO_ACIDS) name = "one_hot_encoding"
[docs] def embed(self, sequence: str) -> ndarray: if not sequence: return numpy.zeros((len(AMINO_ACIDS), 0)) sequence = re.sub(r"[UZOB]", "X", sequence) one_hot = [AMINO_ACIDS == i for i in sequence] return numpy.stack(one_hot).astype(numpy.float32)
[docs] @staticmethod def reduce_per_protein(embedding: ndarray) -> ndarray: """This returns the amino acid composition of the sequence as vector""" return embedding.mean(axis=0)