Source code for immuneML.encodings.kmer_frequency.sequence_encoding.IMGTKmerSequenceEncoder

import logging

from immuneML.data_model.receptor.receptor_sequence.ReceptorSequence import ReceptorSequence
from immuneML.encodings.EncoderParams import EncoderParams
from immuneML.encodings.kmer_frequency.sequence_encoding.SequenceEncodingStrategy import SequenceEncodingStrategy
from immuneML.environment.Constants import Constants
from immuneML.util.KmerHelper import KmerHelper


[docs]class IMGTKmerSequenceEncoder(SequenceEncodingStrategy):
[docs] @staticmethod def encode_sequence(sequence: ReceptorSequence, params: EncoderParams): """ creates overlapping continuous k-mers from a sequence as features for use in KmerFrequencyEncoder object of type EncoderParams, same object as passed into KmerFrequencyEncoder :param sequence: ReceptorSequence :param params: EncoderParams (where params["model"]["k"] is used) :return: SequenceEncodingResult consisting of features and feature information names """ k = params.model["k"] sequence_type = params.model.get('sequence_type', None) length = len(sequence.get_sequence(sequence_type)) if length < k: logging.warning('Sequence length is less than k. Ignoring sequence') return None kmers = KmerHelper.create_IMGT_kmers_from_sequence(sequence=sequence, k=k, sequence_type=sequence_type) kmers = [Constants.FEATURE_DELIMITER.join([str(mer) for mer in kmer]) for kmer in kmers] return kmers
[docs] @staticmethod def get_feature_names(params: EncoderParams): return ["sequence", "imgt_position"]