Loading deepchem/utils/save.py +13 −44 Original line number Diff line number Diff line Loading @@ -17,6 +17,7 @@ import os import deepchem from rdkit import Chem import warnings from deepchem.utils.genomics import encode_bio_sequence as encode_sequence, encode_fasta_sequence as fasta_sequence, seq_one_hot_encode as seq_one_hotencode def log(string, verbose=True): Loading Loading @@ -127,44 +128,10 @@ def seq_one_hot_encode(sequences, letters='ATCGN'): ------- np.ndarray: Shape (N_sequences, N_letters, sequence_length, 1). """ warnings.warn("This will be removed in the Future Releases", FutureWarning) # The label encoder is given characters for ACGTN letter_encoder = {l: i for i, l in enumerate(letters)} alphabet_length = len(letter_encoder) # Peak at the first sequence to get the length of the sequence. try: first_seq = next(sequences) tail_seq = sequences except TypeError: first_seq = sequences[0] tail_seq = sequences[1:] sequence_length = len(first_seq) seqs = [] seqs.append( _seq_to_encoded(first_seq, letter_encoder, alphabet_length, sequence_length)) for other_seq in tail_seq: if len(other_seq) != sequence_length: raise ValueError seqs.append( _seq_to_encoded(other_seq, letter_encoder, alphabet_length, sequence_length)) return np.expand_dims(np.array(seqs), -1) def _seq_to_encoded(seq, letter_encoder, alphabet_length, sequence_length): b = np.zeros((alphabet_length, sequence_length)) seq_ints = [letter_encoder[s] for s in seq] b[seq_ints, np.arange(sequence_length)] = 1 return b warnings.warn( "This Function has been deprecated and now resides in deepchem.utils.genomics ", DeprecationWarning) return seq_one_hotencode(sequences, letters=letters) def encode_fasta_sequence(fname): Loading @@ -180,8 +147,11 @@ def encode_fasta_sequence(fname): ------- np.ndarray: Shape (N_sequences, 5, sequence_length, 1). """ warnings.warn( "This Function has been deprecated and now resides in deepchem.utils.genomics", DeprecationWarning) return encode_bio_sequence(fname) return fasta_sequence(fname) def encode_bio_sequence(fname, file_type="fasta", letters="ATCGN"): Loading @@ -202,11 +172,10 @@ def encode_bio_sequence(fname, file_type="fasta", letters="ATCGN"): ------- np.ndarray: Shape (N_sequences, N_letters, sequence_length, 1). """ warnings.warn("This will be removed in the Future Releases", FutureWarning) from Bio import SeqIO sequences = SeqIO.parse(fname, file_type) return seq_one_hot_encode(sequences, letters) warnings.warn( "This Function has been deprecated and now resides in deepchem.utils.genomics ", DeprecationWarning) return encode_sequence(fname, file_type=file_type, letters=letters) def save_metadata(tasks, metadata_df, data_dir): Loading Loading
deepchem/utils/save.py +13 −44 Original line number Diff line number Diff line Loading @@ -17,6 +17,7 @@ import os import deepchem from rdkit import Chem import warnings from deepchem.utils.genomics import encode_bio_sequence as encode_sequence, encode_fasta_sequence as fasta_sequence, seq_one_hot_encode as seq_one_hotencode def log(string, verbose=True): Loading Loading @@ -127,44 +128,10 @@ def seq_one_hot_encode(sequences, letters='ATCGN'): ------- np.ndarray: Shape (N_sequences, N_letters, sequence_length, 1). """ warnings.warn("This will be removed in the Future Releases", FutureWarning) # The label encoder is given characters for ACGTN letter_encoder = {l: i for i, l in enumerate(letters)} alphabet_length = len(letter_encoder) # Peak at the first sequence to get the length of the sequence. try: first_seq = next(sequences) tail_seq = sequences except TypeError: first_seq = sequences[0] tail_seq = sequences[1:] sequence_length = len(first_seq) seqs = [] seqs.append( _seq_to_encoded(first_seq, letter_encoder, alphabet_length, sequence_length)) for other_seq in tail_seq: if len(other_seq) != sequence_length: raise ValueError seqs.append( _seq_to_encoded(other_seq, letter_encoder, alphabet_length, sequence_length)) return np.expand_dims(np.array(seqs), -1) def _seq_to_encoded(seq, letter_encoder, alphabet_length, sequence_length): b = np.zeros((alphabet_length, sequence_length)) seq_ints = [letter_encoder[s] for s in seq] b[seq_ints, np.arange(sequence_length)] = 1 return b warnings.warn( "This Function has been deprecated and now resides in deepchem.utils.genomics ", DeprecationWarning) return seq_one_hotencode(sequences, letters=letters) def encode_fasta_sequence(fname): Loading @@ -180,8 +147,11 @@ def encode_fasta_sequence(fname): ------- np.ndarray: Shape (N_sequences, 5, sequence_length, 1). """ warnings.warn( "This Function has been deprecated and now resides in deepchem.utils.genomics", DeprecationWarning) return encode_bio_sequence(fname) return fasta_sequence(fname) def encode_bio_sequence(fname, file_type="fasta", letters="ATCGN"): Loading @@ -202,11 +172,10 @@ def encode_bio_sequence(fname, file_type="fasta", letters="ATCGN"): ------- np.ndarray: Shape (N_sequences, N_letters, sequence_length, 1). """ warnings.warn("This will be removed in the Future Releases", FutureWarning) from Bio import SeqIO sequences = SeqIO.parse(fname, file_type) return seq_one_hot_encode(sequences, letters) warnings.warn( "This Function has been deprecated and now resides in deepchem.utils.genomics ", DeprecationWarning) return encode_sequence(fname, file_type=file_type, letters=letters) def save_metadata(tasks, metadata_df, data_dir): Loading
