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| def atomwise_tokenizer(smi, exclusive_tokens = None): | |
| """ | |
| Tokenize a SMILES molecule at atom-level: | |
| (1) 'Br' and 'Cl' are two-character tokens | |
| (2) Symbols with bracket are considered as tokens | |
| exclusive_tokens: A list of specifical symbols with bracket you want to keep. e.g., ['[C@@H]', '[nH]']. | |
| Other symbols with bracket will be replaced by '[UNK]'. default is `None`. | |
| """ | |
| import re | |
| pattern = "(\[[^\]]+]|Br?|Cl?|N|O|S|P|F|I|b|c|n|o|s|p|\(|\)|\.|=|#|-|\+|\\\\|\/|:|~|@|\?|>|\*|\$|\%[0-9]{2}|[0-9])" | |
| regex = re.compile(pattern) | |
| tokens = [token for token in regex.findall(smi)] | |
| if exclusive_tokens: | |
| for i, tok in enumerate(tokens): | |
| if tok.startswith('['): | |
| if tok not in exclusive_tokens: | |
| tokens[i] = '[UNK]' | |
| return tokens | |
| def kmer_tokenizer(smiles, ngram=4, stride=1, remove_last = False, exclusive_tokens = None): | |
| units = atomwise_tokenizer(smiles, exclusive_tokens = exclusive_tokens) #collect all the atom-wise tokens from the SMILES | |
| if ngram == 1: | |
| tokens = units | |
| else: | |
| tokens = [tokens_to_mer(units[i:i+ngram]) for i in range(0, len(units), stride) if len(units[i:i+ngram]) == ngram] | |
| if remove_last: | |
| if len(tokens[-1]) < ngram: #truncate last whole k-mer if the length of the last k-mers is less than ngram. | |
| tokens = tokens[:-1] | |
| return tokens |