Merge pull request #2242 from nd-02110114/fix-mol2vec (6ccf705d) · Commits · 钟慕尧 / deepchem

deepchem/feat/molecule_featurizers/mol2vec_fingerprint.py

+2 −15

Original line number	Diff line number	Diff line
		@@ -42,8 +42,7 @@ class Mol2VecFingerprint(MolecularFeaturizer):
		def __init__(self,
		pretrain_model_path: Optional[str] = None,
		radius: int = 1,
		unseen: str = 'UNK',
		gather_method: str = 'sum'):
		unseen: str = 'UNK'):
		"""
		Parameters
		----------
		@@ -56,9 +55,6 @@ class Mol2VecFingerprint(MolecularFeaturizer):
		github repository.
		unseen: str, optional (default 'UNK')
		The string to used to replace uncommon words/identifiers while training.
		gather_method: str, optional (default 'sum')
		How to aggregate vectors of identifiers are extracted from Mol2vec.
		'sum' or 'mean' is supported.
		"""
		try:
		from gensim.models import word2vec
		@@ -68,7 +64,6 @@ class Mol2VecFingerprint(MolecularFeaturizer):

		self.radius = radius
		self.unseen = unseen
		self.gather_method = gather_method
		self.sentences2vec = sentences2vec
		self.mol2alt_sentence = mol2alt_sentence
		if pretrain_model_path is None:
		@@ -98,13 +93,5 @@ class Mol2VecFingerprint(MolecularFeaturizer):
		1D array of mol2vec fingerprint. The default length is 300.
		"""
		sentence = self.mol2alt_sentence(mol, self.radius)
		vec_identifiers = self.sentences2vec(
		sentence, self.model, unseen=self.unseen)
		if self.gather_method == 'sum':
		feature = np.sum(vec_identifiers, axis=0)
		elif self.gather_method == 'mean':
		feature = np.mean(vec_identifiers, axis=0)
		else:
		raise ValueError(
		'Not supported gather_method type. Please set "sum" or "mean"')
		feature = self.sentences2vec([sentence], self.model, unseen=self.unseen)[0]
		return feature

+2 −8

Original line number	Diff line number	Diff line
		import unittest

		import numpy as np

		from deepchem.feat import Mol2VecFingerprint


		@@ -23,9 +21,5 @@ class TestMol2VecFingerprint(unittest.TestCase):
		Test simple fingerprint.
		"""
		featurizer = Mol2VecFingerprint()
		feature_sum = featurizer([self.mol])
		assert feature_sum.shape == (1, 300)
		featurizer = Mol2VecFingerprint(gather_method='mean')
		feature_mean = featurizer([self.mol])
		assert feature_mean.shape == (1, 300)
		assert not np.allclose(feature_sum, feature_mean)
		feature = featurizer([self.mol])
		assert feature.shape == (1, 300)

+1 −1

Original line number	Diff line number	Diff line
		@@ -21,4 +21,4 @@ dependencies:
		- pymatgen
		- simdna
		- xgboost
		- -e git+https://github.com/samoturk/mol2vec#egg=mol2vec
		- git+https://github.com/samoturk/mol2vec