Loading .travis.yml +1 −1 Original line number Diff line number Diff line Loading @@ -15,7 +15,7 @@ install: - conda config --add channels http://conda.binstar.org/omnia - bash scripts/install_deepchem_conda.sh deepchem - source activate deepchem - pip install yapf==0.20.0 - pip install yapf==0.22.0 - pip install coveralls - python setup.py install script: Loading deepchem/data/tests/test_fasta_loader.py +5 −3 Original line number Diff line number Diff line Loading @@ -9,6 +9,7 @@ __license__ = "MIT" import os import unittest import deepchem as dc Loading @@ -26,7 +27,8 @@ class TestFASTALoader(unittest.TestCase): "../../data/tests/example.fasta") loader = dc.data.FASTALoader() sequences = loader.featurize(input_file) # example.fasta contains 3 sequences each of length 58. # The one-hot encoding turns base-pairs into vectors of length 4. # There is one "image channel") assert sequences.X.shape == (3, 4, 58, 1) # The one-hot encoding turns base-pairs into vectors of length 5 (ATCGN). # There is one "image channel". assert sequences.X.shape == (3, 5, 58, 1) deepchem/feat/fingerprints.py +15 −0 Original line number Diff line number Diff line Loading @@ -94,3 +94,18 @@ class CircularFingerprint(Featurizer): useBondTypes=self.bonds, useFeatures=self.features) return fp def __hash__(self): return hash((self.radius, self.size, self.chiral, self.bonds, self.features, self.sparse, self.smiles)) def __eq__(self, other): if not isinstance(self, other.__class__): return False return self.radius == other.radius and \ self.size == other.size and \ self.chiral == other.chiral and \ self.bonds == other.bonds and \ self.features == other.features and \ self.sparse == other.sparse and \ self.smiles == other.smiles deepchem/feat/graph_features.py +11 −0 Original line number Diff line number Diff line Loading @@ -358,6 +358,17 @@ class ConvMolFeaturizer(Featurizer): def feature_length(self): return 75 + len(self.atom_properties) def __hash__(self): atom_properties = tuple(self.atom_properties) return hash((self.master_atom, self.use_chirality, atom_properties)) def __eq__(self, other): if not isinstance(self, other.__class__): return False return self.master_atom == other.master_atom and \ self.use_chirality == other.use_chirality and \ tuple(self.atom_properties) == tuple(other.atom_properties) class WeaveFeaturizer(Featurizer): name = ['weave_mol'] Loading deepchem/feat/tests/test_features.py +35 −2 Original line number Diff line number Diff line """ Test featurizer class. """ import numpy as np import unittest from deepchem.feat import ConvMolFeaturizer, CircularFingerprint from deepchem.feat.basic import MolecularWeight from rdkit import Chem from deepchem.feat.basic import MolecularWeight class TestFeaturizer(unittest.TestCase): """ Tests for Featurizer. """ def setUp(self): """ Set up tests. Loading @@ -34,3 +35,35 @@ class TestFeaturizer(unittest.TestCase): f = MolecularWeight() rval = f([self.mol]) assert rval.shape == (1, 1) def test_convmol_hashable(self): featurizer1 = ConvMolFeaturizer(atom_properties=['feature']) featurizer2 = ConvMolFeaturizer(atom_properties=['feature']) featurizer3 = ConvMolFeaturizer() d = set() d.add(featurizer1) d.add(featurizer2) d.add(featurizer3) self.assertEqual(2, len(d)) featurizers = [featurizer1, featurizer2, featurizer3] for featurizer in featurizers: self.assertTrue(featurizer in featurizers) def test_circularfingerprint_hashable(self): featurizer1 = CircularFingerprint() featurizer2 = CircularFingerprint() featurizer3 = CircularFingerprint(size=5) d = set() d.add(featurizer1) d.add(featurizer2) d.add(featurizer3) self.assertEqual(2, len(d)) featurizers = [featurizer1, featurizer2, featurizer3] for featurizer in featurizers: self.assertTrue(featurizer in featurizers) Loading
.travis.yml +1 −1 Original line number Diff line number Diff line Loading @@ -15,7 +15,7 @@ install: - conda config --add channels http://conda.binstar.org/omnia - bash scripts/install_deepchem_conda.sh deepchem - source activate deepchem - pip install yapf==0.20.0 - pip install yapf==0.22.0 - pip install coveralls - python setup.py install script: Loading
deepchem/data/tests/test_fasta_loader.py +5 −3 Original line number Diff line number Diff line Loading @@ -9,6 +9,7 @@ __license__ = "MIT" import os import unittest import deepchem as dc Loading @@ -26,7 +27,8 @@ class TestFASTALoader(unittest.TestCase): "../../data/tests/example.fasta") loader = dc.data.FASTALoader() sequences = loader.featurize(input_file) # example.fasta contains 3 sequences each of length 58. # The one-hot encoding turns base-pairs into vectors of length 4. # There is one "image channel") assert sequences.X.shape == (3, 4, 58, 1) # The one-hot encoding turns base-pairs into vectors of length 5 (ATCGN). # There is one "image channel". assert sequences.X.shape == (3, 5, 58, 1)
deepchem/feat/fingerprints.py +15 −0 Original line number Diff line number Diff line Loading @@ -94,3 +94,18 @@ class CircularFingerprint(Featurizer): useBondTypes=self.bonds, useFeatures=self.features) return fp def __hash__(self): return hash((self.radius, self.size, self.chiral, self.bonds, self.features, self.sparse, self.smiles)) def __eq__(self, other): if not isinstance(self, other.__class__): return False return self.radius == other.radius and \ self.size == other.size and \ self.chiral == other.chiral and \ self.bonds == other.bonds and \ self.features == other.features and \ self.sparse == other.sparse and \ self.smiles == other.smiles
deepchem/feat/graph_features.py +11 −0 Original line number Diff line number Diff line Loading @@ -358,6 +358,17 @@ class ConvMolFeaturizer(Featurizer): def feature_length(self): return 75 + len(self.atom_properties) def __hash__(self): atom_properties = tuple(self.atom_properties) return hash((self.master_atom, self.use_chirality, atom_properties)) def __eq__(self, other): if not isinstance(self, other.__class__): return False return self.master_atom == other.master_atom and \ self.use_chirality == other.use_chirality and \ tuple(self.atom_properties) == tuple(other.atom_properties) class WeaveFeaturizer(Featurizer): name = ['weave_mol'] Loading
deepchem/feat/tests/test_features.py +35 −2 Original line number Diff line number Diff line """ Test featurizer class. """ import numpy as np import unittest from deepchem.feat import ConvMolFeaturizer, CircularFingerprint from deepchem.feat.basic import MolecularWeight from rdkit import Chem from deepchem.feat.basic import MolecularWeight class TestFeaturizer(unittest.TestCase): """ Tests for Featurizer. """ def setUp(self): """ Set up tests. Loading @@ -34,3 +35,35 @@ class TestFeaturizer(unittest.TestCase): f = MolecularWeight() rval = f([self.mol]) assert rval.shape == (1, 1) def test_convmol_hashable(self): featurizer1 = ConvMolFeaturizer(atom_properties=['feature']) featurizer2 = ConvMolFeaturizer(atom_properties=['feature']) featurizer3 = ConvMolFeaturizer() d = set() d.add(featurizer1) d.add(featurizer2) d.add(featurizer3) self.assertEqual(2, len(d)) featurizers = [featurizer1, featurizer2, featurizer3] for featurizer in featurizers: self.assertTrue(featurizer in featurizers) def test_circularfingerprint_hashable(self): featurizer1 = CircularFingerprint() featurizer2 = CircularFingerprint() featurizer3 = CircularFingerprint(size=5) d = set() d.add(featurizer1) d.add(featurizer2) d.add(featurizer3) self.assertEqual(2, len(d)) featurizers = [featurizer1, featurizer2, featurizer3] for featurizer in featurizers: self.assertTrue(featurizer in featurizers)
