Cleanup imports

deepdock/__init__.py

@@ -1,11 +1,11 @@
 """
 Imports all submodules 
 """
-from deepchem.dock.pose_generation import PoseGenerator
-from deepchem.dock.pose_generation import VinaPoseGenerator
-from deepchem.dock.pose_scoring import PoseScorer
-from deepchem.dock.pose_scoring import GridPoseScorer
-from deepchem.dock.docking import Docker
-from deepchem.dock.docking import VinaGridRFDocker
-from deepchem.dock.binding_pocket import ConvexHullPocketFinder
-from deepchem.dock.binding_pocket import RFConvexHullPocketFinder
+from deepdock.pose_generation import PoseGenerator
+from deepdock.pose_generation import VinaPoseGenerator
+from deepdock.pose_scoring import PoseScorer
+from deepdock.pose_scoring import GridPoseScorer
+from deepdock.docking import Docker
+from deepdock.docking import VinaGridRFDocker
+from deepdock.binding_pocket import ConvexHullPocketFinder
+from deepdock.binding_pocket import RFConvexHullPocketFinder

deepdock/binding_pocket.py

@@ -11,8 +11,8 @@
 import numpy as np
 from subprocess import call
 from scipy.spatial import ConvexHull
-from deepchem.feat.binding_pocket_features import BindingPocketFeaturizer
-from deepchem.feat.fingerprints import CircularFingerprint
+from moleculenet.featurizers.binding_pocket_features import BindingPocketFeaturizer
+from moleculenet.featurizers.fingerprints import CircularFingerprint
 from deepchem.models.sklearn_models import SklearnModel
 from deepchem.utils import rdkit_util
 

deepdock/docking.py

@@ -9,13 +9,13 @@
 import numpy as np
 import os
 import tempfile
-from deepchem.data import DiskDataset
-from deepchem.models import SklearnModel
-from deepchem.models import MultitaskRegressor
-from deepchem.dock.pose_scoring import GridPoseScorer
-from deepchem.dock.pose_generation import VinaPoseGenerator
 from sklearn.ensemble import RandomForestRegressor
 from subprocess import call
+from moleculenet.data import DiskDataset
+from deepchem.models import SklearnModel
+from deepchem.models import MultitaskRegressor
+from deepdock.pose_scoring import GridPoseScorer
+from deepdock.pose_generation import VinaPoseGenerator
 
 logger = logging.getLogger(__name__)
 

deepdock/pose_generation.py

@@ -1,7 +1,6 @@
 """
 Generates protein-ligand docked poses using Autodock Vina.
 """
-from deepchem.utils import mol_xyz_util
 
 __author__ = "Bharath Ramsundar"
 __copyright__ = "Copyright 2016, Stanford University"
@@ -12,8 +11,9 @@
 import os
 import tempfile
 from subprocess import call
-from deepchem.feat import hydrogenate_and_compute_partial_charges
-from deepchem.dock.binding_pocket import RFConvexHullPocketFinder
+from moleculenet.featurizers import hydrogenate_and_compute_partial_charges
+from deepdock.binding_pocket import RFConvexHullPocketFinder
+from deepchem.utils import mol_xyz_util
 from deepchem.utils import rdkit_util
 
 logger = logging.getLogger(__name__)

deepdock/pose_scoring.py

@@ -1,17 +1,12 @@
 """
 Scores protein-ligand poses using DeepChem.
 """
-from deepchem.feat import RdkitGridFeaturizer
-
-__author__ = "Bharath Ramsundar"
-__copyright__ = "Copyright 2016, Stanford University"
-__license__ = "MIT"
-
 import numpy as np
 import os
 import tempfile
-from deepchem.data import NumpyDataset
 from subprocess import call
+from moleculenet.data import NumpyDataset
+from moleculenet.featurizers import RdkitGridFeaturizer
 
 
 class PoseScorer(object):

deepdock/tests/test_pose_scoring.py

@@ -15,8 +15,9 @@
 import deepchem as dc
 from sklearn.ensemble import RandomForestRegressor
 from subprocess import call
-from deepchem.utils import download_url
-from deepchem.utils import get_data_dir
+import moleculenet
+from moleculenet.utils import download_url
+from moleculenet.utils import get_data_dir
 
 logger = logging.getLogger(__name__)
 
@@ -32,7 +33,7 @@ def setUp(self):
         "http://deepchem.io.s3-website-us-west-1.amazonaws.com/featurized_datasets/core_grid.json"
     )
     json_fname = os.path.join(get_data_dir(), 'core_grid.json')
-    self.core_dataset = dc.data.NumpyDataset.from_json(json_fname)
+    self.core_dataset = moleculenet.data.NumpyDataset.from_json(json_fname)
 
   def test_pose_scorer_init(self):
     """Tests that pose-score works."""
@@ -41,7 +42,7 @@ def test_pose_scorer_init(self):
     logger.info("About to fit model on core set")
     model.fit(self.core_dataset)
 
-    pose_scorer = dc.dock.GridPoseScorer(model, feat="grid")
+    pose_scorer = deepdock.GridPoseScorer(model, feat="grid")
 
   def test_pose_scorer_score(self):
     """Tests that scores are generated"""
@@ -54,6 +55,6 @@ def test_pose_scorer_score(self):
     logger.info("About to fit model on core set")
     model.fit(self.core_dataset)
 
-    pose_scorer = dc.dock.GridPoseScorer(model, feat="grid")
+    pose_scorer = deepdock.GridPoseScorer(model, feat="grid")
     score = pose_scorer.score(protein_file, ligand_file)
     assert score.shape == (1,)