PR Updates

contrib/autoencoder_models/test_tensorflowEncoders.py

@@ -1,7 +1,6 @@
 from unittest import TestCase
 
-from nose.tools import assert_equals
-from nose.plugins.attrib import attr
+import pytest
 from rdkit import Chem
 
 import deepchem as dc
@@ -12,7 +11,7 @@
 
 class TestTensorflowEncoders(TestCase):
 
-  @pytest.mark.slow('slow')
+  @pytest.mark.slow
   def test_fit(self):
     tf_enc = TensorflowMoleculeEncoder.zinc_encoder()
 
@@ -36,4 +35,4 @@ def test_fit(self):
     tf_de = TensorflowMoleculeDecoder.zinc_decoder()
     one_hot_decoded = tf_de.predict_on_batch(prediction)
     decoded_smiles = featurizer.untransform(one_hot_decoded)
-    assert_equals(len(decoded_smiles), len(smiles))
+    assert len(decoded_smiles) == len(smiles)

deepchem/dock/tests/test_binding_pocket.py

@@ -148,7 +148,7 @@ def test_convex_find_pockets(self):
 
     assert len(pockets) < len(all_pockets)
 
-  @pytest.mark.skip(reson="Unknown")
+  @pytest.mark.skip(reason="Unknown")
   def test_rf_convex_find_pockets(self):
     """Test that filter with pre-trained RF models works."""
     if sys.version_info >= (3, 0):

deepchem/dock/tests/test_docking.py

@@ -5,10 +5,9 @@
 __copyright__ = "Copyright 2016, Stanford University"
 __license__ = "MIT"
 
-import unittest
 import os
-
 import sys
+import unittest
 
 import pytest
 
@@ -106,38 +105,3 @@ def test_pocket_vina_grid_rf_docker_dock(self):
       return
 
     assert score.shape == (1,)
-
-  '''
-  @pytest.mark.slow("slow")
-  def test_vina_grid_dnn_docker_dock(self):
-    """Test that VinaGridDNNDocker can dock."""
-    current_dir = os.path.dirname(os.path.realpath(__file__))
-    protein_file = os.path.join(current_dir, "1jld_protein.pdb")
-    ligand_file = os.path.join(current_dir, "1jld_ligand.sdf")
-
-    docker = dc.dock.VinaGridDNNDocker(exhaustiveness=1, detect_pockets=False)
-    (score, (protein_docked, ligand_docked)) = docker.dock(
-        protein_file, ligand_file)
-
-    # Check returned files exist
-    assert score.shape == (1,)
-    assert os.path.exists(protein_docked)
-    assert os.path.exists(ligand_docked)
-
-  @pytest.mark.slow('slow')
-  def test_pocket_vina_grid_dnn_docker_dock(self):
-    """Test that VinaGridDNNDocker can dock."""
-    if sys.version_info >= (3, 0):
-      return
-
-    current_dir = os.path.dirname(os.path.realpath(__file__))
-    protein_file = os.path.join(current_dir, "1jld_protein.pdb")
-    ligand_file = os.path.join(current_dir, "1jld_ligand.sdf")
-
-    docker = dc.dock.VinaGridDNNDocker(exhaustiveness=1, detect_pockets=True)
-    (score, (protein_docked, ligand_docked)) = docker.dock(
-        protein_file, ligand_file, dry_run=True)
-
-    # Check returned files exist
-    assert score.shape == (1,)
-  '''

deepchem/models/tests/test_atomic_conv.py

@@ -66,7 +66,7 @@ def test_atomic_conv(self):
     atomic_convnet.fit(train, nb_epoch=300)
     assert np.allclose(labels, atomic_convnet.predict(train), atol=0.01)
 
-  @pytest.mark.slow("slow")
+  @pytest.mark.slow
   def test_atomic_conv_variable(self):
     """A simple test that initializes and fits an AtomicConvModel on variable input size."""
     # For simplicity, let's assume both molecules have same number of
@@ -102,7 +102,7 @@ def test_atomic_conv_variable(self):
     train = NumpyDataset(features, labels)
     atomic_convnet.fit(train, nb_epoch=1)
 
-  @pytest.mark.slow("slow")
+  @pytest.mark.slow
   def test_atomic_conv_with_feat(self):
     """A simple test for running an atomic convolution on featurized data."""
     dir_path = os.path.dirname(os.path.realpath(__file__))

deepchem/models/tests/test_overfit.py

@@ -7,20 +7,17 @@
 __license__ = "MIT"
 
 import os
-import tempfile
+
 import numpy as np
-import unittest
-import sklearn
-import shutil
+import pytest
 import tensorflow as tf
-import deepchem as dc
-import scipy.io
-from deepchem.models.optimizers import Adam, ExponentialDecay
-from tensorflow.python.framework import test_util
+from flaky import flaky
 from sklearn.ensemble import RandomForestClassifier
 from sklearn.ensemble import RandomForestRegressor
-from flaky import flaky
-import pytest
+from tensorflow.python.framework import test_util
+
+import deepchem as dc
+from deepchem.models.optimizers import Adam
 
 
 class TestOverfit(test_util.TensorFlowTestCase):
@@ -573,7 +570,7 @@ def test_tf_robust_multitask_regression_overfit(self):
     scores = model.evaluate(dataset, [regression_metric])
     assert scores[regression_metric.name] < .2
 
-  @pytest.mark.slow('slow')
+  @pytest.mark.slow
   def test_DAG_singletask_regression_overfit(self):
     """Test DAG regressor multitask overfits tiny data."""
     np.random.seed(123)
@@ -691,7 +688,7 @@ def test_weave_singletask_regression_overfit(self):
 
     assert scores[regression_metric.name] > .8
 
-  @pytest.mark.slow("slow")
+  @pytest.mark.slow
   def test_MPNN_singletask_regression_overfit(self):
     """Test MPNN overfits tiny data."""
     np.random.seed(123)