Fix Tests (f0c50a26) · Commits · 钟慕尧 / deepchem

deepchem/data/datasets.py

+18 −0

Original line number	Diff line number	Diff line
		@@ -14,6 +14,7 @@ from deepchem.utils.save import log
		import tempfile
		import time
		import shutil
		import json
		from multiprocessing.dummy import Pool

		__author__ = "Bharath Ramsundar"
		@@ -417,6 +418,23 @@ class NumpyDataset(Dataset):
		"""
		return NumpyDataset(ds.X, ds.y, ds.w, ds.ids)

		@staticmethod
		def to_json(self, fname):
		d = {
		'X': self.X.tolist(),
		'y': self.y.tolist(),
		'w': self.w.tolist(),
		'ids': self.ids.tolist()
		}
		with open(fname, 'w') as fout:
		json.dump(d, fout)

		@staticmethod
		def from_json(fname):
		with open(fname) as fin:
		d = json.load(fin)
		return NumpyDataset(d['X'], d['y'], d['w'], d['ids'])


		class DiskDataset(Dataset):
		"""

deepchem/dock/tests/test_pose_scoring.py

+9 −13

Original line number	Diff line number	Diff line
		@@ -18,6 +18,8 @@ import numpy as np
		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


		class TestPoseScoring(unittest.TestCase):
		@@ -27,20 +29,16 @@ class TestPoseScoring(unittest.TestCase):

		def setUp(self):
		"""Downloads dataset."""
		call(
		"wget -nv -c http://deepchem.io.s3-website-us-west-1.amazonaws.com/featurized_datasets/core_grid.tar.gz".
		split())
		call("tar -zxvf core_grid.tar.gz".split())
		self.core_dataset = dc.data.DiskDataset("core_grid/")

		def tearDown(self):
		"""Removes dataset"""
		call("rm -rf core_grid/".split())
		download_url(
		"http://deepchem.io.s3-website-us-west-1.amazonaws.com/featurized_datasets/core_grid.json"
		)
		# call("tar -zxvf core_grid.tar.gz".split())
		# self.core_dataset = dc.data.DiskDataset("core_grid/")
		json_fname = os.path.join(get_data_dir(), 'core_grid.json')
		self.core_dataset = dc.data.NumpyDataset.from_json(json_fname)

		def test_pose_scorer_init(self):
		"""Tests that pose-score works."""
		if sys.version_info >= (3, 0):
		return
		sklearn_model = RandomForestRegressor(n_estimators=10)
		model = dc.models.SklearnModel(sklearn_model)
		print("About to fit model on core set")
		@@ -50,8 +48,6 @@ class TestPoseScoring(unittest.TestCase):

		def test_pose_scorer_score(self):
		"""Tests that scores are generated"""
		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")

deepchem/feat/rdkit_grid_featurizer.py

+1 −1

Original line number	Diff line number	Diff line
		@@ -697,7 +697,7 @@ class RdkitGridFeaturizer(ComplexFeaturizer):

		self.box_width = float(box_width)
		self.voxel_width = float(voxel_width)
		self.voxels_per_edge = self.box_width / self.voxel_width
		self.voxels_per_edge = int(self.box_width / self.voxel_width)
		self.voxelize_features = voxelize_features
		self.voxel_feature_types = voxel_feature_types

deepchem/splits/tests/test_splitter.py

+1 −1

Original line number	Diff line number	Diff line
		@@ -340,7 +340,7 @@ class TestSplitters(unittest.TestCase):
		y = np.random.binomial(1, p, size=(n_samples, n_tasks))
		w = np.ones((n_samples, n_tasks))
		# Mask half the examples
		w[:n_samples / 2] = 0
		w[:n_samples // 2] = 0

		stratified_splitter = dc.splits.RandomStratifiedSplitter()
		split_indices = stratified_splitter.get_task_split_indices(

deepchem/trans/transformers.py

+1 −1

Original line number	Diff line number	Diff line
		@@ -491,7 +491,7 @@ class PowerTransformer(Transformer):
		def untransform(self, z):
		# print("Cannot undo Power Transformer, for now.")
		n_powers = len(self.powers)
		orig_len = (z.shape[1]) / n_powers
		orig_len = (z.shape[1]) // n_powers
		z = z[:, :orig_len]
		z = np.power(z, 1 / self.powers[0])
		return z

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