fixing tests (dd3862da) · Commits · 钟慕尧 / deepchem

deepchem/splits/init.py

+9 −3

Original line number	Diff line number	Diff line
		@@ -171,7 +171,8 @@ class StratifiedSplitter(Splitter):
		y_test.append(row)
		w_test.append(weight_test_row)
		id_test.append(id_row)
		elif weight_test_row.count(0) == len(weight_test_row): #entirely train example
		elif weight_test_row.count(0) == len(weight_test_row):
		# entirely train example
		X_train.append(x_row)
		y_train.append(row)
		w_train.append(weight_train_row)
		@@ -186,7 +187,6 @@ class StratifiedSplitter(Splitter):
		id_train.append(id_row)
		id_test.append(id_row)


		X_train_np = np.array(X_train)
		X_test_np = np.array(X_test)
		y_train_np = np.array(y_train)
		@@ -217,10 +217,12 @@ class StratifiedSplitter(Splitter):
		test_data = Dataset.from_numpy(test_dir, X_test_np, y_test_np, w_test_np, id_test_np)
		return (train_data, valid_data, test_data)


		class MolecularWeightSplitter(Splitter):
		"""
		Class for doing data splits by molecular weight.
		"""

		def split(self, dataset, seed=None, frac_train=.8, frac_valid=.1,
		frac_test=.1, log_every_n=None):
		"""
		@@ -247,15 +249,18 @@ class MolecularWeightSplitter(Splitter):
		return (sortidx[:train_cutoff], sortidx[train_cutoff:valid_cutoff],
		sortidx[valid_cutoff:])


		class RandomSplitter(Splitter):
		"""
		Class for doing random data splits.
		"""

		def split(self, dataset, seed=None, frac_train=.8, frac_valid=.1,
		frac_test=.1, log_every_n=None):
		"""
		Splits internal compounds randomly into train/validation/test.
		"""
		<<<<<<< 0017a77551376a895531b1020b82acc9029563cd
		np.testing.assert_almost_equal(frac_train + frac_valid + frac_test, 1.)
		np.random.seed(seed)
		num_datapoints = len(dataset)
		@@ -269,11 +274,13 @@ class ScaffoldSplitter(Splitter):
		"""
		Class for doing data splits based on the scaffold of small molecules.
		"""

		def split(self, dataset, frac_train=.8, frac_valid=.1, frac_test=.1,
		log_every_n=1000):
		"""
		Splits internal compounds into train/validation/test by scaffold.
		"""
		<<<<<<< 0017a77551376a895531b1020b82acc9029563cd
		np.testing.assert_almost_equal(frac_train + frac_valid + frac_test, 1.)
		scaffolds = {}
		log("About to generate scaffolds", self.verbosity)
		@@ -313,7 +320,6 @@ class SpecifiedSplitter(Splitter):
		raw_df = load_data([input_file], shard_size=None).next()
		self.splits = raw_df[split_field].values
		self.verbosity = verbosity

		def split(self, dataset, frac_train=.8, frac_valid=.1, frac_test=.1,
		log_every_n=1000):
		"""

deepchem/splits/tests/test_splitter.py

+3 −1

Original line number	Diff line number	Diff line
		@@ -18,10 +18,12 @@ from deepchem.datasets.tests import TestDatasetAPI
		from deepchem.datasets import Dataset
		import pandas as pd


		class TestSplitters(TestDatasetAPI):
		"""
		Test some basic splitters.
		"""

		def test_singletask_random_split(self):
		"""
		Test singletask RandomSplitter class.
		@@ -93,7 +95,7 @@ class TestSplitters(TestDatasetAPI):
		frac_train=0.8, frac_valid=0.1, frac_test=0.1
		)
		train_np_list = train_data.to_numpy()
		y = train_data[1]
		y = train_np_list[1]
		# verify that each task in the train dataset has some hits
		y_df = pd.DataFrame(data=y)
		totalRows = len(y_df.index)

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