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-rw-r--r--python/pyspark/mllib/tests.py24
1 files changed, 24 insertions, 0 deletions
diff --git a/python/pyspark/mllib/tests.py b/python/pyspark/mllib/tests.py
index 3b40158c12..8eaddcf8b9 100644
--- a/python/pyspark/mllib/tests.py
+++ b/python/pyspark/mllib/tests.py
@@ -44,6 +44,7 @@ from pyspark.mllib.random import RandomRDDs
from pyspark.mllib.stat import Statistics
from pyspark.mllib.feature import Word2Vec
from pyspark.mllib.feature import IDF
+from pyspark.mllib.feature import StandardScaler
from pyspark.serializers import PickleSerializer
from pyspark.sql import SQLContext
from pyspark.tests import ReusedPySparkTestCase as PySparkTestCase
@@ -745,6 +746,29 @@ class Word2VecTests(PySparkTestCase):
model = Word2Vec().fit(self.sc.parallelize(data))
self.assertEquals(len(model.getVectors()), 3)
+
+class StandardScalerTests(PySparkTestCase):
+ def test_model_setters(self):
+ data = [
+ [1.0, 2.0, 3.0],
+ [2.0, 3.0, 4.0],
+ [3.0, 4.0, 5.0]
+ ]
+ model = StandardScaler().fit(self.sc.parallelize(data))
+ self.assertIsNotNone(model.setWithMean(True))
+ self.assertIsNotNone(model.setWithStd(True))
+ self.assertEqual(model.transform([1.0, 2.0, 3.0]), DenseVector([-1.0, -1.0, -1.0]))
+
+ def test_model_transform(self):
+ data = [
+ [1.0, 2.0, 3.0],
+ [2.0, 3.0, 4.0],
+ [3.0, 4.0, 5.0]
+ ]
+ model = StandardScaler().fit(self.sc.parallelize(data))
+ self.assertEqual(model.transform([1.0, 2.0, 3.0]), DenseVector([1.0, 2.0, 3.0]))
+
+
if __name__ == "__main__":
if not _have_scipy:
print "NOTE: Skipping SciPy tests as it does not seem to be installed"