[SPARK-6598] Python API for IDFModel

Author: Lewuathe

python/pyspark/mllib/feature.py

@@ -244,6 +244,12 @@ def transform(self, x):
         x = _convert_to_vector(x)
         return JavaVectorTransformer.transform(self, x)
 
+    def idf(self):
+        """
+        Returns the current IDF vector.
+        """
+        return self.call('idf')
+
 
 class IDF(object):
     """

python/pyspark/mllib/tests.py

@@ -41,6 +41,7 @@
 from pyspark.mllib.regression import LabeledPoint
 from pyspark.mllib.random import RandomRDDs
 from pyspark.mllib.stat import Statistics
+from pyspark.mllib.feature import IDF
 from pyspark.serializers import PickleSerializer
 from pyspark.sql import SQLContext
 from pyspark.tests import ReusedPySparkTestCase as PySparkTestCase
@@ -620,6 +621,19 @@ def test_right_number_of_results(self):
         self.assertEqual(len(chi), num_cols)
         self.assertIsNotNone(chi[1000])
 
+
+class FeatureTest(PySparkTestCase):
+    def test_idf_model(self):
+        data = [
+            Vectors.dense([1, 2, 6, 0, 2, 3, 1, 1, 0, 0, 3]),
+            Vectors.dense([1, 3, 0, 1, 3, 0, 0, 2, 0, 0, 1]),
+            Vectors.dense([1, 4, 1, 0, 0, 4, 9, 0, 1, 2, 0]),
+            Vectors.dense([2, 1, 0, 3, 0, 0, 5, 0, 2, 3, 9])
+        ]
+        model = IDF().fit(self.sc.parallelize(data, 2))
+        idf = model.idf()
+        self.assertEqual(len(idf), 11)
+
 if __name__ == "__main__":
     if not _have_scipy:
         print "NOTE: Skipping SciPy tests as it does not seem to be installed"