From e6e483cc4de740c46398385b03ffe0e662edae39 Mon Sep 17 00:00:00 2001
From: Holden Karau <holden@pigscanfly.ca>
Date: Tue, 1 Sep 2015 10:48:57 -0700
Subject: [SPARK-9679] [ML] [PYSPARK] Add Python API for Stop Words Remover

Add a python API for the Stop Words Remover.

Author: Holden Karau <holden@pigscanfly.ca>

Closes #8118 from holdenk/SPARK-9679-python-StopWordsRemover.
---
 python/pyspark/ml/feature.py | 73 ++++++++++++++++++++++++++++++++++++++++++--
 1 file changed, 71 insertions(+), 2 deletions(-)

(limited to 'python/pyspark/ml/feature.py')

diff --git a/python/pyspark/ml/feature.py b/python/pyspark/ml/feature.py
index 0626281e20..d955307e27 100644
--- a/python/pyspark/ml/feature.py
+++ b/python/pyspark/ml/feature.py
@@ -22,7 +22,7 @@ if sys.version > '3':
 from pyspark.rdd import ignore_unicode_prefix
 from pyspark.ml.param.shared import *
 from pyspark.ml.util import keyword_only
-from pyspark.ml.wrapper import JavaEstimator, JavaModel, JavaTransformer
+from pyspark.ml.wrapper import JavaEstimator, JavaModel, JavaTransformer, _jvm
 from pyspark.mllib.common import inherit_doc
 from pyspark.mllib.linalg import _convert_to_vector
 
@@ -30,7 +30,7 @@ __all__ = ['Binarizer', 'Bucketizer', 'DCT', 'ElementwiseProduct', 'HashingTF',
            'NGram', 'Normalizer', 'OneHotEncoder', 'PolynomialExpansion', 'RegexTokenizer',
            'SQLTransformer', 'StandardScaler', 'StandardScalerModel', 'StringIndexer',
            'StringIndexerModel', 'Tokenizer', 'VectorAssembler', 'VectorIndexer', 'Word2Vec',
-           'Word2VecModel', 'PCA', 'PCAModel', 'RFormula', 'RFormulaModel']
+           'Word2VecModel', 'PCA', 'PCAModel', 'RFormula', 'RFormulaModel', 'StopWordsRemover']
 
 
 @inherit_doc
@@ -933,6 +933,75 @@ class StringIndexerModel(JavaModel):
     """
 
 
+class StopWordsRemover(JavaTransformer, HasInputCol, HasOutputCol):
+    """
+    .. note:: Experimental
+
+    A feature transformer that filters out stop words from input.
+    Note: null values from input array are preserved unless adding null to stopWords explicitly.
+    """
+    # a placeholder to make the stopwords show up in generated doc
+    stopWords = Param(Params._dummy(), "stopWords", "The words to be filtered out")
+    caseSensitive = Param(Params._dummy(), "caseSensitive", "whether to do a case sensitive " +
+                          "comparison over the stop words")
+
+    @keyword_only
+    def __init__(self, inputCol=None, outputCol=None, stopWords=None,
+                 caseSensitive=False):
+        """
+        __init__(self, inputCol=None, outputCol=None, stopWords=None,\
+                 caseSensitive=false)
+        """
+        super(StopWordsRemover, self).__init__()
+        self._java_obj = self._new_java_obj("org.apache.spark.ml.feature.StopWordsRemover",
+                                            self.uid)
+        self.stopWords = Param(self, "stopWords", "The words to be filtered out")
+        self.caseSensitive = Param(self, "caseSensitive", "whether to do a case " +
+                                   "sensitive comparison over the stop words")
+        stopWordsObj = _jvm().org.apache.spark.ml.feature.StopWords
+        defaultStopWords = stopWordsObj.English()
+        self._setDefault(stopWords=defaultStopWords)
+        kwargs = self.__init__._input_kwargs
+        self.setParams(**kwargs)
+
+    @keyword_only
+    def setParams(self, inputCol=None, outputCol=None, stopWords=None,
+                  caseSensitive=False):
+        """
+        setParams(self, inputCol="input", outputCol="output", stopWords=None,\
+                  caseSensitive=false)
+        Sets params for this StopWordRemover.
+        """
+        kwargs = self.setParams._input_kwargs
+        return self._set(**kwargs)
+
+    def setStopWords(self, value):
+        """
+        Specify the stopwords to be filtered.
+        """
+        self._paramMap[self.stopWords] = value
+        return self
+
+    def getStopWords(self):
+        """
+        Get the stopwords.
+        """
+        return self.getOrDefault(self.stopWords)
+
+    def setCaseSensitive(self, value):
+        """
+        Set whether to do a case sensitive comparison over the stop words
+        """
+        self._paramMap[self.caseSensitive] = value
+        return self
+
+    def getCaseSensitive(self):
+        """
+        Get whether to do a case sensitive comparison over the stop words.
+        """
+        return self.getOrDefault(self.caseSensitive)
+
+
 @inherit_doc
 @ignore_unicode_prefix
 class Tokenizer(JavaTransformer, HasInputCol, HasOutputCol):
-- 
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