Fix PEP8 violations in Python mllib.

Author: Reynold Xin <rxin@apache.org>

Closes #871 from rxin/mllib-pep8 and squashes the following commits:

848416f [Reynold Xin] Fixed a typo in the previous cleanup (c -> sc).
a8db4cd [Reynold Xin] Fix PEP8 violations in Python mllib.

1 files changed, 10 insertions, 14 deletions

diff --git a/python/pyspark/mllib/regression.py b/python/pyspark/mllib/regression.py
index 266b31d3fa..bc7de6d2e8 100644
--- a/python/pyspark/mllib/regression.py
+++ b/python/pyspark/mllib/regression.py
@@ -113,10 +113,9 @@ class LinearRegressionWithSGD(object):
               miniBatchFraction=1.0, initialWeights=None):
         """Train a linear regression model on the given data."""
         sc = data.context
-        return _regression_train_wrapper(sc, lambda d, i:
-                sc._jvm.PythonMLLibAPI().trainLinearRegressionModelWithSGD(
-                        d._jrdd, iterations, step, miniBatchFraction, i),
-                LinearRegressionModel, data, initialWeights)
+        train_f = lambda d, i: sc._jvm.PythonMLLibAPI().trainLinearRegressionModelWithSGD(
+            d._jrdd, iterations, step, miniBatchFraction, i)
+        return _regression_train_wrapper(sc, train_f, LinearRegressionModel, data, initialWeights)
 
 
 class LassoModel(LinearRegressionModelBase):
@@ -157,10 +156,9 @@ class LassoWithSGD(object):
               miniBatchFraction=1.0, initialWeights=None):
         """Train a Lasso regression model on the given data."""
         sc = data.context
-        return _regression_train_wrapper(sc, lambda d, i:
-                sc._jvm.PythonMLLibAPI().trainLassoModelWithSGD(d._jrdd,
-                        iterations, step, regParam, miniBatchFraction, i),
-                LassoModel, data, initialWeights)
+        train_f = lambda d, i: sc._jvm.PythonMLLibAPI().trainLassoModelWithSGD(
+            d._jrdd, iterations, step, regParam, miniBatchFraction, i)
+        return _regression_train_wrapper(sc, train_f, LassoModel, data, initialWeights)
 
 
 class RidgeRegressionModel(LinearRegressionModelBase):
@@ -201,18 +199,16 @@ class RidgeRegressionWithSGD(object):
               miniBatchFraction=1.0, initialWeights=None):
         """Train a ridge regression model on the given data."""
         sc = data.context
-        return _regression_train_wrapper(sc, lambda d, i:
-                sc._jvm.PythonMLLibAPI().trainRidgeModelWithSGD(d._jrdd,
-                        iterations, step, regParam, miniBatchFraction, i),
-                RidgeRegressionModel, data, initialWeights)
+        train_func = lambda d, i: sc._jvm.PythonMLLibAPI().trainRidgeModelWithSGD(
+            d._jrdd, iterations, step, regParam, miniBatchFraction, i)
+        return _regression_train_wrapper(sc, train_func, RidgeRegressionModel, data, initialWeights)
 
 
 def _test():
     import doctest
     globs = globals().copy()
     globs['sc'] = SparkContext('local[4]', 'PythonTest', batchSize=2)
-    (failure_count, test_count) = doctest.testmod(globs=globs,
-            optionflags=doctest.ELLIPSIS)
+    (failure_count, test_count) = doctest.testmod(globs=globs, optionflags=doctest.ELLIPSIS)
     globs['sc'].stop()
     if failure_count:
         exit(-1)