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…on-new Conflicts: mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala (not a real conflict; merged by concatenation)
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# | ||
# Licensed to the Apache Software Foundation (ASF) under one or more | ||
# contributor license agreements. See the NOTICE file distributed with | ||
# this work for additional information regarding copyright ownership. | ||
# The ASF licenses this file to You under the Apache License, Version 2.0 | ||
# (the "License"); you may not use this file except in compliance with | ||
# the License. You may obtain a copy of the License at | ||
# | ||
# http://www.apache.org/licenses/LICENSE-2.0 | ||
# | ||
# Unless required by applicable law or agreed to in writing, software | ||
# distributed under the License is distributed on an "AS IS" BASIS, | ||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
# See the License for the specific language governing permissions and | ||
# limitations under the License. | ||
# | ||
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""" | ||
Python package for statistical functions in MLlib. | ||
""" | ||
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from pyspark.mllib._common import \ | ||
_get_unmangled_double_vector_rdd, _get_unmangled_rdd, \ | ||
_serialize_double, _serialize_double_vector, \ | ||
_deserialize_double, _deserialize_double_matrix | ||
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class Statistics(object): | ||
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@staticmethod | ||
def corr(x, y=None, method=None): | ||
""" | ||
Compute the correlation (matrix) for the input RDD(s) using the | ||
specified method. | ||
Methods currently supported: I{pearson (default), spearman}. | ||
If a single RDD of Vectors is passed in, a correlation matrix | ||
comparing the columns in the input RDD is returned. Use C{method=} | ||
to specify the method to be used for single RDD inout. | ||
If two RDDs of floats are passed in, a single float is returned. | ||
>>> x = sc.parallelize([1.0, 0.0, -2.0], 2) | ||
>>> y = sc.parallelize([4.0, 5.0, 3.0], 2) | ||
>>> zeros = sc.parallelize([0.0, 0.0, 0.0], 2) | ||
>>> abs(Statistics.corr(x, y) - 0.6546537) < 1e-7 | ||
True | ||
>>> Statistics.corr(x, y) == Statistics.corr(x, y, "pearson") | ||
True | ||
>>> Statistics.corr(x, y, "spearman") | ||
0.5 | ||
>>> from math import isnan | ||
>>> isnan(Statistics.corr(x, zeros)) | ||
True | ||
>>> from linalg import Vectors | ||
>>> rdd = sc.parallelize([Vectors.dense([1, 0, 0, -2]), Vectors.dense([4, 5, 0, 3]), | ||
... Vectors.dense([6, 7, 0, 8]), Vectors.dense([9, 0, 0, 1])]) | ||
>>> Statistics.corr(rdd) | ||
array([[ 1. , 0.05564149, nan, 0.40047142], | ||
[ 0.05564149, 1. , nan, 0.91359586], | ||
[ nan, nan, 1. , nan], | ||
[ 0.40047142, 0.91359586, nan, 1. ]]) | ||
>>> Statistics.corr(rdd, method="spearman") | ||
array([[ 1. , 0.10540926, nan, 0.4 ], | ||
[ 0.10540926, 1. , nan, 0.9486833 ], | ||
[ nan, nan, 1. , nan], | ||
[ 0.4 , 0.9486833 , nan, 1. ]]) | ||
>>> try: | ||
... Statistics.corr(rdd, "spearman") | ||
... print "Method name as second argument without 'method=' shouldn't be allowed." | ||
... except TypeError: | ||
... pass | ||
""" | ||
sc = x.ctx | ||
# Check inputs to determine whether a single value or a matrix is needed for output. | ||
# Since it's legal for users to use the method name as the second argument, we need to | ||
# check if y is used to specify the method name instead. | ||
if type(y) == str: | ||
raise TypeError("Use 'method=' to specify method name.") | ||
if not y: | ||
try: | ||
Xser = _get_unmangled_double_vector_rdd(x) | ||
except TypeError: | ||
raise TypeError("corr called on a single RDD not consisted of Vectors.") | ||
resultMat = sc._jvm.PythonMLLibAPI().corr(Xser._jrdd, method) | ||
return _deserialize_double_matrix(resultMat) | ||
else: | ||
xSer = _get_unmangled_rdd(x, _serialize_double) | ||
ySer = _get_unmangled_rdd(y, _serialize_double) | ||
result = sc._jvm.PythonMLLibAPI().corr(xSer._jrdd, ySer._jrdd, method) | ||
return result | ||
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def _test(): | ||
import doctest | ||
from pyspark import SparkContext | ||
globs = globals().copy() | ||
globs['sc'] = SparkContext('local[4]', 'PythonTest', batchSize=2) | ||
(failure_count, test_count) = doctest.testmod(globs=globs, optionflags=doctest.ELLIPSIS) | ||
globs['sc'].stop() | ||
if failure_count: | ||
exit(-1) | ||
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if __name__ == "__main__": | ||
_test() |