From a2249359d5b0368318a714b292bb1d0dc70c0e27 Mon Sep 17 00:00:00 2001 From: Yu ISHIKAWA Date: Mon, 14 Sep 2015 21:59:40 -0700 Subject: [SPARK-10275] [MLLIB] Add @since annotation to pyspark.mllib.random Author: Yu ISHIKAWA Closes #8666 from yu-iskw/SPARK-10275. --- python/pyspark/mllib/random.py | 15 +++++++++++++++ 1 file changed, 15 insertions(+) (limited to 'python') diff --git a/python/pyspark/mllib/random.py b/python/pyspark/mllib/random.py index 06fbc0eb6a..9c733b1332 100644 --- a/python/pyspark/mllib/random.py +++ b/python/pyspark/mllib/random.py @@ -21,6 +21,7 @@ Python package for random data generation. from functools import wraps +from pyspark import since from pyspark.mllib.common import callMLlibFunc @@ -39,9 +40,12 @@ class RandomRDDs(object): """ Generator methods for creating RDDs comprised of i.i.d samples from some distribution. + + .. addedversion:: 1.1.0 """ @staticmethod + @since("1.1.0") def uniformRDD(sc, size, numPartitions=None, seed=None): """ Generates an RDD comprised of i.i.d. samples from the @@ -72,6 +76,7 @@ class RandomRDDs(object): return callMLlibFunc("uniformRDD", sc._jsc, size, numPartitions, seed) @staticmethod + @since("1.1.0") def normalRDD(sc, size, numPartitions=None, seed=None): """ Generates an RDD comprised of i.i.d. samples from the standard normal @@ -100,6 +105,7 @@ class RandomRDDs(object): return callMLlibFunc("normalRDD", sc._jsc, size, numPartitions, seed) @staticmethod + @since("1.3.0") def logNormalRDD(sc, mean, std, size, numPartitions=None, seed=None): """ Generates an RDD comprised of i.i.d. samples from the log normal @@ -132,6 +138,7 @@ class RandomRDDs(object): size, numPartitions, seed) @staticmethod + @since("1.1.0") def poissonRDD(sc, mean, size, numPartitions=None, seed=None): """ Generates an RDD comprised of i.i.d. samples from the Poisson @@ -158,6 +165,7 @@ class RandomRDDs(object): return callMLlibFunc("poissonRDD", sc._jsc, float(mean), size, numPartitions, seed) @staticmethod + @since("1.3.0") def exponentialRDD(sc, mean, size, numPartitions=None, seed=None): """ Generates an RDD comprised of i.i.d. samples from the Exponential @@ -184,6 +192,7 @@ class RandomRDDs(object): return callMLlibFunc("exponentialRDD", sc._jsc, float(mean), size, numPartitions, seed) @staticmethod + @since("1.3.0") def gammaRDD(sc, shape, scale, size, numPartitions=None, seed=None): """ Generates an RDD comprised of i.i.d. samples from the Gamma @@ -216,6 +225,7 @@ class RandomRDDs(object): @staticmethod @toArray + @since("1.1.0") def uniformVectorRDD(sc, numRows, numCols, numPartitions=None, seed=None): """ Generates an RDD comprised of vectors containing i.i.d. samples drawn @@ -241,6 +251,7 @@ class RandomRDDs(object): @staticmethod @toArray + @since("1.1.0") def normalVectorRDD(sc, numRows, numCols, numPartitions=None, seed=None): """ Generates an RDD comprised of vectors containing i.i.d. samples drawn @@ -266,6 +277,7 @@ class RandomRDDs(object): @staticmethod @toArray + @since("1.3.0") def logNormalVectorRDD(sc, mean, std, numRows, numCols, numPartitions=None, seed=None): """ Generates an RDD comprised of vectors containing i.i.d. samples drawn @@ -300,6 +312,7 @@ class RandomRDDs(object): @staticmethod @toArray + @since("1.1.0") def poissonVectorRDD(sc, mean, numRows, numCols, numPartitions=None, seed=None): """ Generates an RDD comprised of vectors containing i.i.d. samples drawn @@ -330,6 +343,7 @@ class RandomRDDs(object): @staticmethod @toArray + @since("1.3.0") def exponentialVectorRDD(sc, mean, numRows, numCols, numPartitions=None, seed=None): """ Generates an RDD comprised of vectors containing i.i.d. samples drawn @@ -360,6 +374,7 @@ class RandomRDDs(object): @staticmethod @toArray + @since("1.3.0") def gammaVectorRDD(sc, shape, scale, numRows, numCols, numPartitions=None, seed=None): """ Generates an RDD comprised of vectors containing i.i.d. samples drawn -- cgit v1.2.3