diff options
| -rw-r--r-- | python/pyspark/ml/param/__init__.py | 4 | ||||
| -rw-r--r-- | python/pyspark/ml/pipeline.py | 1 | ||||
| -rw-r--r-- | python/pyspark/ml/tuning.py | 2 | ||||
| -rw-r--r-- | python/pyspark/ml/wrapper.py | 2 | ||||
| -rw-r--r-- | python/pyspark/mllib/evaluation.py | 2 | ||||
| -rw-r--r-- | python/pyspark/mllib/linalg/__init__.py | 1 | ||||
| -rw-r--r-- | python/pyspark/streaming/context.py | 2 | ||||
| -rw-r--r-- | python/pyspark/streaming/mqtt.py | 1 |
8 files changed, 14 insertions, 1 deletions
diff --git a/python/pyspark/ml/param/__init__.py b/python/pyspark/ml/param/__init__.py index eeeac49b21..2e0c63cb47 100644 --- a/python/pyspark/ml/param/__init__.py +++ b/python/pyspark/ml/param/__init__.py @@ -164,6 +164,7 @@ class Params(Identifiable): a flat param map, where the latter value is used if there exist conflicts, i.e., with ordering: default param values < user-supplied values < extra. + :param extra: extra param values :return: merged param map """ @@ -182,6 +183,7 @@ class Params(Identifiable): embedded and extra parameters over and returns the copy. Subclasses should override this method if the default approach is not sufficient. + :param extra: Extra parameters to copy to the new instance :return: Copy of this instance """ @@ -201,6 +203,7 @@ class Params(Identifiable): def _resolveParam(self, param): """ Resolves a param and validates the ownership. + :param param: param name or the param instance, which must belong to this Params instance :return: resolved param instance @@ -243,6 +246,7 @@ class Params(Identifiable): """ Copies param values from this instance to another instance for params shared by them. + :param to: the target instance :param extra: extra params to be copied :return: the target instance with param values copied diff --git a/python/pyspark/ml/pipeline.py b/python/pyspark/ml/pipeline.py index 13cf2b0f7b..312a8502b3 100644 --- a/python/pyspark/ml/pipeline.py +++ b/python/pyspark/ml/pipeline.py @@ -154,6 +154,7 @@ class Pipeline(Estimator): def setStages(self, value): """ Set pipeline stages. + :param value: a list of transformers or estimators :return: the pipeline instance """ diff --git a/python/pyspark/ml/tuning.py b/python/pyspark/ml/tuning.py index ab5621f45c..705ee53685 100644 --- a/python/pyspark/ml/tuning.py +++ b/python/pyspark/ml/tuning.py @@ -254,6 +254,7 @@ class CrossValidator(Estimator): Creates a copy of this instance with a randomly generated uid and some extra params. This copies creates a deep copy of the embedded paramMap, and copies the embedded and extra parameters over. + :param extra: Extra parameters to copy to the new instance :return: Copy of this instance """ @@ -290,6 +291,7 @@ class CrossValidatorModel(Model): and some extra params. This copies the underlying bestModel, creates a deep copy of the embedded paramMap, and copies the embedded and extra parameters over. + :param extra: Extra parameters to copy to the new instance :return: Copy of this instance """ diff --git a/python/pyspark/ml/wrapper.py b/python/pyspark/ml/wrapper.py index 8218c7c5f8..4bcb4aaec8 100644 --- a/python/pyspark/ml/wrapper.py +++ b/python/pyspark/ml/wrapper.py @@ -119,6 +119,7 @@ class JavaEstimator(Estimator, JavaWrapper): def _fit_java(self, dataset): """ Fits a Java model to the input dataset. + :param dataset: input dataset, which is an instance of :py:class:`pyspark.sql.DataFrame` :param params: additional params (overwriting embedded values) @@ -173,6 +174,7 @@ class JavaModel(Model, JavaTransformer): extra params. This implementation first calls Params.copy and then make a copy of the companion Java model with extra params. So both the Python wrapper and the Java model get copied. + :param extra: Extra parameters to copy to the new instance :return: Copy of this instance """ diff --git a/python/pyspark/mllib/evaluation.py b/python/pyspark/mllib/evaluation.py index 4398ca86f2..a90e5c50e5 100644 --- a/python/pyspark/mllib/evaluation.py +++ b/python/pyspark/mllib/evaluation.py @@ -147,7 +147,7 @@ class MulticlassMetrics(JavaModelWrapper): """ Evaluator for multiclass classification. - :param predictionAndLabels an RDD of (prediction, label) pairs. + :param predictionAndLabels: an RDD of (prediction, label) pairs. >>> predictionAndLabels = sc.parallelize([(0.0, 0.0), (0.0, 1.0), (0.0, 0.0), ... (1.0, 0.0), (1.0, 1.0), (1.0, 1.0), (1.0, 1.0), (2.0, 2.0), (2.0, 0.0)]) diff --git a/python/pyspark/mllib/linalg/__init__.py b/python/pyspark/mllib/linalg/__init__.py index f929e3e96f..ea42127f16 100644 --- a/python/pyspark/mllib/linalg/__init__.py +++ b/python/pyspark/mllib/linalg/__init__.py @@ -240,6 +240,7 @@ class Vector(object): def toArray(self): """ Convert the vector into an numpy.ndarray + :return: numpy.ndarray """ raise NotImplementedError diff --git a/python/pyspark/streaming/context.py b/python/pyspark/streaming/context.py index 4069d7a149..a8c9ffc235 100644 --- a/python/pyspark/streaming/context.py +++ b/python/pyspark/streaming/context.py @@ -240,6 +240,7 @@ class StreamingContext(object): def awaitTermination(self, timeout=None): """ Wait for the execution to stop. + @param timeout: time to wait in seconds """ if timeout is None: @@ -252,6 +253,7 @@ class StreamingContext(object): Wait for the execution to stop. Return `true` if it's stopped; or throw the reported error during the execution; or `false` if the waiting time elapsed before returning from the method. + @param timeout: time to wait in seconds """ self._jssc.awaitTerminationOrTimeout(int(timeout * 1000)) diff --git a/python/pyspark/streaming/mqtt.py b/python/pyspark/streaming/mqtt.py index f06598971c..fa83006c36 100644 --- a/python/pyspark/streaming/mqtt.py +++ b/python/pyspark/streaming/mqtt.py @@ -31,6 +31,7 @@ class MQTTUtils(object): storageLevel=StorageLevel.MEMORY_AND_DISK_SER_2): """ Create an input stream that pulls messages from a Mqtt Broker. + :param ssc: StreamingContext object :param brokerUrl: Url of remote mqtt publisher :param topic: topic name to subscribe to |