[GitHub] spark pull request #13248: [SPARK-15194] [ML] Add Python ML API for Multivar...

[lins05 <gi...@git.apache.org>]

Github user lins05 commented on a diff in the pull request:

    https://github.com/apache/spark/pull/13248#discussion_r70182969
  
    --- Diff: python/pyspark/ml/stat/distribution.py ---
    @@ -0,0 +1,267 @@
    +#
    +# 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.
    +#
    +
    +from pyspark.ml.linalg import DenseVector, DenseMatrix, Vector
    +import numpy as np
    +
    +__all__ = ['MultivariateGaussian']
    +
    +
    +
    +class MultivariateGaussian():
    +    """
    +    This class provides basic functionality for a Multivariate Gaussian (Normal) Distribution. In
    +     the event that the covariance matrix is singular, the density will be computed in a
    +    reduced dimensional subspace under which the distribution is supported.
    +    (see [[http://en.wikipedia.org/wiki/Multivariate_normal_distribution#Degenerate_case]])
    +
    +    mu The mean vector of the distribution
    +    sigma The covariance matrix of the distribution
    +
    +
    +    >>> mu = Vectors.dense([0.0, 0.0])
    +    >>> sigma= DenseMatrix(2, 2, [1.0, 1.0, 1.0, 1.0])
    +    >>> x = Vectors.dense([1.0, 1.0])
    +    >>> m = MultivariateGaussian(mu, sigma)
    +    >>> m.pdf(x)
    +    0.0682586811486
    --- End diff --
    
    To run the doctest, I think we need to call the `doctest.testmod()` explicitly like other modules do. Check [mllib/util.py](https://github.com/apache/spark/blob/v2.0.0-rc2/python/pyspark/mllib/util.py#L509-L528).
    
    Also need to add this module to the `python_test_goals` to pyspark_ml module object of [dev/sparktestsupport/modules.py](https://github.com/apache/spark/blob/v2.0.0-rc2/dev/sparktestsupport/modules.py#L401-L411)


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