spark-instrumented-optimizer/python/pyspark/mllib/stat/test.py

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# Licensed to the Apache Software Foundation (ASF) under one or more
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# The ASF licenses this file to You under the Apache License, Version 2.0
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#    http://www.apache.org/licenses/LICENSE-2.0
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from pyspark.mllib.common import inherit_doc, JavaModelWrapper


__all__ = ["ChiSqTestResult", "KolmogorovSmirnovTestResult"]


class TestResult(JavaModelWrapper):
    """
    Base class for all test results.
    """

    @property
    def pValue(self):
        """
        The probability of obtaining a test statistic result at least as
        extreme as the one that was actually observed, assuming that the
        null hypothesis is true.
        """
        return self._java_model.pValue()

    @property
    def degreesOfFreedom(self):
        """
        Returns the degree(s) of freedom of the hypothesis test.
        Return type should be Number(e.g. Int, Double) or tuples of Numbers.
        """
        return self._java_model.degreesOfFreedom()

    @property
    def statistic(self):
        """
        Test statistic.
        """
        return self._java_model.statistic()

    @property
    def nullHypothesis(self):
        """
        Null hypothesis of the test.
        """
        return self._java_model.nullHypothesis()

    def __str__(self):
        return self._java_model.toString()


@inherit_doc
class ChiSqTestResult(TestResult):
    """
    Contains test results for the chi-squared hypothesis test.
    """

    @property
    def method(self):
        """
        Name of the test method
        """
        return self._java_model.method()


@inherit_doc
class KolmogorovSmirnovTestResult(TestResult):
    """
    Contains test results for the Kolmogorov-Smirnov test.
    """