test_analytics.py 文件源码

python
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项目:PyDataLondon29-EmbarrassinglyParallelDAWithAWSLambda 作者: SignalMedia 项目源码 文件源码
def test_corr_rank(self):
        tm._skip_if_no_scipy()

        import scipy
        import scipy.stats as stats

        # kendall and spearman
        A = tm.makeTimeSeries()
        B = tm.makeTimeSeries()
        A[-5:] = A[:5]
        result = A.corr(B, method='kendall')
        expected = stats.kendalltau(A, B)[0]
        self.assertAlmostEqual(result, expected)

        result = A.corr(B, method='spearman')
        expected = stats.spearmanr(A, B)[0]
        self.assertAlmostEqual(result, expected)

        # these methods got rewritten in 0.8
        if scipy.__version__ < LooseVersion('0.9'):
            raise nose.SkipTest("skipping corr rank because of scipy version "
                                "{0}".format(scipy.__version__))

        # results from R
        A = Series(
            [-0.89926396, 0.94209606, -1.03289164, -0.95445587, 0.76910310, -
             0.06430576, -2.09704447, 0.40660407, -0.89926396, 0.94209606])
        B = Series(
            [-1.01270225, -0.62210117, -1.56895827, 0.59592943, -0.01680292,
             1.17258718, -1.06009347, -0.10222060, -0.89076239, 0.89372375])
        kexp = 0.4319297
        sexp = 0.5853767
        self.assertAlmostEqual(A.corr(B, method='kendall'), kexp)
        self.assertAlmostEqual(A.corr(B, method='spearman'), sexp)
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