How to use the pymannkendall.correlated_multivariate_test function in pymannkendall

def test_correlated_multivariate_test(NoTrend2dData,arbitrary_2d_data):
    # check with no trend data
    NoTrendRes = mk.correlated_multivariate_test(NoTrend2dData)
    assert NoTrendRes.trend == 'no trend'
    assert NoTrendRes.h == False
    assert NoTrendRes.Tau == 0.0
    assert NoTrendRes.s == 0.0
    assert NoTrendRes.var_s == 0.0
    assert NoTrendRes.slope == 0.0
    
    # check with arbitrary data
    result = mk.correlated_multivariate_test(arbitrary_2d_data)
    assert result.trend == 'no trend'
    assert result.h == False
    assert result.p == 0.05777683185903615
    assert result.z == -1.8973873659119118
    assert result.Tau == -0.05868196964087375
    assert result.s == -317.0
    assert result.var_s == 27913.000000000007

def test_correlated_multivariate_test(NoTrend2dData,arbitrary_2d_data):
    # check with no trend data
    NoTrendRes = mk.correlated_multivariate_test(NoTrend2dData)
    assert NoTrendRes.trend == 'no trend'
    assert NoTrendRes.h == False
    assert NoTrendRes.Tau == 0.0
    assert NoTrendRes.s == 0.0
    assert NoTrendRes.var_s == 0.0
    assert NoTrendRes.slope == 0.0
    
    # check with arbitrary data
    result = mk.correlated_multivariate_test(arbitrary_2d_data)
    assert result.trend == 'no trend'
    assert result.h == False
    assert result.p == 0.05777683185903615
    assert result.z == -1.8973873659119118
    assert result.Tau == -0.05868196964087375
    assert result.s == -317.0
    assert result.var_s == 27913.000000000007
    assert result.slope == -0.680446465481604