stats.py 文件源码

def correlation(x,y,name="Pearson"):
    # Linear or rank correlation
    # Returns:
    #   r,rho, or tau (float) = the test statistic
    #   pvalue (float) = the p-value for the test

    assert len(x)==len(y), "Arrays x & y must be equal length."

    if name == "Pearson":
        (r,pvalue) = scipy.stats.pearsonr(x,y)
        return r,pvalue

    elif name == "Spearman":
        (rho,pvalue) = scipy.stats.spearmanr(x,y)
        return rho,pvalue

    elif name == "Kendall":
        (tau,pvalue) = scipy.stats.kendalltau(x,y)
        return tau,pvalue

    else:
        error = ("The {} correlation is not available."
                 "Please use 'Pearson', 'Spearman', or 'Kendall.'")
        error.format(name)
        raise ValueError(error)