pyprophet/stats.py
def pnorm(stat, stat0):
    """ [P(X>pi, mu, sigma) for pi in pvalues] for normal distributed stat with
    expectation value mu and std deviation sigma """

    mu, sigma = mean_and_std_dev(stat0)

    stat = to_one_dim_array(stat, np.float64)
    args = (stat - mu) / sigma
    return 1-(0.5 * (1.0 + scipy.special.erf(args / np.sqrt(2.0))))
def pnorm(stat, stat0):
    """ [P(X>pi, mu, sigma) for pi in pvalues] for normal distributed stat with
    expectation value mu and std deviation sigma """

    mu, sigma = mean_and_std_dev(stat0)

    stat = to_one_dim_array(stat, np.float64)
    args = (stat - mu) / sigma
    return 1-(0.5 * (1.0 + scipy.special.erf(args / np.sqrt(2.0))))
[P(X>pi, mu, sigma) for pi in pvalues] for normal distributed stat with
    expectation value mu and std deviation sigma