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