def edf_normal_inverse_transformed(x, alpha=(3.0 / 8), beta=(3.0 / 8), axis=0):
 from scipy import stats
 ranks = plotting_positions(data, alpha=alpha, beta=alpha, axis=0, masknan=False)
 ranks_transf = stats.norm.ppf(ranks)
 return ranks_transf

def edf_normal_inverse_transformed ( x , alpha = ( 3.0 / 8 ) , beta = ( 3.0 / 8 ) , axis = 0 ) : from scipy import stats ranks = plotting_positions ( data , alpha = alpha , beta = alpha , axis = 0 , masknan = False ) ranks_transf = stats . norm . ppf ( ranks ) return ranks_transf
rank based normal inverse transformed cdf .