#! /bin/env python

import numpy as np
from scipy.stats import percentileofscore
from scipy.stats import norm

lle = np.load(open('./lle_summary.npy'))

significances_g = [np.max(lle[lle['i_toy'] == i_toy]['sig_g']) for i_toy in xrange(10000)]
p_value = 1. - percentileofscore(significances_g, 3.8)/100.
print '* Fitting g *'
print 'p value of 3.8', p_value
print 'Significance', norm.ppf(1 - p_value)

significances_r = [np.max(lle[lle['i_toy'] == i_toy]['sig_r']) for i_toy in xrange(10000)]
p_value = 1. - percentileofscore(significances_r, 3.8)/100.
print '* Fitting g *'
print 'p value of 3.8', p_value
print 'Significance', norm.ppf(1 - p_value)