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a guest Feb 17th, 2019 53 Never
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  1. #! /bin/env python
  2.  
  3. import numpy as np
  4. from scipy.stats import percentileofscore
  5. from scipy.stats import norm
  6.  
  7. lle = np.load(open('./lle_summary.npy'))
  8.  
  9. significances_g = [np.max(lle[lle['i_toy'] == i_toy]['sig_g']) for i_toy in xrange(10000)]
  10. p_value = 1. - percentileofscore(significances_g, 3.8)/100.
  11. print '* Fitting g *'
  12. print 'p value of 3.8', p_value
  13. print 'Significance', norm.ppf(1 - p_value)
  14.  
  15. significances_r = [np.max(lle[lle['i_toy'] == i_toy]['sig_r']) for i_toy in xrange(10000)]
  16. p_value = 1. - percentileofscore(significances_r, 3.8)/100.
  17. print '* Fitting g *'
  18. print 'p value of 3.8', p_value
  19. print 'Significance', norm.ppf(1 - p_value)
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