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Commit 2e1b3bfd authored by Nikolai's avatar Nikolai
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Fixing bug for significance scan - wrong ordering of bkg and sig errors

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toolkit.py
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...@@ -922,8 +922,8 @@ class ClassificationProject(object): ...@@ -922,8 +922,8 @@ class ClassificationProject(object):
significances_train = [] significances_train = []
significances_test = [] significances_test = []
for hist_sig, hist_bkg, rel_errors_sig, rel_errors_bkg, significances, w, y in [ for hist_sig, hist_bkg, rel_errors_sig, rel_errors_bkg, significances, w, y in [
(hist_sig_train, hist_bkg_train, rel_errors_bkg_train, rel_errors_sig_train, significances_train, self.w_train, self.y_train), (hist_sig_train, hist_bkg_train, rel_errors_sig_train, rel_errors_bkg_train, significances_train, self.w_train, self.y_train),
(hist_sig_test, hist_bkg_test, rel_errors_bkg_test, rel_errors_sig_test, significances_test, self.w_test, self.y_test), (hist_sig_test, hist_bkg_test, rel_errors_sig_test, rel_errors_bkg_test, significances_test, self.w_test, self.y_test),
]: ]:
# factor to rescale due to using only a fraction of events (training and test samples) # factor to rescale due to using only a fraction of events (training and test samples)
normfactor_sig = (np.sum(self.w_train[self.y_train==1])+np.sum(self.w_test[self.y_test==1]))/np.sum(w[y==1]) normfactor_sig = (np.sum(self.w_train[self.y_train==1])+np.sum(self.w_test[self.y_test==1]))/np.sum(w[y==1])
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