Update PeakOTron.py

PeakOTron.py

@@ -352,48 +352,6 @@ class PeakOTron:
     ########################################################################################################
 
     
-    
-#     def __CalcChi2(self, x, y, y_hat, y_err):
-#         chi2 = np.nansum(((y_hat - y)/y_err)**2)
-#         ndof = len(x) - 10
-#         return chi2, ndof
-    
-    
-    
-#     def GetChi2(self, prefit=False):
-        
-#         if(self._m_DRM is None):
-#             raise Exception ("Fit has not yet been performed. Please first perform a fit.")
-#         else:
-
-#             x_all = self._hist_data["bin_numbers"]
-#             y_all = self._hist_data["counts"]
-#             y_err_all = self._hist_data["counts_error"]
-            
-#             if(self._fit_kwargs["truncate_nsigma0_do"] is not None):
-#                 lim_nsigma0 = self._prefit_values_bin["Q_0"] - self._fit_kwargs["truncate_nsigma0_do"]*self._prefit_values_bin["sigma_0"]
-#                 cond_sel_nsigma0 = (self._hist_data["bin_numbers"]>lim_nsigma0)
-
-#             else:
-#                 cond_sel_nsigma0 = np.full(len(self._hist_data["bin_numbers"]), True).astype(bool)
-
-#             x = x_all[cond_sel_nsigma0]
-#             y = y_all[cond_sel_nsigma0]
-#             y_err = y_err_all[cond_sel_nsigma0]
-
-#             y_hat = self.GetModel(x, prefit=prefit, bin_units=True)
-#             y_hat_err = np.sqrt(y_hat)
-            
-                 
-#             plt.figure()
-#             plt.plot(x, (y-y_hat)/y_err)
-#             plt.show()
-        
-#             chi2, ndof = self.__CalcChi2(x, y, y_hat, y_err)
-
-#             return chi2, ndof
-    
-    
 
     
     def GetChi2(self, pars=None, prefit=False, full=False, n_sigma_lims=[None, None]):