diff --git a/src/bayesvalidrox/post_processing/post_processing.py b/src/bayesvalidrox/post_processing/post_processing.py index 9755d0dccd7248ddff38d7520cc0f6e42d863fed..8300faebf2aff0027b23b0f211191928376cfafe 100644 --- a/src/bayesvalidrox/post_processing/post_processing.py +++ b/src/bayesvalidrox/post_processing/post_processing.py @@ -86,7 +86,6 @@ class PostProcessing: # Read Monte-Carlo reference self.mc_reference = self.engine.Model.read_observation('mc_ref') - self.mc_reference = self.engine.Model.read_observation('mc_ref') # Set the x values x_values_orig = self.engine.ExpDesign.x_values @@ -96,7 +95,6 @@ class PostProcessing: # Plot the best fit line, set the linewidth (lw), color and # transparency (alpha) of the line - for key in self.engine.out_names: for key in self.engine.out_names: fig, ax = plt.subplots(nrows=1, ncols=2) @@ -198,10 +196,8 @@ class PostProcessing: try: key = self.engine.out_names[1] - key = self.engine.out_names[1] except IndexError: key = self.engine.out_names[0] - key = self.engine.out_names[0] n_obs = self.model_out_dict[key].shape[1] @@ -254,7 +250,6 @@ class PostProcessing: self.rmse = {} self.valid_error = {} # Loop over the keys and compute RMSE error. - for key in self.engine.out_names: for key in self.engine.out_names: # Root mena square self.rmse[key] = mean_squared_error(outputs[key], metamod_outputs[key], @@ -274,9 +269,7 @@ class PostProcessing: # Save error dicts in PCEModel object self.engine.MetaModel.rmse = self.rmse self.engine.MetaModel.valid_error = self.valid_error - self.engine.MetaModel.rmse = self.rmse - self.engine.MetaModel.valid_error = self.valid_error - + # ------------------------------------------------------------------------- def plot_seq_design_diagnostics(self, ref_BME_KLD=None) -> None: """ @@ -582,7 +575,6 @@ class PostProcessing: sobol_cell_, total_sobol_ = {}, {} - for output in self.engine.out_names: for output in self.engine.out_names: n_meas_points = len(coeffs_dict[f'b_{b_i+1}'][output])