[docs] Update docstrings for PostProcessing

src/bayesvalidrox/post_processing/post_processing.py

@@ -38,13 +38,6 @@ class PostProcessing:
         self.engine = engine
         self.name = name
         
-        self.out_dir = f'{out_dir}/Outputs_PostProcessing_{self.name}/'
-        
-        # Open a pdf for the plots
-        if not os.path.exists(self.out_dir):
-            os.makedirs(self.out_dir)
-
-
         self.out_dir = f'./{out_dir}/Outputs_PostProcessing_{self.name}/'
 
         # Open a pdf for the plots
@@ -277,9 +270,10 @@ class PostProcessing:
         # Save error dicts in PCEModel object
         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:
+    def plot_seq_design_diagnostics(self, ref_BME_KLD=None)->None:
         """
         Plots the Bayesian Model Evidence (BME) and Kullback-Leibler divergence
         (KLD) for the sequential design.
@@ -526,7 +520,7 @@ class PostProcessing:
 
 
     # -------------------------------------------------------------------------
-    def sobol_indices(self, xlabel: str = 'Time [s]', plot_type: str = None):
+    def sobol_indices(self, xlabel:str='Time [s]', plot_type:str=None):
         """
         Provides Sobol indices as a sensitivity measure to infer the importance
         of the input parameters. See Eq. 27 in [1] for more details. For the
@@ -554,6 +548,7 @@ class PostProcessing:
         ------
         AttributeError
             MetaModel in given Engine needs to be of type 'pce' or 'apce'.
+        
         Returns
         -------
         sobol_cell: dict
@@ -846,7 +841,6 @@ class PostProcessing:
 
     # -------------------------------------------------------------------------
     def check_reg_quality(self, n_samples:int=1000, samples=None, outputs:dict=None)->None:
-
         """
         Checks the quality of the metamodel for single output models based on:
         https://towardsdatascience.com/how-do-you-check-the-quality-of-your-regression-model-in-python-fa61759ff685