Predictions page enhancement

src/data/params/Preprocessing.json

+{"Scatter": "Non", "Saitzky-Golay derivative parameters": {"polyorder": 0, "deriv": 0, "window_length": 23}}
\ No newline at end of file

src/pages/2-model_creation.py

@@ -94,7 +94,7 @@ elif file == files_format[1]:
         with NamedTemporaryFile(delete=False, suffix=".dx") as tmp:
             tmp.write(data_file.read())
             tmp_path = tmp.name
-            chem_data, spectra, meta_data = read_dx(file =  tmp_path)
+            chem_data, spectra, meta_data, meta_data_st = read_dx(file =  tmp_path)
             M3.success("The data have been loaded successfully", icon="✅")
             if chem_data.shape[1]>0:
                 yname = M3.selectbox('Select target', options=chem_data.columns)
@@ -196,8 +196,11 @@ if not spectra.empty and not y.empty:
         yt = Reg.pred_data_[2]
             
         #if
-        #M2.write('-- Spectral preprocessing info --')
-        #M2.write(Reg.best_hyperparams)        
+        M2.write('-- Spectral preprocessing info --')
+        M2.write(Reg.best_hyperparams)
+        with open("data/params/Preprocessing.json", "w") as outfile: 
+            json.dump(Reg.best_hyperparams, outfile)      
+
         M2.write("-- Performance metrics --")
         M2.dataframe(Reg.metrics_)
         #from st_circular_progress import CircularProgress
@@ -207,10 +210,6 @@ if not spectra.empty and not y.empty:
         #my_circular_progress.st_circular_progress()
         #my_circular_progress.update_value(progress=20)
 
-
-
-        
-
         M7.pyplot(reg_plot([y_train, y_train, y_test],[yc, ycv, yt], train_idx = train_index, test_idx = test_index))
         M8.pyplot(resid_plot([y_train, y_train, y_test],[yc, ycv, yt], train_idx = train_index, test_idx = test_index))