Updated thesis

src/data/dataset.py

@@ -169,11 +169,16 @@ class NrvDataset(Dataset):
             all_features = torch.cat(all_features_list, dim=0)
 
         else:
-            all_features_list = [nrv_features.unsqueeze(1)]
+            all_features_list = [nrv_features + self.]
+            
 
             if self.forecast_features.numel() > 0:
                 history_forecast_features = self.forecast_features[
-                    actual_idx + 1 : actual_idx + self.sequence_length + 1, :
+                    actual_idx
+                    + 1 : actual_idx
+                    + self.sequence_length
+                    + self.predict_sequence_length,
+                    :,
                 ]
                 all_features_list.append(history_forecast_features)