remove normalization

src/dataset.py

@@ -20,16 +20,14 @@ class PandemicDataset:
             self.device_name = 'cuda'
         else:
             self.device_name = 'cpu'
-            
+
         self.name = name
         self.N = N
         self.t_init = t.min()
         self.t_final = t.max()
 
         self.t_raw = torch.tensor(t, requires_grad=True, device=self.device_name)
-        self.t_norm = torch.tensor((t - self.t_init) / (self.t_final - self.t_init), requires_grad=True, device=self.device_name)
-
-        self.t_batch = self.t_norm.view(-1, 1).float()
+        self.t_batch = self.t_raw.view(-1, 1).float()
 
         self.__group_dict = {}
         for i, name in enumerate(group_names):
@@ -54,10 +52,6 @@ class PandemicDataset:
     @property
     def group_names(self):
         return self.__group_names
-    
-    @property
-    def normalization_differantial(self):
-        return 1 / (self.t_final - self.t_init)
 
     def get_normalized_data(self, data:list):
         assert len(data) == self.number_groups, f'data parameter needs same length as there are groups in the dataset ({self.number_groups})'