Added test for the scaling and possible problem with param scaling

Author: DavideDC95

ezyrb/plugin/scaler.py

@@ -26,6 +26,9 @@ def __init__(self, scaler, mode, target) -> None:
         self.scaler = scaler
         self.mode = mode
         self.target = target
+        
+        if target == 'parameters': #TODO
+            raise NotImplementedError("Scaling of parameters not implemented yet.")
 
     @property
     def target(self):
@@ -141,5 +144,5 @@ def rom_postprocessing(self, rom):
                 db.parameters_matrix,
                 self.scaler.inverse_transform(self._select_matrix(db)),
             )
-
+            
         rom._reduced_database = new_db

tests/test_scaler.py

@@ -18,22 +18,31 @@ def test_constructor():
     pod = POD()
     import torch
     rbf = RBF()
-    rbf = ANN([10, 10], function=torch.nn.Softplus(), stop_training=[1000])
+    #rbf = ANN([10, 10], function=torch.nn.Softplus(), stop_training=[1000])
     db = Database(param, snapshots.T)
     # rom = ROM(db, pod, rbf, plugins=[DatabaseScaler(StandardScaler(), 'full', 'snapshots')])
     rom = ROM(db, pod, rbf, plugins=[
-        DatabaseScaler(StandardScaler(), 'full', 'parameters'),
+        #DatabaseScaler(StandardScaler(), 'reduced', 'parameters'),
         DatabaseScaler(StandardScaler(), 'reduced', 'snapshots')
     ])
     rom.fit()
-    print(rom.predict(rom.database.parameters_matrix))
-    print(rom.database.snapshots_matrix)
+   
+    
 
 
-# def test_values():
-#     snap = Snapshot(test_value)
-#     snap.values = test_value
-#     snap = Snapshot(test_value, space=test_space)
-#     with pytest.raises(ValueError):
-#         snap.values = test_value[:-2]
+def test_values():
+    pod = POD()
+    rbf = RBF()
+    db = Database(param, snapshots.T)
+    rom = ROM(db, pod, rbf, plugins=[
+        DatabaseScaler(StandardScaler(), 'reduced', 'snapshots')
+    ])
+    rom.fit()
+    test_param = param[2]
+    truth_sol = db.snapshots_matrix[2]
+    predicted_sol = rom.predict(test_param).snapshots_matrix[0]
+    print(predicted_sol)
+    print(truth_sol)
+    np.testing.assert_allclose(predicted_sol, truth_sol, 
+            rtol=1e-5, atol=1e-5)