Fixed policy evaluation for autoregressive

src/policies/PolicyEvaluator.py

@@ -45,7 +45,8 @@ class PolicyEvaluator:
     ):
         idx = test_loader.dataset.get_idx_for_date(date.date())
 
-        print("Evaluated for idx: ", idx)
+        if idx not in idx_samples:
+            print("No samples for idx: ", idx, date)
         (initial, samples) = idx_samples[idx]
 
         if len(initial.shape) == 2:
@@ -98,16 +99,17 @@ class PolicyEvaluator:
 
     def evaluate_test_set(self, idx_samples, test_loader):
         self.profits = []
-        try:
-            for date in tqdm(self.dates):
-                self.evaluate_for_date(date, idx_samples, test_loader)
-        except KeyboardInterrupt:
-            print("Interrupted")
-            raise KeyboardInterrupt
 
-        except Exception as e:
-            print(e)
-            pass
+        for date in tqdm(self.dates):
+            try:
+                self.evaluate_for_date(date, idx_samples, test_loader)
+            except KeyboardInterrupt:
+                print("Interrupted")
+                raise KeyboardInterrupt
+
+            except Exception as e:
+                print(e)
+                pass
 
         self.profits = pd.DataFrame(
             self.profits,