Added crps + profit logging and updated plots for non autoregressive models

src/policies/PolicyEvaluator.py

@@ -239,15 +239,28 @@ class PolicyEvaluator:
                 penalty_profits[penalty] += profit
                 penalty_charge_cycles[penalty] += charge_cycles
 
+        # transform profits to per year: penalty_profits / penalty_charge_cycles * 400 cycles per year
+        transformed_profits_per_year = {}
+        for penalty in penalty_profits:
+            transformed_profits_per_year[penalty] = (
+                penalty_profits[penalty] / penalty_charge_cycles[penalty] * 400
+            )
+
         df = pd.DataFrame(
             list(
                 zip(
                     penalty_profits.keys(),
                     penalty_profits.values(),
                     penalty_charge_cycles.values(),
+                    transformed_profits_per_year.values(),
                 )
             ),
-            columns=["Penalty", "Profit_till_400", "Cycles_till_400"],
+            columns=[
+                "Penalty",
+                "Profit_till_400",
+                f"Cycles_till_400 (max {usable_charge_cycles})",
+                "Profit_per_year_till_400",
+            ],
         )
 
         return df