add id

src/calculation_time_constrains/service.py

@@ -94,6 +94,7 @@ async def get_corrective_cost_time_chart(
         # Fill in missing dates with nearest available value
         complete_data = []
         last_known_value = 0  # Default value if no data is available
+        not_full_data = []
 
         for date in date_range:
             if date in data_dict:
@@ -101,16 +102,16 @@ async def get_corrective_cost_time_chart(
                     last_known_value = data_dict[date]
                 complete_data.append(last_known_value)
             else:
+                not_full_data.append(location_tag)
                 complete_data.append(0)
-
         # Convert to numpy array
         daily_failure = np.array(complete_data)
 
-        failure_counts = np.cumsum(daily_failure)
+        # failure_counts = np.cumsum(daily_failure)
 
         # Calculate corrective costs
         cost_per_failure = material_cost + service_cost
-        corrective_costs = failure_counts * cost_per_failure
+        corrective_costs = daily_failure * cost_per_failure
 
         return corrective_costs, daily_failure