add id

src/calculation_time_constrains/service.py

@@ -30,11 +30,14 @@ def get_overhaul_cost_by_time_chart(
     if days <= 0:
         raise ValueError("Days must be positive")
 
-    exponents = np.arange(1, days+1)
+    hours = days * 24
+
+    rate = np.arange(1, hours+1)
+
     cost_per_equipment = overhaul_cost / numEquipments
-    # Using a slower decay base to spread the budget depletion over more days
-    results = cost_per_equipment - ((cost_per_equipment / days) * exponents)
-    results = np.where(np.isfinite(results), results, 0)
+
+    results = cost_per_equipment - ((cost_per_equipment / hours) * rate)
+
     return results
 
 
@@ -58,21 +61,8 @@ def get_overhaul_cost_by_time_chart(
 async def get_corrective_cost_time_chart(
     material_cost: float, service_cost: float, location_tag: str, token, max_days: int
 ) -> Tuple[np.ndarray, np.ndarray]:
-    """
-    Fetch failure data from API and calculate corrective costs, ensuring 365 days of data.
-
-    Args:
-        material_cost: Cost of materials per failure
-        service_cost: Cost of service per failure
-        location_tag: Location tag of the equipment
-        token: Authorization token
-
-    Returns:
-        Tuple of (corrective_costs, daily_failure_rate)
-    """
-    start_date = datetime.datetime(2025, 1, 1)
 
-# Calculate end date (667 days after start date)
+    start_date = datetime.datetime(2025, 1, 1)
     end_date = start_date + datetime.timedelta(days=max_days)
     url = f"http://192.168.1.82:8000/reliability/main/number-of-failures/{location_tag}/{start_date.strftime('%Y-%m-%d')}/{end_date.strftime('%Y-%m-%d')}"
 
@@ -120,6 +110,10 @@ async def get_corrective_cost_time_chart(
         # Convert to numpy array
         daily_failure = np.array(complete_data)
 
+        hourly_failure = np.repeat(daily_failure, 24) / 24
+
+
+
         # failure_counts = np.cumsum(daily_failure)
 
         # Calculate corrective costs
@@ -128,9 +122,10 @@ async def get_corrective_cost_time_chart(
         if cost_per_failure == 0:
             raise ValueError("Cost per failure cannot be zero")
 
-        corrective_costs = daily_failure * cost_per_failure
+        corrective_costs = hourly_failure * cost_per_failure
+
 
-        return corrective_costs, daily_failure
+        return corrective_costs, hourly_failure
 
     except Exception as e:
         print(f"Error fetching or processing data: {str(e)}")
@@ -190,7 +185,7 @@ async def create_param_and_data(
 
 
 async def get_calculation_result(db_session: DbSession, calculation_id: str):
-    days = 667
+    days = 667*24
     scope_calculation = await get_calculation_data_by_id(
         db_session=db_session, calculation_id=calculation_id
     )
@@ -332,8 +327,8 @@ async def create_calculation_result_service(
 
     # Store results for each equipment
     equipment_results: List[CalculationEquipmentResult] = []
-    total_corrective_costs = np.zeros(days)
-    total_daily_failures = np.zeros(days)
+    total_corrective_costs = np.zeros(days*24)
+    total_daily_failures = np.zeros(days*24)
 
     # Calculate for each equipment
     for eq in equipments:
@@ -344,16 +339,10 @@ async def create_calculation_result_service(
             location_tag=eq.equipment.location_tag,
             max_days=667
         )
-        # corrective_costs, daily_failures = get_corrective_cost_time_chart(
-        #     material_cost=eq.material_cost,
-        #     service_cost=eq.service_cost,
-        #     days=days,
-        #     numEquipments=len(equipments),
-        # )
 
         overhaul_cost_points = get_overhaul_cost_by_time_chart(
             calculation_data.parameter.overhaul_cost,
-            days=len(corrective_costs),
+            days=667,
             numEquipments=len(equipments),
         )