import sys

with open('/home/atra/Development/be-optimumoh/src/calculation_time_constrains/service.py', 'r') as f:
    lines = f.readlines()

# Find the point where it broke
# Line 159 is '                \'month_index\': i + 1,\n'
# We want to keep up to line 159 (index 158)

new_lines = lines[:159]
new_lines.append("                'source': source\n")
new_lines.append("            }\n")
new_lines.append("        \n")
new_lines.append("        return monthly_data\n")
new_lines.append("\n")
new_lines.append("    async def get_simulation_results(self, simulation_id: str = \"default\"):\n")
new_lines.append("        \"\"\"Get simulation results for Birnbaum importance calculations\"\"\"\n")
new_lines.append("        headers = {\n")
new_lines.append("            \"Authorization\": f\"Bearer {self.token}\",\n")
new_lines.append("            \"Content-Type\": \"application/json\"\n")
new_lines.append("        }\n")
new_lines.append("\n")
new_lines.append("        calc_result_url = f\"{self.api_base_url}/aeros/simulation/result/calc/{simulation_id}?nodetype=RegularNode\"\n")
new_lines.append("        plant_result_url = f\"{self.api_base_url}/aeros/simulation/result/calc/{simulation_id}/plant\"\n")
new_lines.append("\n")
new_lines.append("        async with httpx.AsyncClient(timeout=300.0) as client:\n")
new_lines.append("            calc_task = client.get(calc_result_url, headers=headers)\n")
new_lines.append("            plant_task = client.get(plant_result_url, headers=headers)\n")
new_lines.append("\n")
new_lines.append("            calc_response, plant_response = await asyncio.gather(calc_task, plant_task)\n")
new_lines.append("\n")
new_lines.append("            calc_response.raise_for_status()\n")
new_lines.append("            plant_response.raise_for_status()\n")
new_lines.append("\n")
new_lines.append("            calc_data = calc_response.json()[\"data\"]\n")
new_lines.append("            plant_data = plant_response.json()[\"data\"]\n")
new_lines.append("\n")
new_lines.append("            return {\n")
new_lines.append("                \"calc_result\": calc_data,\n")
new_lines.append("                \"plant_result\": plant_data\n")
new_lines.append("            }\n")
new_lines.append("\n")
new_lines.append("    def _calculate_equipment_costs_with_spareparts(self, failures_prediction: Dict, birnbaum_importance: float,\n")
new_lines.append("                                                 preventive_cost: float, failure_replacement_cost: float, ecs,\n")
new_lines.append("                                                 location_tag: str, planned_overhauls: List = None, loss_production_permonth=0) -> List[Dict]:\n")
new_lines.append("        \"\"\"Calculate costs for each month including sparepart costs and availability\"\"\"\n")
new_lines.append("        \n")
new_lines.append("        if not failures_prediction:\n")
new_lines.append("            self.logger.warning(f\"No failure prediction data for {location_tag}\")\n")
new_lines.append("            return []\n")
new_lines.append("\n")
new_lines.append("        results = []\n")
new_lines.append("        months = list(failures_prediction.keys())\n")
new_lines.append("        num_months = len(months)\n")
new_lines.append("        failure_counts = []\n")
new_lines.append("        \n")
new_lines.append("        monthly_risk_cost_per_failure = 0\n")
new_lines.append("        \n")
new_lines.append("        if ecs:\n")
new_lines.append("            is_trip = 1 if ecs.get(\"Diskripsi Operasional Akibat Equip. Failure\") == \"Trip\" else 0\n")
new_lines.append("            is_series = 0 if not birnbaum_importance else math.floor(birnbaum_importance)\n")
new_lines.append("            if is_trip:\n")
new_lines.append("                downtime = ecs.get(\"Estimasi Waktu Maint. / Downtime / Gangguan (Jam)\")\n")
new_lines.append("                monthly_risk_cost_per_failure = 660 * 1000000 * is_trip * downtime * is_series\n")
new_lines.append("        \n")
new_lines.append("        for month_key in months:\n")
new_lines.append("            data = failures_prediction[month_key]\n")
new_lines.append("            failure_counts.append(data['cumulative_failures'])\n")
new_lines.append("        \n")
new_lines.append("        for i in range(num_months):\n")
new_lines.append("            month_index = i + 1\n")
new_lines.append("            \n")
new_lines.append("            # Use only months within the analysis window\n")
new_lines.append("            if month_index > self.time_window_months:\n")
new_lines.append("                continue\n")
new_lines.append("\n")
new_lines.append("            # Check sparepart availability for this month\n")
new_lines.append("            sparepart_analysis = self._analyze_sparepart_availability(\n")
new_lines.append("                location_tag, month_index - 1, planned_overhauls or []\n")
new_lines.append("            )\n")
new_lines.append("            \n")
new_lines.append("            # THEORY: Total Expected Cost per Unit Time (CPUT)\n")
new_lines.append("            # Reference: Maintenance Optimization Models (Age/Block Replacement)\n")
new_lines.append("            # C(T) = [Total Preventive Cost + Total Expected Corrective Cost(T)] / T\n")
new_lines.append("            \n")
new_lines.append("            # 1. Total Expected Corrective Cost until month_index (Expected number of failures * cost per failure)\n")
new_lines.append("            # In NHPP model, Expected Failures E[N(T)] = Cumulative Failures\n")
new_lines.append("            total_expected_failure_cost = failure_counts[i] * (failure_replacement_cost + monthly_risk_cost_per_failure)\n")
new_lines.append("            \n")
new_lines.append("            # 2. Total Preventive Cost (One-time cost at month_index)\n")
new_lines.append("            # Includes labor, materials, and procurement delays\n")
new_lines.append("            procurement_cost = sparepart_analysis['total_procurement_cost']\n")
new_lines.append("            total_preventive_cost = preventive_cost + procurement_cost\n")
new_lines.append("            \n")
new_lines.append("            # 3. Expected Total Cycle Cost\n")
new_lines.append("            total_cycle_cost = total_expected_failure_cost + total_preventive_cost\n")
new_lines.append("            \n")
new_lines.append("            # 4. Expected Cost Per Unit Time (Optimization Target)\n")
new_lines.append("            # This value forms the U-shaped curve\n")
new_lines.append("            cput = total_cycle_cost / month_index\n")
new_lines.append("            \n")
new_lines.append("            # Store both absolute and amortized components for visualization\n")
new_lines.append("            results.append({\n")
new_lines.append("                'month': month_index,\n")
new_lines.append("                'number_of_failures': failure_counts[i],\n")
new_lines.append("                'is_actual': failures_prediction[months[i]].get('source') == 'actual',\n")
new_lines.append("                \n")
new_lines.append("                # Amortized components (for the \"U\" chart)\n")
new_lines.append("                'failure_cost': total_expected_failure_cost / month_index,\n")
new_lines.append("                'preventive_cost': preventive_cost / month_index,\n")
new_lines.append("                'procurement_cost': procurement_cost / month_index,\n")
new_lines.append("                'total_cost': cput,\n")
new_lines.append("                \n")
new_lines.append("                # Absolute values (for breakdown analysis)\n")
new_lines.append("                'absolute_failure_cost': total_expected_failure_cost,\n")
new_lines.append("                'absolute_overhaul_cost': preventive_cost,\n")
new_lines.append("                'absolute_procurement_cost': procurement_cost,\n")
new_lines.append("                'total_cycle_cost': total_cycle_cost,\n")
new_lines.append("\n")
new_lines.append("                'is_after_planned_oh': month_index > self.planned_oh_months,\n")
new_lines.append("                'delay_months': max(0, month_index - self.planned_oh_months),\n")
new_lines.append("                'procurement_details': sparepart_analysis,\n")
new_lines.append("                'sparepart_available': sparepart_analysis['available'],\n")
new_lines.append("                'sparepart_status': sparepart_analysis['message'],\n")
new_lines.append("                'can_proceed': sparepart_analysis['can_proceed_with_delays']\n")
new_lines.append("            })\n")
new_lines.append("        \n")
new_lines.append("        return results\n")
new_lines.append("\n")
new_lines.append("    def _analyze_sparepart_availability(self, equipment_tag: str, target_month: int, \n")
new_lines.append("                                      planned_overhauls: List) -> Dict:\n")
new_lines.append("        \"\"\"Analyze sparepart availability for equipment at target month\"\"\"\n")
new_lines.append("        if not self.sparepart_manager:\n")
new_lines.append("            return {\n")
new_lines.append("                'available': True,\n")
new_lines.append("                'message': 'Sparepart manager not initialized',\n")
new_lines.append("                'total_procurement_cost': 0,\n")
new_lines.append("                'procurement_needed': [],\n")
new_lines.append("                'can_proceed_with_delays': True\n")
new_lines.append("            }\n")
new_lines.append("        \n")
new_lines.append("        # Convert planned overhauls to format expected by sparepart manager\n")
new_lines.append("        other_overhauls = [(eq_tag, month) for eq_tag, month in planned_overhauls\n")
new_lines.append("                          if eq_tag != equipment_tag and month <= target_month]\n")
new_lines.append("\n")
new_lines.append("        return self.sparepart_manager.check_sparepart_availability(\n")
new_lines.append("            equipment_tag, target_month, other_overhauls\n")
new_lines.append("        )\n")
new_lines.append("\n")

new_lines.extend(lines[159:])

with open('/home/atra/Development/be-optimumoh/src/calculation_time_constrains/service.py', 'w') as f:
    f.writelines(new_lines)