style corrections, documentation, duplicate removal, flow improvement

backend/src/tester.py

@@ -1,17 +1,19 @@
 import pandas as pd
-
-from typing import List
-from landmarks_manager import LandmarkManager
+import logging
 from fastapi.encoders import jsonable_encoder
 
-from optimizer import Optimizer
-from refiner import Refiner
-from structs.landmarks import Landmark
+from utils.landmarks_manager import LandmarkManager
+from utils.optimizer import Optimizer
+from utils.refiner import Refiner
+from structs.landmark import Landmark
+from structs.linked_landmarks import LinkedLandmarks
 from structs.preferences import Preferences, Preference
 
 
+logger = logging.getLogger(__name__)
+
 # Helper function to create a .txt file with results
-def write_data(L: List[Landmark], file_name: str): 
+def write_data(L: list[Landmark], file_name: str): 
 
     data = pd.DataFrame()
     i = 0
@@ -23,8 +25,10 @@ def write_data(L: List[Landmark], file_name: str):
     data.to_json(file_name, indent = 2, force_ascii=False)
 
 
-def test(start_coords: tuple[float, float], finish_coords: tuple[float, float] = None) -> List[Landmark]:
+def test(start_coords: tuple[float, float], finish_coords: tuple[float, float] = None) -> list[Landmark]:
     manager = LandmarkManager()
+    optimizer = Optimizer()
+    refiner = Refiner(optimizer=optimizer)
 
     
     preferences = Preferences(
@@ -42,7 +46,7 @@ def test(start_coords: tuple[float, float], finish_coords: tuple[float, float] =
                                   score = 5),
 
                     max_time_minute=180,
-                    detour_tolerance_minute=0
+                    detour_tolerance_minute=30
                     )
 
     # Create start and finish 
@@ -71,15 +75,15 @@ def test(start_coords: tuple[float, float], finish_coords: tuple[float, float] =
     landmarks_short.append(finish)
 
     # First stage optimization
-    optimizer = Optimizer(max_time=preferences.max_time_minute, landmarks=landmarks_short)
-    base_tour = optimizer.solve_optimization()
+    base_tour = optimizer.solve_optimization(max_time=preferences.max_time_minute, landmarks=landmarks_short)
 
     # Second stage using linear optimization
-    refiner = Refiner(max_time = preferences.max_time_minute, detour = preferences.detour_tolerance_minute)
-    refined_tour = refiner.refine_optimization(all_landmarks=landmarks, base_tour=base_tour)
+    refined_tour = refiner.refine_optimization(all_landmarks=landmarks, base_tour=base_tour, max_time = preferences.max_time_minute, detour = preferences.detour_tolerance_minute)
 
+    linked_tour = LinkedLandmarks(refined_tour)
+    logger.info(f"Optimized route: {linked_tour}")
 
-    return refined_tour
+    return linked_tour
 
 
 #test(tuple((48.8344400, 2.3220540)))       # Café Chez César