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cleaned up backend to use classes and yaml files

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This commit is contained in:
Helldragon67
2024-07-20 23:16:35 +02:00
parent 14a7f555df
commit 94fa735d54
9 changed files with 1300 additions and 935 deletions
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55
backend/src/tester.py
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@@ -4,10 +4,9 @@ from typing import List
from landmarks_manager import LandmarkManager
from fastapi.encoders import jsonable_encoder
from optimizer_v4 import solve_optimization
from refiner import refine_optimization
from optimizer import Optimizer
from refiner import Refiner
from structs.landmarks import Landmark
from structs.landmarktype import LandmarkType
from structs.preferences import Preferences, Preference
@@ -24,58 +23,66 @@ def write_data(L: List[Landmark], file_name: str):
data.to_json(file_name, indent = 2, force_ascii=False)
def test4(coordinates: tuple[float, float]) -> List[Landmark]:
def test(start_coords: tuple[float, float], finish_coords: tuple[float, float] = None) -> List[Landmark]:
manager = LandmarkManager()
preferences = Preferences(
sightseeing=Preference(
name='sightseeing',
type=LandmarkType(landmark_type='sightseeing'),
type='sightseeing',
score = 5),
nature=Preference(
name='nature',
type=LandmarkType(landmark_type='nature'),
type='nature',
score = 0),
shopping=Preference(
name='shopping',
type=LandmarkType(landmark_type='shopping'),
score = 0))
type='shopping',
score = 0),
max_time_minute=180,
detour_tolerance_minute=0
)
# Create start and finish
start = Landmark(name='start', type=LandmarkType(landmark_type='start'), location=coordinates, osm_type='start', osm_id=0, attractiveness=0, must_do=False, n_tags = 0)
finish = Landmark(name='finish', type=LandmarkType(landmark_type='finish'), location=coordinates, osm_type='finish', osm_id=0, attractiveness=0, must_do=False, n_tags = 0)
if finish_coords is None :
finish_coords = start_coords
start = Landmark(name='start', type='start', location=start_coords, osm_type='', osm_id=0, attractiveness=0, n_tags = 0)
finish = Landmark(name='finish', type='start', location=finish_coords, osm_type='', osm_id=0, attractiveness=0, n_tags = 0)
#finish = Landmark(name='finish', type=LandmarkType(landmark_type='finish'), location=(48.8777055, 2.3640967), osm_type='finish', osm_id=0, attractiveness=0, must_do=True, n_tags = 0)
#start = Landmark(name='start', type=LandmarkType(landmark_type='start'), location=(48.847132, 2.312359), osm_type='start', osm_id=0, attractiveness=0, must_do=True, n_tags = 0)
#finish = Landmark(name='finish', type=LandmarkType(landmark_type='finish'), location=(48.843185, 2.344533), osm_type='finish', osm_id=0, attractiveness=0, must_do=True, n_tags = 0)
#finish = Landmark(name='finish', type=LandmarkType(landmark_type='finish'), location=(48.847132, 2.312359), osm_type='finish', osm_id=0, attractiveness=0, must_do=True, n_tags = 0)
manager = LandmarkManager(preferences=preferences, coordinates=start_coords)
# Generate the landmarks from the start location
landmarks, landmarks_short = generate_landmarks(preferences=preferences, coordinates=start.location)
landmarks, landmarks_short = manager.generate_landmarks_list()
# Store data to file for debug purposes
#write_data(landmarks, "landmarks_Wien.txt")
# Insert start and finish to the landmarks list
landmarks_short.insert(0, start)
landmarks_short.append(finish)
max_walking_time = 180 # minutes
detour = 0 # minutes
# First stage optimization
base_tour = solve_optimization(landmarks_short, max_walking_time, True)
optimizer = Optimizer(max_time=preferences.max_time_minute, landmarks=landmarks_short)
base_tour = optimizer.solve_optimization()
# Second stage using linear optimization
refined_tour = refine_optimization(landmarks, base_tour, max_walking_time, detour, True)
refiner = Refiner(max_time = preferences.max_time_minute, detour = preferences.detour_tolerance_minute, all_landmarks=landmarks, base_tour=base_tour)
refined_tour = refiner.refine_optimization()
return refined_tour
#test4(tuple((48.8344400, 2.3220540))) # Café Chez César
#test4(tuple((48.8375946, 2.2949904))) # Point random
#test4(tuple((47.377859, 8.540585))) # Zurich HB
#test4(tuple((45.7576485, 4.8330241))) # Lyon Bellecour
test4(tuple((48.5848435, 7.7332974))) # Strasbourg Gare
#test4(tuple((48.2067858, 16.3692340))) # Vienne
#test(tuple((48.8344400, 2.3220540))) # Café Chez César
#test(tuple((48.8375946, 2.2949904))) # Point random
#test(tuple((47.377859, 8.540585))) # Zurich HB
#test(tuple((45.7576485, 4.8330241))) # Lyon Bellecour
test(tuple((48.5848435, 7.7332974))) # Strasbourg Gare
#test(tuple((48.2067858, 16.3692340))) # Vienne