diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..9ddf6b2 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,3 @@ +{ + "cmake.ignoreCMakeListsMissing": true +} \ No newline at end of file diff --git a/backend/README.md b/backend/README.md index 1def675..7c30ebb 100644 --- a/backend/README.md +++ b/backend/README.md @@ -1,12 +1,37 @@ # Backend -This repository contains the backend code for the application. It utilizes FastAPI that allows to quickly create a RESTful API that exposes the endpoints of the route optimizer. - +This repository contains the backend code for the application. It utilizes **FastAPI** to quickly create a RESTful API that exposes the endpoints of the route optimizer. ## Getting Started -- The code of the python application is located in the `src` directory. -- Package management is handled with `pipenv` and the dependencies are listed in the `Pipfile`. -- Since the application is aimed to be deployed in a container, the `Dockerfile` is provided to build the image. + +### Directory Structure +- The code for the Python application is located in the `src` directory. +- Package management is handled with **pipenv**, and the dependencies are listed in the `Pipfile`. +- Since the application is designed to be deployed in a container, the `Dockerfile` is provided to build the image. + +### Setting Up the Development Environment + +To set up your development environment using **pipenv**, follow these steps: + +1. Install `pipenv` by running: + ```bash + sudo apt install pipenv + ``` + +2. Create and activate a virtual environment: + ```bash + pipenv shell + ``` + +3. Install the dependencies listed in the `Pipfile`: + ```bash + pipenv install + ``` + +4. The virtual environment will be created under: + ```bash + ~/.local/share/virtualenvs/... + ``` ### Deployment To deploy the backend docker container, we use kubernetes. Modifications to the backend are automatically pushed to a two-stage environment through the CI pipeline. See [deployment/README](deployment/README.md] for further information. diff --git a/backend/src/parameters/amenity_selectors.yaml b/backend/src/parameters/amenity_selectors.yaml index 87b4b42..7d0fabc 100644 --- a/backend/src/parameters/amenity_selectors.yaml +++ b/backend/src/parameters/amenity_selectors.yaml @@ -45,7 +45,6 @@ sightseeing: - gallery - artwork - aquarium - historic: '' amenity: - planetarium diff --git a/backend/src/tester.py b/backend/src/tester.py index bea9e41..31543b6 100644 --- a/backend/src/tester.py +++ b/backend/src/tester.py @@ -23,7 +23,7 @@ def test(start_coords: tuple[float, float], finish_coords: tuple[float, float] = sightseeing=Preference(type='sightseeing', score = 5), nature=Preference(type='nature', score = 5), shopping=Preference(type='shopping', score = 5), - max_time_minute=100, + max_time_minute=15, detour_tolerance_minute=0 ) @@ -74,6 +74,7 @@ def test(start_coords: tuple[float, float], finish_coords: tuple[float, float] = # 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((45.758217, 4.831814))) # Lyon Bellecour -test(tuple((48.5848435, 7.7332974))) # Strasbourg Gare +# test(tuple((45.758217, 4.831814))) # Lyon Bellecour +# test(tuple((48.5848435, 7.7332974))) # Strasbourg Gare # test(tuple((48.2067858, 16.3692340))) # Vienne +test(tuple((48.084588, 7.280405))) # Turckheim diff --git a/backend/src/utils/landmarks_manager.py b/backend/src/utils/landmarks_manager.py index 68dcb2e..f205132 100644 --- a/backend/src/utils/landmarks_manager.py +++ b/backend/src/utils/landmarks_manager.py @@ -94,6 +94,8 @@ class LandmarkManager: if preferences.shopping.score != 0: score_function = lambda score: score * 10 * preferences.shopping.score / 5 current_landmarks = self.fetch_landmarks(bbox, self.amenity_selectors['shopping'], preferences.shopping.type, score_function) + # set time for all shopping activites : + for landmark in current_landmarks : landmark.duration = 45 all_landmarks.update(current_landmarks) @@ -246,11 +248,11 @@ class LandmarkManager: image_url = None name_en = None - # remove specific tags + # Adjust scoring skip = False for tag in elem.tags().keys(): if "pay" in tag: - # payment options are a good sign + # payment options are misleading and should not count for the scoring. score += self.pay_bonus if "disused" in tag: @@ -263,10 +265,12 @@ class LandmarkManager: score += self.wikipedia_bonus if "viewpoint" in tag: + # viewpoints must count more score += self.viewpoint_bonus duration = 10 if "image" in tag: + # images must count more score += self.image_bonus if elem_type != "nature": @@ -282,6 +286,7 @@ class LandmarkManager: skip = True break + # Extract image, website and english name if tag in ['website', 'contact:website']: website_url = elem.tag(tag) if tag == 'image': @@ -295,10 +300,9 @@ class LandmarkManager: score = score_function(score) if "place_of_worship" in elem.tags().values(): score = score * self.church_coeff - duration = 15 + duration = 10 - elif "museum" in elem.tags().values(): - score = score * self.church_coeff + elif "museum" in elem.tags().values() or "aquarium" in elem.tags().values() or "planetarium" in elem.tags().values(): duration = 60 else: diff --git a/backend/src/utils/optimizer.py b/backend/src/utils/optimizer.py index 93ea448..c627c40 100644 --- a/backend/src/utils/optimizer.py +++ b/backend/src/utils/optimizer.py @@ -487,7 +487,7 @@ class Optimizer: # Raise error if no solution is found if not res.success : - raise ArithmeticError("No solution could be found, the problem is overconstrained. Please adapt your must_dos") + raise ArithmeticError("No solution could be found, the problem is overconstrained. Try with a longer trip (>30 minutes).") # If there is a solution, we're good to go, just check for connectiveness order, circles = self.is_connected(res.x) diff --git a/backend/src/utils/refiner.py b/backend/src/utils/refiner.py index 626bf4d..001936e 100644 --- a/backend/src/utils/refiner.py +++ b/backend/src/utils/refiner.py @@ -2,6 +2,7 @@ import yaml, logging from shapely import buffer, LineString, Point, Polygon, MultiPoint, concave_hull from math import pi +from typing import List from structs.landmark import Landmark from . import take_most_important, get_time_separation @@ -133,6 +134,21 @@ class Refiner : i += 1 return tour + + def integrate_landmarks(self, sub_list: List[Landmark], main_list: List[Landmark]) : + """ + Inserts 'sub_list' of Landmarks inside the 'main_list' by leaving the ends untouched. + + Args: + sub_list : the list of Landmarks to be inserted inside of the 'main_list'. + main_list : the original list with start and finish. + + Returns: + the full list. + """ + sub_list.append(main_list[-1]) # add finish back + return main_list[:-1] + sub_list # create full set of possible landmarks + def find_shortest_path_through_all_landmarks(self, landmarks: list[Landmark]) -> tuple[list[Landmark], Polygon]: @@ -253,6 +269,11 @@ class Refiner : except : better_tour_poly = concave_hull(MultiPoint(coords)) # Create concave hull with "core" of tour leaving out start and finish xs, ys = better_tour_poly.exterior.xy + """ + ERROR HERE : + Exception has occurred: AttributeError + 'LineString' object has no attribute 'exterior' + """ # reverse the xs and ys @@ -315,26 +336,30 @@ class Refiner : self.logger.info(f"Using {len(minor_landmarks)} minor landmarks around the predicted path") - # full set of visitable landmarks - full_set = base_tour[:-1] + minor_landmarks # create full set of possible landmarks (without finish) - full_set.append(base_tour[-1]) # add finish back + # Full set of visitable landmarks. + full_set = self.integrate_landmarks(minor_landmarks, base_tour) # could probably be optimized with less overhead - # get a new tour + # Generate a new tour with the optimizer. new_tour = self.optimizer.solve_optimization( max_time = max_time + detour, landmarks = full_set, max_landmarks = self.max_landmarks_refiner ) + # If unsuccessful optimization, use the base_tour. if new_tour is None: self.logger.warning("No solution found for the refined tour. Returning the initial tour.") new_tour = base_tour + # If only one landmark, return it. + if len(new_tour) < 4 : + return new_tour - # Find shortest path using the nearest neighbor heuristic + # Find shortest path using the nearest neighbor heuristic. better_tour, better_poly = self.find_shortest_path_through_all_landmarks(new_tour) - # Fix the tour using Polygons if the path looks weird + # Fix the tour using Polygons if the path looks weird. + # Conditions : circular trip and invalid polygon. if base_tour[0].location == base_tour[-1].location and not better_poly.is_valid : better_tour = self.fix_using_polygon(better_tour)