undo add test.py

backend/test.py

@@ -1,111 +0,0 @@
-import numpy as np
-
-def euclidean_distance(p1, p2):
-    print(p1, p2)
-    return np.sqrt((p1[0] - p2[0])**2 + (p1[1] - p2[1])**2)
-
-
-def maximize_score(places, max_distance, fixed_entry, top_k=3):
-    """
-    Maximizes the total score of visited places while staying below the maximum distance.
-    
-    Parameters:
-    places (list of tuples): Each tuple contains (score, (x, y), location).
-    max_distance (float): The maximum distance that can be traveled.
-    fixed_entry (tuple): The place that needs to be visited independently of its score.
-    top_k (int): Number of top candidates to consider in each iteration.
-    
-    Returns:
-    list of tuples: The visited places.
-    float: The total score of the visited places.
-    """
-    # Initialize total distance and score
-    total_distance = 0
-    total_score = 0
-    visited_places = []
-
-    # Add the fixed entry to the visited list
-    score, (x, y), _ = fixed_entry
-    visited_places.append(fixed_entry)
-    total_score += score
-
-    # Remove the fixed entry from the list of places
-    remaining_places = [place for place in places if place != fixed_entry]
-
-    # Sort remaining places by score-to-distance ratio
-    
-    remaining_places.sort(key=lambda p: p[0] / euclidean_distance((x, y), (p[1][0], p[1][1])), reverse=True)
-
-    # Add places to the visited list if they don't exceed the maximum distance
-    current_location = (x, y)
-    while remaining_places and total_distance < max_distance:
-        # Consider top_k candidates
-        candidates = remaining_places[:top_k]
-        best_candidate = None
-        best_score_increase = -np.inf
-
-        for candidate in candidates:
-            score, (cx, cy), location = candidate
-            distance = euclidean_distance(current_location, (cx, cy))
-            if total_distance + distance <= max_distance:
-                score_increase = score / distance
-                if score_increase > best_score_increase:
-                    best_score_increase = score_increase
-                    best_candidate = candidate
-
-        if best_candidate:
-            visited_places.append(best_candidate)
-            total_distance += euclidean_distance(current_location, best_candidate[1])
-            total_score += best_candidate[0]
-            current_location = best_candidate[1]
-            remaining_places.remove(best_candidate)
-        else:
-            break
-
-    return visited_places, total_score
-
-# Example usage
-places = [
-    (10, (0, 0), 'A'),
-    (8, (4, 2), 'B'),
-    (15, (6, 4), 'C'),
-    (7, (5, 6), 'D'),
-    (12, (1, 8), 'E'),
-    (14, (34, 10), 'F'),
-    (15, (65, 12), 'G'),
-    (12, (3, 14), 'H'),
-    (12, (15, 1), 'I'),
-    (7, (17, 4), 'J'),
-    (12, (3, 3), 'K'),
-    (4, (21, 22), 'L'),
-    (12, (23, 24), 'M'),
-    (4, (25, 26), 'N'),
-    (2, (27, 28), 'O'),
-]
-fixed_entry = (10, (0, 0), 'A')
-max_distance = 50
-
-visited_places, total_score = maximize_score(places, max_distance, fixed_entry)
-print("Visited Places:", visited_places)
-print("Total Score:", total_score)
-
-import matplotlib.pyplot as plt
-
-# Plot the route
-def plot_route(visited_places):
-    x_coords = [place[1][0] for place in visited_places]
-    y_coords = [place[1][1] for place in visited_places]
-    labels = [place[2] for place in visited_places]
-
-    plt.figure(figsize=(10, 6))
-    plt.plot(x_coords, y_coords, marker='o', linestyle='-', color='b')
-    for i, label in enumerate(labels):
-        plt.text(x_coords[i], y_coords[i], label, fontsize=12, ha='right')
-
-    plt.title('Route of Visited Places')
-    plt.xlabel('X Coordinate')
-    plt.ylabel('Y Coordinate')
-    plt.grid(True)
-    plt.savefig('route.png')
-
-plot_route(visited_places)