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route.py

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+import math
+import itertools
+import requests
+from typing import List, Tuple, Dict, Optional, Set
+
+class Point:
+    def __init__(self, coord: List[float], tag: str, visit_time: int):
+        self.coord = coord
+        self.tag = tag
+        self.visit_time = visit_time
+        self.matrix_index = None  # Индекс точки в матрице расстояний
+        self.estimated_time = None  # Оценочное время (перемещение + посещение)
+
+def haversine(coord1: List[float], coord2: List[float]) -> float:
+    """Calculate the great-circle distance between two points in kilometers."""
+    lat1, lon1 = coord1
+    lat2, lon2 = coord2
+    R = 6371  # Earth radius in km
+    
+    dlat = math.radians(lat2 - lat1)
+    dlon = math.radians(lon2 - lon1)
+    a = (math.sin(dlat/2) * math.sin(dlat/2) + 
+         math.cos(math.radians(lat1)) * math.cos(math.radians(lat2)) * 
+         math.sin(dlon/2) * math.sin(dlon/2))
+    return R * 2 * math.atan2(math.sqrt(a), math.sqrt(1 - a))
+
+def filter_points_by_time(start_coord: List[float], points: List[Point], total_time: int) -> List[Point]:
+    """Filter points based on straight-line distance and visit time."""
+    filtered = []
+    for point in points:
+        distance = haversine(start_coord, point.coord)
+        travel_time = distance * 10  # Assume 6 km/h walking speed (10 min/km)
+        point.estimated_time = travel_time + point.visit_time
+        if point.estimated_time <= total_time:
+            filtered.append(point)
+    return filtered
+
+def filter_points_by_tag_proximity(points: List[Point], max_per_tag: int = 10) -> List[Point]:
+    """For each tag, keep only the closest points (by estimated time)."""
+    # Group points by tag
+    tag_to_points = {}
+    for point in points:
+        if point.tag not in tag_to_points:
+            tag_to_points[point.tag] = []
+        tag_to_points[point.tag].append(point)
+    
+    # For each tag, sort by estimated time and keep top max_per_tag
+    filtered_points = []
+    for tag, tag_points in tag_to_points.items():
+        # Sort by estimated time (ascending)
+        sorted_points = sorted(tag_points, key=lambda p: p.estimated_time)
+        # Keep at most max_per_tag points
+        kept_points = sorted_points[:max_per_tag]
+        filtered_points.extend(kept_points)
+        print(f"Tag '{tag}': kept {len(kept_points)} out of {len(tag_points)} points")
+    
+    return filtered_points
+
+def get_duration_matrix(points: List[List[float]]) -> Optional[Tuple[List[List[float]], List[List[float]]]]:
+    """Get duration matrix from server."""
+    url = "https://ha1m-maap-pdmc.gw-1a.dockhost.net/table"
+    payload = {"points": points}
+    headers = {"content-type": "application/json"}
+    
+    try:
+        response = requests.post(url, json=payload, headers=headers, timeout=30)
+        if response.status_code == 200:
+            data = response.json()
+            return data.get("distances"), data.get("durations")
+        else:
+            print(f"Server error: {response.status_code}")
+            return None
+    except Exception as e:
+        print(f"Error requesting duration matrix: {e}")
+        return None
+
+def group_points_by_significance(points: List[Point], tag_importance: Dict[str, int]) -> Dict[int, List[Point]]:
+    """Group points by their importance level."""
+    grouped = {}
+    for point in points:
+        importance = tag_importance.get(point.tag, float('inf'))
+        if importance not in grouped:
+            grouped[importance] = []
+        grouped[importance].append(point)
+    return grouped
+
+def calculate_route_time_with_matrix(route: List[Point], start_coord: List[float], 
+                                   duration_matrix: List[List[float]]) -> float:
+    """Calculate total time for a route using the duration matrix."""
+    total_time = 0
+    current_index = 0  # Start point index
+    
+    for point in route:
+        next_index = point.matrix_index
+        travel_time_seconds = duration_matrix[current_index][next_index]
+        travel_time_minutes = travel_time_seconds / 60.0
+        total_time += travel_time_minutes + point.visit_time
+        current_index = next_index
+    
+    return total_time
+
+def check_tags_constraint(points: List[Point]) -> bool:
+    """Check if there are no more than 5 unique tags."""
+    unique_tags = set(point.tag for point in points)
+    return len(unique_tags) <= 5
+
+def generate_routes_exact_tags(grouped_points: Dict[int, List[Point]], 
+                              all_tags: Set[str],
+                              tag_importance: Dict[str, int]) -> List[List[Point]]:
+    """Generate routes where each tag is visited exactly once using different coordinates."""
+    # Create a mapping from tag to points
+    tag_to_points = {}
+    for points_list in grouped_points.values():
+        for point in points_list:
+            if point.tag not in tag_to_points:
+                tag_to_points[point.tag] = []
+            tag_to_points[point.tag].append(point)
+    
+    # For each tag, we need to select exactly one point
+    tag_selections = []
+    for tag in all_tags:
+        tag_selections.append(tag_to_points[tag])
+    
+    # Generate all combinations of points (one per tag)
+    all_routes = []
+    print(len(list(itertools.product(*tag_selections))))
+    for point_combination in itertools.product(*tag_selections):
+
+        # Check if all points have unique coordinates
+        coords = [tuple(point.coord) for point in point_combination]
+        if len(coords) != len(set(coords)):
+            continue  # Skip if any coordinates are duplicated
+        
+        # Group points by importance
+        points_by_importance = {}
+        for point in point_combination:
+            imp = tag_importance[point.tag]
+            if imp not in points_by_importance:
+                points_by_importance[imp] = []
+            points_by_importance[imp].append(point)
+        
+        # Sort by importance
+        sorted_importances = sorted(points_by_importance.keys())
+        
+        # Generate all permutations within each importance group
+        importance_groups = [points_by_importance[imp] for imp in sorted_importances]
+        
+        for ordering in itertools.product(*[itertools.permutations(group) for group in importance_groups]):
+            route = []
+            for group in ordering:
+                route.extend(group)
+            all_routes.append(route)
+    
+    return all_routes
+
+def generate_routes_with_repeats(grouped_points: Dict[int, List[Point]], 
+                                all_tags: Set[str],
+                                tag_importance: Dict[str, int],
+                                num_points: int) -> List[List[Point]]:
+    """Generate routes when we need to repeat tags to reach the required number of points, ensuring unique coordinates."""
+    # Create a mapping from tag to points
+    tag_to_points = {}
+    for points_list in grouped_points.values():
+        for point in points_list:
+            if point.tag not in tag_to_points:
+                tag_to_points[point.tag] = []
+            tag_to_points[point.tag].append(point)
+    
+    all_routes = []
+    
+    # First, select one point for each tag (mandatory points)
+    mandatory_selections = [tag_to_points[tag] for tag in all_tags]
+    
+    # Generate all combinations of mandatory points (one per tag)
+    for mandatory_combo in itertools.product(*mandatory_selections):
+        mandatory_points = list(mandatory_combo)
+        
+        # Check if mandatory points have unique coordinates
+        mandatory_coords = [tuple(point.coord) for point in mandatory_points]
+        if len(mandatory_coords) != len(set(mandatory_coords)):
+            continue  # Skip if any coordinates are duplicated in mandatory points
+        
+        # We need to add (num_points - len(mandatory_points)) additional points
+        num_additional = num_points - len(mandatory_points)
+        
+        if num_additional == 0:
+            # We have exactly the right number of points
+            points_by_importance = {}
+            for point in mandatory_points:
+                imp = tag_importance[point.tag]
+                if imp not in points_by_importance:
+                    points_by_importance[imp] = []
+                points_by_importance[imp].append(point)
+            
+            sorted_importances = sorted(points_by_importance.keys())
+            importance_groups = [points_by_importance[imp] for imp in sorted_importances]
+            
+            for ordering in itertools.product(*[itertools.permutations(group) for group in importance_groups]):
+                route = []
+                for group in ordering:
+                    route.extend(group)
+                all_routes.append(route)
+        else:
+            # We need to add additional points (can be from any tag, including repeats)
+            # But we must ensure all coordinates are unique
+            
+            # Get all available points excluding mandatory points
+            all_available_points = []
+            for points_list in grouped_points.values():
+                all_available_points.extend(points_list)
+            
+            # Remove mandatory points from available points
+            available_points = [p for p in all_available_points if p not in mandatory_points]
+            
+            # Generate combinations of additional points
+            for additional_combo in itertools.combinations(available_points, num_additional):
+                # Check if additional points have unique coordinates and don't duplicate with mandatory
+                additional_coords = [tuple(point.coord) for point in additional_combo]
+                if len(additional_coords) != len(set(additional_coords)):
+                    continue  # Skip if any coordinates are duplicated in additional points
+                
+                # Check if additional points don't duplicate with mandatory points
+                all_coords = mandatory_coords + additional_coords
+                if len(all_coords) != len(set(all_coords)):
+                    continue  # Skip if any coordinates are duplicated between mandatory and additional
+                
+                full_route_candidate = mandatory_points + list(additional_combo)
+                
+                # Group by importance
+                points_by_importance = {}
+                for point in full_route_candidate:
+                    imp = tag_importance[point.tag]
+                    if imp not in points_by_importance:
+                        points_by_importance[imp] = []
+                    points_by_importance[imp].append(point)
+                
+                sorted_importances = sorted(points_by_importance.keys())
+                importance_groups = [points_by_importance[imp] for imp in sorted_importances]
+                
+                for ordering in itertools.product(*[itertools.permutations(group) for group in importance_groups]):
+                    route = []
+                    for group in ordering:
+                        route.extend(group)
+                    all_routes.append(route)
+    
+    return all_routes
+
+def form_point_list(data):
+    point_list =[]
+    for entry in data:
+        point = Point(list(map(float,entry['coordinate'].split(', '))),entry['type'],entry['time_to_visit'])
+        point_list.append(point)
+    return point_list
+
+def build_route(data, mapping,start_coord,total_time,n_nodes):
+    # Example input data - теперь с не более чем 5 уникальными тегами
+
+    start_coord_test = [56.331576, 44.003277]
+    total_time_test = 180  # Увеличим время до 4 часов для большего выбора
+    points = form_point_list(data)
+    tag_importance =mapping
+    # Используем 3 уникальных тега для демонстрации
+    points_test = [
+        Point([56.32448, 43.983546], "Памятник", 20),
+        Point([56.335607, 43.97481], "Архитектура", 20),
+        Point([56.313472, 43.990747], "Памятник", 20),
+        #Point([56.324157, 44.002696], "Памятник", 20),
+        #Point([56.316436, 43.994177], "Памятник", 20),
+        #Point([56.32377, 44.001879], "Памятник", 20),
+        #Point([56.329867, 43.99687], "Памятник", 20),
+        Point([56.311066, 43.94595], "Памятник", 20),
+        Point([56.333265, 43.972417], "Памятник", 20),
+       # Point([56.332166, 44.012111], "Памятник", 20),
+        #Point([56.326786, 44.006836], "Памятник", 20),
+        Point([56.330232, 44.010941], "Парк", 20),
+        Point([56.282221, 43.979263], "Парк", 20),
+        Point([56.277315, 43.921408], "Мозаика", 20),
+        Point([56.284829, 44.01893], "Парк", 20),
+        Point([56.308973, 43.99821], "Парк", 20),
+        Point([56.321545, 44.001921], "Парк", 20),
+        #Point([56.301798, 44.044003], "Мозаика", 20),
+        Point([56.268282, 43.919475], "Парк", 20),
+        Point([56.239625, 43.854551], "Парк", 20),
+        #Point([56.311214, 43.933981], "Парк", 20),
+        Point([56.314984, 44.007347], "Парк", 20),
+        Point([56.32509, 43.983433], "Парк", 20),
+        Point([56.27449, 43.973357], "Парк", 20),
+        Point([56.278073, 43.940886], "Парк", 20),
+        Point([56.358805, 43.825376], "Парк", 20),
+        Point([56.329995, 44.009444], "Памятник", 20),
+        Point([56.328551, 43.998718], "Памятник", 20),
+        Point([56.330355, 43.993105], "Архитектура", 20),
+        Point([56.321416, 43.973897], "Архитектура", 20),
+       # Point([56.327298, 44.005706], "Архитектура", 20),
+        #Point([56.328757, 43.998183], "Архитектура", 20),
+       # Point([56.328908, 43.995645], "Архитектура", 20),
+        Point([56.317578, 43.995805], "Архитектура", 20),
+        Point([56.329433, 44.012764], "Архитектура", 20),
+        Point([56.3301, 44.008831], "Архитектура", 20),
+        #Point([56.32995, 43.999495], "Архитектура", 20),
+        Point([56.327454, 44.041745], "Архитектура", 20),
+        #Point([56.328576, 44.004872], "Архитектура", 20),
+        Point([56.3275, 44.007658], "Архитектура", 20),
+        Point([56.330679, 44.013874], "Архитектура", 20),
+       # Point([56.331541, 44.001747], "Архитектура", 20),
+       # Point([56.335071, 43.974627], "Архитектура", 20),
+        #Point([56.317707, 43.995847], "Архитектура", 20),
+        #Point([56.323851, 43.985939], "Архитектура", 20),
+        Point([56.325701, 44.001527], "Архитектура", 20),
+        Point([56.328754, 43.998954], "Архитектура", 20),
+        #Point([56.323937, 43.990728], "Музей", 20),
+        #Point([56.2841, 43.84621], "Музей", 20),
+        #Point([56.328646, 44.028973], "Музей", 20),
+        Point([56.327391, 43.857522], "Мозаика", 20),
+        #Point([56.252239, 43.889066], "Мозаика", 20),
+        #Point([56.248436, 43.88106], "Мозаика", 20),
+        #Point([56.321257, 43.94545], "Мозаика", 20),
+       # Point([56.365284, 43.823251], "Мозаика", 20),
+        Point([56.294371, 43.912625], "Мозаика", 20),
+        #Point([56.241768, 43.859687], "Мозаика", 20),
+        #Point([56.300073, 43.938526], "Мозаика", 20),
+        #Point([56.229652, 43.947973], "Мозаика", 20),
+       # Point([56.269486, 43.9238], "Мозаика", 20),
+        Point([56.299251, 43.985146], "Мозаика", 20),
+        Point([56.293297, 44.034095], "Мозаика", 20),
+        Point([56.299251, 43.985146], "Мозаика", 20),
+        Point([56.229652, 43.947973], "Мозаика", 20),
+        Point([56.269486, 43.9238], "Мозаика", 20),
+        #Point([56.293297, 44.034095], "Мозаика", 20),
+        #Point([56.229652, 43.947973], "Мозаика", 20)
+    ]
+    
+    tag_importance_test = {
+        "Памятник": 1,
+        "Парк": 1,
+        "Мозаика": 1,
+        "Архитектура": 1,
+        #"Музей": 1
+    }
+    
+    # Check tags constraint
+    if not check_tags_constraint(points):
+        print("Error: More than 5 unique tags in the input data")
+        return
+    
+    print("Input data validation: OK (5 or fewer unique tags)")
+    
+    # Step 1: Filter points using straight-line distance and total time
+    filtered_by_time = filter_points_by_time(start_coord, points, total_time)
+    print(f"After initial time filtering: {len(filtered_by_time)} points")
+    
+    if len(filtered_by_time) < 3:
+        print("Not enough points after time filtering")
+        return
+    
+    # Step 2: Filter points by tag proximity (keep max 10 closest points per tag)
+    filtered_points = filter_points_by_tag_proximity(filtered_by_time, max_per_tag=10)
+    print(f"After tag proximity filtering: {len(filtered_points)} points")
+    
+    if len(filtered_points) < 3:
+        print("Not enough points after tag proximity filtering")
+        return
+    
+    # Step 3: Prepare points for server request (start point + filtered points)
+    points_for_matrix = [start_coord] + [point.coord for point in filtered_points]
+    
+    print("Requesting duration matrix from server...")
+    # Step 4: Get duration matrix from server
+    result = get_duration_matrix(points_for_matrix)
+    if result is None:
+        print("Failed to get duration matrix from server")
+        return
+    
+    distances_matrix, durations_matrix = result
+    print("Duration matrix received successfully")
+    
+    # Assign matrix indices to points
+    for i, point in enumerate(filtered_points):
+        point.matrix_index = i + 1  # +1 because index 0 is the start point
+    
+    # Step 5: Group by importance
+    grouped_points = group_points_by_significance(filtered_points, tag_importance)
+    
+    # Get all unique tags
+    all_tags = set(point.tag for point in filtered_points)
+    num_unique_tags = len(all_tags)
+    
+    print(f"Unique tags: {all_tags} ({num_unique_tags} tags)")
+    
+    # Step 6: Generate possible routes
+    print("Generating possible routes...")
+    
+    # Determine the number of points in the route
+    if num_unique_tags >= n_nodes:
+        # Each tag must be visited exactly once
+        print("Each tag will be visited exactly once with unique coordinates")
+        possible_routes = generate_routes_exact_tags(grouped_points, all_tags, tag_importance)
+    else:
+        # We have fewer than 3 unique tags, need to repeat some tags
+        print(f"Only {num_unique_tags} unique tags available, will repeat tags to reach 3 points with unique coordinates")
+        possible_routes = generate_routes_with_repeats(grouped_points, all_tags, tag_importance, n_nodes)
+    
+    if not possible_routes:
+        print("No valid routes found that cover all tags with unique coordinates")
+        return
+    
+    # Step 7: Calculate time for each route and filter by total_time
+    valid_routes = []
+    for route in possible_routes:
+        route_time = calculate_route_time_with_matrix(route, start_coord, durations_matrix)
+        if route_time <= total_time:
+            valid_routes.append((route, route_time))
+    
+    if not valid_routes:
+        print("No valid routes found within time constraint")
+        return
+    
+    # Step 8: Find optimal route (minimum time)
+    optimal_route, min_time = min(valid_routes, key=lambda x: x[1])
+    
+    print(f"\nOptimal route (time: {min_time:.2f} min):")
+    for i, point in enumerate(optimal_route, 1):
+        print(f"{i}. {point.tag} at {point.coord} ({point.visit_time} min)")
+    
+    # Print route details with travel times
+    print("\nRoute details:")
+    current_index = 0
+    total_route_time = 0
+    for i, point in enumerate(optimal_route):
+        travel_time_seconds = durations_matrix[current_index][point.matrix_index]
+        travel_time_minutes = travel_time_seconds / 60.0
+        segment_time = travel_time_minutes + point.visit_time
+        total_route_time += segment_time
+        
+        print(f"Segment {i+1}: {travel_time_minutes:.2f} min travel + {point.visit_time} min visit = {segment_time:.2f} min")
+        current_index = point.matrix_index
+    
+    print(f"Total route time: {total_route_time:.2f} min")
+    
+    # Display all tags covered by the route
+    route_tags = set(point.tag for point in optimal_route)
+    print(f"\nTags covered in this route: {', '.join(route_tags)}")
+    if all_tags.issubset(route_tags):
+        print("All tags are covered in this route!")
+    
+    # Verify all coordinates are unique
+    route_coords = [tuple(point.coord) for point in optimal_route]
+    if len(route_coords) == len(set(route_coords)):
+        print("All coordinates in the route are unique!")
+    else:
+        print("ERROR: Duplicate coordinates found in the route!")
+
+#if __name__ == "__main__":
+  # build_route()