diff options
| -rw-r--r-- | algorithms.py | 34 | ||||
| -rw-r--r-- | server.py | 27 | ||||
| -rw-r--r-- | store.py | 13 |
3 files changed, 56 insertions, 18 deletions
diff --git a/algorithms.py b/algorithms.py index cc8d35f..6e01287 100644 --- a/algorithms.py +++ b/algorithms.py @@ -1,3 +1,4 @@ +import heapq import math @@ -23,7 +24,7 @@ def get_closest_node_id(nodes, source_node): for node_id, node in nodes.items(): length = length_haversine(source_node, node) - if min_node == None or length < min_value: + if min_node is None or length < min_value: min_node = node_id min_value = length @@ -32,4 +33,33 @@ def get_closest_node_id(nodes, source_node): def find_shortest_path(nodes, source_id, target_id): """ Return the shortest path using Dijkstra's algortihm. """ - return [] + # queue contains multiple (walk_dist, (node_0, node_1, ... node_n))-tuples + # where (node_0, node_1, ... node_n) is a walk to node_n + # and walk_dist is the total length of the walk in meters + queue = [(0, (source_id,))] + visited = set() + + while queue: + # consider an unchecked walk + walk_dist, walk = heapq.heappop(queue) + walk_end = walk[-1] + if walk_end == target_id: + # you have reached your destination + return walk + if walk_end in visited: + # there exists a shorter walk to walk_end + continue + # otherwise this is the shortest walk to walk_end + visited.add(walk_end) + # consider all our neighbours + for neighbour in nodes[walk_end].neighbours: + if neighbour in visited: + # there exists a shorter walk to neighbour + continue + # otherwise this MIGHT be the shortest walk to neighbour + # so put it in the queue + new_dist = walk_dist + length_haversine(nodes[walk_end], neighbour) + new_walk = walk + (neighbour.id,) + heapq.heappush(queue, (new_dist, new_walk)) + # no path found + return None @@ -5,29 +5,34 @@ import store from lib import run_server, get, post, read_html +nodes = None + + @get('/') def index(): + global nodes + nodes = store.extract_osm_nodes("university.osm") return read_html('templates/index.html') @get('/show-area') def show_area(): - all = dict() - for (k, node) in enumerate(store.select_nodes_in_rectangle(store.extract_osm_nodes("university.osm"), 58.3984, 58.3990, 15.5733, 15.576)): - all[node.id] = node.coord_tuple() - return json.dumps(all) + rect = dict() + for (k, node) in enumerate(store.select_nodes_in_rectangle(nodes, 58.3984, 58.3990, 15.5733, 15.576)): + rect[node.id] = node.coord_tuple() + return json.dumps(rect) @post('/shortest-path') def shortest_path(body): body = json.loads(body) - source_id = algorithms.get_closest_node_id(store.nodes, store.Node(-1, body['lat1'], body['lng1'])) - target_id = algorithms.get_closest_node_id(store.nodes, store.Node(-1, body['lat2'], body['lng2'])) - print(source_id, target_id) - source_node = store.nodes[source_id] - target_node = store.nodes[target_id] - path = [(source_node.lat, source_node.lng), (target_node.lat, target_node.lng)] - response = {'path': path} + source_id = algorithms.get_closest_node_id(nodes, store.Node(-1, body['lat1'], body['lng1'])) + target_id = algorithms.get_closest_node_id(nodes, store.Node(-1, body['lat2'], body['lng2'])) + + path = algorithms.find_shortest_path(nodes, source_id, target_id) + print(path) + response = {"path": [(nodes[node].lat, nodes[node].lng) for node in path]} + return json.dumps(response) @@ -6,7 +6,7 @@ class Node: self.id = id self.lat = float(lat) self.lng = float(lng) - self.neighbors = [] + self.neighbours = [] def coord_tuple(self): @@ -14,7 +14,6 @@ class Node: parser = None # Have a global reusable parser object -nodes = None def add_neighbours(nodes): @@ -28,15 +27,14 @@ def add_neighbours(nodes): node1 = road[i] node2 = road[i + 1] - nodes[node1].neighbors.append(nodes[node2]) - nodes[node2].neighbors.append(nodes[node1]) + nodes[node1].neighbours.append(nodes[node2]) + nodes[node2].neighbours.append(nodes[node1]) return nodes def extract_osm_nodes(f_name): global parser - global nodes parser = get_default_parser(f_name) nodes = dict() @@ -45,6 +43,11 @@ def extract_osm_nodes(f_name): add_neighbours(nodes) + # remove nodes without neighbours + for node_id, node in nodes.copy().items(): + if not node.neighbours: + del nodes[node_id] + return nodes |