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greedy.py
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greedy.py
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from itertools import count
from queue import PriorityQueue
def greedy(graph, start, target, metric="0", weight="length", **kwargs):
"""
GBFS(Graph G, Vertex s, Vertex t) {
PriorityQueue Q;
Q. insert (s , h(s , t )) // Füge Startknoten hinzu
while (! Q.empty()) { // Solange noch Knoten unbesucht
u = Q.getMin(); // Nächster + bester Knoten
if (u == t) // Ziel erreicht
return;
for (jeden Nachbarn v von u) { // Alle ausgehenden Kanten
v. dist = u. dist + w(u,v) //Tatsächliche Kosten bis v
h = h(v,t ); // Berechne Schätzung zum Ziel
if (v. dist ist noch undefiniert )
Q.add(v, h) // Füge Knoten mit Schätzung zur Schlange hinzu } } }
"""
match metric:
case "0":
heuristik = null
case "euklid":
heuristik = euklid
case "euklid_quadrat":
heuristik = euklid_quadrat
case "manhattan":
heuristik = manhattan
case _:
heuristik = euklid
todo = PriorityQueue()
cost = {start: 0}
counter = count()
todo.put((0, next(counter), start))
matrix = []
parent = {start: None}
visited = set()
# Haben schon die Kosten anhand des aktuellen Gewichts,
# wollen aber immer die Länge und Dauer:
length = {start: 0}
travel_time = {start: 0}
while not todo.empty():
inner_array = []
_, _, vertex = todo.get()
visited.add(vertex)
if vertex == target:
return (
matrix,
make_path(parent, target),
cost.get(target, 0),
length.get(target, 0),
travel_time.get(target, 0),
)
for adjacent, _ in graph._adj[vertex].items():
if adjacent in visited:
continue # skip these to save time
inner_array.append([vertex, adjacent])
new_cost = cost[vertex] + graph.edges[vertex, adjacent, 0][weight]
# if cost.get(adjacent, None) is None:
if cost.get(adjacent, float("inf")) > new_cost:
parent[adjacent] = vertex
cost[adjacent] = new_cost
# Immer Länge und Dauer sammeln
length[adjacent] = (
length[vertex] + graph.edges[vertex, adjacent, 0]["length"]
)
travel_time[adjacent] = (
travel_time[vertex]
+ graph.edges[vertex, adjacent, 0]["travel_time"]
)
if adjacent == target:
matrix.append(inner_array)
return (
matrix,
make_path(parent, target),
cost.get(target, 0),
length.get(target, 0),
travel_time.get(target, 0),
)
h = heuristik(graph, adjacent, target)
todo.put((h, next(counter), adjacent))
if len(inner_array) > 0:
matrix.append(inner_array)
return (
matrix,
make_path(parent, target),
cost.get(target, 0),
length.get(target, 0),
travel_time.get(target, 0),
)
def null(G, v, t):
return 0
def manhattan(G, v, t):
v = G.nodes[v]
t = G.nodes[t]
return abs(v["x"] - t["x"]) + abs(v["y"] - t["y"])
def euklid(G, v, t):
v = G.nodes[v]
t = G.nodes[t]
return ((v["x"] - t["x"]) ** 2 + (v["y"] - t["y"]) ** 2) ** 0.5
def euklid_quadrat(G, v, t):
v = G.nodes[v]
t = G.nodes[t]
return (v["x"] - t["x"]) ** 2 + (v["y"] - t["y"]) ** 2
def make_path(parent, target):
if target not in parent:
return []
v = target
path = []
while v is not None: # root has null parent
path.append(v)
v = parent[v]
return path[::-1]
if __name__ == "__main__":
import osmnx as ox
## Bbox vom Start
north, south, east, west = (
50.32942276889266,
50.32049083973944,
11.944606304168701,
11.929510831832886,
)
## create network from that bounding box
G = ox.graph_from_bbox(north, south, east, west, network_type="drive")
G = ox.add_edge_speeds(G)
G = ox.add_edge_travel_times(G)
# 295704008
# 295704255
print("greedy")
matrix, path, cost, length, time = greedy(
G, 379493008, 295704255, weight="travel_time"
)
print(matrix)
print(path)
print(cost)
print(length)
print(time)