def run_dijkstra(graph, source, target):
"""Dijkstra's shortest path algorithm"""
queue = PriorityQueue()
dist = {source: 0}
prev = {}
for vertex in graph:
if vertex != source:
dist[vertex] = float("inf")
queue.insert(vertex, dist[vertex])
while not queue.is_empty():
u_dist, u = queue.pop()
u_node = graph[u]
if u == target:
break
for v in u_node['linkTo']:
if queue.is_node_in_queue(v):
alt = dist[u] + \
calc_distance(int(u_node['x']), int(u_node['y']),
int(graph[v]['x']), int(graph[v]['y']))
if alt < dist[v]:
dist[v] = alt
prev[v] = u
queue.insert(v, alt)
path = []
curr = target
while curr in prev:
path.append(curr)
curr = prev[curr]
path.append(source)
return path[::-1]
def dijkstra(graph, start):
prev = {}
costs = {}
costs[start] = 0
visited = set()
pq = PriorityQueue()
for node in graph.nodes():
if node != -1:
pq.insert(float('inf'), node)
pq.insert(0, start)
while not pq.is_empty():
cost, ele = pq.delete_min()
visited.add(ele)
for successor in graph.get_successors(ele):
new_cost = cost + graph.get_cost(ele, successor)
if successor not in visited and (successor not in costs or new_cost < costs[successor]):
costs[successor] = new_cost
prev[successor] = ele
pq.update(new_cost, successor)
res = {}
for key in costs:
res[(start, key)] = costs[key]
return res
def prim(graph, start):
# heap to have the vertex that are not added
# key is the cheapest edge
edge = set()
overall_cost = 0
prev = {}
prev[start] = start
costs = {}
costs[start] = 0
pq = PriorityQueue()
visited = set()
for node in graph.nodes():
pq.insert(float('inf'), node)
pq.insert(0, start)
while not pq.is_empty():
cost, ele = pq.delete_min()
edge.add((prev[ele], ele))
overall_cost += cost
visited.add(ele)
for successor, edge_cost in graph.get_successors(ele):
new_cost = edge_cost
if successor not in visited and (successor not in costs or new_cost < costs[successor]):
costs[successor] = new_cost
prev[successor] = ele
pq.update(new_cost, successor)
return edge, overall_cost
def run_dijkstra(graph, source, target):
"""Dijkstra's shortest path algorithm"""
queue = PriorityQueue()
dist = {source: 0}
prev = {}
for vertex in graph:
if vertex != source:
dist[vertex] = float("inf")
queue.insert(vertex, dist[vertex])
while not queue.is_empty():
u_dist, u = queue.pop()
u_node = graph[u]
if u == target:
break
for v in u_node['linkTo']:
if queue.is_node_in_queue(v):
alt = dist[u] + \
calc_distance(int(u_node['x']), int(u_node['y']),
int(graph[v]['x']), int(graph[v]['y']))
if alt < dist[v]:
dist[v] = alt
prev[v] = u
queue.insert(v, alt)
path = []
curr = target
while curr in prev:
path.append(curr)
curr = prev[curr]
path.append(source)
return path[::-1]
def dijkstra(graph, start):
prev = {}
costs = {}
costs[start] = 0
pq = PriorityQueue()
for node in graph.nodes():
pq.insert(float('inf'), node)
pq.insert(0, start)
while not pq.is_empty():
cost, ele = pq.delete_min()
for successor, edge_cost in graph.get_successors(ele):
new_cost = cost + edge_cost
if successor not in costs or new_cost < costs[successor]:
costs[successor] = new_cost
prev[successor] = ele
pq.update(new_cost, successor)
return prev, costs
