def dijkstra(graph, start_vtx_id):
# shortest path from one node to all others
if not graph.is_weighted:
for vtx in graph.get_all_vertices():
for nbr_id in vtx.get_nbr_ids:
vtx.set_weight(nbr_id, 1)
import sys
graph.re_initialize_all_vertex_attr("distance", sys.maxsize)
graph.get_vertex(start_vtx_id).set_distance(0)
#graph.get_vertex(start_vtx_id).set_pred(None)
v_pq = PriorityQueue([[vtx.get_distance(), vtx.get_id()] for vtx in graph.get_all_vertices()])
while not v_pq.is_empty():
current_vertex_id = v_pq.del_min()
cur_vtx = graph.get_vertex(current_vertex_id)
# todo maybe sorting is not required here
#for nbr_id in cur_vtx.get_nbr_ids_sorted_by_attribute("weight"):
for nbr_id in cur_vtx.get_nbr_ids():
nbr = graph.get_vertex(nbr_id)
new_dist = cur_vtx.get_distance() + cur_vtx.get_weight(nbr_id)
if nbr.get_distance() > new_dist:
nbr.set_distance(new_dist)
nbr.set_pred(current_vertex_id)
v_pq.decrease_key(nbr_id, new_dist)
def prim(graph, start_vtx_id):
# minimum spanning tree
# shortest path from one node to all others
ans = []
if not graph.is_weighted:
for vtx in graph.get_all_vertices():
for nbr_id in vtx.get_nbr_ids:
vtx.set_weight(nbr_id, 1)
import sys
graph.re_initialize_all_vertex_attr("distance", sys.maxsize)
graph.re_initialize_all_vertex_attr("predecessor_id", None)
graph.get_vertex(start_vtx_id).set_distance(0)
v_pq = PriorityQueue([[vtx.get_distance(),
vtx.get_id()] for vtx in graph.get_all_vertices()])
while not v_pq.is_empty():
current_vertex_id = v_pq.del_min()
ans.append(current_vertex_id)
cur_vtx = graph.get_vertex(current_vertex_id)
# todo maybe sorting is not required here
#for nbr_id in cur_vtx.get_nbr_ids_sorted_by_attribute("weight"):
for nbr_id in cur_vtx.get_nbr_ids():
nbr = graph.get_vertex(nbr_id)
new_dist = cur_vtx.get_weight(nbr_id)
if nbr.get_distance() > new_dist and v_pq.has_vertex(nbr):
nbr.set_distance(new_dist)
nbr.set_pred(current_vertex_id)
v_pq.decrease_key(nbr_id, new_dist)
return ans
def dijkstra(graph, start_vtx_id):
# shortest path from one node to all others
if not graph.is_weighted:
for vtx in graph.get_all_vertices():
for nbr_id in vtx.get_nbr_ids:
vtx.set_weight(nbr_id, 1)
import sys
graph.re_initialize_all_vertex_attr("distance", sys.maxsize)
graph.get_vertex(start_vtx_id).set_distance(0)
#graph.get_vertex(start_vtx_id).set_pred(None)
v_pq = PriorityQueue([[vtx.get_distance(),
vtx.get_id()] for vtx in graph.get_all_vertices()])
while not v_pq.is_empty():
current_vertex_id = v_pq.del_min()
cur_vtx = graph.get_vertex(current_vertex_id)
# todo maybe sorting is not required here
#for nbr_id in cur_vtx.get_nbr_ids_sorted_by_attribute("weight"):
for nbr_id in cur_vtx.get_nbr_ids():
nbr = graph.get_vertex(nbr_id)
new_dist = cur_vtx.get_distance() + cur_vtx.get_weight(nbr_id)
if nbr.get_distance() > new_dist:
nbr.set_distance(new_dist)
nbr.set_pred(current_vertex_id)
v_pq.decrease_key(nbr_id, new_dist)
def prim(graph, start_vtx_id):
# minimum spanning tree
# shortest path from one node to all others
ans = []
if not graph.is_weighted:
for vtx in graph.get_all_vertices():
for nbr_id in vtx.get_nbr_ids:
vtx.set_weight(nbr_id, 1)
import sys
graph.re_initialize_all_vertex_attr("distance", sys.maxsize)
graph.re_initialize_all_vertex_attr("predecessor_id", None)
graph.get_vertex(start_vtx_id).set_distance(0)
v_pq = PriorityQueue([[vtx.get_distance(), vtx.get_id()] for vtx in graph.get_all_vertices()])
while not v_pq.is_empty():
current_vertex_id = v_pq.del_min()
ans.append(current_vertex_id)
cur_vtx = graph.get_vertex(current_vertex_id)
# todo maybe sorting is not required here
#for nbr_id in cur_vtx.get_nbr_ids_sorted_by_attribute("weight"):
for nbr_id in cur_vtx.get_nbr_ids():
nbr = graph.get_vertex(nbr_id)
new_dist = cur_vtx.get_weight(nbr_id)
if nbr.get_distance() > new_dist and v_pq.has_vertex(nbr):
nbr.set_distance(new_dist)
nbr.set_pred(current_vertex_id)
v_pq.decrease_key(nbr_id, new_dist)
return ans
