def nearest_neighbour(start_point, vectors):
min_dist = None
nearest = None
for potential in vectors:
dist_to = Vector.distance(start_point, potential)
if min_dist is None or dist_to < min_dist:
min_dist = dist_to
nearest = potential
return nearest
def nearest_neighbour(start_point, vectors):
min_dist = None
nearest = None
for potential in vectors:
dist_to = Vector.distance(start_point, potential)
if min_dist is None or dist_to < min_dist:
min_dist = dist_to
nearest = potential
return nearest
def greedy_ts_path(vec_list):
graph = dict()
used = []
current = vec_list[0]
# print vec_list
while len(used) + 1 < len(vec_list):
used.append(current)
min_dist = None
nearest_neighbour = None
for potential in vec_list:
if potential not in used:
dist_to = Vector.distance(current, potential)
if min_dist is None or dist_to < min_dist:
min_dist = dist_to
nearest_neighbour = potential
graph[current] = nearest_neighbour
current = nearest_neighbour
return graph
def greedy_ts_path(vec_list):
graph = dict()
used = []
current = vec_list[0]
# print vec_list
while len(used) + 1 < len(vec_list):
used.append(current)
min_dist = None
nearest_neighbour = None
for potential in vec_list:
if potential not in used:
dist_to = Vector.distance(current, potential)
if min_dist is None or dist_to < min_dist:
min_dist = dist_to
nearest_neighbour = potential
graph[current] = nearest_neighbour
current = nearest_neighbour
return graph
def __inner(from_node, to_node):
return Vector.distance(vec_list[from_node], vec_list[to_node])
def length(tour):
length = 0
for i in range(len(tour) - 1):
length += Vector.distance(tour[i], tour[i + 1])
return length
def __inner(from_node, to_node):
return Vector.distance(vec_list[from_node], vec_list[to_node])
def length(tour):
length = 0
for i in range(len(tour) - 1):
length += Vector.distance(tour[i], tour[i + 1])
return length
