def depth_first_search_recursive(graph, start, goal, parent=None):
if parent is None:
parent = {}
visited = set()
visited.add(start)
for vertex, weight in graph.get_neighbors(start):
if vertex not in visited:
parent[vertex] = start
if vertex != goal:
depth_first_search_recursive(graph, vertex, goal, parent)
return get_path(goal, parent)
def djikstra_heap(graph, start, goal):
all_nodes = graph._container.keys()
distances = {node: float('inf') for node in all_nodes}
distances[start] = 0
to_explore = [(distances[start], start)]
parent = {}
while to_explore:
origin_wt, origin = heappop(to_explore)
for vertex, weight in graph.get_neighbors(origin):
if distances[vertex] > origin_wt + weight:
distances[vertex] = origin_wt + weight
heappush(to_explore, (origin_wt + weight, vertex))
parent[vertex] = origin
return get_path(goal, parent)
def bfs(graph, start: str, goal: str):
visited = []
parent = {}
frontier = deque()
frontier.append(start)
while frontier:
check = frontier.popleft()
visited.append(check)
for dest, weight in graph.get_neighbors(check):
if dest not in visited:
frontier.append(dest)
parent[dest] = check
if dest == goal:
return get_path(goal, parent)
return False
def depth_first_search_stack(graph, start, goal) -> List[str]:
frontier = deque()
visited = set()
parent = {}
frontier.append(start)
while frontier:
checked_vertex = frontier.pop()
visited.add(checked_vertex)
for vertex, weight in graph.get_neighbors(checked_vertex):
if vertex not in visited:
frontier.append(vertex)
parent[vertex] = checked_vertex
if vertex == goal:
return get_path(goal, parent)
return False
def djikstra(graph, start, goal):
all_nodes = graph._container.keys()
distances = {node: float('inf') for node in all_nodes}
distances[start] = 0
processed = set()
node = start
parent = {}
while all_nodes - processed:
processed.add(node) # add node to set 'processed'
for vertex, weight in graph.get_neighbors(node):
# check if weight in distances dictionary is larger than this path
if vertex not in processed:
if distances[vertex] > distances[node] + weight:
distances[vertex] = distances[node] + weight
parent[vertex] = node
if all_nodes - processed: # gives set of all unprocessed nodes
# sets variable 'node' to smallest remaining unprocessed node
node = min([i for i in all_nodes - processed],
key=lambda x: distances[x])
return get_path(goal, parent)