[英]Detect cycle in a directed graph using iterative stack approach
這是我試過的:
VISITED = 1
UNVISITED = -1
VISITING = 0
def dfs(g, start, num):
state = {}
for i in range(num):
state[i] = UNVISITED
stack = [start]
while(stack != []):
node = stack.pop()
if(state[node] == VISITED):
continue
state[node] = VISITING
if(node in g):
for i in g[node]:
stack.append(i)
if(state[i] == VISITED):
return True
state[node] = VISITED
def detect_cycle(n, edges):
g = {}
# adjacency list
for (x, y) in edges:
g[x] = g.get(x, []) + [y]
for i in range(n):
if(i in g):
if(dfs(g, i, n) == True):
return True
return False
print(detect_cycle(5, [[1,4],[2,4],[3,1],[3,2]])) # outputs True (should be false)
圖形圖像:
上面的示例edges = [[1,4],[2,4],[3,1],[3,2]]
不包含循環但它返回True
。 所以我的算法不適用於這種情況。
我正在嘗試使用着色圖檢測循環算法,但我不確定如何在不遞歸的情況下做到這一點。
我嘗試遵循但迭代的算法: Detecting a cycle in a directed graph using DFS?
如果訪問節點(灰色)遇到與另一個訪問節點的邊,則檢測到循環。 我在初始代碼中遇到的問題是無法以回溯方式設置節點 VISITED(黑色)。 新代碼現在有 ENTER = 0 和 EXIT = 1。Enter = 0 意味着它是我第一次訪問該節點,我將它設置為灰色(訪問)我第二次訪問節點出口將是 1,所以我可以設置它變黑(完全訪問)。
WHITE = 0
GRAY = 1
BLACK = 2
ENTER = 0
EXIT = 1
def dfs(graph, start, n):
state = {}
for i in range(n):
state[i] = WHITE
stack = [(start, ENTER)]
while(stack != []):
node, pos = stack.pop()
if(pos == EXIT):
state[node] = BLACK
continue
state[node] = GRAY
stack.append((node, EXIT))
if(node in graph):
for v in graph[node]:
if state[v] == GRAY:
return True
elif(state[v] == WHITE):
stack.append((v, ENTER))
return False
def detect_cycle(n, edges):
g = {}
for (x, y) in edges:
g[x] = g.get(x, []) + [y]
for i in range(n):
if(i in g):
if(dfs(g, i, n) == True):
return True
return False
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