我试图在 Python 中提出一个贪心算法,它在给定某个起始顶点的情况下返回无向图中的顶点。我知道 DFS 确定是否存在循环,但我试图实际返回形成循环的顶点。我使用邻接矩阵来表示下图:
adjacencyMatrix = [[0, 1, 1, 0], [1, 0, 0, 1], [1, 0, 0, 1], [0, 1, 1, 0]]
从图形上看,这是一个由单个循环组成的无向图。
我目前的思考过程是将我的起始索引设置为1
我遇到的第一个索引(在这种情况下adjacencyMatrix[0][1]
)。然后我会查看该行的其余部分,看看是否1
有另一个,因为这意味着我当前的顶点连接到该索引。但是,我不完全确定(a)这是否是正确的方法以及(b)如何“移动”到下一个顶点。例如,我将如何导航我的嵌套for
循环以从adjacencyMatrix[0][1]
顶点移动到adjacencyMatrix[0][2]
顶点?我会交换行和列索引吗?
编辑 我想出的这个解决方案似乎适用于我尝试过的几个图表:
def findCycle(matrix):
visited = list()
cycleNotFound = True
row = 0
col = 0
startVertex = (0, 0)
while cycleNotFound:
# Only add a vertex if it has not already been visited
if (matrix[row][col] == 1) and ((row, col) not in visited):
# Set the startVertex when the first node is found
if len(visited) == 0:
startVertex = (row, col)
# Add the current vertex and its counter part
visited.append((row, col))
visited.append((col, row))
# If row and col are equal, infite loop will get created
if row != col:
row = col
col = 0
else:
row += 1
# If back at starting point, break look
elif ((row, col) == startVertex) and (len(visited) > 1):
cycleNotFound = False
visited.append(startVertex)
# Else, continue to look for unvisted neighbors
else:
col += 1
return visited
if __name__ == "__main__":
matrix = [[0, 1, 1, 0], [1, 0, 0, 1], [1, 0, 0, 1], [0, 1, 1, 0]]
cycle = findCycle(matrix)
index = 0
# Print the vertices. Only print even vertices to avoid duplicates.
while (index < len(cycle)):
print cycle[index]
index += 2
这不是最优雅的解决方案,我确信需要进行一些重大的重构。