Description
You are given an undirected weighted graph of n
 nodes (0-indexed), represented by an edge list where edges[i] = [a, b]
 is an undirected edge connecting the nodes a
 and b
 with a probability of success of traversing that edge succProb[i]
.
Given two nodes start
 and end
, find the path with the maximum probability of success to go from start
 to end
 and return its success probability.
If there is no path from start
 to end
, return 0. Your answer will be accepted if it differs from the correct answer by at most 1e-5.
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Example 1:
Input: n = 3, edges = [[0,1],[1,2],[0,2]], succProb = [0.5,0.5,0.2], start = 0, end = 2 Output: 0.25000 Explanation:Â There are two paths from start to end, one having a probability of success = 0.2 and the other has 0.5 * 0.5 = 0.25.
Example 2:
Input: n = 3, edges = [[0,1],[1,2],[0,2]], succProb = [0.5,0.5,0.3], start = 0, end = 2 Output: 0.30000
Example 3:
Input: n = 3, edges = [[0,1]], succProb = [0.5], start = 0, end = 2 Output: 0.00000 Explanation:Â There is no path between 0 and 2.
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Constraints:
2 <= n <= 10^4
0 <= start, end < n
start != end
0 <= a, b < n
a != b
0 <= succProb.length == edges.length <= 2*10^4
0 <= succProb[i] <= 1
- There is at most one edge between every two nodes.
Solution
Python3
class Solution:
def maxProbability(self, n: int, edges: List[List[int]], succProb: List[float], start_node: int, end_node: int) -> float:
graph = defaultdict(list)
for (a, b), prob in zip(edges, succProb):
graph[a].append((b, prob))
graph[b].append((a, prob))
dist = [0] * n
dist[start_node] = 1
pq = [(-1, start_node)]
while pq:
d, node = heappop(pq)
d = -d
if d != dist[node]:
continue
for adj, prob in graph[node]:
newProb = d * prob
if newProb > dist[adj]:
dist[adj] = newProb
heappush(pq, (-newProb, adj))
return dist[end_node]