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-rw-r--r--min_cost_walk_weight_graph.py72
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diff --git a/min_cost_walk_weight_graph.py b/min_cost_walk_weight_graph.py
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+# 3108. Minimum Cost Walk in Weighted Graph
+
+"""
+there is an undirected weighted graph with 'n' vertices labeled from 0 to 'n
+- 1'. you are given the integer 'n' and an array 'edges', where 'edges[i] =
+[u_i, v_i, w_i]' indicates that there is an edge between vertices 'u_i' and
+'v_i' with a weight of 'w_i'. a walk on the graph is a sequence of vertices
+and edges. the walk starts and ends with a vertex, and each edge connects the
+vertex that comes before it and the vertex that comes after it. it's
+important to note that a walk may visit the same edge or vertex more than
+once. return the array 'answer' where 'answer[i]' denotes the minimum cost of
+a walk for query 'i'.
+"""
+
+
+class UnionFind:
+ def __init__(self, size):
+ self.parent = [i for i in range(size)]
+ self.rank = [0 for _ in range(size)]
+ self.d = [~0 for _ in range(size)]
+
+ def find(self, node):
+ if self.parent[node] != node:
+ self.parent[node] = self.find(self.parent[node])
+ return self.parent[node]
+
+ def union(self, a, b, val):
+ p1, p2 = self.find(a), self.find(b)
+ if self.rank[p1] > self.rank[p2]:
+ self.parent[p2] = p1
+ self.d[p1] &= self.d[p2] & val
+ elif self.rank[p1] < self.rank[p2]:
+ self.parent[p1] = p2
+ self.d[p2] &= self.d[p1] & val
+ else:
+ self.parent[p1] = p2
+ self.d[p2] &= self.d[p1] & val
+ self.rank[p2] += 1
+
+
+class Solution(object):
+ def minimumCost(self, n, edges, query):
+ """
+ :type n: int
+ :type edges: List[List[int]]
+ :type query: List[List[int]]
+ :rtype: List[int]
+ """
+ uf = UnionFind(n)
+ for u, v, w in edges:
+ uf.union(u, v, w)
+ ans = []
+ for u, v in query:
+ if uf.find(u) != uf.find(v):
+ ans.append(-1)
+ else:
+ ans.append(uf.d[uf.find(u)])
+ return ans
+
+
+if __name__ == "__main__":
+ obj = Solution()
+ print(
+ obj.minimumCost(
+ n=5, edges=[[0, 1, 7], [1, 3, 7], [1, 2, 1]], query=[[0, 3], [3, 4]]
+ )
+ )
+ print(
+ obj.minimumCost(
+ n=3, edges=[[0, 2, 7], [0, 1, 15], [1, 2, 6], [1, 2, 1]], query=[[1, 2]]
+ )
+ )