Reachable Nodes In Subdivided Graph — LeetCode 882 Python Solution

The problem

You are given an undirected graph (the "original graph") with n nodes labeled from 0 to n - 1. You decide to subdivide each edge in the graph into a chain of nodes, with the number of new nodes varying between each edge.

Example

Input

edges = [[0,1,10],[0,2,1],[1,2,2]], maxMoves = 6, n = 3

Output

13

Explanation

The edge subdivisions are shown in the image above.

Python solution

class Solution:
    def reachableNodes(self, edges: List[List[int]], maxMoves: int, n: int) -> int:
        g = defaultdict(list)
        for u, v, cnt in edges:
            g[u].append((v, cnt + 1))
            g[v].append((u, cnt + 1))
        q = [(0, 0)]
        dist = [0] + [inf] * n
        while q:
            d, u = heappop(q)
            for v, cnt in g[u]:
                if (t := d + cnt) < dist[v]:
                    dist[v] = t
                    q.append((t, v))
        ans = sum(d <= maxMoves for d in dist)
        for u, v, cnt in edges:
            a = min(cnt, max(0, maxMoves - dist[u]))
            b = min(cnt, max(0, maxMoves - dist[v]))
            ans += min(cnt, a + b)
        return ans

Complexity

Pattern: Heap / Priority Queue

Keep only the best k elements, or always pull the smallest, in log time. LeetCode 882. Reachable Nodes In Subdivided Graph is filed here on both counts: the reference solution below belongs to the algorithm family this hub collects, and LeetCode tags it Heap (Priority Queue).

The heap / priority queue guide has the Python template for the pattern and the 163 LeetCode problems that use it.

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