Choose Edges to Maximize Score in a Tree
We traverse a tree, and, for a node j, track and return best result with_j (when we pick an edge coming out of j) and without_j (no edge coming out of j).
That way, for a parent node i, we can find the best edge [i, j] to take (maximize weight + without_j), and best score if we do not take any edge.
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| from typing import List, Tuple
class Solution:
def dfs(self, i: int, al: List[List[Tuple[int, int]]]) -> Tuple[int, int]:
best_i = 0
without_i = 0
for j, w in al[i]:
with_j, without_j = self.dfs(j, al)
best_i = max(best_i, max(0, w) + without_j - with_j)
without_i += max(with_j, without_j)
return best_i + without_i, without_i
def maxScore(self, edges: List[List[int]]) -> int:
al = [[] for _ in range(len(edges))]
for i in range(1, len(edges)):
al[edges[i][0]].append((i, edges[i][1]))
with_0, without_0 = self.dfs(0, al)
return max(with_0, without_0)
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