Let u and v be two distinct vertices in a direct...

생성일: 2025년 6월 23일

답변에 사용된 모델 O4 Mini High by Chat01

질문

Let u
and v
be two distinct vertices in a directed graph. Let's call the ordered pair (u,v)
good if there exists a path from vertex u
to vertex v
along the edges of the graph.

You are given an undirected tree with n
vertices and n−1
edges. Determine whether it is possible to assign a direction to each edge of this tree so that the number of good pairs in it is exactly n
. If it is possible, print any way to direct the edges resulting in exactly n
good pairs.
Input
The first line contains one integer t
(1≤t≤104
) — the number of test cases.

The first line of each test case contains one integer n
(2≤n≤2⋅105
) — the number of vertices in the tree.

The next n−1
lines describe the edges. The i
-th line contains two integers ui
and vi
(1≤ui,vi≤n
; ui≠vi
) — the vertices connected by the i
-th edge.

It is guaranteed that the edges in each test case form an undirected tree and that the sum of n
over all test cases does not exceed 2⋅105
.

Output
For each test case, print "NO" (case-insensitive) if it is impossible to direct all edges of the tree and obtain exactly n
good pairs of vertices.

Otherwise, print "YES" (case-insensitive) and then print n−1
pairs of integers ui
and vi
separated by spaces — the edges directed from ui
to vi
.

The edges can be printed in any order. If there are multiple answers, output any.

code in java

사고

Evaluating the problem

The user wants Java code to solve a problem about assigning directions to edges in an undirected tree, such that there are exactly "n" good pairs (reachable ordered pairs of vertices). The task is algorithmic, requiring directing edges such that the count of paths between vertices matches a given condition. In this case, the number of good pairs is equivalent to having exactly "n" reachable ordered pairs. I'll think how to approach this in Java code.

Thinking about reachable pairs

The goal is to direct the edges of a tree such that there are exactly n good pairs. In a directed tree, the number of reachable pairs depends on how the tree is oriented, which leads us to calculate the sum of subtree sizes. The total reachable pairs are determined by how nodes are related as descendants and ancestors. For example, in a star tree with one root and n-1 children, each child had depth 1. I'll need to refine this thinking to make sure I approach it properly for the Java code.

Thinking about tree depths

To achieve exactly n reachable pairs, the sum of depths for a particular tree must equal n. I realize that for small n (like n=3 or n=4), we need to arrange the tree in such a way that there’s one node with depth 2, and others with depth 1. This suggests an orientation that places most nodes at depth 1 and one at depth 2, forming a tree shape, and then orienting the edges appropriately. The root can be chosen arbitrarily, and I’d need to check the sum of depths for each possible root to determine if it's valid.

Considering possible orientations

For the tree, I need to determine whether an orientation can create exactly n reachable pairs. The basic idea is that we can orient edges toward or away from chosen roots, trying to match the sum of distances of nodes to be exactly n. By testing each root's distance sum and adjusting the edge directions, I can check if it's possible to get the desired number of reachable pairs. If such an orientation exists, I'll output it; otherwise, I'll conclude that it's not possible. I'll need efficient algorithms due to the constraint of large input sizes.

Evaluating reachability and orientations

It looks like I'm trying to determine how to calculate reachable pairs for a tree by orienting its edges. If the sum of distances from one root equals n, the tree could be orientable to produce exactly n reachable pairs. This requires calculating subtree sizes, depth, and adjusting edge orientations. For each node, the distance sum is recalculated as the root shifts. If no root gives the correct sum, the answer is impossible. The approach seems to involve efficient DFS/iterative methods due to large input sizes.

Thought for 1m 8s

답변

Here’s a Java solution that runs in O(n)O(n) per test case by using a two-pass “rerooting” DP to compute, for every node rr, the sum of distances

S(r)=v=1ndist(r,v).S(r)=\sum_{v=1}^n \mathrm{dist}(r,v).

In a tree oriented as an arborescence away from rr, the number of good pairs is exactly S(r)S(r). We look for a node rr with S(r)=nS(r)=n. If found, we root the tree at rr, direct every edge away from rr, and print “YES” plus that orientation. Otherwise we print “NO.”

java
import java.io.*; import java.util.*; public class Main { static int n; static List<Integer>[] g; static long[] depth, sz, distSum; static int[] parent0; public static void main(String[] args) throws IOException { BufferedReader br = new BufferedReader(new InputStreamReader(System.in)); PrintWriter out = new PrintWriter(System.out); int t = Integer.parseInt(br.readLine().trim()); while (t-- > 0) { n = Integer.parseInt(br.readLine().trim()); g = new ArrayList[n+1]; for (int i = 1; i <= n; i++) g[i] = new ArrayList<>(); for (int i = 0; i < n-1; i++) { String[] uv = br.readLine().split(" "); int u = Integer.parseInt(uv[0]); int v = Integer.parseInt(uv[1]); g[u].add(v); g[v].add(u); } if (n == 2) { // Only one edge → only 1 good pair possible out.println("NO"); continue; } // 1) First DFS from node 1 to compute depth[] and subtree sizes sz[] depth = new long[n+1]; sz = new long[n+1]; parent0 = new int[n+1]; dfs1(1); // initial sum of distances from 1: long initSum = 0; for (int i = 1; i <= n; i++) initSum += depth[i]; // 2) Reroot DP to compute distSum[r] for all r distSum = new long[n+1]; distSum[1] = initSum; dfsReroot(1); // 3) Find a node r with distSum[r] == n int goodRoot = -1; for (int i = 1; i <= n; i++) { if (distSum[i] == n) { goodRoot = i; break; } } if (goodRoot == -1) { out.println("NO"); } else { out.println("YES"); // 4) BFS from goodRoot to orient every edge away from it Queue<Integer> q = new ArrayDeque<>(); int[] parentR = new int[n+1]; parentR[goodRoot] = 0; q.add(goodRoot); StringBuilder sb = new StringBuilder(); while (!q.isEmpty()) { int u = q.poll(); for (int v : g[u]) { if (v == parentR[u]) continue; parentR[v] = u; // direct edge u->v sb.append(u).append(' ').append(v).append('\n'); q.add(v); } } // Print the n-1 directed edges out.print(sb); } } out.flush(); } // Iterative two-phase DFS to get depth[] and subtree sizes sz[] static void dfs1(int root) { class Frame { int u, p; boolean post; } Deque<Frame> st = new ArrayDeque<>(); depth[root] = 0; parent0[root] = 0; st.push(new Frame(){ {u = root; p = 0; post = false;} }); while (!st.isEmpty()) { Frame f = st.pop(); int u = f.u, p = f.p; if (f.post) { // post-order: compute size[u] sz[u] = 1; for (int v : g[u]) { if (v == p) continue; sz[u] += sz[v]; } } else { // pre-order parent0[u] = p; // push post-frame st.push(new Frame(){ {u = u; p = p; post = true;} }); // push children for (int v : g[u]) { if (v == p) continue; depth[v] = depth[u] + 1; st.push(new Frame(){ {u = v; p = u; post = false;} }); } } } } // DFS to reroot distances: distSum[v] = distSum[u] + n - 2*sz[v] static void dfsReroot(int root) { Deque<Integer> st = new ArrayDeque<>(); st.push(root); while (!st.isEmpty()) { int u = st.pop(); for (int v : g[u]) { if (v == parent0[u]) continue; parent0[v] = u; // keep following the initial tree structure distSum[v] = distSum[u] + n - 2L*sz[v]; st.push(v); } } } }

Explanation of key steps

  1. Compute depths & subtree-sizes
    We run an iterative “two-phase” DFS from node 1. On the way down (pre-order) we set depth[v] = depth[u] + 1. On the way back up (post-order) we sum children’s sizes to get the subtree size sz[u].

  2. Initial sum of distances

    S(1)  =  v=1ndepth[v]. S(1) \;=\;\sum_{v=1}^n \mathrm{depth}[v].
  3. Reroot DP
    There is a classic identity for trees: if you move the root from u to its child v, the sum of distances changes by

    S(v)  =  S(u)  +  n    2sz[v]. S(v) \;=\; S(u)\;+\;n \;-\;2\,\text{sz}[v].

    We do a second DFS (again iterative) along the same parent pointers to fill distSum[v] for every node.

  4. Check for target
    We scan for any node r with distSum[r] == n. Orienting all edges away from r yields exactly n good pairs.

  5. Output
    If no such r exists, print “NO”. Otherwise print “YES” and then do a BFS from r, directing every tree edge from parent to child (this produces an arborescence rooted at r with exactly n good pairs).

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