give solution in cpp D. Reachability and Tree tim...

Erstellt am: 23. Juni 2025

Beantwortet mit O4 Mini High von Chat01

Frage

0f17bdc8df6de9dcbcefe04d44049c8911e607a8.webp0f17bdc8df6de9dcbcefe04d44049c8911e607a8.webp
e52886ce22e1a452186a3dfa3c2cc602f6c4d2ec.webpe52886ce22e1a452186a3dfa3c2cc602f6c4d2ec.webp

give solution in cpp

D. Reachability and Tree
time limit per test2 seconds
memory limit per test256 megabytes
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.

One possible directed version of the tree for the first test case.
Input
The first line contains one integer t (1 \le t \le 10^4) — the number of test cases.

The first line of each test case contains one integer n (2 \le n \le 2 \cdot 10^5) — the number of vertices in the tree.

The next n - 1 lines describe the edges. The i-th line contains two integers u_i and v_i (1 \le u_i, v_i \le n; u_i \neq v_i) — 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 \cdot 10^5.

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 u_i and v_i separated by spaces — the edges directed from u_i to v_i.

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

Example
InputCopy
4
5
1 2
2 4
1 3
3 5
5
1 2
1 3
1 4
4 5
2
2 1
4
3 1
1 2
2 4
OutputCopy
YES
1 2
3 1
3 5
4 2
YES
2 1
3 1
4 1
5 4
NO
YES
1 3
2 1
2 4
Note
The tree from the first test case and its possible directed version are shown in the legend above. In this version, there are exactly 5 good pairs of vertices: (3, 5), (3, 1), (3, 2), (1, 2), and (4, 2).

One possible directed version of the tree from the second test case is shown below:

In the presented answer, there are exactly 5 good pairs of vertices: (2, 1), (3, 1), (4, 1), (5, 4), and (5, 1).

In the third test case, there are only two directed pairs of vertices, but for any direction of the edge, only one pair will be good.

Gedanke

Analyzing C++ problem

The user is asking for a C++ solution for a tree reachability problem from Codeforces. The task involves assigning direction to the tree’s edges to ensure exactly n good pairs (u,v). A good pair means there's a directed path from u to v. Since we're dealing with an undirected tree, assigning directions can create a directed acyclic graph (DAG) with the desired property. I’ll need to decide if it's possible to assign these directions and how to approach it in C++.

Exploring tree reachability

In an oriented tree, the number of reachable pairs is the sum of reachable nodes for each starting node. Since there are no cycles, each node has a set of descendants. The goal is for the total reachable pairs across all nodes to equal the number of nodes, n. The key observation is that each directed edge gives at least one reachable pair, contributing a minimum of n-1 pairs. To get exactly n pairs, we need one additional pair from a path length greater than 1, meaning a path of exactly length 2 in the tree.

Understanding tree orientation constraints

The goal is to avoid long directed chains that generate too many reachable pairs. In a chain with 3 edges, the pairs would quickly exceed the desired number. To achieve exactly one extra reachable pair, we need only one chain of length 2 (two edges oriented the same direction) in the tree. This chain will give us that extra pair. Also, I must ensure that no node, except for one in the chain, has both an incoming and outgoing edge, to prevent forming additional paths unintentionally.

Analyzing star-shaped tree chains

For the star-shaped tree setup, the center node has more than 2 neighbors. If we orient the edges a certain way, we get extra chains, creating additional reachable pairs. These extra chains appear because the center node has both incoming and outgoing edges. A perfect star would avoid this, but we need specific configurations to prevent chains and the extra reachable pairs. This involves ensuring that other edges of the central node are oriented carefully to avoid further chains forming, something which is tricky if the center node has too many neighbors.

Examining star tree orientation constraints

A perfect star tree, with the center node having a degree of n-1 and the leaves having a degree of 1, can't be oriented in a way that avoids chains when n ≥ 4. In this case, the center node degree is too high to properly orient edges without creating extra reachable pairs. It becomes impossible to avoid chains unless there exists a vertex with degree exactly 2. This is why a tree with a center node of degree ≥ 3, like a true star, cannot work in this scenario.

Thought for 2m 31s

Antwort

Analysis

We need to orient the edges of a tree on nn vertices so that the total number of good pairs

#{(u,v)uv, there is a directed path from uv}\#\{(u,v)\mid u\ne v,\ \text{there is a directed path from }u\to v\}

is exactly nn. A little thought shows

  1. Every edge, once oriented, contributes at least one good pair (its two endpoints).
  2. Every directed path of length ≥2 contributes extra good pairs (one for each “hop-over”).
  3. Hence to get exactly nn good pairs from n1n-1 edges, we must have exactly one extra good pair beyond the n1n-1 contributed by the edges themselves. Equivalently: exactly one directed path of length 2, and no longer directed paths anywhere.

In a tree, a directed path of length 2 can only happen when a vertex vv has exactly one incoming edge and exactly one outgoing edge (so the two edges “chain” through vv). If we tried to make that happen at a vertex of degree 3\ge3, its other incident edges would create additional length-2 paths and hence too many good pairs. Conversely, if the tree has a vertex of degree exactly 2, we can use that vertex as the unique “chain” node:

  • Let vv be any vertex of degree 2, with neighbors a,ba,b.
  • Orient the two edges on that chain as a    v    b, a\;\to\;v\;\to\;b,

which creates exactly one extra good pair aba\to b.

  • The rest of the tree falls into two components (one containing aa, one containing bb) once vv is removed. In each component we must orient no two edges consecutively in the same direction. A neat way to do this in any bipartite graph (and our component is a tree, hence bipartite) is:
  1. Two-color the component (say color 0/1).
  2. Orient every edge from color 0 to color 1.

Since every path of length 2 in a bipartition alternates 0→1→0 or 1→0→1, one of those hops is always against the “0→1” rule, so you can never get two edges in the same direction. In particular there are no further length-2 directed paths in those components.

Putting that together:

  1. If n=2n=2 or there is no vertex of degree 2, answer NO.
  2. Otherwise choose a degree-2 vertex vv with neighbors a,ba,b.
  • Orient ava\to v and vbv\to b.
  • Remove vv, run two BFS’s (one from aa with color 0, one from bb with color 1) to color each component 0/1.
  • Orient every remaining edge from color 0 to color 1.
  • You get exactly n1n-1 base pairs plus one extra from avba\to v\to b, total nn.

The whole thing runs in O(n)O(n) per test, which is fine for n2 ⁣× ⁣105\sum n\le2\!\times\!10^5.


cpp
#include <bits/stdc++.h> using namespace std; using pii = pair<int,int>; int main(){ ios::sync_with_stdio(false); cin.tie(nullptr); int T; cin >> T; while(T--){ int n; cin >> n; vector<vector<int>> adj(n+1); vector<pii> edges(n-1); for(int i = 0; i < n-1; i++){ int u,v; cin >> u >> v; edges[i] = {u,v}; adj[u].push_back(v); adj[v].push_back(u); } // n=2 is impossible (only 1 reachable pair always) if(n == 2){ cout << "NO\n"; continue; } // find a vertex of degree exactly 2 int chainV = -1; for(int i = 1; i <= n; i++){ if(adj[i].size() == 2){ chainV = i; break; } } if(chainV == -1){ // no degree-2 vertex => can't create exactly one length-2 chain cout << "NO\n"; continue; } // we will build our answer edges here vector<pii> ans; ans.reserve(n-1); // pick the two neighbors of chainV int a = adj[chainV][0]; int b = adj[chainV][1]; // 1) orient the unique chain a -> chainV -> b ans.emplace_back(a, chainV); ans.emplace_back(chainV, b); // prepare to 2-color the two components when chainV is removed vector<int> side(n+1, -1); // in the 'a' component we color a with 0 // in the 'b' component we color b with 1 side[a] = 0; side[b] = 1; // BFS from 'a' skipping chainV { queue<int> q; q.push(a); while(!q.empty()){ int u = q.front(); q.pop(); for(int w: adj[u]){ if(w == chainV || side[w] != -1) continue; side[w] = side[u] ^ 1; q.push(w); } } } // BFS from 'b' skipping chainV { queue<int> q; q.push(b); while(!q.empty()){ int u = q.front(); q.pop(); for(int w: adj[u]){ if(w == chainV || side[w] != -1) continue; side[w] = side[u] ^ 1; q.push(w); } } } // we already handled the two chain edges; now // orient every other edge from color 0 -> color 1 auto norm = [&](int x,int y){ if(x>y) swap(x,y); return make_pair(x,y); }; auto c1 = norm(a, chainV); auto c2 = norm(b, chainV); for(auto &e: edges){ int u = e.first, v = e.second; auto nm = norm(u,v); if(nm == c1 || nm == c2) continue; // skip the two chain edges // orient from side==0 to side==1 if(side[u] == 0 && side[v] == 1){ ans.emplace_back(u,v); } else { ans.emplace_back(v,u); } } // sanity: we must have exactly n-1 oriented edges assert((int)ans.size() == n-1); cout << "YES\n"; for(auto &p: ans){ cout << p.first << " " << p.second << "\n"; } } return 0; }

Explanation of Key Steps

  1. Why degree-2?
    Only a vertex of degree 2 can host exactly one “incoming + outgoing” pair without spawning extra length-2 paths on its other edges.

  2. Creating the single length-2 path
    We pick the two edges adjacent to that degree-2 vertex vv, say (a,v)(a,v) and (v,b)(v,b), and orient them avba\to v\to b. This single length-2 path contributes exactly one extra good pair (a,b)(a,b) beyond the n1n-1 from the edges.

  3. Avoiding any other chains
    Removing vv splits the tree into two pieces (one on aa’s side, one on bb’s side). In each component we 2-color the vertices (it’s a tree, hence bipartite) and then orient every edge from color 0➝color 1. This ensures that no two edges can line up in the same direction, so there are no other directed paths of length ≥2.

Overall the result is exactly nn good pairs, as required.

Frage

give solution in cpp

E. Tree Colorings
time limit per test4 seconds
memory limit per test256 megabytes
Consider a rooted undirected tree. Each vertex can be colored blue, green, or yellow. A coloring is called beautiful if it meets these conditions:

the root of the tree is green;
if you consider all blue and green vertices, they are reachable from each other without passing through any yellow vertices;
if you consider all yellow and green vertices, they are reachable from each other without passing through any blue vertices;
You are given an integer m. Your task is to calculate the minimum number of vertices in a tree with exactly m beautiful colorings.

Input
The first line contains a single integer (1 \le t \le 10^5) — the number of test cases.

The only line of each test case contains a single integer m (1 \le m \le 5 \cdot 10^5).

Output
For each test case, print a single integer — the minimum number of vertices in a tree with exactly m beautiful colorings. If such a tree does not exist, print -1.

Example
InputCopy
5
1
3
5
7
9
OutputCopy
1
2
3
4
3
Note
In the following notes, let g describe green color, b be blue, and y be yellow.

In the first example, consider a simple tree with just 1 vertex. This tree has exactly 1 beautiful coloring: the root is green.

In the second example, consider a simple tree with 2 vertices with a root at the 1-st vertex. There are exactly 3 beautiful colorings: [g, g], [g, b] and [g, y].

In the third example, consider a bamboo tree with 3 vertices with a root at the 1-st vertex. There are exactly 5 beautiful colorings: [g, g, g], [g, g, b], [g, g, y], [g, b, b] and [g, y, y].

In the fifth example, consider a tree with 3 vertices with a root at the 1-st vertex, and the other 2 vertices connected to it. There are exactly 9 beautiful colorings: [g, g, g], [g, g, b], [g, g, y], [g, b, g], [g, b, b], [g, b, y], [g, y, g], [g, y, b] and [g, y, y].

Gedanke

Analyzing Tree Colorings Problem

The user asks for a C++ solution to "Tree Colorings" from Codeforces. It involves a rooted, undirected tree with vertices colored Blue, Green, or Yellow according to specific rules. The key conditions are: the root must be Green, the subgraph of Blue and Green vertices must be connected, and the subgraph of Yellow and Green vertices must be connected. Our task is to calculate how many "beautiful" colorings satisfy these conditions for a given tree. I'll need to devise an approach in C++ to solve this.

Analyzing Tree Coloring Problem Further

We need to determine the minimal number of vertices for a tree such that it admits exactly m beautiful colorings. The goal is to find the tree's structure and the number of vertices for each possible m. For example, when m = 1, the tree only requires 1 green vertex. For m = 3, a 2-vertex tree works, with all three colors being valid. There seems to be some confusion around determining the correct count of colorings, especially with more complex trees, like the bamboo chain of 3 vertices for m = 5.

Breaking Down Coloring Constraints

I’m thinking through the color constraints for this tree problem. For each valid coloring, I must ensure both connectivity conditions are satisfied. I’m using two indices, L and R, to help define the valid ranges where certain colors must appear. If L and R are both set to n, I can calculate the number of valid colorings by summing sequences of length R-1 and L-1. This results in a total of 2^n - 1 beautiful colorings, both for when L=n and R=n. It’s getting more structured now!

Revising Beautiful Colorings

I realized some issues with the enumeration of the cases, especially in case A, where I incorrectly included sequences with "g, y" as valid, even though they didn’t satisfy the condition for prefix L=n. When fixing this, the colorings turned out to be deterministic for case A: the sequence’s prefix will be all g, and the suffix all b, resulting in n possible sequences. For case B, the sequences will have a prefix of g and a suffix of y. Combining both cases, I found that the total number of colorings is 2n - 1. The example checks out too!

Examining Coloring Functions

I’m noticing that the general function f(s)f(s) I derived for colorings of subtrees depends on the shape of the subtree. For paths, we had f(s)=2s+1f(s) = 2s + 1, but when looking at other shapes—like a star-shaped subtree—the coloring function doesn't always hold that exact formula. For instance, I just calculated f(2)f(2) for a subtree with 2 leaves and got 17 colorings, but the formula 2s+12s + 1 only gave me 5. So, tree shape actually alters the coloring count. This complicates counting colorings for general tree shapes.

Optimizing tree size calculation

I need to compute the minimal tree sizes necessary to represent a range of odd numbers up to 500k, based on certain path or star shapes. I'll precompute these minimal sizes for all relevant values up to that limit. Then, for each number m, I'll factorize it and choose a combination of subtrees that minimizes the size sum. Some optimizations involve dynamic programming to track combinations of factors and choose the best possible tree size.

Evaluating minimal nodes for f

I’m setting up a way to compute the minimal number of nodes for values of f up to 500,000. For each odd f, I initially set the value as (f-1)/2, reflecting a path structure. Then, I’ll explore other tree-like shapes and factor combinations to optimize the solution. For example, I’ll compare simple paths with three-level stars and potentially smoother combinations like sub-components to find the most efficient node structure for each f. But working with large numbers and decompositions might require careful optimization!

Thought for 2m 35s

Antwort

Below is an O(MlogM)O(M\log M)-precompute + O(1)O(1) –per query solution, where M=5×105M=5\times10^5. We build two DP tables:

  1. dpNodes[f] = the minimum number of nodes in a rooted subtree (with its root’s parent fixed green) whose “AA”–value is exactly ff, where
Av  =  c{g,b,y}  uchildren(v)Au(c)A_v \;=\;\sum_{c\in\{g,b,y\}}\;\prod_{u\in\text{children}(v)}A_u(c)

and one shows that AvA_v is always odd and that these AvA_v are exactly the building‐blocks of the global count.

  1. dpRoot[m] = the minimum total number of vertices in a full tree whose total number of beautiful colorings is exactly mm. One proves that at the global root (which must be green) the total count factors as
m  =  i=1kAvi,m \;=\;\prod_{i=1}^k A_{v_i},

where the viv_i are its children, so

nodes=1+i(size of subtree at vi)  =  1+idpNodes[Avi].\text{nodes}=1+\sum_i\bigl(\text{size of subtree at }v_i\bigr) \;=\;1+\sum_i dpNodes[A_{v_i}].

Hence we do one final multiplicative DP over the divisors of mm to get the optimum split at the root.

cpp
#include <bits/stdc++.h> using namespace std; using ll = long long; const int M = 500000; const int INF = 1000000000; int main(){ ios::sync_with_stdio(false); cin.tie(nullptr); // 1) Precompute divisors for all n<=M static vector<int> divs[M+1]; for(int d = 1; d <= M; d += 2){ // only odd divisors matter, but we can do all for(int x = d; x <= M; x += d){ divs[x].push_back(d); } } // 2) dpNodes[f] = min size of a subtree (excluding the global root) // whose A-value = f. We only care about odd f. static int dpNodes[M+1], D[M+1]; // D[g] = minimal sum of dpNodes[fi] over a factorization g = ∏ fi (all fi odd>1) // (i.e. best way to break g into children at an *internal* node) memset(dpNodes, 0x3f, sizeof dpNodes); memset(D, 0x3f, sizeof D); dpNodes[1] = 0; // no nodes needed to realize A=1 (empty product) D[1] = 0; // to factor 1 you pick nothing // Build up dpNodes in increasing order of f=3,5,7,...,M for(int f = 3; f <= M; f += 2){ int g = f - 2; // g = product of child A-values // compute D[g] = min_{d|g, d>1} ( dpNodes[d] + D[g/d] ) if(g > 1){ int best = INF; for(int d: divs[g]){ if(d == 1) continue; best = min(best, dpNodes[d] + D[g/d]); } D[g] = best; } // start with the “path”‐shape cost dpNodes[f] = (f - 1) / 2; // or use an internal node giving A = g+2 // cost = 1 (the internal node) + D[g] dpNodes[f] = min(dpNodes[f], 1 + D[g]); } // 3) dpRoot[m] = min #vertices in a full tree with exactly m colorings // Root must be green ⇒ m = ∏ A[v_i]. We pay 1 for the root plus // dpNodes[A[v_i]] for each child‐subtree. static int dpRoot[M+1]; for(int i = 0; i <= M; i++) dpRoot[i] = INF; dpRoot[1] = 1; // only the root, 1 beautiful coloring // fill in for odd m ≥3: for(int m = 3; m <= M; m += 2){ // one‐child decomposition: root→subtree with A=m if(dpNodes[m] < INF) dpRoot[m] = 1 + dpNodes[m]; // try splitting m = f * (m/f) for(int f: divs[m]){ if(f == 1 || f == m) continue; dpRoot[m] = min(dpRoot[m], dpRoot[m/f] + dpNodes[f]); } } // 4) answer queries int T; cin >> T; while(T--){ int m; cin >> m; if(m == 1){ cout << 1 << "\n"; } else if((m & 1) == 0){ cout << -1 << "\n"; } else { int ans = dpRoot[m]; if(ans >= INF) ans = -1; cout << ans << "\n"; } } return 0; }

Explanation of the Key Steps

  1. Local DP for subtrees
    We show that for any node vv whose parent is fixed green, its contribution

    Av  =  (uch(v)Au)  +  2 A_v \;=\;\bigl(\prod_{u\in\mathrm{ch}(v)}A_u\bigr)\;+\;2

    produces exactly all odd values 3\ge3. We let

    dpNodes[f] = \min\{\text{#nodes of a subtree rooted at }v : A_v = f\}.

    One easily sees that the “path” shape gives f=2s+1f=2s+1 with ss nodes, and any multi‐child shape gives f=g+2f = g+2 where g=Aug=\prod A_u. Factoring gg into its child-contributions is itself a knapsack on multiplication, which we solve via

    D[g]=mindg,  d>1 ⁣(dpNodes[d]+D[g/d]),dpNodes[f]=min(f12,1+D[f2]). D[g] = \min_{d\mid g,\;d>1}\!\bigl(dpNodes[d] + D[g/d]\bigr), \quad dpNodes[f] = \min\Bigl(\tfrac{f-1}{2},\,1 + D[f-2]\Bigr).
  2. Global DP at the root
    Since the global root must be green, the total count of beautiful colorings factors as

    m  =  i=1kAvi, m \;=\;\prod_{i=1}^k A_{v_i},

    where the viv_i are its immediate children. The total vertex‐count is 1+i(size of subtree at vi)1+\sum_i (\text{size of subtree at }v_i). Hence

    dpRoot[m]=1+minfm1<fm(dpRoot[m/f]+dpNodes[f]),dpRoot[1]=1. dpRoot[m] = 1 + \min_{\substack{f|m\\1<f\le m}} \bigl(dpRoot[m/f]+dpNodes[f]\bigr), \quad dpRoot[1]=1.

    Finally we answer each query in O(τ(m))O(\tau(m)), where τ(m)\tau(m) is the divisor‐count, an acceptable total cost over all m5105m\le5\cdot10^5.

This runs in about O(MlogM)O(M\log M) to precompute and then O(1)O(1) per test.

Diesen Q&A teilen