Dado un árbol, y los pesos de todos los Nodes y un número entero x , la tarea es encontrar un Node i tal que el peso[i] x o x sea máximo.
Ejemplos:
Aporte:
x = 15
Salida: 1
Node 1: 5 xor 15 = 10
Node 2: 10 xor 15 = 5
Node 3: 11 xor 15 = 4
Node 4: 8 xor 15 = 7
Node 5: 6 xor 15 = 9
Enfoque: Realice dfs en el árbol y realice un seguimiento del Node cuyo xor ponderado con x da el valor máximo.
A continuación se muestra la implementación del enfoque anterior:
C++
// C++ implementation of the approach #include <bits/stdc++.h> using namespace std; int maximum = INT_MIN, x, ans; vector<int> graph[100]; vector<int> weight(100); // Function to perform dfs to find // the maximum xored value void dfs(int node, int parent) { // If current value is less than // the current maximum if (maximum < (weight[node] ^ x)) { maximum = weight[node] ^ x; ans = node; } for (int to : graph[node]) { if (to == parent) continue; dfs(to, node); } } // Driver code int main() { x = 15; // Weights of the node weight[1] = 5; weight[2] = 10; weight[3] = 11; weight[4] = 8; weight[5] = 6; // Edges of the tree graph[1].push_back(2); graph[2].push_back(3); graph[2].push_back(4); graph[1].push_back(5); dfs(1, 1); cout << ans; return 0; }
Java
// Java implementation of the approach import java.util.*; class GFG { static int maximum = Integer.MIN_VALUE, x, ans; @SuppressWarnings("unchecked") static Vector<Integer>[] graph = new Vector[100]; static int[] weight = new int[100]; // This block is executed even before main() function // This is necessary otherwise this program will // throw "NullPointerException" static { for (int i = 0; i < 100; i++) graph[i] = new Vector<>(); } // Function to perform dfs to find // the maximum xored value static void dfs(int node, int parent) { // If current value is less than // the current maximum if (maximum < (weight[node] ^ x)) { maximum = weight[node] ^ x; ans = node; } for (int to : graph[node]) { if (to == parent) continue; dfs(to, node); } } // Driver Code public static void main(String[] args) { x = 15; // Weights of the node weight[1] = 5; weight[2] = 10; weight[3] = 11; weight[4] = 8; weight[5] = 6; // Edges of the tree graph[1].add(2); graph[2].add(3); graph[2].add(4); graph[1].add(5); dfs(1, 1); System.out.println(ans); } } // This code is contributed by // sanjeev2552
Python3
# Python3 implementation of the approach import sys maximum = -sys.maxsize - 1 graph = [[0 for i in range(100)] for j in range(100)] weight = [0 for i in range(100)] ans = [] # Function to perform dfs to find # the maximum xored value def dfs(node, parent): global maximum # If current value is less than # the current maximum if (maximum < (weight[node] ^ x)): maximum = weight[node] ^ x ans.append(node) for to in graph[node]: if (to == parent): continue dfs(to, node) # Driver code if __name__ == '__main__': x = 15 # Weights of the node weight[1] = 5 weight[2] = 10 weight[3] = 11 weight[4] = 8 weight[5] = 6 # Edges of the tree graph[1].append(2) graph[2].append(3) graph[2].append(4) graph[1].append(5) dfs(1, 1) print(ans[0]) # This code is contributed by # Surendra_Gangwar
C#
// C# implementation of the approach using System; using System.Collections.Generic; class GFG { static int maximum = int.MinValue, x, ans = int.MaxValue; static List<List<int>> graph = new List<List<int>>(); static List<int> weight = new List<int>(); // Function to perform dfs to find // the maximum value static void dfs(int node, int parent) { // If current value is less than // the current maximum if (maximum < (weight[node] ^ x)) { maximum = weight[node] ^ x; ans = node; } for (int i = 0; i < graph[node].Count; i++) { if (graph[node][i] == parent) continue; dfs(graph[node][i], node); } } // Driver code public static void Main() { x = 15; // Weights of the node weight.Add(0); weight.Add(5); weight.Add(10); weight.Add(11);; weight.Add(8); weight.Add(6); for(int i = 0; i < 100; i++) graph.Add(new List<int>()); // Edges of the tree graph[1].Add(2); graph[2].Add(3); graph[2].Add(4); graph[1].Add(5); dfs(1, 1); Console.Write( ans); } } // This code is contributed by SHUBHAMSINGH10
Javascript
<script> // Javascript implementation of the approach let maximum = Number.MIN_SAFE_INTEGER; let ans = []; let graph = new Array(); for(let i = 0; i < 100; i++){ graph.push(new Array().fill(0)); } let weight = new Array(100).fill(0); // Function to perform dfs to find // the maximum xored value function dfs(node, parent) { // If current value is less than // the current maximum if (maximum < (weight[node] ^ x)) { maximum = weight[node] ^ x; ans = node; } for (let to of graph[node]) { if (to == parent) continue; dfs(to, node); } } // Driver code let x = 15; // Weights of the node weight[1] = 5; weight[2] = 10; weight[3] = 11; weight[4] = 8; weight[5] = 6; // Edges of the tree graph[1].push(2); graph[2].push(3); graph[2].push(4); graph[1].push(5); dfs(1, 1); document.write(ans); // This code is contributed by gfgking </script>
Producción:
1
Análisis de Complejidad:
- Complejidad temporal: O(N).
En dfs, cada Node del árbol se procesa una vez y, por lo tanto, la complejidad debida a dfs es O(N) si hay un total de N Nodes en el árbol. Por lo tanto, la complejidad del tiempo es O(N). - Espacio Auxiliar : O(1).
No se requiere ningún espacio adicional, por lo que la complejidad del espacio es constante.
Publicación traducida automáticamente
Artículo escrito por mohit kumar 29 y traducido por Barcelona Geeks. The original can be accessed here. Licence: CCBY-SA