Dado un vértice V de un árbol N-ario y un número entero K , la tarea es imprimir el Kth ancestro del vértice dado en el árbol. Si no existe ningún ancestro de este tipo, imprima -1 .
Ejemplos:
Entrada: K = 2, V = 4
Salida: 1
2º padre del vértice 4 es 1 .
Entrada: K = 3, V = 4
Salida: -1
Enfoque: La idea es utilizar la técnica de elevación binaria . Esta técnica se basa en el hecho de que todo número entero se puede representar en forma binaria. A través del preprocesamiento, se puede calcular una tabla dispersa table [v][i] que almacena el 2 i-ésimo padre del vértice v donde 0 ≤ i ≤ log 2 N . Este preprocesamiento lleva un tiempo O(NlogN) .
Para encontrar el K -ésimo padre del vértice V , sea K = b 0 b 1 b 2 …b n un nnúmero de bit en la representación binaria, sean p 1 , p 2 , p 3 , …, p j los índices donde el valor del bit es 1 , entonces K se puede representar como K = 2 p 1 + 2 p 2 + 2 p 3 + … + 2 p j . Así, para llegar al K -ésimo padre de V , tenemos que hacer saltos a 2 pth 1 , 2 pth 2 , 2 pth 3 hasta2 pth j padre en cualquier orden. Esto se puede hacer de manera eficiente a través de la tabla dispersa calculada anteriormente en O(logN) .
A continuación se muestra la implementación del enfoque anterior:
C++
// CPP implementation of the approach #include <bits/stdc++.h> using namespace std; // Table for storing 2^ith parent int **table; // To store the height of the tree int height; // initializing the table and // the height of the tree void initialize(int n) { height = (int)ceil(log2(n)); table = new int *[n + 1]; } // Filling with -1 as initial void preprocessing(int n) { for (int i = 0; i < n + 1; i++) { table[i] = new int[height + 1]; memset(table[i], -1, sizeof table[i]); } } // Calculating sparse table[][] dynamically void calculateSparse(int u, int v) { // Using the recurrence relation to // calculate the values of table[][] table[v][0] = u; for (int i = 1; i <= height; i++) { table[v][i] = table[table[v][i - 1]][i - 1]; // If we go out of bounds of the tree if (table[v][i] == -1) break; } } // Function to return the Kth ancestor of V int kthancestor(int V, int k) { // Doing bitwise operation to // check the set bit for (int i = 0; i <= height; i++) { if (k & (1 << i)) { V = table[V][i]; if (V == -1) break; } } return V; } // Driver Code int main() { // Number of vertices int n = 6; // initializing initialize(n); // Pre-processing preprocessing(n); // Calculating ancestors of v calculateSparse(1, 2); calculateSparse(1, 3); calculateSparse(2, 4); calculateSparse(2, 5); calculateSparse(3, 6); int K = 2, V = 5; cout << kthancestor(V, K) << endl; return 0; } // This code is contributed by // sanjeev2552
Java
// Java implementation of the approach import java.util.Arrays; class GfG { // Table for storing 2^ith parent private static int table[][]; // To store the height of the tree private static int height; // Private constructor for initializing // the table and the height of the tree private GfG(int n) { // log(n) with base 2 height = (int)Math.ceil(Math.log10(n) / Math.log10(2)); table = new int[n + 1][height + 1]; } // Filling with -1 as initial private static void preprocessing() { for (int i = 0; i < table.length; i++) { Arrays.fill(table[i], -1); } } // Calculating sparse table[][] dynamically private static void calculateSparse(int u, int v) { // Using the recurrence relation to // calculate the values of table[][] table[v][0] = u; for (int i = 1; i <= height; i++) { table[v][i] = table[table[v][i - 1]][i - 1]; // If we go out of bounds of the tree if (table[v][i] == -1) break; } } // Function to return the Kth ancestor of V private static int kthancestor(int V, int k) { // Doing bitwise operation to // check the set bit for (int i = 0; i <= height; i++) { if ((k & (1 << i)) != 0) { V = table[V][i]; if (V == -1) break; } } return V; } // Driver code public static void main(String args[]) { // Number of vertices int n = 6; // Calling the constructor GfG obj = new GfG(n); // Pre-processing preprocessing(); // Calculating ancestors of v calculateSparse(1, 2); calculateSparse(1, 3); calculateSparse(2, 4); calculateSparse(2, 5); calculateSparse(3, 6); int K = 2, V = 5; System.out.print(kthancestor(V, K)); } }
Python3
# Python3 implementation of the approach import math class GfG : # Private constructor for initializing # the table and the height of the tree def __init__(self, n): # log(n) with base 2 # To store the height of the tree self.height = int(math.ceil(math.log10(n) / math.log10(2))) # Table for storing 2^ith parent self.table = [0] * (n + 1) # Filling with -1 as initial def preprocessing(self): i = 0 while ( i < len(self.table)) : self.table[i] = [-1]*(self.height + 1) i = i + 1 # Calculating sparse table[][] dynamically def calculateSparse(self, u, v): # Using the recurrence relation to # calculate the values of table[][] self.table[v][0] = u i = 1 while ( i <= self.height) : self.table[v][i] = self.table[self.table[v][i - 1]][i - 1] # If we go out of bounds of the tree if (self.table[v][i] == -1): break i = i + 1 # Function to return the Kth ancestor of V def kthancestor(self, V, k): i = 0 # Doing bitwise operation to # check the set bit while ( i <= self.height) : if ((k & (1 << i)) != 0) : V = self.table[V][i] if (V == -1): break i = i + 1 return V # Driver code # Number of vertices n = 6 # Calling the constructor obj = GfG(n) # Pre-processing obj.preprocessing() # Calculating ancestors of v obj.calculateSparse(1, 2) obj.calculateSparse(1, 3) obj.calculateSparse(2, 4) obj.calculateSparse(2, 5) obj.calculateSparse(3, 6) K = 2 V = 5 print(obj.kthancestor(V, K)) # This code is contributed by Arnab Kundu
C#
// C# implementation of the approach using System; class GFG { class GfG { // Table for storing 2^ith parent private static int [,]table ; // To store the height of the tree private static int height; // Private constructor for initializing // the table and the height of the tree private GfG(int n) { // log(n) with base 2 height = (int)Math.Ceiling(Math.Log10(n) / Math.Log10(2)); table = new int[n + 1, height + 1]; } // Filling with -1 as initial private static void preprocessing() { for (int i = 0; i < table.GetLength(0); i++) { for (int j = 0; j < table.GetLength(1); j++) { table[i, j] = -1; } } } // Calculating sparse table[,] dynamically private static void calculateSparse(int u, int v) { // Using the recurrence relation to // calculate the values of table[,] table[v, 0] = u; for (int i = 1; i <= height; i++) { table[v, i] = table[table[v, i - 1], i - 1]; // If we go out of bounds of the tree if (table[v, i] == -1) break; } } // Function to return the Kth ancestor of V private static int kthancestor(int V, int k) { // Doing bitwise operation to // check the set bit for (int i = 0; i <= height; i++) { if ((k & (1 << i)) != 0) { V = table[V, i]; if (V == -1) break; } } return V; } // Driver code public static void Main() { // Number of vertices int n = 6; // Calling the constructor GfG obj = new GfG(n); // Pre-processing preprocessing(); // Calculating ancestors of v calculateSparse(1, 2); calculateSparse(1, 3); calculateSparse(2, 4); calculateSparse(2, 5); calculateSparse(3, 6); int K = 2, V = 5; Console.Write(kthancestor(V, K)); } } } // This code is contributed by AnkitRai01
Javascript
<script> // Javascript implementation of the approach // Table for storing 2^ith parent let table; // To store the height of the tree let height; // initializing the table and // the height of the tree function initialize(n) { height = Math.ceil(Math.log2(n)); } // Filling with -1 as initial function preprocessing() { table = new Array(n + 1); for (let i = 0; i < n + 1; i++) { table[i] = new Array(height + 1); for (let j = 0; j < height + 1; j++) { table[i][j] = -1; } } } // Calculating sparse table[][] dynamically function calculateSparse(u, v) { // Using the recurrence relation to // calculate the values of table[][] table[v][0] = u; for (let i = 1; i <= height; i++) { table[v][i] = table[table[v][i - 1]][i - 1]; // If we go out of bounds of the tree if (table[v][i] == -1) break; } } // Function to return the Kth ancestor of V function kthancestor(V, k) { // Doing bitwise operation to // check the set bit for (let i = 0; i <= height; i++) { if ((k & (1 << i)) != 0) { V = table[V][i]; if (V == -1) break; } } return V; } // Number of vertices let n = 6; // Calling the constructor initialize(n); // Pre-processing preprocessing(); // Calculating ancestors of v calculateSparse(1, 2); calculateSparse(1, 3); calculateSparse(2, 4); calculateSparse(2, 5); calculateSparse(3, 6); let K = 2, V = 5; document.write(kthancestor(V, K)); // This code is contributed by divyeshrabadiya07. </script>
1
Complejidad de tiempo: O (NlogN) para preprocesamiento y logN para encontrar el antepasado.
Publicación traducida automáticamente
Artículo escrito por ishan_trivedi y traducido por Barcelona Geeks. The original can be accessed here. Licence: CCBY-SA