Impresión de la subsecuencia bitónica más larga
El problema de la subsecuencia bitónica más larga consiste en encontrar la subsecuencia más larga de una secuencia dada de modo que primero aumente y luego decrezca. Una secuencia ordenada en orden creciente se considera bitónica con la parte decreciente vacía. De manera similar, la secuencia de orden decreciente se considera bitónica con la parte creciente vacía. Ejemplos:
Input: [1 11 2 10 4 5 2 1] Output: [1 2 10 4 2 1] OR [1 11 10 5 2 1] OR [1 2 4 5 2 1] Input: [12 11 40 5 3 1] Output: [12 11 5 3 1] OR [12 40 5 3 1] Input: [80 60 30 40 20 10] Output: [80 60 30 20 10] OR [80 60 40 20 10]
En anterior publicación que hemos discutido sobre el problema de la subsecuencia bitónica más larga. Sin embargo, la publicación solo cubría el código relacionado con encontrar la suma máxima de una subsecuencia creciente, pero no con la construcción de una subsecuencia. En esta publicación discutiremos cómo construir la propia subsecuencia bitónica más larga. Sea arr[0..n-1] la matriz de entrada. Definimos el vector LIS de manera que LIS[i] sea en sí mismo un vector que almacena la subsecuencia creciente más larga de arr[0..i] que termina con arr[i]. Por lo tanto, para un índice i, LIS[i] se puede escribir de forma recursiva como:
LIS[0] = {arr[O]} LIS[i] = {Max(LIS[j])} + arr[i] where j < i and arr[j] < arr[i] = arr[i] if there is no such j También definimos un vector LDS tal que LDS[i] es en sí mismo un vector que almacena la subsecuencia decreciente más larga de arr[i..n] que comienza con arr[i]. Por lo tanto, para un índice i, LDS[i] se puede escribir de forma recursiva como:
LDS[n] = {arr[n]} LDS[i] = arr[i] + {Max(LDS[j])} where j > i and arr[j] < arr[i] = arr[i] if there is no such j Por ejemplo, para la matriz [1 11 2 10 4 5 2 1]
LIS[0]: 1 LIS[1]: 1 11 LIS[2]: 1 2 LIS[3]: 1 2 10 LIS[4]: 1 2 4 LIS[5]: 1 2 4 5 LIS[6]: 1 2 LIS[7]: 1
LDS[0]: 1 LDS[1]: 11 10 5 2 1 LDS[2]: 2 1 LDS[3]: 10 5 2 1 LDS[4]: 4 2 1 LDS[5]: 5 2 1 LDS[6]: 2 1 LDS[7]: 1
Por lo tanto, la subsecuencia bitónica más larga puede ser
LIS[1] + LDS[1] = [1 11 10 5 2 1] OR LIS[3] + LDS[3] = [1 2 10 5 2 1] OR LIS[5] + LDS[5] = [1 2 4 5 2 1]
A continuación se muestra la implementación de la idea anterior:
C++ /* Dynamic Programming solution to print Longest Bitonic Subsequence */ #include using namespace std ; // Utility function to print Longest Bitonic // Subsequence void print ( vector < int >& arr int size ) { for ( int i = 0 ; i < size ; i ++ ) cout < < arr [ i ] < < ' ' ; } // Function to construct and print Longest // Bitonic Subsequence void printLBS ( int arr [] int n ) { // LIS[i] stores the length of the longest // increasing subsequence ending with arr[i] vector < vector < int >> LIS ( n ); // initialize LIS[0] to arr[0] LIS [ 0 ]. push_back ( arr [ 0 ]); // Compute LIS values from left to right for ( int i = 1 ; i < n ; i ++ ) { // for every j less than i for ( int j = 0 ; j < i ; j ++ ) { if (( arr [ j ] < arr [ i ]) && ( LIS [ j ]. size () > LIS [ i ]. size ())) LIS [ i ] = LIS [ j ]; } LIS [ i ]. push_back ( arr [ i ]); } /* LIS[i] now stores Maximum Increasing Subsequence of arr[0..i] that ends with arr[i] */ // LDS[i] stores the length of the longest // decreasing subsequence starting with arr[i] vector < vector < int >> LDS ( n ); // initialize LDS[n-1] to arr[n-1] LDS [ n - 1 ]. push_back ( arr [ n - 1 ]); // Compute LDS values from right to left for ( int i = n - 2 ; i >= 0 ; i -- ) { // for every j greater than i for ( int j = n - 1 ; j > i ; j -- ) { if (( arr [ j ] < arr [ i ]) && ( LDS [ j ]. size () > LDS [ i ]. size ())) LDS [ i ] = LDS [ j ]; } LDS [ i ]. push_back ( arr [ i ]); } // reverse as vector as we're inserting at end for ( int i = 0 ; i < n ; i ++ ) reverse ( LDS [ i ]. begin () LDS [ i ]. end ()); /* LDS[i] now stores Maximum Decreasing Subsequence of arr[i..n] that starts with arr[i] */ int max = 0 ; int maxIndex = -1 ; for ( int i = 0 ; i < n ; i ++ ) { // Find maximum value of size of LIS[i] + size // of LDS[i] - 1 if ( LIS [ i ]. size () + LDS [ i ]. size () - 1 > max ) { max = LIS [ i ]. size () + LDS [ i ]. size () - 1 ; maxIndex = i ; } } // print all but last element of LIS[maxIndex] vector print ( LIS [ maxIndex ] LIS [ maxIndex ]. size () - 1 ); // print all elements of LDS[maxIndex] vector print ( LDS [ maxIndex ] LDS [ maxIndex ]. size ()); } // Driver program int main () { int arr [] = { 1 11 2 10 4 5 2 1 }; int n = sizeof ( arr ) / sizeof ( arr [ 0 ]); printLBS ( arr n ); return 0 ; }
Java /* Dynamic Programming solution to print Longest Bitonic Subsequence */ import java.util.* ; class GFG { // Utility function to print Longest Bitonic // Subsequence static void print ( Vector < Integer > arr int size ) { for ( int i = 0 ; i < size ; i ++ ) System . out . print ( arr . elementAt ( i ) + ' ' ); } // Function to construct and print Longest // Bitonic Subsequence static void printLBS ( int [] arr int n ) { // LIS[i] stores the length of the longest // increasing subsequence ending with arr[i] @SuppressWarnings ( 'unchecked' ) Vector < Integer >[] LIS = new Vector [ n ] ; for ( int i = 0 ; i < n ; i ++ ) LIS [ i ] = new Vector <> (); // initialize LIS[0] to arr[0] LIS [ 0 ] . add ( arr [ 0 ] ); // Compute LIS values from left to right for ( int i = 1 ; i < n ; i ++ ) { // for every j less than i for ( int j = 0 ; j < i ; j ++ ) { if (( arr [ i ] > arr [ j ] ) && LIS [ j ] . size () > LIS [ i ] . size ()) { for ( int k : LIS [ j ] ) if ( ! LIS [ i ] . contains ( k )) LIS [ i ] . add ( k ); } } LIS [ i ] . add ( arr [ i ] ); } /* * LIS[i] now stores Maximum Increasing Subsequence * of arr[0..i] that ends with arr[i] */ // LDS[i] stores the length of the longest // decreasing subsequence starting with arr[i] @SuppressWarnings ( 'unchecked' ) Vector < Integer >[] LDS = new Vector [ n ] ; for ( int i = 0 ; i < n ; i ++ ) LDS [ i ] = new Vector <> (); // initialize LDS[n-1] to arr[n-1] LDS [ n - 1 ] . add ( arr [ n - 1 ] ); // Compute LDS values from right to left for ( int i = n - 2 ; i >= 0 ; i -- ) { // for every j greater than i for ( int j = n - 1 ; j > i ; j -- ) { if ( arr [ j ] < arr [ i ] && LDS [ j ] . size () > LDS [ i ] . size ()) for ( int k : LDS [ j ] ) if ( ! LDS [ i ] . contains ( k )) LDS [ i ] . add ( k ); } LDS [ i ] . add ( arr [ i ] ); } // reverse as vector as we're inserting at end for ( int i = 0 ; i < n ; i ++ ) Collections . reverse ( LDS [ i ] ); /* * LDS[i] now stores Maximum Decreasing Subsequence * of arr[i..n] that starts with arr[i] */ int max = 0 ; int maxIndex = - 1 ; for ( int i = 0 ; i < n ; i ++ ) { // Find maximum value of size of // LIS[i] + size of LDS[i] - 1 if ( LIS [ i ] . size () + LDS [ i ] . size () - 1 > max ) { max = LIS [ i ] . size () + LDS [ i ] . size () - 1 ; maxIndex = i ; } } // print all but last element of LIS[maxIndex] vector print ( LIS [ maxIndex ] LIS [ maxIndex ] . size () - 1 ); // print all elements of LDS[maxIndex] vector print ( LDS [ maxIndex ] LDS [ maxIndex ] . size ()); } // Driver Code public static void main ( String [] args ) { int [] arr = { 1 11 2 10 4 5 2 1 }; int n = arr . length ; printLBS ( arr n ); } } // This code is contributed by // sanjeev2552
Python3 # Dynamic Programming solution to print Longest # Bitonic Subsequence def _print ( arr : list size : int ): for i in range ( size ): print ( arr [ i ] end = ' ' ) # Function to construct and print Longest # Bitonic Subsequence def printLBS ( arr : list n : int ): # LIS[i] stores the length of the longest # increasing subsequence ending with arr[i] LIS = [ 0 ] * n for i in range ( n ): LIS [ i ] = [] # initialize LIS[0] to arr[0] LIS [ 0 ] . append ( arr [ 0 ]) # Compute LIS values from left to right for i in range ( 1 n ): # for every j less than i for j in range ( i ): if (( arr [ j ] < arr [ i ]) and ( len ( LIS [ j ]) > len ( LIS [ i ]))): LIS [ i ] = LIS [ j ] . copy () LIS [ i ] . append ( arr [ i ]) # LIS[i] now stores Maximum Increasing # Subsequence of arr[0..i] that ends with # arr[i] # LDS[i] stores the length of the longest # decreasing subsequence starting with arr[i] LDS = [ 0 ] * n for i in range ( n ): LDS [ i ] = [] # initialize LDS[n-1] to arr[n-1] LDS [ n - 1 ] . append ( arr [ n - 1 ]) # Compute LDS values from right to left for i in range ( n - 2 - 1 - 1 ): # for every j greater than i for j in range ( n - 1 i - 1 ): if (( arr [ j ] < arr [ i ]) and ( len ( LDS [ j ]) > len ( LDS [ i ]))): LDS [ i ] = LDS [ j ] . copy () LDS [ i ] . append ( arr [ i ]) # reverse as vector as we're inserting at end for i in range ( n ): LDS [ i ] = list ( reversed ( LDS [ i ])) # LDS[i] now stores Maximum Decreasing Subsequence # of arr[i..n] that starts with arr[i] max = 0 maxIndex = - 1 for i in range ( n ): # Find maximum value of size of LIS[i] + size # of LDS[i] - 1 if ( len ( LIS [ i ]) + len ( LDS [ i ]) - 1 > max ): max = len ( LIS [ i ]) + len ( LDS [ i ]) - 1 maxIndex = i # print all but last element of LIS[maxIndex] vector _print ( LIS [ maxIndex ] len ( LIS [ maxIndex ]) - 1 ) # print all elements of LDS[maxIndex] vector _print ( LDS [ maxIndex ] len ( LDS [ maxIndex ])) # Driver Code if __name__ == '__main__' : arr = [ 1 11 2 10 4 5 2 1 ] n = len ( arr ) printLBS ( arr n ) # This code is contributed by # sanjeev2552
C# /* Dynamic Programming solution to print longest Bitonic Subsequence */ using System ; using System.Linq ; using System.Collections.Generic ; class GFG { // Utility function to print longest Bitonic // Subsequence static void print ( List < int > arr int size ) { for ( int i = 0 ; i < size ; i ++ ) Console . Write ( arr [ i ] + ' ' ); } // Function to construct and print longest // Bitonic Subsequence static void printLBS ( int [] arr int n ) { // LIS[i] stores the length of the longest // increasing subsequence ending with arr[i] List < int > [] LIS = new List < int > [ n ]; for ( int i = 0 ; i < n ; i ++ ) LIS [ i ] = new List < int > (); // initialize LIS[0] to arr[0] LIS [ 0 ]. Add ( arr [ 0 ]); // Compute LIS values from left to right for ( int i = 1 ; i < n ; i ++ ) { // for every j less than i for ( int j = 0 ; j < i ; j ++ ) { if (( arr [ i ] > arr [ j ]) && LIS [ j ]. Count > LIS [ i ]. Count ) { foreach ( int k in LIS [ j ]) if ( ! LIS [ i ]. Contains ( k )) LIS [ i ]. Add ( k ); } } LIS [ i ]. Add ( arr [ i ]); } /* * LIS[i] now stores Maximum Increasing Subsequence * of arr[0..i] that ends with arr[i] */ // LDS[i] stores the length of the longest // decreasing subsequence starting with arr[i] List < int > [] LDS = new List < int > [ n ]; for ( int i = 0 ; i < n ; i ++ ) LDS [ i ] = new List < int > (); // initialize LDS[n-1] to arr[n-1] LDS [ n - 1 ]. Add ( arr [ n - 1 ]); // Compute LDS values from right to left for ( int i = n - 2 ; i >= 0 ; i -- ) { // for every j greater than i for ( int j = n - 1 ; j > i ; j -- ) { if ( arr [ j ] < arr [ i ] && LDS [ j ]. Count > LDS [ i ]. Count ) foreach ( int k in LDS [ j ]) if ( ! LDS [ i ]. Contains ( k )) LDS [ i ]. Add ( k ); } LDS [ i ]. Add ( arr [ i ]); } // reverse as vector as we're inserting at end for ( int i = 0 ; i < n ; i ++ ) LDS [ i ]. Reverse (); /* * LDS[i] now stores Maximum Decreasing Subsequence * of arr[i..n] that starts with arr[i] */ int max = 0 ; int maxIndex = - 1 ; for ( int i = 0 ; i < n ; i ++ ) { // Find maximum value of size of // LIS[i] + size of LDS[i] - 1 if ( LIS [ i ]. Count + LDS [ i ]. Count - 1 > max ) { max = LIS [ i ]. Count + LDS [ i ]. Count - 1 ; maxIndex = i ; } } // print all but last element of LIS[maxIndex] vector print ( LIS [ maxIndex ] LIS [ maxIndex ]. Count - 1 ); // print all elements of LDS[maxIndex] vector print ( LDS [ maxIndex ] LDS [ maxIndex ]. Count ); } // Driver Code public static void Main ( String [] args ) { int [] arr = { 1 11 2 10 4 5 2 1 }; int n = arr . Length ; printLBS ( arr n ); } } // This code is contributed by PrinciRaj1992
JavaScript // Function to print the longest bitonic subsequence function _print ( arr size ) { for ( let i = 0 ; i < size ; i ++ ) { process . stdout . write ( arr [ i ] + ' ' ); } } // Function to construct and print the longest bitonic subsequence function printLBS ( arr n ) { // LIS[i] stores the length of the longest increasing subsequence ending with arr[i] let LIS = new Array ( n ); for ( let i = 0 ; i < n ; i ++ ) { LIS [ i ] = []; } // initialize LIS[0] to arr[0] LIS [ 0 ]. push ( arr [ 0 ]); // Compute LIS values from left to right for ( let i = 1 ; i < n ; i ++ ) { // for every j less than i for ( let j = 0 ; j < i ; j ++ ) { if ( arr [ j ] < arr [ i ] && LIS [ j ]. length > LIS [ i ]. length ) { LIS [ i ] = LIS [ j ]. slice (); } } LIS [ i ]. push ( arr [ i ]); } // LIS[i] now stores the Maximum Increasing Subsequence of arr[0..i] that ends with arr[i] // LDS[i] stores the length of the longest decreasing subsequence starting with arr[i] let LDS = new Array ( n ); for ( let i = 0 ; i < n ; i ++ ) { LDS [ i ] = []; } // initialize LDS[n-1] to arr[n-1] LDS [ n - 1 ]. push ( arr [ n - 1 ]); // Compute LDS values from right to left for ( let i = n - 2 ; i >= 0 ; i -- ) { // for every j greater than i for ( let j = n - 1 ; j > i ; j -- ) { if ( arr [ j ] < arr [ i ] && LDS [ j ]. length > LDS [ i ]. length ) { LDS [ i ] = LDS [ j ]. slice (); } } LDS [ i ]. push ( arr [ i ]); } // reverse the LDS vector as we're inserting at the end for ( let i = 0 ; i < n ; i ++ ) { LDS [ i ]. reverse (); } // LDS[i] now stores the Maximum Decreasing Subsequence of arr[i..n] that starts with arr[i] let max = 0 ; let maxIndex = - 1 ; for ( let i = 0 ; i < n ; i ++ ) { // Find maximum value of size of LIS[i] + size of LDS[i] - 1 if ( LIS [ i ]. length + LDS [ i ]. length - 1 > max ) { max = LIS [ i ]. length + LDS [ i ]. length - 1 ; maxIndex = i ; } } // print all but // print all but last element of LIS[maxIndex] array _print ( LIS [ maxIndex ]. slice ( 0 - 1 ) LIS [ maxIndex ]. length - 1 ); // print all elements of LDS[maxIndex] array _print ( LDS [ maxIndex ] LDS [ maxIndex ]. length ); } // Driver program const arr = [ 1 11 2 10 4 5 2 1 ]; const n = arr . length ; printLBS ( arr n );
Producción:
1 11 10 5 2 1
Complejidad del tiempo de la solución de programación dinámica anterior es O (n 2 ). Espacio auxiliar utilizado por el programa es O(n 2 ).
