Impressió de la suma màxima en subseqüència creixent
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El problema de la subseqüència creixent de suma màxima és trobar la subseqüència de suma màxima d'una seqüència donada de manera que tots els elements de la subseqüència s'ordenin en ordre creixent.
Exemples:
Input: [1 101 2 3 100 4 5]
Output: [1 2 3 100]
Input: [3 4 5 10]
Output: [3 4 5 10]
Input: [10 5 4 3]
Output: [10]
Input: [3 2 6 4 5 1]
Output: [3 4 5]A la publicació anterior hem tractat el problema de la subseqüència creixent de la suma màxima. Tanmateix, la publicació només cobria codi relacionat amb la cerca de la suma màxima de la subseqüència creixent, però no amb la construcció de la subseqüència. En aquesta publicació parlarem de com construir una subseqüència creixent de suma màxima.
Sigui arr[0..n-1] la matriu d'entrada. Definim el vector L de manera que L[i] és en si mateix un vector que emmagatzema la subseqüència creixent de suma màxima de arr[0..i] que acaba amb arr[i]. Per tant, per a l'índex i L[i] es pot escriure recursivament com
L[0] = {arr[0]}
L[i] = {MaxSum(L[j])} + arr[i] where j < i and arr[j] < arr[i]
= arr[i] if there is no j such that arr[j] < arr[i]
Per exemple, per a la matriu [3 2 6 4 5 1]L[0]: 3
L[1]: 2
L[2]: 3 6
L[3]: 3 4
L[4]: 3 4 5
L[5]: 1C++
A continuació es mostra la implementació de la idea anterior:Java/* Dynamic Programming solution to construct Maximum Sum Increasing Subsequence */ #include#include using namespace std ; // Utility function to calculate sum of all // vector elements int findSum ( vector < int > arr ) { int sum = 0 ; for ( int i : arr ) sum += i ; return sum ; } // Function to construct Maximum Sum Increasing // Subsequence void printMaxSumIS ( int arr [] int n ) { // L[i] - The Maximum Sum Increasing // Subsequence that ends with arr[i] vector < vector < int > > L ( n ); // L[0] is equal to arr[0] L [ 0 ]. push_back ( arr [ 0 ]); // start from index 1 for ( int i = 1 ; i < n ; i ++ ) { // for every j less than i for ( int j = 0 ; j < i ; j ++ ) { /* L[i] = {MaxSum(L[j])} + arr[i] where j < i and arr[j] < arr[i] */ if (( arr [ i ] > arr [ j ]) && ( findSum ( L [ i ]) < findSum ( L [ j ]))) L [ i ] = L [ j ]; } // L[i] ends with arr[i] L [ i ]. push_back ( arr [ i ]); // L[i] now stores Maximum Sum Increasing // Subsequence of arr[0..i] that ends with // arr[i] } vector < int > res = L [ 0 ]; // find max for ( vector < int > x : L ) if ( findSum ( x ) > findSum ( res )) res = x ; // max will contain result for ( int i : res ) cout < < i < < ' ' ; cout < < endl ; } // Driver Code int main () { int arr [] = { 3 2 6 4 5 1 }; int n = sizeof ( arr ) / sizeof ( arr [ 0 ]); // construct and print Max Sum IS of arr printMaxSumIS ( arr n ); return 0 ; } Python/* Dynamic Programming solution to construct Maximum Sum Increasing Subsequence */ import java.util.* ; class GFG { // Utility function to calculate sum of all // vector elements static int findSum ( Vector < Integer > arr ) { int sum = 0 ; for ( int i : arr ) sum += i ; return sum ; } // Function to construct Maximum Sum Increasing // Subsequence static void printMaxSumIs ( int [] arr int n ) { // L[i] - The Maximum Sum Increasing // Subsequence that ends with arr[i] @SuppressWarnings ( 'unchecked' ) Vector < Integer >[] L = new Vector [ n ] ; for ( int i = 0 ; i < n ; i ++ ) L [ i ] = new Vector <> (); // L[0] is equal to arr[0] L [ 0 ] . add ( arr [ 0 ] ); // start from index 1 for ( int i = 1 ; i < n ; i ++ ) { // for every j less than i for ( int j = 0 ; j < i ; j ++ ) { /* * L[i] = {MaxSum(L[j])} + arr[i] where j < i and arr[j] < arr[i] */ if (( arr [ i ] > arr [ j ] ) && ( findSum ( L [ i ] ) < findSum ( L [ j ] ))) { for ( int k : L [ j ] ) if ( ! L [ i ] . contains ( k )) L [ i ] . add ( k ); } } // L[i] ends with arr[i] L [ i ] . add ( arr [ i ] ); // L[i] now stores Maximum Sum Increasing // Subsequence of arr[0..i] that ends with // arr[i] } Vector < Integer > res = new Vector <> ( L [ 0 ] ); // res = L[0]; // find max for ( Vector < Integer > x : L ) if ( findSum ( x ) > findSum ( res )) res = x ; // max will contain result for ( int i : res ) System . out . print ( i + ' ' ); System . out . println (); } // Driver Code public static void main ( String [] args ) { int [] arr = { 3 2 6 4 5 1 }; int n = arr . length ; // construct and print Max Sum IS of arr printMaxSumIs ( arr n ); } } // This code is contributed by // sanjeev2552C## Dynamic Programming solution to construct # Maximum Sum Increasing Subsequence */ # Utility function to calculate sum of all # vector elements def findSum ( arr ): summ = 0 for i in arr : summ += i return summ # Function to construct Maximum Sum Increasing # Subsequence def printMaxSumIS ( arr n ): # L[i] - The Maximum Sum Increasing # Subsequence that ends with arr[i] L = [[] for i in range ( n )] # L[0] is equal to arr[0] L [ 0 ] . append ( arr [ 0 ]) # start from index 1 for i in range ( 1 n ): # for every j less than i for j in range ( i ): # L[i] = {MaxSum(L[j])} + arr[i] # where j < i and arr[j] < arr[i] if (( arr [ i ] > arr [ j ]) and ( findSum ( L [ i ]) < findSum ( L [ j ]))): for e in L [ j ]: if e not in L [ i ]: L [ i ] . append ( e ) # L[i] ends with arr[i] L [ i ] . append ( arr [ i ]) # L[i] now stores Maximum Sum Increasing # Subsequence of arr[0..i] that ends with # arr[i] res = L [ 0 ] # find max for x in L : if ( findSum ( x ) > findSum ( res )): res = x # max will contain result for i in res : print ( i end = ' ' ) # Driver Code arr = [ 3 2 6 4 5 1 ] n = len ( arr ) # construct and prMax Sum IS of arr printMaxSumIS ( arr n ) # This code is contributed by Mohit KumarJavaScript/* Dynamic Programming solution to construct Maximum Sum Increasing Subsequence */ using System ; using System.Collections.Generic ; class GFG { // Utility function to calculate sum of all // vector elements static int findSum ( List < int > arr ) { int sum = 0 ; foreach ( int i in arr ) sum += i ; return sum ; } // Function to construct Maximum Sum Increasing // Subsequence static void printMaxSumIs ( int [] arr int n ) { // L[i] - The Maximum Sum Increasing // Subsequence that ends with arr[i] List < int > [] L = new List < int > [ n ]; for ( int i = 0 ; i < n ; i ++ ) L [ i ] = new List < int > (); // L[0] is equal to arr[0] L [ 0 ]. Add ( arr [ 0 ]); // start from index 1 for ( int i = 1 ; i < n ; i ++ ) { // for every j less than i for ( int j = 0 ; j < i ; j ++ ) { /* * L[i] = {MaxSum(L[j])} + arr[i] where j < i and arr[j] < arr[i] */ if (( arr [ i ] > arr [ j ]) && ( findSum ( L [ i ]) < findSum ( L [ j ]))) { foreach ( int k in L [ j ]) if ( ! L [ i ]. Contains ( k )) L [ i ] . Add ( k ); } } // L[i] ends with arr[i] L [ i ]. Add ( arr [ i ]); // L[i] now stores Maximum Sum Increasing // Subsequence of arr[0..i] that ends with // arr[i] } List < int > res = new List < int > ( L [ 0 ]); // res = L[0]; // find max foreach ( List < int > x in L ) if ( findSum ( x ) > findSum ( res )) res = x ; // max will contain result foreach ( int i in res ) Console . Write ( i + ' ' ); Console . WriteLine (); } // Driver Code public static void Main ( String [] args ) { int [] arr = { 3 2 6 4 5 1 }; int n = arr . Length ; // construct and print Max Sum IS of arr printMaxSumIs ( arr n ); } } // This code is contributed by PrinciRaj1992
' ); } // Driver Code let arr = [ 3 2 6 4 5 1 ]; let n = arr . length ; // construct and print Max Sum IS of arr printMaxSumIs ( arr n ); // This code is contributed by unknown2108 < /script>
Sortida3 4 5
Podem optimitzar la solució DP anterior eliminant la funció findSum(). En canvi, podem mantenir un altre vector/matriu per emmagatzemar la suma de la subseqüència creixent de la suma màxima que acaba amb arr[i].Complexitat temporal La solució de programació dinàmica anterior és O(n 2 ).
Espai auxiliar utilitzat pel programa és O(n 2 ).Enfocament 2: ( Utilitzant Programació dinàmica utilitzant l'espai O(N).
L'enfocament anterior va incloure com construir una subseqüència creixent de suma màxima en O (N 2 ) temps i O(N 2 ) espai. En aquest enfocament optimitzarem la complexitat de l'espai i construirem la subseqüència creixent de suma màxima en O(N 2 ) temps i espai O(N).
- Sigui arr[0..n-1] la matriu d'entrada.
- Definim un vector de parells L tal que L[i] primer emmagatzema la subseqüència creixent de suma màxima de arr[0..i] que acaba amb arr[i] i L[i].second emmagatzema l'índex de l'element anterior utilitzat per generar la suma.
- Com que el primer element no té cap element anterior, el seu índex seria -1 a L[0].
Per exemple
array = [3 2 6 4 5 1]
L[0]: {3 -1}
L[1]: {2 1}
L[2]: {9 0}
L[3]: {7 0}
L[4]: {12 3}
L[5]: {1 5}Com podem veure més amunt, el valor de la subseqüència creixent de suma màxima és 12. Per construir la subseqüència real utilitzarem l'índex emmagatzemat a L[i].segon. Els passos per construir la subseqüència es mostren a continuació:
- En un resultat vectorial emmagatzemeu el valor de l'element on es va trobar la subseqüència creixent de la suma màxima (és a dir, a currIndex = 4). Així que al vector de resultats afegirem arr[currIndex].
- Actualitzeu el currIndex a L[currIndex].segon i repetiu el pas 1 fins que currIndex no sigui -1 o no canviï (és a dir, currIndex == previousIndex).
- Mostra els elements del vector resultat en ordre invers.
A continuació es mostra la implementació de la idea anterior:
C++14 /* Dynamic Programming solution to construct Maximum Sum Increasing Subsequence */ #include using namespace std ; // Function to construct and print the Maximum Sum // Increasing Subsequence void constructMaxSumIS ( vector < int > arr int n ) { // L[i] stores the value of Maximum Sum Increasing // Subsequence that ends with arr[i] and the index of // previous element used to construct the Subsequence vector < pair < int int > > L ( n ); int index = 0 ; for ( int i : arr ) { L [ index ] = { i index }; index ++ ; } // Set L[0].second equal to -1 L [ 0 ]. second = -1 ; // start from index 1 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 ] and L [ i ]. first < arr [ i ] + L [ j ]. first ) { L [ i ]. first = arr [ i ] + L [ j ]. first ; L [ i ]. second = j ; } } } int maxi = INT_MIN currIndex track = 0 ; for ( auto p : L ) { if ( p . first > maxi ) { maxi = p . first ; currIndex = track ; } track ++ ; } // Stores the final Subsequence vector < int > result ; // Index of previous element // used to construct the Subsequence int prevoiusIndex ; while ( currIndex >= 0 ) { result . push_back ( arr [ currIndex ]); prevoiusIndex = L [ currIndex ]. second ; if ( currIndex == prevoiusIndex ) break ; currIndex = prevoiusIndex ; } for ( int i = result . size () - 1 ; i >= 0 ; i -- ) cout < < result [ i ] < < ' ' ; } // Driver Code int main () { vector < int > arr = { 1 101 2 3 100 4 5 }; int n = arr . size (); // Function call constructMaxSumIS ( arr n ); return 0 ; }
Java // Dynamic Programming solution to construct // Maximum Sum Increasing Subsequence import java.util.* ; import java.awt.Point ; class GFG { // Function to construct and print the Maximum Sum // Increasing Subsequence static void constructMaxSumIS ( List < Integer > arr int n ) { // L.get(i) stores the value of Maximum Sum Increasing // Subsequence that ends with arr.get(i) and the index of // previous element used to construct the Subsequence List < Point > L = new ArrayList < Point > (); int index = 0 ; for ( int i : arr ) { L . add ( new Point ( i index )); index ++ ; } // Set L[0].second equal to -1 L . set ( 0 new Point ( L . get ( 0 ). x - 1 )); // Start from index 1 for ( int i = 1 ; i < n ; i ++ ) { // For every j less than i for ( int j = 0 ; j < i ; j ++ ) { if ( arr . get ( i ) > arr . get ( j ) && L . get ( i ). x < arr . get ( i ) + L . get ( j ). x ) { L . set ( i new Point ( arr . get ( i ) + L . get ( j ). x j )); } } } int maxi = - 100000000 currIndex = 0 track = 0 ; for ( Point p : L ) { if ( p . x > maxi ) { maxi = p . x ; currIndex = track ; } track ++ ; } // Stores the final Subsequence List < Integer > result = new ArrayList < Integer > (); // Index of previous element // used to construct the Subsequence int prevoiusIndex ; while ( currIndex >= 0 ) { result . add ( arr . get ( currIndex )); prevoiusIndex = L . get ( currIndex ). y ; if ( currIndex == prevoiusIndex ) break ; currIndex = prevoiusIndex ; } for ( int i = result . size () - 1 ; i >= 0 ; i -- ) System . out . print ( result . get ( i ) + ' ' ); } // Driver Code public static void main ( String [] s ) { List < Integer > arr = new ArrayList < Integer > (); arr . add ( 1 ); arr . add ( 101 ); arr . add ( 2 ); arr . add ( 3 ); arr . add ( 100 ); arr . add ( 4 ); arr . add ( 5 ); int n = arr . size (); // Function call constructMaxSumIS ( arr n ); } } // This code is contributed by rutvik_56
Python # Dynamic Programming solution to construct # Maximum Sum Increasing Subsequence import sys # Function to construct and print the Maximum Sum # Increasing Subsequence def constructMaxSumIS ( arr n ) : # L[i] stores the value of Maximum Sum Increasing # Subsequence that ends with arr[i] and the index of # previous element used to construct the Subsequence L = [] index = 0 for i in arr : L . append ([ i index ]) index += 1 # Set L[0].second equal to -1 L [ 0 ][ 1 ] = - 1 # start from index 1 for i in range ( 1 n ) : # for every j less than i for j in range ( i ) : if ( arr [ i ] > arr [ j ] and L [ i ][ 0 ] < arr [ i ] + L [ j ][ 0 ]) : L [ i ][ 0 ] = arr [ i ] + L [ j ][ 0 ] L [ i ][ 1 ] = j maxi currIndex track = - sys . maxsize 0 0 for p in L : if ( p [ 0 ] > maxi ) : maxi = p [ 0 ] currIndex = track track += 1 # Stores the final Subsequence result = [] while ( currIndex >= 0 ) : result . append ( arr [ currIndex ]) prevoiusIndex = L [ currIndex ][ 1 ] if ( currIndex == prevoiusIndex ) : break currIndex = prevoiusIndex for i in range ( len ( result ) - 1 - 1 - 1 ) : print ( result [ i ] end = ' ' ) arr = [ 1 101 2 3 100 4 5 ] n = len ( arr ) # Function call constructMaxSumIS ( arr n ) # This code is contributed by divyeshrabadiya07
C# /* Dynamic Programming solution to construct Maximum Sum Increasing Subsequence */ using System ; using System.Collections.Generic ; class GFG { // Function to construct and print the Maximum Sum // Increasing Subsequence static void constructMaxSumIS ( List < int > arr int n ) { // L[i] stores the value of Maximum Sum Increasing // Subsequence that ends with arr[i] and the index of // previous element used to construct the Subsequence List < Tuple < int int >> L = new List < Tuple < int int >> (); int index = 0 ; foreach ( int i in arr ) { L . Add ( new Tuple < int int > ( i index )); index ++ ; } // Set L[0].second equal to -1 L [ 0 ] = new Tuple < int int > ( L [ 0 ]. Item1 - 1 ); // start from index 1 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 ] && L [ i ]. Item1 < arr [ i ] + L [ j ]. Item1 ) { L [ i ] = new Tuple < int int > ( arr [ i ] + L [ j ]. Item1 j ); } } } int maxi = Int32 . MinValue currIndex = 0 track = 0 ; foreach ( Tuple < int int > p in L ) { if ( p . Item1 > maxi ) { maxi = p . Item1 ; currIndex = track ; } track ++ ; } // Stores the final Subsequence List < int > result = new List < int > (); // Index of previous element // used to construct the Subsequence int prevoiusIndex ; while ( currIndex >= 0 ) { result . Add ( arr [ currIndex ]); prevoiusIndex = L [ currIndex ]. Item2 ; if ( currIndex == prevoiusIndex ) break ; currIndex = prevoiusIndex ; } for ( int i = result . Count - 1 ; i >= 0 ; i -- ) Console . Write ( result [ i ] + ' ' ); } static void Main () { List < int > arr = new List < int > ( new int [] { 1 101 2 3 100 4 5 }); int n = arr . Count ; // Function call constructMaxSumIS ( arr n ); } } // This code is contributed by divyesh072019
JavaScript < script > // Dynamic Programming solution to construct // Maximum Sum Increasing Subsequence // Function to construct and print the Maximum Sum // Increasing Subsequence function constructMaxSumIS ( arr n ){ // L[i] stores the value of Maximum Sum Increasing // Subsequence that ends with arr[i] and the index of // previous element used to construct the Subsequence let L = [] let index = 0 for ( let i of arr ){ L . push ([ i index ]) index += 1 } // Set L[0].second equal to -1 L [ 0 ][ 1 ] = - 1 // start from index 1 for ( let i = 1 ; i < n ; i ++ ){ // for every j less than i for ( let j = 0 ; j < i ; j ++ ){ if ( arr [ i ] > arr [ j ] && L [ i ][ 0 ] < arr [ i ] + L [ j ][ 0 ]){ L [ i ][ 0 ] = arr [ i ] + L [ j ][ 0 ] L [ i ][ 1 ] = j } } } let maxi = Number . MIN_VALUE currIndex = 0 track = 0 for ( let p of L ){ if ( p [ 0 ] > maxi ){ maxi = p [ 0 ] currIndex = track } track += 1 } // Stores the final Subsequence let result = [] while ( currIndex >= 0 ){ result . push ( arr [ currIndex ]) let prevoiusIndex = L [ currIndex ][ 1 ] if ( currIndex == prevoiusIndex ) break currIndex = prevoiusIndex } for ( let i = result . length - 1 ; i >= 0 ; i -- ) document . write ( result [ i ] ' ' ) } let arr = [ 1 101 2 3 100 4 5 ] let n = arr . length // Function call constructMaxSumIS ( arr n ) // This code is contributed by shinjanpatra < /script>
Sortida
1 2 3 100
Complexitat temporal: O(N 2 )
Complexitat espacial: O(N)
