Største sum sammenhængende stigende subarray
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#practiceLinkDiv { display: ingen !important; }
#practiceLinkDiv { display: ingen !important; } Givet en matrix af n positive distinkte heltal. Problemet er at finde den største sum af sammenhængende stigende subarray i O(n) tidskompleksitet.
Eksempler:
Input : arr[] = {2 1 4 7 3 6}
Output : 12
Contiguous Increasing subarray {1 4 7} = 12
Input : arr[] = {38 7 8 10 12}
Output : 38
Recommended Practice Grådige ræv Prøv det!EN enkel løsning er til generere alle underarrays og beregne deres beløb. Til sidst returnerer subarrayet med maksimal sum. Tidskompleksiteten af denne løsning er O(n 2 ).
An effektiv løsning er baseret på, at alle elementer er positive. Så vi overvejer længst voksende subarrays og sammenligner deres summer. Til stigende subarrays kan ikke overlappe, så vores tidskompleksitet bliver O(n).
Algoritme:
Let arr be the array of size n
Let result be the required sum
int largestSum(arr n)
result = INT_MIN // Initialize result
i = 0
while i < n
// Find sum of longest increasing subarray
// starting with i
curr_sum = arr[i];
while i+1 < n && arr[i] < arr[i+1]
curr_sum += arr[i+1];
i++;
// If current sum is greater than current
// result.
if result < curr_sum
result = curr_sum;
i++;
return result
Nedenfor er implementeringen af ovenstående algoritme.
C++Java// C++ implementation of largest sum // contiguous increasing subarray #includeusing namespace std ; // Returns sum of longest // increasing subarray. int largestSum ( int arr [] int n ) { // Initialize result int result = INT_MIN ; // Note that i is incremented // by inner loop also so overall // time complexity is O(n) for ( int i = 0 ; i < n ; i ++ ) { // Find sum of longest // increasing subarray // starting from arr[i] int curr_sum = arr [ i ]; while ( i + 1 < n && arr [ i + 1 ] > arr [ i ]) { curr_sum += arr [ i + 1 ]; i ++ ; } // Update result if required if ( curr_sum > result ) result = curr_sum ; } // required largest sum return result ; } // Driver Code int main () { int arr [] = { 1 1 4 7 3 6 }; int n = sizeof ( arr ) / sizeof ( arr [ 0 ]); cout < < 'Largest sum = ' < < largestSum ( arr n ); return 0 ; } Python3// Java implementation of largest sum // contiguous increasing subarray class GFG { // Returns sum of longest // increasing subarray. static int largestSum ( int arr [] int n ) { // Initialize result int result = - 9999999 ; // Note that i is incremented // by inner loop also so overall // time complexity is O(n) for ( int i = 0 ; i < n ; i ++ ) { // Find sum of longest // increasing subarray // starting from arr[i] int curr_sum = arr [ i ] ; while ( i + 1 < n && arr [ i + 1 ] > arr [ i ] ) { curr_sum += arr [ i + 1 ] ; i ++ ; } // Update result if required if ( curr_sum > result ) result = curr_sum ; } // required largest sum return result ; } // Driver Code public static void main ( String [] args ) { int arr [] = { 1 1 4 7 3 6 }; int n = arr . length ; System . out . println ( 'Largest sum = ' + largestSum ( arr n )); } }C## Python3 implementation of largest # sum contiguous increasing subarray # Returns sum of longest # increasing subarray. def largestSum ( arr n ): # Initialize result result = - 2147483648 # Note that i is incremented # by inner loop also so overall # time complexity is O(n) for i in range ( n ): # Find sum of longest increasing # subarray starting from arr[i] curr_sum = arr [ i ] while ( i + 1 < n and arr [ i + 1 ] > arr [ i ]): curr_sum += arr [ i + 1 ] i += 1 # Update result if required if ( curr_sum > result ): result = curr_sum # required largest sum return result # Driver Code arr = [ 1 1 4 7 3 6 ] n = len ( arr ) print ( 'Largest sum = ' largestSum ( arr n )) # This code is contributed by Anant Agarwal.JavaScript// C# implementation of largest sum // contiguous increasing subarray using System ; class GFG { // Returns sum of longest // increasing subarray. static int largestSum ( int [] arr int n ) { // Initialize result int result = - 9999999 ; // Note that i is incremented by // inner loop also so overall // time complexity is O(n) for ( int i = 0 ; i < n ; i ++ ) { // Find sum of longest increasing // subarray starting from arr[i] int curr_sum = arr [ i ]; while ( i + 1 < n && arr [ i + 1 ] > arr [ i ]) { curr_sum += arr [ i + 1 ]; i ++ ; } // Update result if required if ( curr_sum > result ) result = curr_sum ; } // required largest sum return result ; } // Driver code public static void Main () { int [] arr = { 1 1 4 7 3 6 }; int n = arr . Length ; Console . Write ( 'Largest sum = ' + largestSum ( arr n )); } } // This code is contributed // by Nitin Mittal.PHP< script > // Javascript implementation of largest sum // contiguous increasing subarray // Returns sum of longest // increasing subarray. function largestSum ( arr n ) { // Initialize result var result = - 1000000000 ; // Note that i is incremented // by inner loop also so overall // time complexity is O(n) for ( var i = 0 ; i < n ; i ++ ) { // Find sum of longest // increasing subarray // starting from arr[i] var curr_sum = arr [ i ]; while ( i + 1 < n && arr [ i + 1 ] > arr [ i ]) { curr_sum += arr [ i + 1 ]; i ++ ; } // Update result if required if ( curr_sum > result ) result = curr_sum ; } // required largest sum return result ; } // Driver Code var arr = [ 1 1 4 7 3 6 ]; var n = arr . length ; document . write ( 'Largest sum = ' + largestSum ( arr n )); // This code is contributed by itsok. < /script>
ProduktionLargest sum = 12Tidskompleksitet: O(n)
Største sum sammenhængende stigende subarray Bruger Rekursion :
Rekursiv algoritme til at løse dette problem:
Her er trin-for-trin algoritmen for problemet:
- Funktionen 'største Sum' tager array 'arr' og dens størrelse er 'n'.
- Hvis 'n==1' vend derefter tilbage arr[0]th element.
- Hvis 'n != 1' derefter et rekursivt kald til funktionen 'største Sum' for at finde den største sum af underarrayet 'arr[0...n-1]' eksklusive det sidste element 'arr[n-1]' .
- Ved at iterere over arrayet i omvendt rækkefølge begyndende med det næstsidste element, beregnes summen af det stigende underarray, der slutter kl. 'arr[n-1]' . Hvis et element er mindre end det næste, skal det lægges til den aktuelle sum. Ellers skulle løkken brydes.
- Returner derefter maksimum af den største sum dvs. ' return max(max_sum curr_sum);' .
Her er implementeringen af ovenstående algoritme:
C++C#includeusing namespace std ; // Recursive function to find the largest sum // of contiguous increasing subarray int largestSum ( int arr [] int n ) { // Base case if ( n == 1 ) return arr [ 0 ]; // Recursive call to find the largest sum int max_sum = max ( largestSum ( arr n - 1 ) arr [ n - 1 ]); // Compute the sum of the increasing subarray int curr_sum = arr [ n - 1 ]; for ( int i = n - 2 ; i >= 0 ; i -- ) { if ( arr [ i ] < arr [ i + 1 ]) curr_sum += arr [ i ]; else break ; } // Return the maximum of the largest sum so far // and the sum of the current increasing subarray return max ( max_sum curr_sum ); } // Driver Code int main () { int arr [] = { 1 1 4 7 3 6 }; int n = sizeof ( arr ) / sizeof ( arr [ 0 ]); cout < < 'Largest sum = ' < < largestSum ( arr n ); return 0 ; } // This code is contributed by Vaibhav Saroj. Java#include#include // Returns sum of longest increasing subarray int largestSum ( int arr [] int n ) { // Initialize result int result = INT_MIN ; // Note that i is incremented // by inner loop also so overall // time complexity is O(n) for ( int i = 0 ; i < n ; i ++ ) { // Find sum of longest // increasing subarray // starting from arr[i] int curr_sum = arr [ i ]; while ( i + 1 < n && arr [ i + 1 ] > arr [ i ]) { curr_sum += arr [ i + 1 ]; i ++ ; } // Update result if required if ( curr_sum > result ) result = curr_sum ; } // required largest sum return result ; } // Driver code int main () { int arr [] = { 1 1 4 7 3 6 }; int n = sizeof ( arr ) / sizeof ( arr [ 0 ]); printf ( 'Largest sum = %d n ' largestSum ( arr n )); return 0 ; } // This code is contributed by Vaibhav Saroj. Python/*package whatever //do not write package name here */ import java.util.* ; public class Main { // Recursive function to find the largest sum // of contiguous increasing subarray public static int largestSum ( int arr [] int n ) { // Base case if ( n == 1 ) return arr [ 0 ] ; // Recursive call to find the largest sum int max_sum = Math . max ( largestSum ( arr n - 1 ) arr [ n - 1 ] ); // Compute the sum of the increasing subarray int curr_sum = arr [ n - 1 ] ; for ( int i = n - 2 ; i >= 0 ; i -- ) { if ( arr [ i ] < arr [ i + 1 ] ) curr_sum += arr [ i ] ; else break ; } // Return the maximum of the largest sum so far // and the sum of the current increasing subarray return Math . max ( max_sum curr_sum ); } // Driver code public static void main ( String [] args ) { int arr [] = { 1 1 4 7 3 6 }; int n = arr . length ; System . out . println ( 'Largest sum = ' + largestSum ( arr n )); } } // This code is contributed by Vaibhav Saroj.C#def largestSum ( arr n ): # Base case if n == 1 : return arr [ 0 ] # Recursive call to find the largest sum max_sum = max ( largestSum ( arr n - 1 ) arr [ n - 1 ]) # Compute the sum of the increasing subarray curr_sum = arr [ n - 1 ] for i in range ( n - 2 - 1 - 1 ): if arr [ i ] < arr [ i + 1 ]: curr_sum += arr [ i ] else : break # Return the maximum of the largest sum so far # and the sum of the current increasing subarray return max ( max_sum curr_sum ) # Driver code arr = [ 1 1 4 7 3 6 ] n = len ( arr ) print ( 'Largest sum =' largestSum ( arr n )) # This code is contributed by Vaibhav Saroj.JavaScript// C# program for above approach using System ; public static class GFG { // Recursive function to find the largest sum // of contiguous increasing subarray public static int largestSum ( int [] arr int n ) { // Base case if ( n == 1 ) return arr [ 0 ]; // Recursive call to find the largest sum int max_sum = Math . Max ( largestSum ( arr n - 1 ) arr [ n - 1 ]); // Compute the sum of the increasing subarray int curr_sum = arr [ n - 1 ]; for ( int i = n - 2 ; i >= 0 ; i -- ) { if ( arr [ i ] < arr [ i + 1 ]) curr_sum += arr [ i ]; else break ; } // Return the maximum of the largest sum so far // and the sum of the current increasing subarray return Math . Max ( max_sum curr_sum ); } // Driver code public static void Main () { int [] arr = { 1 1 4 7 3 6 }; int n = arr . Length ; Console . WriteLine ( 'Largest sum = ' + largestSum ( arr n )); } } // This code is contributed by Utkarsh KumarPHPfunction largestSum ( arr n ) { // Base case if ( n == 1 ) return arr [ 0 ]; // Recursive call to find the largest sum let max_sum = Math . max ( largestSum ( arr n - 1 ) arr [ n - 1 ]); // Compute the sum of the increasing subarray let curr_sum = arr [ n - 1 ]; for ( let i = n - 2 ; i >= 0 ; i -- ) { if ( arr [ i ] < arr [ i + 1 ]) curr_sum += arr [ i ]; else break ; } // Return the maximum of the largest sum so far // and the sum of the current increasing subarray return Math . max ( max_sum curr_sum ); } // Driver Code let arr = [ 1 1 4 7 3 6 ]; let n = arr . length ; console . log ( 'Largest sum = ' + largestSum ( arr n ));
ProduktionLargest sum = 12Tidskompleksitet: O(n^2).
Rumkompleksitet: På).Største sum sammenhængende stigende subarray ved hjælp af Kadanes algoritme:-
For at få den største sum-subarray anvendes Kadanes tilgang, men det forudsætter, at arrayet indeholder både positive og negative værdier. I dette tilfælde skal vi ændre algoritmen, så den kun virker på sammenhængende stigende subarrays.
Det følgende er, hvordan vi kan modificere Kadanes algoritme for at finde den største sum sammenhængende stigende subarray:
C++
- Initialiser to variable: max_sum og curr_sum til det første element i arrayet.
- Sløjfe gennem arrayet startende fra det andet element.
- hvis det aktuelle element er større end det forrige element, føje det til curr_sum. Ellers nulstil curr_sum til det aktuelle element.
- Hvis curr_sum er større end max_sum, opdater max_sum.
- Efter løkken vil max_sum indeholde den største sum sammenhængende stigende subarray.
Java#includeusing namespace std ; int largest_sum_contiguous_increasing_subarray ( int arr [] int n ) { int max_sum = arr [ 0 ]; int curr_sum = arr [ 0 ]; for ( int i = 1 ; i < n ; i ++ ) { if ( arr [ i ] > arr [ i -1 ]) { curr_sum += arr [ i ]; } else { curr_sum = arr [ i ]; } if ( curr_sum > max_sum ) { max_sum = curr_sum ; } } return max_sum ; } int main () { int arr [] = { 1 1 4 7 3 6 }; int n = sizeof ( arr ) / sizeof ( arr [ 0 ]); cout < < largest_sum_contiguous_increasing_subarray ( arr n ) < < endl ; // Output: 44 (1+2+3+5+7+8+9+10) return 0 ; } Python3public class Main { public static int largestSumContiguousIncreasingSubarray ( int [] arr int n ) { int maxSum = arr [ 0 ] ; int currSum = arr [ 0 ] ; for ( int i = 1 ; i < n ; i ++ ) { if ( arr [ i ] > arr [ i - 1 ] ) { currSum += arr [ i ] ; } else { currSum = arr [ i ] ; } if ( currSum > maxSum ) { maxSum = currSum ; } } return maxSum ; } public static void main ( String [] args ) { int [] arr = { 1 1 4 7 3 6 }; int n = arr . length ; System . out . println ( largestSumContiguousIncreasingSubarray ( arr n )); // Output: 44 (1+2+3+5+7+8+9+10) } }C#def largest_sum_contiguous_increasing_subarray ( arr n ): max_sum = arr [ 0 ] curr_sum = arr [ 0 ] for i in range ( 1 n ): if arr [ i ] > arr [ i - 1 ]: curr_sum += arr [ i ] else : curr_sum = arr [ i ] if curr_sum > max_sum : max_sum = curr_sum return max_sum arr = [ 1 1 4 7 3 6 ] n = len ( arr ) print ( largest_sum_contiguous_increasing_subarray ( arr n )) #output 12 (1+4+7)JavaScriptusing System ; class GFG { // Function to find the largest sum of a contiguous // increasing subarray static int LargestSumContiguousIncreasingSubarray ( int [] arr int n ) { int maxSum = arr [ 0 ]; // Initialize the maximum sum // and current sum int currSum = arr [ 0 ]; for ( int i = 1 ; i < n ; i ++ ) { if ( arr [ i ] > arr [ i - 1 ]) // Check if the current // element is greater than the // previous element { currSum += arr [ i ]; // If increasing add the // element to the current sum } else { currSum = arr [ i ]; // If not increasing start a // new increasing subarray // from the current element } if ( currSum > maxSum ) // Update the maximum sum if the // current sum is greater { maxSum = currSum ; } } return maxSum ; } static void Main () { int [] arr = { 1 1 4 7 3 6 }; int n = arr . Length ; Console . WriteLine ( LargestSumContiguousIncreasingSubarray ( arr n )); } } // This code is contributed by akshitaguprzj3
Produktion12Tidskompleksitet: O(n).
Opret quiz
Rumkompleksitet: O(1).
