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📜  跳转最大长度为K的数组可能获得的最大分数

📅  最后修改于: 2021-05-18 00:28:11             🧑  作者: Mango

给定一个数组arr []和一个整数K (第0索引),任务是通过执行以下操作来收集最大分数:

  • 从数组的0索引开始。
  • 通过在每一步中最多跳转K个索引来达到数组的最后一个索引。
  • 将每次跳转后达到的每个索引的值相加。
    • 初始化数组dp []以存储先前计算的结果。
    • 现在,从第0索引开始,对每个i索引执行以下操作:
      • 如果当前索引大于或等于最后一个元素的索引,则返回数组的最后一个元素。
      • 如果当前索引的值是预先计算的,则返回预先计算的值。
      • 否则,计算可移动到i +1i + K范围内的所有步骤可获得的最大分数,并使用以下递归关系将各个索引的结果存储在dp []数组中:
  • 现在,将dp [0]打印为必需的答案。

下面是上述方法的实现:

C++
// C++ program for the above approach
#include 
using namespace std;
 
// Function to count the maximum
// score of an index
int maxScore(int i, int A[], int K, int N, int dp[])
{
    // Base Case
    if (i >= N - 1)
        return A[N - 1];
 
    // If the value for the current
    // index is pre-calculated
    if (dp[i] != -1)
        return dp[i];
 
    int score = INT_MIN;
 
    // Calculate maximum score
    // for all the steps in the
    // range from i + 1 to i + k
    for (int j = 1; j <= K; j++) {
 
        // Score for index (i + j)
        score = max(score, maxScore(i + j, A, K, N, dp));
    }
 
    // Update dp[i] and return
    // the maximum value
    return dp[i] = score + A[i];
}
 
// Function to get maximum score
// possible from the array A[]
int getScore(int A[], int N, int K)
{
    // Array to store memoization
    int dp[N];
 
    // Initialize dp[] with -1
    for (int i = 0; i < N; i++)
        dp[i] = -1;
 
    cout << maxScore(0, A, K, N, dp);
}
 
// Driver Code
int main()
{
    int A[] = { 100, -30, -50, -15, -20, -30 };
    int K = 3;
    int N = sizeof(A) / sizeof(A[0]);
 
    getScore(A, N, K);
 
    return 0;
}


Java
// JAVA program for the above approach
import java.io.*;
import java.math.*;
import java.util.*;
public class GFG
{
 
  // Function to count the maximum
  // score of an index
  static int maxScore(int i, int A[], int K, int N,
                      int dp[])
  {
 
    // Base Case
    if (i >= N - 1)
      return A[N - 1];
 
    // If the value for the current
    // index is pre-calculated
    if (dp[i] != -1)
      return dp[i];
    int score = Integer.MIN_VALUE;
 
    // Calculate maximum score
    // for all the steps in the
    // range from i + 1 to i + k
    for (int j = 1; j <= K; j++)
    {
 
      // Score for index (i + j)
      score = Math.max(score,
                       maxScore(i + j, A, K, N, dp));
    }
 
    // Update dp[i] and return
    // the maximum value
    return dp[i] = score + A[i];
  }
 
  // Function to get maximum score
  // possible from the array A[]
  static void getScore(int A[], int N, int K)
  {
 
    // Array to store memoization
    int dp[] = new int[N];
 
    // Initialize dp[] with -1
    for (int i = 0; i < N; i++)
      dp[i] = -1;
    System.out.println(maxScore(0, A, K, N, dp));
  }
 
  // Driver Code
  public static void main(String args[])
  {
    int A[] = { 100, -30, -50, -15, -20, -30 };
    int K = 3;
    int N = A.length;
 
    getScore(A, N, K);
  }
}
 
// This code is contributed by jyoti369


Python3
# Python program for the above approach
import sys
 
# Function to count the maximum
# score of an index
def maxScore(i, A, K, N, dp):
   
    # Base Case
    if (i >= N - 1):
        return A[N - 1];
 
    # If the value for the current
    # index is pre-calculated
    if (dp[i] != -1):
        return dp[i];
    score = 1-sys.maxsize;
 
    # Calculate maximum score
    # for all the steps in the
    # range from i + 1 to i + k
    for j in range(1, K + 1):
       
        # Score for index (i + j)
        score = max(score, maxScore(i + j, A, K, N, dp));
 
    # Update dp[i] and return
    # the maximum value
    dp[i] = score + A[i];
    return dp[i];
 
 
# Function to get maximum score
# possible from the array A
def getScore(A, N, K):
    # Array to store memoization
    dp = [0]*N;
 
    # Initialize dp with -1
    for i in range(N):
        dp[i] = -1;
    print(maxScore(0, A, K, N, dp));
 
# Driver Code
if __name__ == '__main__':
    A = [100, -30, -50, -15, -20, -30];
    K = 3;
    N = len(A);
 
    getScore(A, N, K);
     
# This code contributed by shikhasingrajput


C#
// C# program for the above approach
using System;
class GFG
{
 
  // Function to count the maximum
  // score of an index
  static int maxScore(int i, int []A, int K, int N,
                      int []dp)
  {
 
    // Base Case
    if (i >= N - 1)
      return A[N - 1];
 
    // If the value for the current
    // index is pre-calculated
    if (dp[i] != -1)
      return dp[i];
    int score = int.MinValue;
 
    // Calculate maximum score
    // for all the steps in the
    // range from i + 1 to i + k
    for (int j = 1; j <= K; j++)
    {
 
      // Score for index (i + j)
      score = Math.Max(score,
                       maxScore(i + j, A, K, N, dp));
    }
 
    // Update dp[i] and return
    // the maximum value
    return dp[i] = score + A[i];
  }
 
  // Function to get maximum score
  // possible from the array A[]
  static void getScore(int []A, int N, int K)
  {
 
    // Array to store memoization
    int []dp = new int[N];
 
    // Initialize dp[] with -1
    for (int i = 0; i < N; i++)
      dp[i] = -1;
    Console.WriteLine(maxScore(0, A, K, N, dp));
  }
 
// Driver Code
static public void Main()
{
    int []A = { 100, -30, -50, -15, -20, -30 };
    int K = 3;
    int N = A.Length;
 
    getScore(A, N, K);
}
}
 
// This code is contributed by jana_sayantan.


C++
// C++ program for the above approach
#include 
using namespace std;
 
// Structure to sort a priority queue on
// the basis of first element of the pair
struct mycomp {
    bool operator()(pair p1,
                    pair p2)
    {
        return p1.first < p2.first;
    }
};
 
// Function to calculate maximum
// score possible from the array A[]
int maxScore(int A[], int K, int N)
{
    // Stores the score of previous k indices
    priority_queue,
                vector >, mycomp>
        maxheap;
 
    // Stores the maximum
    // score for current index
    int maxScore = 0;
 
    // Maximum score at first index
    maxheap.push({ A[0], 0 });
 
    // Traverse the array to calculate
    // maximum score for all indices
    for (int i = 1; i < N; i++) {
 
        // Remove maximum scores for
        // indices less than i - K
        while (maxheap.top().second < (i - K)) {
            maxheap.pop();
        }
 
        // Calculate maximum score for current index
        maxScore = A[i] + maxheap.top().first;
 
        // Push maximum score of
        // current index along
        // with index in maxheap
        maxheap.push({ maxScore, i });
    }
 
    // Return the maximum score
    return maxScore;
}
 
// Driver Code
int main()
{
    int A[] = { -44, -17, -54, 79 };
    int K = 2;
    int N = sizeof(A) / sizeof(A[0]);
 
    // Function call to calculate
    // maximum score from the array A[]
    cout << maxScore(A, K, N);
 
    return 0;
}


输出
55

时间复杂度: O(N * K)

辅助空间: O(N * K)

高效方法:按照以下步骤解决问题

  • 初始化最大堆以存储以前的K个索引的结果。
  • 现在,遍历数组A []以计算所有索引的最大分数。
    • 对于0索引,得分将是第0索引的值。
    • 现在,对于在范围[1,N – 1]i指数。
      • 首先,从最大堆中删除小于i – K的指数的最高分数。
      • 现在计算第i索引的最大分数。
        最大分数= A [i] +最大堆顶部的分数
      • 现在,将最大分数及其索引插入最大堆。
  • 返回获得的最高分数

C++

// C++ program for the above approach
#include 
using namespace std;
 
// Structure to sort a priority queue on
// the basis of first element of the pair
struct mycomp {
    bool operator()(pair p1,
                    pair p2)
    {
        return p1.first < p2.first;
    }
};
 
// Function to calculate maximum
// score possible from the array A[]
int maxScore(int A[], int K, int N)
{
    // Stores the score of previous k indices
    priority_queue,
                vector >, mycomp>
        maxheap;
 
    // Stores the maximum
    // score for current index
    int maxScore = 0;
 
    // Maximum score at first index
    maxheap.push({ A[0], 0 });
 
    // Traverse the array to calculate
    // maximum score for all indices
    for (int i = 1; i < N; i++) {
 
        // Remove maximum scores for
        // indices less than i - K
        while (maxheap.top().second < (i - K)) {
            maxheap.pop();
        }
 
        // Calculate maximum score for current index
        maxScore = A[i] + maxheap.top().first;
 
        // Push maximum score of
        // current index along
        // with index in maxheap
        maxheap.push({ maxScore, i });
    }
 
    // Return the maximum score
    return maxScore;
}
 
// Driver Code
int main()
{
    int A[] = { -44, -17, -54, 79 };
    int K = 2;
    int N = sizeof(A) / sizeof(A[0]);
 
    // Function call to calculate
    // maximum score from the array A[]
    cout << maxScore(A, K, N);
 
    return 0;
}
输出
18

时间复杂度: O(N * log K)

辅助空间: O(N)