Standard Priority Queue IV

Easy Sunday Morning LC problem: straight pQueue implementation. Code is down below, cheers, ACC.

Maximum Sum With Exactly K Elements - LeetCode

2656. Maximum Sum With Exactly K Elements

Easy

You are given a 0-indexed integer array nums and an integer k. Your task is to perform the following operation exactly k times in order to maximize your score:

1. Select an element m from nums.
2. Remove the selected element m from the array.
3. Add a new element with a value of m + 1 to the array.
4. Increase your score by m.

Return the maximum score you can achieve after performing the operation exactly k times.

 

Example 1:

Input: nums = [1,2,3,4,5], k = 3
Output: 18
Explanation: We need to choose exactly 3 elements from nums to maximize the sum.
For the first iteration, we choose 5. Then sum is 5 and nums = [1,2,3,4,6]
For the second iteration, we choose 6. Then sum is 5 + 6 and nums = [1,2,3,4,7]
For the third iteration, we choose 7. Then sum is 5 + 6 + 7 = 18 and nums = [1,2,3,4,8]
So, we will return 18.
It can be proven, that 18 is the maximum answer that we can achieve.

Example 2:

Input: nums = [5,5,5], k = 2
Output: 11
Explanation: We need to choose exactly 2 elements from nums to maximize the sum.
For the first iteration, we choose 5. Then sum is 5 and nums = [5,5,6]
For the second iteration, we choose 6. Then sum is 5 + 6 = 11 and nums = [5,5,7]
So, we will return 11.
It can be proven, that 11 is the maximum answer that we can achieve.

 

Constraints:

• 1 <= nums.length <= 100
• 1 <= nums[i] <= 100
• 1 <= k <= 100

public class Solution {
    public int MaximizeSum(int[] nums, int k)
    {
        int maxScore = 0;

        PriorityQueue pQueue = new PriorityQueue(false);
        foreach (int n in nums) pQueue.Enqueue(n, n);

        for (int i = 0; i < k; i++)
        {
            double temp = 0;
            int val = (int)pQueue.Dequeue(out temp);
            maxScore += val;
            pQueue.Enqueue(val + 1, val + 1);
        }
        return maxScore;
    }
    
    public class PriorityQueue
{
    public struct HeapEntry
    {
        private object item;
        private double priority;
        public HeapEntry(object item, double priority)
        {
            this.item = item;
            this.priority = priority;
        }
        public object Item
        {
            get
            {
                return item;
            }
        }
        public double Priority
        {
            get
            {
                return priority;
            }
        }
    }

    private bool ascend;
    private int count;
    private int capacity;
    private HeapEntry[] heap;

    public int Count
    {
        get
        {
            return this.count;
        }
    }

    public PriorityQueue(bool ascend, int cap = -1)
    {
        capacity = 10000000;
        if (cap > 0) capacity = cap;
        heap = new HeapEntry[capacity];
        this.ascend = ascend;
    }

    public object Dequeue(out double priority)
    {
        priority = heap[0].Priority;
        object result = heap[0].Item;
        count--;
        trickleDown(0, heap[count]);
        return result;
    }
    public object Peak(out double priority)
    {
        priority = heap[0].Priority;
        object result = heap[0].Item;
        return result;
    }

    public object Peak(/*out double priority*/)
    {
        //priority = heap[0].Priority;
        object result = heap[0].Item;
        return result;
    }

    public void Enqueue(object item, double priority)
    {
        count++;
        bubbleUp(count - 1, new HeapEntry(item, priority));
    }

    private void bubbleUp(int index, HeapEntry he)
    {
        int parent = (index - 1) / 2;
        // note: (index > 0) means there is a parent
        if (this.ascend)
        {
            while ((index > 0) && (heap[parent].Priority > he.Priority))
            {
                heap[index] = heap[parent];
                index = parent;
                parent = (index - 1) / 2;
            }
            heap[index] = he;
        }
        else
        {
            while ((index > 0) && (heap[parent].Priority < he.Priority))
            {
                heap[index] = heap[parent];
                index = parent;
                parent = (index - 1) / 2;
            }
            heap[index] = he;
        }
    }

    private void trickleDown(int index, HeapEntry he)
    {
        int child = (index * 2) + 1;
        while (child < count)
        {
            if (this.ascend)
            {
                if (((child + 1) < count) &&
                    (heap[child].Priority > heap[child + 1].Priority))
                {
                    child++;
                }
            }
            else
            {
                if (((child + 1) < count) &&
                    (heap[child].Priority < heap[child + 1].Priority))
                {
                    child++;
                }
            }
            heap[index] = heap[child];
            index = child;
            child = (index * 2) + 1;
        }
        bubbleUp(index, he);
    }
}

}