用BFS求出与给定整数集距离最小的积分点

2021年4月29日18:29:09 发表评论 950 次浏览

本文概述

给定一个长度为N的整数数组A[]和一个整数K，任务是找到在给定数组中不存在的K个不同的整数点，使它们到A[]中最近点的距离之和最小化。

积分点定义为两个坐标均为整数的点。另外, 在x轴上, 我们无需考虑y坐标, 因为所有点的y坐标都等于零。

例子：

输入：A [] = {-1, 4, 6}, K = 3
输出：-2, 0, 3
说明：
A[]中-2的最近点是-1 -> distance = 1
A[]中0的最近点是-1 -> distance = 1
A[]中3的最近点是4 -> distance = 1
总距离= 1 + 1 + 1 = 3，这是可能的最小距离。
在相同的最小距离下，其他结果也是可能的。
输入：A [] = {0, 1, 3, 4}, K = 5
输出：-1, 2, 5, 5, -2, 6
说明：
A []中-1的最近点是0-> distance = 1
A []中2的最近点是3->distance= 1
A []中5的最近点是4->距离= 1
A []中-2的最近点是0->距离= 2
6的最近点在A []中为4->距离= 2
总距离= 2 +1 + 1 +1 + 2 = 7, 这是最小的可能距离。

方法：我们将通过使用广度优先搜索.

  1. 我们首先将给定的整数集作为根元素并将其压入队列和杂凑.
  2. 然后对于任何说X的元素, 我们将仅使用哈希图检查是否遇到(X-1)或(X + 1)。如果到目前为止还没有遇到任何问题, 那么我们将该元素推送到答案数组中, 并同时进行队列和哈希处理。
  3. 重复此过程, 直到遇到K个新元素。

下面是上述方法的实现。

C ++

//C++ implementation of above approach
 
#include <bits/stdc++.h>
using namespace std;
 
//Function to find points at
//minimum distance
void minDistancePoints( int A[], int K, int n)
{
 
     //Hash to store points
     //that are encountered
     map<int , int> m;
 
     //Queue to store initial
     //set of points
     queue<int> q;
 
     for ( int i = 0; i <n; ++i) {
         m[A[i]] = 1;
         q.push(A[i]);
     }
 
     //Vector to store integral
     //points
     vector<int> ans;
 
     //Using bfs to visit nearest
     //points from already
     //visited points
     while (K> 0) {
 
         //Get first element from
         //queue
         int x = q.front();
         q.pop();
 
         //Check if (x-1) is not
         //encountered so far
         if (!m[x - 1] && K> 0) {
             //Update hash with
             //this new element
             m[x - 1] = 1;
 
             //Insert (x-1) into
             //queue
             q.push(x - 1);
 
             //Push (x-1) as
             //new element
             ans.push_back(x - 1);
 
             //Decrement counter
             //by 1
             K--;
         }
 
         //Check if (x+1) is not
         //encountered so far
         if (!m[x + 1] && K> 0) {
             //Update hash with
             //this new element
             m[x + 1] = 1;
 
             //Insert (x+1) into
             //queue
             q.push(x + 1);
 
             //Push (x+1) as
             //new element
             ans.push_back(x + 1);
 
             //Decrement counter
             //by 1
             K--;
         }
     }
 
     //Print result array
     for ( auto i : ans)
         cout <<i <<" " ;
}
 
//Driver code
int main()
{
 
     int A[] = { -1, 4, 6 };
     int K = 3;
     int n = sizeof (A) /sizeof (A[0]);
 
     minDistancePoints(A, K, n);
 
     return 0;
}

Java

//Java implementation of above approach
import java.util.HashMap;
import java.util.LinkedList;
import java.util.Map;
import java.util.Queue;
 
class Geeks{
     
//Function to find points at
//minimum distance
static void minDistancePoints( int A[], int K, int n)
{
     
     //Hash to store points
     //that are encountered
     Map<Integer, Boolean> m = new HashMap<Integer, Boolean>();
 
     //Queue to store initial
     //set of points
     Queue<Integer> q = new LinkedList<Integer>();
 
     for ( int i = 0 ; i <n; ++i)
     {
         m.put(A[i], true );
         q.add(A[i]);
     }
 
     //List to store integral
     //points
     LinkedList<Integer> ans = new LinkedList<Integer>();
 
     //Using bfs to visit nearest
     //points from already
     //visited points
     while (K> 0 )
     {
         
         //Get first element from
         //queue
         int x = q.poll();
 
         //Check if (x-1) is not
         //encountered so far
         if (!m.containsKey(x - 1 ) && K> 0 )
         {
             
             //Update hash with
             //this new element
             m.put(x - 1 , true );
 
             //Insert (x-1) into
             //queue
             q.add(x - 1 );
 
             //Push (x-1) as
             //new element
             ans.add(x - 1 );
 
             //Decrement counter
             //by 1
             K--;
         }
 
         //Check if (x+1) is not
         //encountered so far
         if (!m.containsKey(x + 1 ) && K> 0 )
         {
             
             //Update hash with
             //this new element
             m.put(x + 1 , true );
 
             //Insert (x+1) into
             //queue
             q.add(x + 1 );
 
             //Push (x+1) as
             //new element
             ans.add(x + 1 );
 
             //Decrement counter
             //by 1
             K--;
         }
     }
 
     //Print result array
     for (Integer i : ans)
         System.out.print(i + " " );
}
 
//Driver code
public static void main(String[] args)
{
     int A[] = new int [] { - 1 , 4 , 6 };
     int K = 3 ;
     int n = A.length;
     
     minDistancePoints(A, K, n);
}
}
 
//This code is contributed by Rajnis09

Python3

# Python 3 implementation
# of above approach
 
# Function to find points
# at minimum distance
def minDistancePoints(A, K, n):
   
     # Hash to store points
     # that are encountered
     m = {}
 
     # Queue to store initial
     # set of points
     q = []
 
     for i in range (n):
         m[A[i]] = 1
         q.append(A[i])
 
     # Vector to store
     # integral points
     ans = []
 
     # Using bfs to visit nearest
     # points from already
     # visited points
     while (K> 0 ):
       
         # Get first element from
         # queue
         x = q[ 0 ]
         q = q[ 1 ::]
 
         # Check if (x-1) is not
         # encountered so far
         if ((x - 1 ) not in m and
              K> 0 ):
           
             # Update hash with
             # this new element
             m[x - 1 ] = m.get(x - 1 , 0 ) + 1
 
             # Insert (x-1) into
             # queue
             q.append(x - 1 )
 
             # Push (x-1) as
             # new element
             ans.append(x - 1 )
 
             # Decrement counter
             # by 1
             K - = 1
 
         # Check if (x+1) is not
         # encountered so far
         if ((x + 1 ) not in m and
              K> 0 ):
             # Update hash with
             # this new element
             m[x + 1 ] = m.get(x + 1 , 0 ) + 1
 
             # Insert (x+1) into
             # queue
             q.append(x + 1 )
 
             # Push (x+1) as
             # new element
             ans.append(x + 1 )
             # Decrement counter
             # by 1
             K - = 1
 
     # Print result array
     for i in ans:
         print (i, end = " " )
 
# Driver code
if __name__ = = '__main__' :
   
     A =  [ - 1 , 4 , 6 ]
     K = 3
     n =  len (A)
     minDistancePoints(A, K, n)
 
# This code is contributed by bgangwar59

C#

//C# implementation of above approach
using System;
using System.Collections.Generic;
 
class GFG{
     
//Function to find points at
//minimum distance
static void minDistancePoints( int []A, int K, int n)
{
     
     //Hash to store points
     //that are encountered
     Dictionary<int , Boolean> m = new Dictionary<int , Boolean>();
 
     //Queue to store initial
     //set of points
     Queue<int> q = new Queue<int>();
 
     for ( int i = 0; i <n; ++i)
     {
         m.Add(A[i], true );
         q.Enqueue(A[i]);
     }
 
     //List to store integral
     //points
     List<int> ans = new List<int>();
 
     //Using bfs to visit nearest
     //points from already
     //visited points
     while (K> 0)
     {
         
         //Get first element from
         //queue
         int x = q.Dequeue();
 
         //Check if (x-1) is not
         //encountered so far
         if (!m.ContainsKey(x - 1) && K> 0)
         {
             
             //Update hash with
             //this new element
             m.Add(x - 1, true );
 
             //Insert (x-1) into
             //queue
             q.Enqueue(x - 1);
 
             //Push (x-1) as
             //new element
             ans.Add(x - 1);
 
             //Decrement counter
             //by 1
             K--;
         }
 
         //Check if (x+1) is not
         //encountered so far
         if (!m.ContainsKey(x + 1) && K> 0)
         {
             
             //Update hash with
             //this new element
             m.Add(x + 1, true );
 
             //Insert (x+1) into
             //queue
             q.Enqueue(x + 1);
 
             //Push (x+1) as
             //new element
             ans.Add(x + 1);
 
             //Decrement counter
             //by 1
             K--;
         }
     }
 
     //Print result array
     foreach ( int i in ans)
         Console.Write(i + " " );
}
 
//Driver code
public static void Main(String[] args)
{
     int []A = new int [] { -1, 4, 6 };
     int K = 3;
     int n = A.Length;
     
     minDistancePoints(A, K, n);
}
}
 
//This code is contributed by Amit Katiyar

输出如下：

-2 0 3

时间复杂度：O(M * log(M)), 其中M = N +K。

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