给定一个由N个整数组成的数组arr [] ,每个数组元素arr [i]的任务是打印| i – j |的和。对于所有可能的索引j ,使得arr [i] = arr [j] 。
例子:
Input: arr[] = {1, 3, 1, 1, 2}
Output: 5 0 3 4 0
Explanation:
For arr[0], sum = |0 – 0| + |0 – 2| + |0 – 3| = 5.
For arr[1], sum = |1 – 1| = 0.
For arr[2], sum = |2 – 0| + |2 – 2| + |2 – 3| = 3.
For arr[3], sum = |3 – 0| + |3 – 2| + |3 – 3| = 4.
For arr[4], sum = |4 – 4| = 0.
Therefore, the required output is 5 0 3 4 0.
Input: arr[] = {1, 1, 1}
Output: 3 2 3
简单方法:最简单的方法是遍历给定的阵列和用于每个元素ARR [I](0≤I≤N),遍历数组,并检查是否ARR [i]是相同ARR [J](0≤Ĵ≤ N )。如果发现为真,则将abs(i – j)添加到总和中,然后打印出每个数组元素获得的总和。
时间复杂度: O(N 2 ),其中N是给定数组的大小。
辅助空间: O(N)
高效方法:想法是使用Map数据结构来优化上述方法。请按照以下步骤解决问题:
- 初始化Map来存储索引向量,以重复数组中存在的每个唯一元素。
- 从i = 0到N – 1遍历给定的数组,并且对于每个数组元素arr [i] ,将其和初始化为0,并遍历矢量映射[arr [i]] ,该映射存储元素arr [的出现次数的索引我] 。
- 对于向量中存在的每个值j ,将总和增加abs(i – j) 。
- 遍历向量后,将元素的总和存储在索引i并打印总和。
下面是上述方法的实现:
C++
// C++ program for the above approach
#include
using namespace std;
// Function to find sum of differences
// of indices of occurrences of each
// unique array element
void sum(int arr[], int n)
{
// Stores indices of each
// array element
map > mp;
// Store the indices
for (int i = 0; i < n; i++) {
mp[arr[i]].push_back(i);
}
// Stores the sums
int ans[n];
// Traverse the array
for (int i = 0; i < n; i++) {
// Find sum for each element
int sum = 0;
// Iterate over the Map
for (auto it : mp[arr[i]]) {
// Calculate sum of
// occurrences of arr[i]
sum += abs(it - i);
}
// Store sum for
// current element
ans[i] = sum;
}
// Print answer for each element
for (int i = 0; i < n; i++) {
cout << ans[i] << " ";
}
return;
}
// Driver Code
int main()
{
// Given array
int arr[] = { 1, 3, 1, 1, 2 };
// Given size
int n = sizeof(arr)
/ sizeof(arr[0]);
// Function call
sum(arr, n);
return 0;
}
Java
// Java program for the above approach
import java.util.*;
class GFG{
// Function to find sum of differences
// of indices of occurrences of each
// unique array element
static void sum(int arr[], int n)
{
// Stores indices of each
// array element
HashMap> mp = new HashMap<>();
// Store the indices
for(int i = 0; i < n; i++)
{
Vector v = new Vector<>();
v.add(i);
if (mp.containsKey(arr[i]))
v.addAll(mp.get(arr[i]));
mp.put(arr[i], v);
}
// Stores the sums
int []ans = new int[n];
// Traverse the array
for(int i = 0; i < n; i++)
{
// Find sum for each element
int sum = 0;
// Iterate over the Map
for(int it : mp.get(arr[i]))
{
// Calculate sum of
// occurrences of arr[i]
sum += Math.abs(it - i);
}
// Store sum for
// current element
ans[i] = sum;
}
// Print answer for each element
for(int i = 0; i < n; i++)
{
System.out.print(ans[i] + " ");
}
return;
}
// Driver Code
public static void main(String[] args)
{
// Given array
int arr[] = { 1, 3, 1, 1, 2 };
// Given size
int n = arr.length;
// Function call
sum(arr, n);
}
}
// This code is contributed by Princi Singh
Python3
# Python3 program for the above approach
from collections import defaultdict
# Function to find sum of differences
# of indices of occurrences of each
# unique array element
def sum_i(arr, n):
# Stores indices of each
# array element
mp = defaultdict(lambda : [])
# Store the indices
for i in range(n):
mp[arr[i]].append(i)
# Stores the sums
ans = [0] * n
# Traverse the array
for i in range(n):
# Find sum for each element
sum = 0
# Iterate over the Map
for it in mp[arr[i]]:
# Calculate sum of
# occurrences of arr[i]
sum += abs(it - i)
# Store sum for
# current element
ans[i] = sum
# Print answer for each element
for i in range(n):
print(ans[i], end = " ")
# Driver code
if __name__ == '__main__':
# Given array
arr = [ 1, 3, 1, 1, 2 ]
# Given size
n = len(arr)
# Function Call
sum_i(arr, n)
# This code is contributed by Shivam Singh
C#
// C# program for the above approach
using System;
using System.Collections.Generic;
class GFG{
// Function to find sum of differences
// of indices of occurrences of each
// unique array element
static void sum(int []arr, int n)
{
// Stores indices of each
// array element
Dictionary> mp = new Dictionary>();
// Store the indices
for(int i = 0; i < n; i++)
{
List v = new List();
v.Add(i);
if (mp.ContainsKey(arr[i]))
v.AddRange(mp[arr[i]]);
mp[arr[i]]= v;
}
// Stores the sums
int []ans = new int[n];
// Traverse the array
for(int i = 0; i < n; i++)
{
// Find sum for each element
int sum = 0;
// Iterate over the Map
foreach(int it in mp[arr[i]])
{
// Calculate sum of
// occurrences of arr[i]
sum += Math.Abs(it - i);
}
// Store sum for
// current element
ans[i] = sum;
}
// Print answer for each element
for(int i = 0; i < n; i++)
{
Console.Write(ans[i] + " ");
}
return;
}
// Driver Code
public static void Main(String[] args)
{
// Given array
int []arr = { 1, 3, 1, 1, 2 };
// Given size
int n = arr.Length;
// Function call
sum(arr, n);
}
}
// This code is contributed by shikhasingrajput
5 0 3 4 0
时间复杂度: O(N * L)其中N是给定数组的大小, L是任何数组元素的最大频率。
辅助空间: O(N)