# Posts tagged as “hashtable”

You are given an integer array nums. The unique elements of an array are the elements that appear exactly once in the array.

Return the sum of all the unique elements of nums.

Example 1:

Input: nums = [1,2,3,2]
Output: 4
Explanation: The unique elements are [1,3], and the sum is 4.


Example 2:

Input: nums = [1,1,1,1,1]
Output: 0
Explanation: There are no unique elements, and the sum is 0.


Example 3:

Input: nums = [1,2,3,4,5]
Output: 15
Explanation: The unique elements are [1,2,3,4,5], and the sum is 15.


Constraints:

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

## Solution: Hashtable

Time complexity: O(n)
Space complexity: O(100)

## C++

There is an integer array nums that consists of n unique elements, but you have forgotten it. However, you do remember every pair of adjacent elements in nums.

You are given a 2D integer array adjacentPairs of size n - 1 where each adjacentPairs[i] = [ui, vi] indicates that the elements ui and vi are adjacent in nums.

It is guaranteed that every adjacent pair of elements nums[i] and nums[i+1] will exist in adjacentPairs, either as [nums[i], nums[i+1]] or [nums[i+1], nums[i]]. The pairs can appear in any order.

Return the original array nums. If there are multiple solutions, return any of them.

Example 1:

Input: adjacentPairs = [[2,1],[3,4],[3,2]]
Output: [1,2,3,4]
Notice that adjacentPairs[i] may not be in left-to-right order.


Example 2:

Input: adjacentPairs = [[4,-2],[1,4],[-3,1]]
Output: [-2,4,1,-3]
Explanation: There can be negative numbers.
Another solution is [-3,1,4,-2], which would also be accepted.


Example 3:

Input: adjacentPairs = [[100000,-100000]]
Output: [100000,-100000]


Constraints:

• nums.length == n
• adjacentPairs.length == n - 1
• adjacentPairs[i].length == 2
• 2 <= n <= 105
• -105 <= nums[i], ui, vi <= 105
• There exists some nums that has adjacentPairs as its pairs.

## Solution: Hashtable

Reverse thinking! For a given input array, e.g.
[1, 2, 3, 4, 5]
it’s adjacent pairs are [1,2] , [2,3], [3,4], [4,5]
all numbers appeared exactly twice except 1 and 5, since they are on the boundary.
We just need to find the head or tail of the input array, and construct the rest of the array in order.

Time complexity:O(n)
Space complexity: O(n)

## C++

You are working in a ball factory where you have n balls numbered from lowLimit up to highLimit inclusive (i.e., n == highLimit - lowLimit + 1), and an infinite number of boxes numbered from 1 to infinity.

Your job at this factory is to put each ball in the box with a number equal to the sum of digits of the ball’s number. For example, the ball number 321 will be put in the box number 3 + 2 + 1 = 6 and the ball number 10 will be put in the box number 1 + 0 = 1.

Given two integers lowLimit and highLimit, return the number of balls in the box with the most balls.

Example 1:

Input: lowLimit = 1, highLimit = 10
Output: 2
Explanation:
Box Number:  1 2 3 4 5 6 7 8 9 10 11 ...
Ball Count:  2 1 1 1 1 1 1 1 1 0  0  ...
Box 1 has the most number of balls with 2 balls.

Example 2:

Input: lowLimit = 5, highLimit = 15
Output: 2
Explanation:
Box Number:  1 2 3 4 5 6 7 8 9 10 11 ...
Ball Count:  1 1 1 1 2 2 1 1 1 0  0  ...
Boxes 5 and 6 have the most number of balls with 2 balls in each.


Example 3:

Input: lowLimit = 19, highLimit = 28
Output: 2
Explanation:
Box Number:  1 2 3 4 5 6 7 8 9 10 11 12 ...
Ball Count:  0 1 1 1 1 1 1 1 1 2  0  0  ...
Box 10 has the most number of balls with 2 balls.


Constraints:

• 1 <= lowLimit <= highLimit <= 105

## Solution: Hashtable and base-10

Max sum will be 9+9+9+9+9 = 45

Time complexity: O((hi-lo) * log(hi))
Space complexity: O(1)

## Python3

Given an array nums of distinct positive integers, return the number of tuples (a, b, c, d) such that a * b = c * d where abc, and d are elements of nums, and a != b != c != d.

Example 1:

Input: nums = [2,3,4,6]
Output: 8
Explanation: There are 8 valid tuples:
(2,6,3,4) , (2,6,4,3) , (6,2,3,4) , (6,2,4,3)
(3,4,2,6) , (4,3,2,6) , (3,4,6,2) , (4,3,6,2)


Example 2:

Input: nums = [1,2,4,5,10]
Output: 16
Explanation: There are 16 valids tuples:
(1,10,2,5) , (1,10,5,2) , (10,1,2,5) , (10,1,5,2)
(2,5,1,10) , (2,5,10,1) , (5,2,1,10) , (5,2,10,1)
(2,10,4,5) , (2,10,5,4) , (10,2,4,5) , (10,2,4,5)
(4,5,2,10) , (4,5,10,2) , (5,4,2,10) , (5,4,10,2)


Example 3:

Input: nums = [2,3,4,6,8,12]
Output: 40


Example 4:

Input: nums = [2,3,5,7]
Output: 0


Constraints:

• 1 <= nums.length <= 1000
• 1 <= nums[i] <= 104
• All elements in nums are distinct.

## Solution: HashTable

Similar idea to 花花酱 LeetCode 1. Two Sum

Use a hashtable to store all the pair product counts.

Enumerate all possible pairs, increase the answer by the same product counts * 8.

Why time 8? C(4,1) * C(1,1) * C(2,1) * C(1,1)

For pair one AxB, A can be placed at any position in a four tuple, B’s position is then fixed. For another pair CxD, C has two positions to choose from, D is fixed.

Time complexity: O(n^2)
Space complexity: O(n^2)

## C++

good meal is a meal that contains exactly two different food items with a sum of deliciousness equal to a power of two.

You can pick any two different foods to make a good meal.

Given an array of integers deliciousness where deliciousness[i] is the deliciousness of the i​​​​​​th​​​​​​​​ item of food, return the number of different good meals you can make from this list modulo 109 + 7.

Note that items with different indices are considered different even if they have the same deliciousness value.

Example 1:

Input: deliciousness = [1,3,5,7,9]
Output: 4
Explanation: The good meals are (1,3), (1,7), (3,5) and, (7,9).
Their respective sums are 4, 8, 8, and 16, all of which are powers of 2.


Example 2:

Input: deliciousness = [1,1,1,3,3,3,7]
Output: 15
Explanation: The good meals are (1,1) with 3 ways, (1,3) with 9 ways, and (1,7) with 3 ways.

Constraints:

• 1 <= deliciousness.length <= 105
• 0 <= deliciousness[i] <= 220

## Solution: Hashtable

Same idea as LeetCode 1: Two Sum

Use a hashtable to store the occurrences of all the numbers added so far. For a new number x, check all possible 2^i – x. ans += freq[2^i – x] 0 <= i <= 21

Time complexity: O(22n)
Space complexity: O(n)