# Posts published in “Simulation”

Given the array queries of positive integers between 1 and m, you have to process all queries[i] (from i=0 to i=queries.length-1) according to the following rules:

• In the beginning, you have the permutation P=[1,2,3,...,m].
• For the current i, find the position of queries[i] in the permutation P (indexing from 0) and then move this at the beginning of the permutation P. Notice that the position of queries[i] in P is the result for queries[i].

Return an array containing the result for the given queries.

Example 1:

Input: queries = [3,1,2,1], m = 5
Output: [2,1,2,1]
Explanation: The queries are processed as follow:
For i=0: queries[i]=3, P=[1,2,3,4,5], position of 3 in P is 2, then we move 3 to the beginning of P resulting in P=[3,1,2,4,5].
For i=1: queries[i]=1, P=[3,1,2,4,5], position of 1 in P is 1, then we move 1 to the beginning of P resulting in P=[1,3,2,4,5].
For i=2: queries[i]=2, P=[1,3,2,4,5], position of 2 in P is 2, then we move 2 to the beginning of P resulting in P=[2,1,3,4,5].
For i=3: queries[i]=1, P=[2,1,3,4,5], position of 1 in P is 1, then we move 1 to the beginning of P resulting in P=[1,2,3,4,5].
Therefore, the array containing the result is [2,1,2,1].


Example 2:

Input: queries = [4,1,2,2], m = 4
Output: [3,1,2,0]


Example 3:

Input: queries = [7,5,5,8,3], m = 8
Output: [6,5,0,7,5]


Constraints:

• 1 <= m <= 10^3
• 1 <= queries.length <= m
• 1 <= queries[i] <= m

## Solution1: Simulation + Hashtable

Use a hashtable to store the location of each key.
For each query q, use h[q] to get the index of q, for each key, if its current index is less than q, increase their indices by 1. (move right). Set h[q] to 0.

Time complexity: O(q*m)
Space complexity: O(m)

## Solution 2: Fenwick Tree + HashTable

Time complexity: O(qlogm)
Space complexity: O(m)

## Python3

Given two arrays of integers nums and index. Your task is to create target array under the following rules:

• Initially target array is empty.
• From left to right read nums[i] and index[i], insert at index index[i] the value nums[i] in target array.
• Repeat the previous step until there are no elements to read in nums and index.

Return the target array.

It is guaranteed that the insertion operations will be valid.

Example 1:

Input: nums = [0,1,2,3,4], index = [0,1,2,2,1]
Output: [0,4,1,3,2]
Explanation:
nums       index     target
0            0        [0]
1            1        [0,1]
2            2        [0,1,2]
3            2        [0,1,3,2]
4            1        [0,4,1,3,2]


Example 2:

Input: nums = [1,2,3,4,0], index = [0,1,2,3,0]
Output: [0,1,2,3,4]
Explanation:
nums       index     target
1            0        [1]
2            1        [1,2]
3            2        [1,2,3]
4            3        [1,2,3,4]
0            0        [0,1,2,3,4]


Example 3:

Input: nums = [1], index = [0]
Output: [1]


Constraints:

• 1 <= nums.length, index.length <= 100
• nums.length == index.length
• 0 <= nums[i] <= 100
• 0 <= index[i] <= i

## Solution: Simulation

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

## C++

The power of an integer x is defined as the number of steps needed to transform x into 1 using the following steps:

• if x is even then x = x / 2
• if x is odd then x = 3 * x + 1

For example, the power of x = 3 is 7 because 3 needs 7 steps to become 1 (3 –> 10 –> 5 –> 16 –> 8 –> 4 –> 2 –> 1).

Given three integers lohi and k. The task is to sort all integers in the interval [lo, hi] by the power value in ascending order, if two or more integers have the same power value sort them by ascending order.

Return the k-th integer in the range [lo, hi] sorted by the power value.

Notice that for any integer x (lo <= x <= hi) it is guaranteed that x will transform into 1 using these steps and that the power of x is will fit in 32 bit signed integer.

Example 1:

Input: lo = 12, hi = 15, k = 2
Output: 13
Explanation: The power of 12 is 9 (12 --> 6 --> 3 --> 10 --> 5 --> 16 --> 8 --> 4 --> 2 --> 1)
The power of 13 is 9
The power of 14 is 17
The power of 15 is 17
The interval sorted by the power value [12,13,14,15]. For k = 2 answer is the second element which is 13.
Notice that 12 and 13 have the same power value and we sorted them in ascending order. Same for 14 and 15.


Example 2:

Input: lo = 1, hi = 1, k = 1
Output: 1


Example 3:

Input: lo = 7, hi = 11, k = 4
Output: 7
Explanation: The power array corresponding to the interval [7, 8, 9, 10, 11] is [16, 3, 19, 6, 14].
The interval sorted by power is [8, 10, 11, 7, 9].
The fourth number in the sorted array is 7.


Example 4:

Input: lo = 10, hi = 20, k = 5
Output: 13


Example 5:

Input: lo = 1, hi = 1000, k = 777
Output: 570


Constraints:

• 1 <= lo <= hi <= 1000
• 1 <= k <= hi - lo + 1

## Solution: Precompute + quick select

Time complexity: O(nlogn) + O(n)
Space complexity: O(1)

## C++

There is a room with n lights which are turned on initially and 4 buttons on the wall. After performing exactly m unknown operations towards buttons, you need to return how many different kinds of status of the n lights could be.

Suppose n lights are labeled as number [1, 2, 3 …, n], function of these 4 buttons are given below:

1. Flip all the lights.
2. Flip lights with even numbers.
3. Flip lights with odd numbers.
4. Flip lights with (3k + 1) numbers, k = 0, 1, 2, …

Example 1:

Input: n = 1, m = 1.
Output: 2
Explanation: Status can be: [on], [off]


Example 2:

Input: n = 2, m = 1.
Output: 3
Explanation: Status can be: [on, off], [off, on], [off, off]


Example 3:

Input: n = 3, m = 1.
Output: 4
Explanation: Status can be: [off, on, off], [on, off, on], [off, off, off], [off, on, on].


Note: n and m both fit in range [0, 1000].

The light pattern will be repeated if we have more than 6 lights, so n = n % 6, n = 6 if n == 0.

Time complexity: O(m*2^6)
Space complexity: O(2^6)

## C++

Given a non-negative integer num, repeatedly add all its digits until the result has only one digit.

Example:

Input: 38
Output: 2
Explanation: The process is like: 3 + 8 = 11, 1 + 1 = 2.
Since 2 has only one digit, return it.


Could you do it without any loop/recursion in O(1) runtime?

## Solution 1: Simulation

Time complexity: O(logn)
Space complexity: O(1)

## Solution 2: Math

https://en.wikipedia.org/wiki/Digital_root#Congruence_formula

Digit root = num % 9 if num % 9 != 0 else min(num, 9) e.g. 0 or 9

Time complexity: O(1)
Space complexity: O(1)

## C++

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