We are given an array A of integers. I want to find 2 contiguous subarrays of the largest length(both subarrays must be equal in length) that have the same weighted average. The weights are the positions in the subarray. For example
A=41111921111119
Subarrays:: (11119) and (11119)
Ive tried to find the weighted average of all subarrays by DP and then sorting them columnwise to find 2 with same length.But I cant proceed further and my approach seems too vague/bruteforce.I would appreciate any help. Thanks in advance.
The first step should be to sort the array. Any pairs of equal values can then be identified and factored out. The remaining numbers will all be different, like this:
2, 3, 5, 9, 14, 19 ... etc
The next step would be to compare pairs to their center:
2 + 5 == 2 * 3 ?
3 + 9 == 2 * 5 ?
5 + 14 == 2 * 9 ?
9 + 19 == 2 * 14 ?
The next step is to compare nested pairs, meaning if you have A B C D, you compare A+D to B+C. So for the above example it would be:
2+9 == 3+5 ?
3+15 == 5+9 ?
5+19 == 9+14 ?
Next you would compare triples to the two inside values:
2 + 3 + 9 == 3 * 5 ?
2 + 5 + 9 == 3 * 3 ?
3 + 5 + 14 == 3 * 9 ?
3 + 9 + 14 == 3 * 5 ?
5 + 9 + 19 == 3 * 14 ?
5 + 14 + 19 == 3 * 9 ?
Then you would compare pairs of triples:
2 + 3 + 19 == 5 + 9 + 14 ?
2 + 5 + 19 == 3 + 9 + 14 ?
2 + 9 + 19 == 3 + 5 + 14 ?
and so on. There are different ways to do the ordering. One way is to create an initial bracket, for example, given A B C D E F G H, the initial bracket is ABGH versus CDEF, ie the outside compared to the center. Then switch values according to the comparison. For example, if ABGH > CDEF, then you can try all switches where the left value is greater than the right value. In this case G and H are greater than E and F, so the possible switches are:
G <-> E
G <-> F
H <-> E
H <-> F
GH <-> EF
First, as the length of the two subarray must be equal, you can consider the length from 1 to n step by step.
For length i, you can calculate the weighted sum of every subarray in a total complexity of O(n). Then sort the sums to determine if there's an equal pair.
Because you sort n times the time would be O(n^2 log n) while the space is O(n).
Maybe I just repeated your solution mentioned in the question? But I don't think it can be optimized any more...
Related
I am trying to implement this code and this website has kindly provided their algorithm but I am trying to Find out what is "N" I understood what "I" and "M" is but not "N", is "N" the Total input(in the below example 5 because there are 5 letters)?
Algorithm:
Combinations are generated in lexicographical order. The algorithm uses indexes of the elements of the set. Here is how it works on example: Suppose we have a set of 5 elements with indexes 1 2 3 4 5 (starting from 1), and we need to generate all combinations of size m
= 3.
First, we initialize the first combination of size m - with indexes in ascending order
1 2 3
Then we check the last element (i = 3). If its value is less than n - m + i, it is incremented by 1.
1 2 4
Again we check the last element, and since it is still less than n - m
i, it is incremented by 1.
1 2 5
Now it has the maximum allowed value: n - m + i = 5 - 3 + 3 = 5, so we move on to the previous element (i = 2).
If its value less than n - m + i, it is incremented by 1, and all following elements are set to value of their previous neighbor plus 1
1 (2+1)3 (3+1)4 = 1 3 4
Then we again start from the last element i = 3
1 3 5
Back to i = 2
1 4 5
Now it finally equals n - m + i = 5 - 3 + 2 = 4, so we can move to first element (i = 1) (1+1)2 (2+1)3 (3+1)4 = 2 3 4
And then,
2 3 5
2 4 5
3 4 5
and it is the last combination since all values are set to the maximum possible value of n - m + i.
Input:
A
B
C
D
E
Output:
A B C
A B D
A B E
A C D
A C E
A D E
B C D
B C E
B D E
C D E
Take a look at the very first paragraf of the link you provided.
It states that
This combinations calculator generates all possible combinations of m elements from the set of n elements.
So yes, n is the number of elements or letters that the algorithm needs to use.
N here is the size of the set of set from which you generate the combinations. In the given example, "Suppose we have a set of 5 elements with indexes 1 2 3 4 5 (starting from 1)", N is 5.
Combinations are usually symbolized with nCm, or n choose m. So n is the total set size(in this example 5) and m is the number chosen(3).
I know that I can get the nth element of the following sequence
1 3 6 10 15 21
With the formula
(n * (n + 1)) / 2
where n is the nth number I want. How can I generalise the formula to get the nth element of the following sequences where by following sequences I mean
1 -> 1 3 6 10 15 21
2 -> 2 5 9 14 20
3 -> 4 8 13 19
4 -> 7 12 18
5 -> 11 17
6 -> 16
It is not quite clear what do you mean by n-th element in 2D-table (potentially infinite)
Simple formula for element at row and column (numbered from 1):
(r+c-1)*(r+c)/2 - (r-1)
Possible intuition for this formula:
Key moment: element with coordinates r,c stands on the diagonal number d, where d = r + c - 1
There are s = d*(d+1)/2 elements in d filled diagonals, so the last element of d-th diagonal (rightmost top) has value s, and element in r-th row of the same diagonal is
v(r,c) = s-(r-1) = (d)*(d+1)/2 -(r-1) = (r+c-1)*(r+c)/2 - (r-1)
Assume we have a d-ary heap and we index the nodes from top to bottom and from left to right(starting with 1). Then the children from node i are the nodes with index di,...,di+(d-1). I read this formula in a couple of books but in none of them were an explanation why these formulas are true. Maybe I am overlooking something but is it really that clear that these formulas are true?
I find d * i + 2 - d for the index of the first child, if items
are numbered starting from 1. Here is the reasoning
Each row contains the children of the previous row. If n[r] are
the number of items on row r, one must have n[r+1] = d * n[r], which
proves that n[r] = d**r if the first row is numbered 0. The index
of the first item of row r is f[r] = 1 + (d**r - 1)/(d - 1) by the sum
of geometric sequences. If item X with number i is on row r, let's write
i = f[r] + k with 0 <= k < d**r. There are k items on the row before X,
hence there are d * k items before X's first child on row r+1. The
index of X's first child is f[r+1] + d * k = f[r+1] + d * (i - f[r])
The calculus gives d * i + 2 - d for the index of the first child.
Actually, if we start numbering the items from 0 instead of 1, the formula becomes simply d * i + 1 for the index of the first child, and this can be easily proven by induction because the index of the first child of item i+1 is obtained by adding d, but (d * i + 1) + d = d * (i + 1) + 1.
Maybe this diagram will help, at least for d=2:
1
2 3
4 5 6 7
8 9 10 11 12 13 14 15
16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
I was recently solving a problem when I encountered this one: APAC Round E Q2
Basically the question asks to find the smallest base (>1) in which if the number (input) is written then the number would only consist of 1s. Like 3 if represented in base 2 would become 1 (consisting of only 1s).
Now, I tried to solve this the brute force way trying out all bases from 2 till the number to find such a base. But the constraints required a more efficient one.
Can anyone provide some help on how to approach this?
Here is one suggestion: A number x that can be represented as all 1s in a base b can be written as x = b^n + b^(n-1) + b^(n-2) + ... + b^1 + 1
If you subtract 1 from this number you end up with a number divisble by b:
b^n + b^(n-1) + b^(n-2) + ... + b^1 which has the representation 111...110. Dividing by b means shifting it right once so the resulting number is now b^(n-1) + b^(n-2) + ... + b^1 or 111...111 with one digit less than before. Now you can repeat the process until you reach 0.
For example 13 which is 111 in base 3:
13 - 1 = 12 --> 110
12 / 3 = 4 --> 11
4 - 1 = 3 --> 10
3 / 3 = 1 --> 1
1 - 1 = 0 --> 0
Done => 13 can be represented as all 1s in base 3
So in order to check if a given number can be written with all 1s in a base b you can check if that number is divisble by b after subtracting 1. If not you can immediately start with the next base.
This is also pretty brute-forcey but it doesn't do any base conversions, only one subtraction, one divisions and one mod operation per iteration.
We can solve this in O( (log2 n)^2 ) complexity by recognizing that the highest power attainable in the sequence would correspond with the smallest base, 2, and using the formula for geometric sum:
1 + r + r^2 + r^3 ... + r^(n-1) = (1 - r^n) / (1 - r)
Renaming the variables, we get:
n = (1 - base^power) / (1 - base)
Now we only need to check power's from (floor(log2 n) + 1) down to 2, and for each given power, use a binary search for the base. For example:
n = 13:
p = floor(log2 13) + 1 = 4:
Binary search for base:
(1 - 13^4) / (1 - 13) = 2380
...
No match for power = 4.
Try power = 3:
(1 - 13^3) / (1 - 13) = 183
(1 - 6^3) / (1 - 6) = 43
(1 - 3^3) / (1 - 3) = 13 # match
For n around 10^18 we may need up to (floor(log2 (10^18)) + 1)^2 = 3600 iterations.
I have N integers numbers: 1,2,3...N
The task is to use +,-,*,/ to make expression 0.
For example -1*2+3+4-5=0
How can I do it?
May be some code on C/C++ ?
If N % 4 == 0, for every four consecutive integers a, b, c, d, take a - b - c + d
If N % 4 == 1, use 1 * 2 to start, then proceed as before. (i.e., 1*2 - 3 - 4 + 5 + 6 - 8 - 8 + 9 ...)
If N % 4 == 2, start with 1 - 2 + 3 * 4 - 5 - 6, then proceed as in the N % 4 == 0 example.
If N % 4 == 3, start with 1 + 2 - 3, then proceed as in the N%4 == 0 example.
All of these find a way to get zero out of the first few integers, leaving a multiple of four integers to work on, then take advantage of the fact that the pattern a - b - c + d = 0 for any four consecutive integers.
This is essentially SAT, or do you know that the numbers are a sequence (e.g. 2 1 8 is forbidden). What about negative numbers?
If the sequence is not too large, i would recommend to simply bootforce it. A greedy solution would be to reduce the problem by finding subsets which can be evaluated to zero.