Hi,↵
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I wanted to explain you the method I used to upsolve the problem of [problem:https://codeforces.com/contest/1478/problem/C]. ↵
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First of all they define a new kind of thing called symmetric array `A[]` of where there are `n` distinct positive integers and n additive inverse (multiplied by -1) of same integers. Whenever a problem define a new property or a thing , I find it better to make some specific and general example of it i.e `A = {1, 2, 3, 4, -1, -2, -3, -4}` or `{a, b, c, d, -a, -b, -c, -d}`↵
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Second thing they define are `D[]` where each i-th term `D[i]` is the sum of (absolute differences between `A[i]` to all other possible `A[j], j in [1,n])`. ↵
For ex: `n = 3, D[0] = |A[0] - A[0]| + |A[0] - (-A[0])| + |A[0] - A[1]| + |A[0] - (-A[1])| + |A[0] - A[2]| + |A[0] - (-A[2])|`↵
Similarly for all other D[1], D[2], D[3], D[4], D[5]. It is easy to see that this D value would be same for `A[i]` and `-A[i]`.↵
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Question is to tell whether its a valid `D[]` or not ? ↵
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I don't like absolute function but it has this property `|negative value| = -1*(negative_value) = positive` (basically distances between values or locations) Lets call it `distance sum` for future reference. so I try to visualize all numbers in sorted order since order of `A[]` doesn't matter I can freely choose to look at them in sorted way (make a 2d graph) so I get an idea which distance is going to have what value as it always equal to (larger value — smaller value) and its easy to see what is bigger and smaller in a picture. ↵
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We are working with a generic example of `n = 4 A[] = {a, b, c, d, -a, -b, -c, -d}`. I assumed `a < b < c < d`↵
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Now lets choose the smallest one and start calculating the total distances from `A` to every other number. Now from the picture, it might be easy to see why distance sum value would be same for `A[i]` and `-A[i]`.↵
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5. Here you will see that distance sum for a is 2*(a + b + c + d) and same for -a. I drew the negative terms right below the positive terms for better clarity↵
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You will notice that distance sum terms are↵
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~~~~~↵
2 * (a + b + c + d) , 2 * (b + b + c + d), 2 * (c + c + c + d), 2 * (d + d + d + d), 2 * (a + b + c + d) , 2 * (b + b + c + d), 2 * (c + c + c + d), 2 * (d + d + d + d)↵
~~~~~↵
They all are even and distinct (if you ignore the distances sum generated by negatives)↵
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looks great to me which means that the largest distance sum is 1. `(d * 4) * 2` ↵
and in general let's say we sort all distance sum then `D[2n] = 2 * n * A[n] => A[n] = D[2n] / (2n)` where `(D[2n] % (2n))=0` otherwise `A[n]` will be in floating points which contradicts that `A[]` are positive distinct integers. ↵
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Let's get back to our convenient example of `{a, b, c, d, -a, -b, -c, -d}` and distance sums as above. 2nd largest distance sum is `2 * (c + c + c + d)` and we know `d` now so we can easily calculate `c = (D[6] - 2 * d) / 2 * (3)` ↵
but generally `A[n - 1] = (D[2n - 2] - 2 * A[n] ) / 2 * (n - 1)` **Note [check if its perfectly dividing and positive after subtracting.]** . (We use `D[2n-2]` because `D[2n-1]` is same as `D[2n]` , but you can use **std:set** and make implementation easy at `log(n)` insertion cost)↵
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You can get the whole `A[]` back like this. Lastly check that they is no zero created as it also contradicts the properties of `A[]`. If you want to check my code [submission:105777562]. Yeah this was a long tutorial but I hope its understandable. If anyone has a suggestion on how to improve the reasoning Please share it. Thank you.
↵
I wanted to explain you the method I used to upsolve the problem of [problem:https://codeforces.com/contest/1478/problem/C]. ↵
↵
First of all they define a new kind of thing called symmetric array `A[]` of where there are `n` distinct positive integers and n additive inverse (multiplied by -1) of same integers. Whenever a problem define a new property or a thing , I find it better to make some specific and general example of it i.e `A = {1, 2, 3, 4, -1, -2, -3, -4}` or `{a, b, c, d, -a, -b, -c, -d}`↵
↵
Second thing they define are `D[]` where each i-th term `D[i]` is the sum of (absolute differences between `A[i]` to all other possible `A[j], j in [1,n])`. ↵
For ex: `n = 3, D[0] = |A[0] - A[0]| + |A[0] - (-A[0])| + |A[0] - A[1]| + |A[0] - (-A[1])| + |A[0] - A[2]| + |A[0] - (-A[2])|`↵
Similarly for all other D[1], D[2], D[3], D[4], D[5]. It is easy to see that this D value would be same for `A[i]` and `-A[i]`.↵
↵
Question is to tell whether its a valid `D[]` or not ? ↵
↵
I don't like absolute function but it has this property `|negative value| = -1*(negative_value) = positive` (basically distances between values or locations) Lets call it `distance sum` for future reference. so I try to visualize all numbers in sorted order since order of `A[]` doesn't matter I can freely choose to look at them in sorted way (make a 2d graph) so I get an idea which distance is going to have what value as it always equal to (larger value — smaller value) and its easy to see what is bigger and smaller in a picture. ↵
↵
We are working with a generic example of `n = 4 A[] = {a, b, c, d, -a, -b, -c, -d}`. I assumed `a < b < c < d`↵
↵
↵
↵
Now lets choose the smallest one and start calculating the total distances from `A` to every other number. Now from the picture, it might be easy to see why distance sum value would be same for `A[i]` and `-A[i]`.↵
↵
↵
↵
5. Here you will see that distance sum for a is 2*(a + b + c + d) and same for -a. I drew the negative terms right below the positive terms for better clarity↵
↵
↵
↵
↵
↵
↵
↵
You will notice that distance sum terms are↵
↵
~~~~~↵
2 * (a + b + c + d) , 2 * (b + b + c + d), 2 * (c + c + c + d), 2 * (d + d + d + d), 2 * (a + b + c + d) , 2 * (b + b + c + d), 2 * (c + c + c + d), 2 * (d + d + d + d)↵
~~~~~↵
They all are even and distinct (if you ignore the distances sum generated by negatives)↵
↵
looks great to me which means that the largest distance sum is 1. `(d * 4) * 2` ↵
and in general let's say we sort all distance sum then `D[2n] = 2 * n * A[n] => A[n] = D[2n] / (2n)` where `(D[2n] % (2n))=0` otherwise `A[n]` will be in floating points which contradicts that `A[]` are positive distinct integers. ↵
↵
Let's get back to our convenient example of `{a, b, c, d, -a, -b, -c, -d}` and distance sums as above. 2nd largest distance sum is `2 * (c + c + c + d)` and we know `d` now so we can easily calculate `c = (D[6] - 2 * d) / 2 * (3)` ↵
but generally `A[n - 1] = (D[2n - 2] - 2 * A[n] ) / 2 * (n - 1)` **Note [check if its perfectly dividing and positive after subtracting.]** . (We use `D[2n-2]` because `D[2n-1]` is same as `D[2n]` , but you can use **std:set** and make implementation easy at `log(n)` insertion cost)↵
↵
You can get the whole `A[]` back like this. Lastly check that they is no zero created as it also contradicts the properties of `A[]`. If you want to check my code [submission:105777562]. Yeah this was a long tutorial but I hope its understandable. If anyone has a suggestion on how to improve the reasoning Please share it. Thank you.
