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Some thoughts on this problem:
We can do simple mathematics to get sum of distances from city_i to all previous cities efficiently. Assume that cities from 0 to i-1 are divided into to categories:
To get right & left cities count & coordinate sum, we can use augmented BST to store visited cities coordinates, we can insert, get count of values > threshold, get sum of values > threshold, get count of values < threshold, get sum of values < threshold, all in O(log n) time complixity, hence the overall time complixity is O(n log n)
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I used 4 BITs (count, x, p, x*p) and it felt as good as pissing after holding it in all day ngl.