KD-tree VS kactl

Multidimensional data indexing implementation

As a competitive programmer, I’ve seen similar ‘magic’ tricks here: https://github.com/kth-competitive-programming/kactl/blob/ma... (page 23)

Printed references (e.g. KACTL) are allowed.

There's not _that_ many algorithms or data structures you see in competitive programming, and the vast majority of them aren't advanced. You do need to memorize a good portion of them, but doing so is the easy part towards becoming good at it.

You can read one moderate length book and know all of the DSes and algorithms you'll need for 99.9% of the time. cses.fi/book is a good one with a free version if you're curious.

https://github.com/kth-competitive-programming/kactl may also be of interest, it contains a good amount of the algorithms/DSes you'd ever need on a few printable pages (20ish).

Finally, there are certain types of algorithms/operations that can be very sensitive to implementation. For example, a "good" Fast Fourier Transform implementation may be 3-4 orders of magnitude faster than a naive recursive one (with the same complexity!). Another fun case is something like (a*b)%c when the numbers are 64 bit. Using a fast implementation like this one (https://github.com/kth-competitive-programming/kactl/blob/master/content/number-theory/ModMulLL.h#L20) can speed up your code by 3-4x compared to using a naive implementation.