I've upvoted this. Even the "optimized" solution here is so horrible that I almost thought the article was satire when I first read it. Maybe it is.
Even if we ignore the fact that it's grid to grid conversion, (which should just let you math the answer, without any searching) the fact that all the data is sorted means you can do the equivalent of a merge sort and only have to look at a two point for each step.
And how on earth can you take .117 seconds to line up a half a megapixel worth of grid points, even with their "fast" algorithm. They are using the R language which should be fast, right? Are they doing something expensive with it? Or perhaps there is an insane amount of data elsewhere making these lookups super expensive?
My apologies. While I don't see the name-calling towards an individual, my previous post did mention possible bad faith, and I would not been glad to have my post written about my code. I also slightly misunderstood what the author's code was doing. I can see how it is not conducive to helpful discussion.
The author optimized their code in a way that was fast enough, and fast enough to massively change the entire business process around their code. It's very commendable. Further optimizations may have not been worth it.
R in general and especially loops are slow; slower than even Python. Making a function and applying it on a vector is a simple way to boost performance. Also recursion seems[1] to be faster than iteration.
Seeing the code in article, it can be that a part in that speedup is because R is used and not only of a better algorithm.
Even if we ignore the fact that it's grid to grid conversion, (which should just let you math the answer, without any searching) the fact that all the data is sorted means you can do the equivalent of a merge sort and only have to look at a two point for each step.
And how on earth can you take .117 seconds to line up a half a megapixel worth of grid points, even with their "fast" algorithm. They are using the R language which should be fast, right? Are they doing something expensive with it? Or perhaps there is an insane amount of data elsewhere making these lookups super expensive?