[rladd]

We can easily reduce this to effectively time=0 which is an infinite speedup.

Since the membership of any of the local cells in the global cells is static, we only have to compute this once. Then we add a globalCell parameter to each local cell to specify which global cell it's contained in.

If this uses up too much memory, we could go to a slower but still much, much faster than the blog post's method of something like:

- Create 2d array where the 1st dimension is a sorted list of local row values, one per global row value, that represent the maximum X value within any global cell. Then the the 2nd dimension are local column values, one per global column value that similarly correspond to the maximum Y value of any local cell per global cell. (mapping the coordinates to an array)

- Find the entry that the current local row value fits into (for example the entry with a value higher than the local row value, which is higher than the next list entry).

- This selects a second dimension array for that global row that has similar properties: it's only necessary to then find which value the local row fits into to determine the global cell (which would be the array's value at that index).