I have a group of objects identified by unique (x,y) pairs and I want to
find out an object's "neighbors" in a matrix of size 2400 x 2400.
#############
#obj# # #
#############
# # #obj# 3 x 3 Example
#############
# # # #
#############
There is either a neighbor, or a null value. I always know the (x,y)
pair to check the neighbors of, so is doing,
>> obj = grid[x][y] #lists, doesn't scale with num of objects
or,
>> obj = grid.get((x,y),None) #dictionary, scales with num of objects
the fastest? I can't seem to find a conclusion by testing each alone,
then in the full environment. Is it that, depending on the number of
objects, each has an advantage?
I know the fastest way to retrieve them would be to have them store
pointers to their neighbors, then use those for retrieval. When large
numbers of objects are changing their (x,y) pairs, rebuilding the
pointers is too slow.
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