How Does One Sum Dimensions Of An Array Specified At Run-Time?
I am working on a function to establish the entropy of a distribution. It uses a copula, if any are familiar with that. I need to sum up the values in the array based on which dimensions are "cared about."
Example: Consider the following example...
Dimension 0 (across) _ _ _ _ _ _ _ _ _ _ _ _ _ |_ 0 _|_ 0 _|_ 0 _|_ 2 _| Dimension 1 |_ 1 _|_ 0 _|_ 2 _|_ 0 _| (down) |_ 0 _|_ 3 _|_ 0 _|_ 6 _| |_ 0 _|_ 0 _|_ 0 _|_ 0 _| I "care about" dimension 0 only, and "don't care" about the rest (dim 1). Summing this array with the above specifications will "collapse" the "stacks" of dimension 1 down to a single 4 x 1 array: _ _ _ _ _ _ _ _ _ _ _ _ _ |_ 1 _|_ 3 _|_ 2 _|_ 8 _| This can then be summed, or have any operation performed.
I need to do this with an array of 'n' dimensions, which could feasibly be 20. Also, I need to be able to do this, caring about certain dimensions, and collapsing the rest. I am having an especially hard time with this because I cant visualize 20 dimensions :p . If anyone could help me set up some c/c++ code to collapse/sum, I would be very very grateful.
Just got home. Here is some info to answer your questions:
- Sorry for rolling back the edits, I was hoping when I clicked roll-back it would show me the changes so I could see what I messed up, a bit like wikipedia. This wasn't the case, as I found out.
- @jeff - What doesnt make sense? I am using this great service for (what I think is) a legit reason. I want to get better at my hobby, which is all it is, as I am in high school. Many of my posts regard implementing a genetic algorithm (This post, sparsearray, rank an array, pointer manipulation).
- I am using a sparse array representation, as it is possible to exceed the number of molecules in the universe using a traditional (dense) array. For now, the implementation of the sparsearray itself doesnt matter a whole lot, as I am working to make it work with a standard array before going to a sparse representation. For those who havent seen my previous questions, I am using a binary search tree as the structure to contain the sparse array points, and a "driver" function to traverse the tree as necessary, returning whatever the function is designed to do. This is flexible, so I can accomodate a lot of different methods of accessing the array.
- The structure is a hypercube, and the number of dimensions is specified at run time, as well as the length of each dimension (which are all the same, as it is a hypercube).
Thanks everyone for your imput.
This could have applications. Lets say you implemented a 2D Conway's Game of Life (which defines a 2D plane, 1 for 'alive', 0 for 'dead') and you stored the Games history for every iteration (which then defines a 3D cube). If you wanted to know how many bacteria there was alive over history, you would use the above algorithm. You could use the same algorithm for a 3D, (and 4D, 5D etc.) version of Game of Life grid.
I'd say this was a question for recursion, I'm not yet a C programmer but I know it is possible in C. In python,
def iter_arr(array): sum = 0 for i in array: if type(i) == type(list()): sum = sum + iter_arr(i) else: sum = sum + i return sum
- Iterate over each element in array
- If element is another array, call the function again
- If element is not array, add it to the sum
- Return sum
You would then apply this to each element in the 'cared about' dimension.
This is easier in python due to duck-typing though ...
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