Question

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.

Update:

Just got home. Here is some info to answer your questions:

1. 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.
2. @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).
3. 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.
4. 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.

Answer 1

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  

1. Iterate over each element in array
2. If element is another array, call the function again
3. If element is not array, add it to the sum
4. 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 …