[Octave-bug-tracker] [bug #41478] Include non-standard logical matrix-multiply operations

[David Spies]

URL:
  <http://savannah.gnu.org/bugs/?41478>

                 Summary: Include non-standard logical matrix-multiply
operations
                 Project: GNU Octave
            Submitted by: dspyz
            Submitted on: Thu 06 Feb 2014 07:56:21 GMT
                Category: Octave Function
                Severity: 3 - Normal
                Priority: 5 - Normal
              Item Group: Feature Request
                  Status: None
             Assigned to: None
         Originator Name: 
        Originator Email: 
             Open/Closed: Open
         Discussion Lock: Any
                 Release: dev
        Operating System: Any

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Details:

Can you add three fairly standard logical matrix multiply operations
(particularly for sparse matrices) which can be useful for dealing with graphs
and adjacency matrices?

mult_any
Same as
res = logical(A * B)

mult_all
Same as
res = A * B == sum(B,1)
(here the '==' is automatically broadcasted)
This one is the one I actually need since the matrix A * B may require more
memory than I have available, but I suspect there's a more memory efficient
way to make this particular computation.
Particularly if we find a k such that A(i,k) is false and B(k,j) is true than
res(i,j) must be false (without having to explore other k-values)

mult_parity
Same as
res = logical(mod(A * B,2))



You can think of these operations in the context that the columns of B mark
sets of relevant variables and the rows of A are values for those variables. 
The resulting matrix represents each of the operations (any, or, parity) for
each set of values on each set of variables.

Note that a normal matrix multiply can be thought of as mult_join_sum for a
logical matrix B.

I suppose there could be others like mult_maj, but that doesn't correspond to
a commutative associative binary operation like the others (and, or, xor), so
I expect there might not be anything to be gained by implementing it
explicitly.




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