Edward Grace wrote:
I don't quite understand why you wouldn't want a DSL like MATLAB? After all, MATLAB remember is essentially FORTRAN with different horse shoes, that's why so many scientific / engineering types pick it up so fast - there is very little that's new to learn.
Not saying that I wouldn't want it, saying that perhaps there are some gems in other languages, too. I do not have a Fortran background, but I have to admit that I have used R rather extensively. R/S stuff like A[row(A)==col(A)] <- 2 is easy to use, but does not really match with something like std::fill( diag(A).begin(), diag(A).end(), 2 ); which would perhaps be the C++ way.
For example,
alpha(2:10)=alpha(1:9)
Is the above MATLAB or FORTRAN? How would you express this in C++ (note the aliasing)? Perhaps
alpha(range(2,10))=alpha(range(1,9));
or some-such?
Not sure, but given your example, something like std::rotate( alpha.begin(), alpha.begin()+1, alpha.end() ); :-). I agree the Matlab code is more readable in this case.
How about,
vec=mat(:,4)
(Again, is that MATLAB or is it FORTRAN?)
Are you copying or keeping a reference? Anyway, vec = row(mat,4) vec = diag(mat) etc.
Have you considered creating a more C++-like domain-specific language, taking elements from various domain-specific languages?
Can you give some examples?
E.g., I would prefer x = solve( A, b ) over x = A\b;
If you go and write a whole new paradigm (interface) for linear algebra without at least a nod to it's heritage it will probably be ignored by many of the people who actually *do* it for a living and get used just by hobbyists who enjoy the process rather than the result. (I'm guilty of that myself - hence I'm here).
I'm not after that. I'm just saying that there might be people who actually do stuff in other packages than Matlab (like R et al.). What I also wanted to add is that many (real-life) examples of algorithms do not contain that much linear algebra. I've seen a great deal of .m files which have about 20% linear algebra. About 80% is conditional program flow and bookkeeping stuff. This is where C++ has a clear edge. If we're going to mix them, it should look natural.
In my humble opinion, for C++ to really take off in next generation scientific applications (believe me I'd love to see it happen), the language should keep out of the way. Ultimately application writers just want the answer - they really don't want to have to figure out how the minutiae of template meta-programming works.
Indeed, it should be easy to write. Just as an example, a function "solve" would already cover a large portion of the whole of LAPACK. A DSL for linear algebra does not need to be complex. The more expressiveness, the better, I would say. Cheers, Rutger