Subject: Re: [boost] different matrix library?
From: DE (satan66613_at_[hidden])
Date: 2009-08-14 17:49:49
on 15.08.2009 at 1:28
Edward Grace wrote :
> Would it be possible to have entirely abstracted matrices, ones that
> do not contain any numbers, just rules for their combination
> (multiplication etc)?
> For example, if we were to do:
> abstract_matrix<2> Z;
> // First template argument is number of dims, second the locations
> of the +1 elements.
> Z = 3.0*abstract_symmetric_matrix<2,0>() +
> we would end up with a matrix Z that contains just two independent
> values (3,4) as before but crucially also contains all the rules for
> its multiplication so that:
> double length_squared = Z*transpose(Z);
> is, for example, an entirely valid operation that reduces to
> length_squared = 3^2+4^2 and has the type of an
> abstract_symmetric_matrix<2,0> which is identically castable to a
i think theoretically it's possible
since one can compute any computable value thriugh template
metaprogramming - why not?
but i have doubts about profits of all that stuff
> As another example, the previously quoted:
> outer product when applied to a pair of vectors of length 3 will
> always result in a matrix with 6 independent components (the same
> number of degrees of freedom that we started with). The resulting
> matrix (representing a 2 form) is therefore not a general matrix at
> all. Therefore when using that resulting matrix why should we use up
> 9 chunks of memory and repeat calculations when we only need to store
> 6 and can subsequently reduce the number of calculations. Obviously
> this is a trivial example, but when the matrix is NxN it can be
> The parting shot is that if one can see through the layers of
> abstraction there is a real possibility for building a phenomenally
> efficient linear algebra library that is practically self aware!
actually, if i got the point right, an implementation might do just
what you wrote
it doesn't hold the resulting matrix but rather an expression with
some rules of computing the elements of resulting matrix
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