
Boost : 
From: Joerg Walter (jhr.walter_at_[hidden])
Date: 20020326 16:07:46
Hi Kresimir,
you wrote:
> > [...] If a sparse matrix result is assigned to a dense matrix,
> > the assignment operation should be dispatched to
> > the sparse matrix logic: clear the dense matrix and insert
> > the rhs elements at the corresponding positions.
>
> I am afraid that I found a bug in the implementation of this
> assignment:
I simply shouldn't tell you, how the software is supposed to work ;)
> This works:
>
> // default array_type: unbounded_array<>
> typedef numerics::vector<double> vct_t;
> typedef numerics::sparse_vector<double> sp_vct_t;
>
> vct_t v (8);
> sp_vct_t sv (8, 3);
>
> sv[1] = 1.1; sv[3] = 3.1; sv[4] = 4.1;
>
> v = sv;
> cout << v << endl;
> // output is, of course: [8](0,1.1,0,3.1,4.1,0,0,0)
>
> This works, too:
>
> typedef numerics::vector< double,
> numerics::array_adaptor<double> > vct_t;
> typedef numerics::sparse_vector<double> sp_vct_t;
>
> std::vector<double> storage (8); // ;o)
> numerics::array_adaptor<double> aa (8, &storage[0]);
Funny.
> vct_t v (8, aa);
>
> vct_t v (8);
> sp_vct_t sv (8, 3);
> sv[1] = 1.1; sv[3] = 3.1; sv[4] = 4.1;
>
> v = sv; // same output
>
> But this doesn't:
>
> typedef numerics::vector< double,
> std::vector<double> > vct_t;
> typedef numerics::sparse_vector<double> sp_vct_t;
>
> vct_t v (8);
> sp_vct_t sv (8, 3);
> sv[1] = 1.1; sv[3] = 3.1; sv[4] = 4.1;
>
> v = sv;
>
> It causes ``Segmentation fault'' (at least on Linux
> with g++ 3.0.4). And IMHO with good reason:
>
> `numerics::vector_assign<>::operator()' with `sparse_tag'
> uses `array_type::clear()' to clear `numerics::vector<>'
> before assignement, that is, before the call to
> `array_type::insert()'. But the behaviour and semantics of
> `numerics::unbounded_array<>::clear()' and
> `numerics::array_adaptor<>::clear()' is very different
> from the behaviour of `std::vector<>::clear()'.
>
> First two simply assign `0' to all elements. But
> `std::vector<>::clear()' really clears the vector,
> ie. it *removes* all elements, and the postcondition
> is, according to standard, `size() == 0' which
> means that the vector is empty. And after that
> the insertation at particular position (except at the
> very beginning) fails because this position simply
> doesn't exist.
>
> Either the lines
>
> if (v.data().size() == 0)
> v.data().resize (e().size());
>
> should be added after `v.clear()' in
> `vector_assign<>::operator() (vct, vct_expr, sparse_tag)',
> or
>
> std::fill (v.begin(), v.end(), value_type());
>
> should be used instead of `v.clear ();'.
You're right. I've changed the code in numerics::vector<>::clear and
numerics::matrix<>::clear to use std::fill instead. The change is checked in
already.
> Another possibilities are to specialize `vector_assign<>'
> for `std::vector<>' or to use some traits class.
>
> Sincerely,
>
> fres
>
>
> PS. BTW, arguments of the constructor of `sparse_vector<>'
> are `size' and `non_zero', that is vector size and number of
> nonzeros. Documentation says only: ``Allocates a
> sparse_vector that holds at most size elements.'' What about
> `non_zero'? Can it hold more than `non_zero' nonzeros?
> Less? Or must one call `resize (size, non_zero2)' to change
> the number of nonzeros?
I introduced the argument 'non_zero' in anticipation of a 'true' sparse
vector implementation, where it should state the maximum number of non zero
elements the vector can hold. We've recently added a such a traditional
sparse vector under the name compressed_vector. OTOH, our current
sparse_vector is interesting, because it can be used in conjunction with
std::map :).
So two questions arise:
 should we eliminate the superfluous non_zero for sparse_vector?
 should we rename sparse_vector and/or compressed_vector?
> PPS. It would be useful to add `num_non_zeros()' function
> to `sparse_vector<>' which returns the number of nonzero
> elements.
Agreed.
Thanks for your feedback and best regards
Joerg
Boost list run by bdawes at acm.org, gregod at cs.rpi.edu, cpdaniel at pacbell.net, john at johnmaddock.co.uk