dolfin team mailing list archive

[Kent-Andre Mardal <kent-and@xxxxxxxxx>]

I think it should be disabled in parallel. Matrix slicing is very useful
during
development, testing and debugging, but introduces more troubles than
uses in parallel.

Kent

On 2 January 2011 07:47, Johan Hake <johan.hake@xxxxxxxxx> wrote:

> Hello!
>
> As pointed out by Garth in a couple of commit messages lately we need to
> consider the slicing interface for vectors and matrices in PyDOLFIN.
>
> Now that the parallel interface are starting to get more and more robust
> (great work Garth!) we need to consider what:
>
>  v[6], v[4:], v[index_array] # returning a scalar and a vector
>  A[5,6], A[5:,6], A[5:,6:] # returning a scalar, a vector and a matrix
>
> should return for serial and parallel structures.
>
> I guess Garth comments that the Matrix slicing "is just a toy" has some
> merits
> as it uses a dense representation of the Matrix (even though it is erasing
> zero entries). Regardless if we decide to discard the Matrix slicing or not
> we
> need to decide how off process indices should be treated.
>
> As it is now, a user need to check whether an index is owned by the local
> processor or not, by using GenericVector::owns_index, before he access the
> data.
>
> An other scenario would be to always allow a user to write:
>
>  v[5], v[4:] and v[index_array]
>
> and then return for example None (for single value access) and a reduced
> vector (only including local values) for the two other alternatives. Then
> the
> user need to deal with the result knowing how we treat this in parallel.
>
> Matrix slicing is more tricky especially now when GenericMatrix::resize is
> removed. There are probably ways of getting around this by building a
> SparsityPattern based on the slice. But I am not sure it makes any senses
> to
> do a matrix slice for a parallel structure, as it is only the rows that are
> local. Then we need to decide if the Matrix slicing should be:
>
>  1) removed
>  2) reimplemented but disabled in parallel
>  3) reimplemented for both serial and parallel cases using for example
>     a similar approach as sketched above for vectors, that is always
>     returning something.
>
> Best regards,
>
> Johan
>
>
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