dolfin team mailing list archive

[Ola Skavhaug <skavhaug@xxxxxxxxx>]

On Mon, Jun 22, 2009 at 10:44 AM, Garth N. Wells<gnw20@xxxxxxxxx> wrote:
> Johan Hake wrote:
>> On Saturday 20 June 2009 13:10:46 Garth N. Wells wrote:
>>> I tried to do
>>>
>>>    u0.vector() = u1.vector()
>>>
>>> where u0 and u1 are both discrete functions, in PyDOLFIN but it doesn't
>>> work so I'm using
>>>
>>>    u0.vector().assign( u1.vector() )
>>
>> This is the correct way to do it. Assignment operators are just ignored for
>> the dynamically typed languges supported by SWIG. We therefore rename the
>> foo.operator= to foo.assign.
>>
>> However for the Vector and Matrix interfaces we also support the numpy
>> lookalike assignment:
>>
>>   v[:] = u
>>
>> and
>>
>>   A[:,:] = B
>>
>> I have talked to Anders about removing both v.assign and v.set(double *)
>> and "force" the PyDOLFIN users to use the numpy assignments.
>>
>
> Is there any difference in performance between the two?
>
> Garth

The slicing means that the actual memory of A is overwritten. I guess
that is the same as the operator= did before?
Hence, I guess there will be no big difference.

Ola

>> Johan
>>
>>
>>> Is there a fundamental reason why '=' can't be used or does SWIG just
>>> need to be told how to overload '=' for vectors?
>>>
>>> Garth
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>
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-- 
Ola Skavhaug