> I think it would give a good insight of Eigen and, since this is
tutorial
> number 7, the user should already have a good background on Eigen.
I could
> explain what is happening at each '.' in the previous _expression_
to make it
> clear and show how powerful Eigen is.
> However, I know that this might be a bit advanced for a starters'
tutorial,
> so I will wait for your thoughts on this.
> Cheers,
> Carlos
>
>
> On Thu, Jul 1, 2010 at 5:12 PM, Carlos Becker <
carlosbecker@xxxxxxxxx>
> wrote:
>>
>> Thanks. It was to know what to put in each subsection since I
made one for
>> visitors, one for reductions and one for broadcasting. So now
it is clear.
>> Thanks
>>
>>
>> On Thu, Jul 1, 2010 at 3:10 PM, Benoit Jacob <
jacob.benoit.1@xxxxxxxxx>
>> wrote:
>>>
>>> 2010/7/1 Carlos Becker <
carlosbecker@xxxxxxxxx>:
>>> > I thought that with matrix.colwise().sum(), colwise()
is treated as a
>>> > visitor, and with += it is a broadcasting operation.
This is because I
>>> > read
>>> > this on your tutorial proposal:
>>> > 7. Reductions, visitors, and broadcasting
>>> > - for all kinds of matrices/arrays
>>> > - sum() etc...
>>> > - mention partial reductions with .colwise()...
>>> > - mention broadcasting e.g. m.colwise() += vector;
>>> > I thought that partial reductions were done with
visitors and
>>> > broadcasting
>>> > was something similar but with 'write access'. Or
maybe both are
>>> > visitors, I
>>> > guess I am missing many concepts here.
>>>
>>> computing a sum is a reduction (or partial reduction) not
a visitor.
>>>
>>> a visitor is when you want to find, as output, a location
inside of a
>>> matrix.
>>>
>>> For example, this is a reduction:
>>>
>>> result = matrix.maxCoeff();
>>>
>>> this is a visitor:
>>>
>>> Index i, j;
>>> matrix.maxCoeff(&i, &j);
>>>
>>> Anyway, don't bother learning a new area of Eigen just to
write docs
>>> about it :-)
>>>
>>> Benoit
>>>
>>>
>>>
>>>
>>> >
>>> >
>>> > On Thu, Jul 1, 2010 at 2:46 PM, Benoit Jacob <
jacob.benoit.1@xxxxxxxxx>
>>> > wrote:
>>> >>
>>> >> Broadcasting means e.g.
>>> >>
>>> >> matrix.colwise() += vector;
>>> >>
>>> >> Visitors are e.g.
>>> >>
>>> >> Index i, j;
>>> >> matrix.maxCoeff(&i, &j);
>>> >>
>>> >> These are two really different things, no?
>>> >> Benoit
>>> >>
>>> >> 2010/7/1 Carlos Becker <
carlosbecker@xxxxxxxxx>:
>>> >> > Just a quick question: what would be the
difference between visitors
>>> >> > and
>>> >> > broadcasting? Seems to me that broadcasting
is able to 'visit'
>>> >> > column or
>>> >> > row-wise, also modifying the data inside the
matrix/array object, am
>>> >> > I
>>> >> > right? I haven't used broadcasting with
eigen before.
>>> >> >
>>> >> >
>>> >> >
>>> >> > On Wed, Jun 30, 2010 at 1:30 PM, Carlos
Becker
>>> >> > <
carlosbecker@xxxxxxxxx>
>>> >> > wrote:
>>> >> >>
>>> >> >> oh ok sorry, got confused since I
thought that someone was alreay
>>> >> >> writing
>>> >> >> the sparse tut
>>> >> >>
>>> >> >>
>>> >> >> On Wed, Jun 30, 2010 at 1:29 PM, Gael
Guennebaud
>>> >> >> <
gael.guennebaud@xxxxxxxxx>
wrote:
>>> >> >>>
>>> >> >>> nevermind, this
C07_TutorialSparse.dox file is an old one...
>>> >> >>>
>>> >> >>> gael
>>> >> >>>
>>> >> >>> On Wed, Jun 30, 2010 at 2:26 PM,
Carlos Becker
>>> >> >>> <
carlosbecker@xxxxxxxxx>
>>> >> >>> wrote:
>>> >> >>> > I am starting with the
reductions/visitors/broadcasting tutorial
>>> >> >>> > and
>>> >> >>> > just
>>> >> >>> > noticed that the sparse
tutorial is named as
>>> >> >>> > C07_TutorialSparse.dox.
>>> >> >>> > According to the order
>>> >> >>> > in
http://eigen.tuxfamily.org/dox-devel/ it
>>> >> >>> > should be
>>> >> >>> > C08 and C07 is to be the one I
am doing. This is a silly
>>> >> >>> > question
>>> >> >>> > but
>>> >> >>> > just
>>> >> >>> > wanted to make sure we are all
following the same conventions.
>>> >> >>> > Carlos
>>> >> >>> >
>>> >> >>> > On Sun, Jun 27, 2010 at 1:59
PM, Gael Guennebaud
>>> >> >>> > <
gael.guennebaud@xxxxxxxxx>
>>> >> >>> > wrote:
>>> >> >>> >>
>>> >> >>> >> On Sun, Jun 27, 2010 at
12:41 PM, Carlos Becker
>>> >> >>> >> <
carlosbecker@xxxxxxxxx>
>>> >> >>> >> wrote:
>>> >> >>> >> > Mmm I am trying to
think of a straightforward explanation for
>>> >> >>> >> > this.
>>> >> >>> >> > What
>>> >> >>> >> > do
>>> >> >>> >> > you think about
calling them fixed-size and dynamic-size
>>> >> >>> >> > blocks,
>>> >> >>> >> > where
>>> >> >>> >> > the
>>> >> >>> >> > former differs from
the later because its size is known at
>>> >> >>> >> > compile-time.
>>> >> >>> >>
>>> >> >>> >> a slightly more precise
variant: "the latter are optimized
>>> >> >>> >> versions
>>> >> >>> >> of
>>> >> >>> >> the former when the size is
known at compile-time." I just
>>> >> >>> >> added
>>> >> >>> >> the
>>> >> >>> >> word "optimized"
>>> >> >>> >>
>>> >> >>> >> you might also have a look
at the reference tables, section
>>> >> >>> >> "Sub
>>> >> >>> >> matrices" to see how they
are presented. The old version of
>>> >> >>> >> this
>>> >> >>> >> section is available online
there:
>>> >> >>> >>
>>> >> >>> >>
>>> >> >>> >>
>>> >> >>> >>
>>> >> >>> >>
>>> >> >>> >>
http://eigen.tuxfamily.org/dox-devel/TutorialCore.html#TutorialCoreMatrixBlocks
>>> >> >>> >>
>>> >> >>> >> gael
>>> >> >>> >>
>>> >> >>> >> >
>>> >> >>> >> >
>>> >> >>> >> > On Sun, Jun 27, 2010
at 11:02 AM, Carlos Becker
>>> >> >>> >> > <
carlosbecker@xxxxxxxxx>
>>> >> >>> >> > wrote:
>>> >> >>> >> >>
>>> >> >>> >> >> Yes, I got that
and actually it was my mistake since I
>>> >> >>> >> >> supposed
>>> >> >>> >> >> that it
>>> >> >>> >> >> was only for
fixed-size matrices, so now I am changing it.
>>> >> >>> >> >> Thanks,
>>> >> >>> >> >>
>>> >> >>> >> >>
>>> >> >>> >> >> 2010/6/27 Björn
Piltz <
bjornpiltz@xxxxxxxxxxxxxx>
>>> >> >>> >> >>>
>>> >> >>> >> >>> "The following
tables show a summary of Eigen's block
>>> >> >>> >> >>> operations
>>> >> >>> >> >>> and
>>> >> >>> >> >>> how
>>> >> >>> >> >>> they are
applied to fixed- and dynamic-sized Eigen
>>> >> >>> >> >>> objects."
>>> >> >>> >> >>> This quote and
the following table gives the impression
>>> >> >>> >> >>> that
>>> >> >>> >> >>> the
>>> >> >>> >> >>> fixed
>>> >> >>> >> >>> size functions
are only available for fixed size matrices.
>>> >> >>> >> >>> But
>>> >> >>> >> >>> using
>>> >> >>> >> >>> fixed
>>> >> >>> >> >>> size vs
dynamic size functions acually only determin the
>>> >> >>> >> >>> return
>>> >> >>> >> >>> type.
>>> >> >>> >> >>> Björn
>>> >> >>> >> >
>>> >> >>> >> >
>>> >> >>> >>
>>> >> >>> >>
>>> >> >>> >
>>> >> >>> >
>>> >> >>>
>>> >> >>>
>>> >> >>
>>> >> >
>>> >> >
>>> >>
>>> >>
>>> >
>>> >
>>>
>>>
>>
>
>