fenics team mailing list archive

[Anders Logg <logg@xxxxxxxxx>]

On Tue, Sep 07, 2010 at 10:19:15AM -0700, Johan Hake wrote:
> On Tuesday September 7 2010 10:08:34 Kristian Ølgaard wrote:
> > On 7 September 2010 18:51, Johan Hake <johan.hake@xxxxxxxxx> wrote:
> > > On Tuesday September 7 2010 09:24:40 Kristian Ølgaard wrote:
> > >> On 7 September 2010 17:59, Johan Hake <johan.hake@xxxxxxxxx> wrote:
> > >> > [snip]
> > >> >
> > >> >> > But how do we extract the different arguments? I suppose this is
> > >> >> > collected by Doxygen, and we just need to parse these and output
> > >> >> > them in a correct way?
> > >> >>
> > >> >> I don't think we need to parse the arguments and output them. We just
> > >> >> get the function name and if we have more than one set of arguments
> > >> >> i.e., a different signature we know that we have an overloaded method
> > >> >> and how to handle it.
> > >> >
> > >> > And I guess the almighty generate_cpp_documentation.py script are able
> > >> > to extract the argument information?
> > >>
> > >> No, but we should be able to figure this out from the signature (split
> > >> ',' in '()').
> > >
> > > Ok! Anders mentioned this too.
> > >
> > >> >> The arguments should be described in the *Arguments* section of the
> > >> >> individual docstring with links to classes formatted like
> > >> >> _MeshEntity_, which we will substitute with :py:class:`MeshEntity` or
> > >> >>
> > >> >> :cpp:class:`MeshEntity` depending on which interface we document.
> > >> >
> > >> > Ok, but we only want that once for each method in python, even if it
> > >> > is overloaded?
> > >>
> > >> No, I think we need to document the argument list for every overloaded
> > >> version like it is done in docstrings.dolfin.cpp.Mesh.
> > >
> > > Agree, I think I misunderstood you.
> > >
> > >> >> Although I just realized that standard C++ stuff like double* which
> > >> >> end up as numpy.array etc. should probably be handled.
> > >> >
> > >> > Yes this part I am a little worried about... But maybe a god
> > >> > handwritten lookup table will do the trick? At least for 99% of the
> > >> > cases ;)
> > >>
> > >> I share your concern, but if, as you suggest, we'll be able to get God
> > >> to hand write our documentation I think we should be OK. :)
> > >
> > > Good to have God on our side!
> > >
> > >> (a lookup table would be my best bet at the moment)
> > >
> > > Ok!
> > >
> > >> >> On a related note:
> > >> >> int some_func()
> > >> >> and
> > >> >> const int some_func() const
> > >> >> are different in C++, but in Python we don't have const right?
> > >> >> This will simplify the documentation a lot.
> > >> >
> > >> > Yes, we tend to %ignore all const versions of different methods.
> > >> >
> > >> > [snap]
> > >> >
> > >> >> >> >  * Extended methods needs to be handled in one of three ways:
> > >> >> >> >    1) Write the docstring directly into the foo_post.i file
> > >> >>
> > >> >> I like this option, if this is where we have the code for a function,
> > >> >> then this is where the docstring should be as it increases the
> > >> >> probability of the docstring being up to date.
> > >> >
> > >> > Ok, lets settle on this one. We also need to make sure that all
> > >> > %extended methods in the C++ layer gets a proper docstring. However I
> > >> > am not really sure how this can be done :P
> > >>
> > >> I'm not sure I follow this, which %extended methods do you mean?
> > >
> > > There are two ways to extend a class.
> > >
> > >  1) The C++ layer
> > >  2) The Python layer
> > >
> > > often we use 1) to create a protected helper method which is called using
> > > an extended method in the Python layer, 2). The latter can be properly
> > > documented directly.
> > >
> > > But some cases excists where we just extend the C++ layer, see for
> > > example the IMPLEMENT_VARIABLE_INTERFACE macro in shared_ptr_classes.i.
> > > These methods gets no docstrings and I am not sure it is possible to add
> > > them later.
> >
> > OK, docstrings for 2) should go in the code as we agreed, and I guess
> > 1) will fall under the 1% category which we may/may not be able to
> > handle in a clever way later.
>
> Ok.
>
> > >> > [snup]
> > >> >
> > >> >> > Why do we need to assign to these methods? They already get their
> > >> >> > docstrings from the docstrings.i file. However if we want to get
> > >> >> > rid of the new_instancemethod assignment above, we can just remove
> > >> >> > the
> > >> >>
> > >> >> Some history.
> > >> >> Initially, we wanted to have all docstrings separated from the DOLFIN
> > >> >> code and collected in the fenics-doc module. The easiest way to get
> > >> >> the >>> help(dolfin) docstring correct is to assign to __doc__
> > >> >> dynamically.
> > >> >> If we could do this we wouldn't even need the docstrings.i file and
> > >> >> things would be simple.
> > >> >> However, we discovered that this was not possible, and because of
> > >> >> that we still need to generate the docstrings.i file.
> > >> >> Then, still assuming we wanted to separate docs from code and keeping
> > >> >> docstrings in fenics-doc, I thought it would be easier to generate
> > >> >> the docstrings.i file from the handwritten docstrings module in
> > >> >> fenics-doc.
> > >> >> Some methods don't get their docstrings from the docstrings.i file
> > >> >> though, so we still need to assign to __doc__ which is the easiest
> > >> >> thing to do.
> > >> >> Just recently we decided to extract the docstrings from the C++
> > >> >> implementation thus moving the docs back into DOLFIN. This makes the
> > >> >> docstrings module almost superfluous with the only practical usage is
> > >> >> to have documentation for the extended methods defined in the _post.i
> > >> >> files but if we put the docstrings directly in the _post.i files we
> > >> >> no longer need it.
> > >> >
> > >> > Ok, then I do not see any reason for a separate docstring module,
> > >> > makes life a lite bit easier...
> > >>
> > >> Agree.
> > >
> > > Ok.
> > >
> > >> > [snep]
> > >> >
> > >> >> > I am confused. Do you suggest that we just document the extended
> > >> >> > Python layer directly in the python module as it is today? Why
> > >> >> > should we then dumpt the docstrings in a separate docstring
> > >> >> > module? So autodoc can have something to shew on? Couldn't autodoc
> > >> >> > just shew on the dolfin module directly?
> > >> >>
> > >> >> I'm confused too. :) I guess my head has not been properly reset
> > >> >> between the changes in documentation strategies.
> > >> >> The Sphinx autodoc can only handle one dolfin module, so we need to
> > >> >> either import the 'real' one or the docstrings dolfin module.
> > >> >> If we can completely remove the need for the docstrings module, then
> > >> >> we should of course include the 'real' one.
> > >> >
> > >> > Ok!
> > >> >
> > >> >> >> Then programmer's writing the Python
> > >> >> >> layer just need to document while they're coding, where they are
> > >> >> >> coding just like they do (or should anyways) for the C++ part.
> > >> >> >
> > >> >> > Still confused why we need a certain docstring module.
> > >> >>
> > >> >> Maybe we don't.
> > >> >>
> > >> >> >> >  2) for the extended Python layer in the cpp.py
> > >> >> >> >
> > >> >> >> > For the rest, and this will be the main part, we rely on parsed
> > >> >> >> > docstrings from the headers.
> > >> >> >> >
> > >> >> >> > The python programmers reference will then be generated based on
> > >> >> >> > the actual dolfin module using sphinx and autodoc.
> > >> >> >>
> > >> >> >> We could/should probably use either the dolfin module or the
> > >> >> >> generated docstring module to generate the relevant reST files.
> > >> >> >> Although we might need to run some cross-checks with the Doxygen
> > >> >> >> xml to get the correct file names where the classes are defined
> > >> >> >> in DOLFIN such that we retain the original DOLFIN source tree
> > >> >> >> structure. Otherwise all our documentation will end up in cpp.rst
> > >> >> >> which I would hate to navigate through as a user.
> > >> >> >
> > >> >> > This one got to technical for me. Do you say that there is no way
> > >> >> > to split the documentation into smaller parts without relying on
> > >> >> > the c++ module/file structure?
> > >> >>
> > >> >> But how would you split it?
> > >> >
> > >> > I do not know. But then I do not know what the generation step can
> > >> > take as different inputs.
> > >>
> > >> The write_python_documentation step should probably take the dolfin
> > >> module and the intermediate representation.
> > >
> > > What is the intermediate representation?
> >
> > It is whatever output we get from the extract_documentation script
> > which we'll add to the dolfin module. How it will look depends a bit
> > on what we need in the write_cpp_documentation and
> > write_python_documentation functions in fenics-doc.
>
> Ok.
>
> > >> >> It makes sense to keep the classes Mesh
> > >> >> and MeshEntity in the mesh/ part of the documentation. Unfortunately,
> > >> >> Swig doesn't add info to the classes in the cpp.py module about where
> > >> >> they were originally defined. This is why we need to pair it with
> > >> >> info from the xml output.
> > >> >
> > >> > Ok, but say we keep all documentation in one module. If you are able
> > >> > to pair the different classes or functions with a module name, or
> > >> > file name you are able to create documentation which is structured
> > >> > after this hierarchy?
> > >>
> > >> We need to figure out something, having everything in the cpp.py
> > >> module would create one big mess and it makes sense to follow the
> > >> DOLFIN C++ structure even for the Python interface.
> > >
> > > Ok, but we do not have everything in a big cpp file. Types get imported
> > > into the Dolfin namespace in __init__ mostly from cpp.py.
> >
> > My point is, there's no telling where the cpp.Mesh class was
> > originally defined. Everything from la to mesh to fem is dumped in the
> > cpp.py module.
>
> Ok, but don't you just need a way to associate the classes to different
> modules? I thought this was what you used the doxygen output to. If we instead
> use the module representation we should be able to do this association
> directly with just the dolfin tree as the assosiated types should reside in:
>
>   dolfin.submodule.__dict__
>
> > > Would it help to add the cpp imports to submodules instead of the main
> > > __init__ file? We already have the submodules:
> > >
> > >  mesh, common, compilemodules, fem, adaptivity and function
> > >
> > > We could add:
> > >
> > >  io, log, nls, ode, parameter, ale
> > >
> > > and drag in stuff from cpp.py in these modules instead. In this way we
> > > structure the main __init__ file better, and you might be able to
> > > structure the pythons reference manual better?
> >
> > I'm quite sure I tried something like this, and the problem was that
> > even if you do:
> >
> > from dolfin.cpp import Mesh
> >
> > in dolfin/mesh/__init__.py
> >
> > the Mesh class will still point to dolfin.cpp when you inspect it -->
> > difficult to create the proper structure for the *.rst files.
>
> Would something that I sceted above work?
>
> > I'll need to double check though that this is really the case.
> > And even if we can use the approach you outline above it means that we
> > have more stuff we need to manually maintain.
>
> Sure, but now everything is throwed into dolfin/__init__.py which is really a
> mess now.
>
> Johan

This discussion is getting long and complex. I'm tempted to just let
the two of you sort it out between you and then ask for a 10-line
summary.

And then, of course, suggest a completely different solution. :-)

--
Anders