dolfin team mailing list archive

[Johan Hake <hake@xxxxxxxxx>]

Ali!

> def numpyArrayToDolfinMatrix(a):
>     nx = a.shape[0]
>     ny = a.shape[1]
>     m = dolfin.Matrix(nx, ny)
>     m.set(a, numpy.arange(0, nx, dtype=numpy.uint0), numpy.arange(0,
> ny, dtype=numpy.uint0))
>     m.apply();
>     return m
>
> Can you confirm that from the c++ side, just a buffer pointer is
> passed and there is no loop involved?

For the DOLFIN library this depends on which linear backend you are using. 
This is given by:

  dolfin_get("linear algebra backend")

For the uBLAS and MTL4 backend we do a loop. For the PETSc and Epetra backend 
we just send the pointer to the underlying library. The last ones support 
distributed data, which DOLFIN also intend to use, so there will probably be 
some loop in these libraries too.

> I'm actually trying to convert a c++ image data structure to dolfin
> matrix, why shouldn't dolfin have a design to dynamically accept this
> sort of input? 

Well, the DOLFIN library is built to produce the matrices by assembling 
variational problems defined by forms. The DOLFIN linear algebra part is 
built to facilitate this, and to be able to use different backends.

> Here is how the c++ image data is converted from/to 
> numpy in our project:
>
> http://code.google.com/p/wrapitk/source/browse/trunk/ExternalProjects/PyBuf
>fer/itkPyBuffer.txx
>
> I'm trying to solve some variational image processing problems where
> the data term in the PDE comes from the image buffer. Just to make
> sure, is dolfin matrix the right way of inputing the image data or am
> I missing something?

I think the best way to find out is to state your question in mathematical 
terms. Who knows maybee someone on the list are trying to solve the same 
problem, I am not...

Probably you want to read in the data in a Function and use this in your 
variational formulation. 

Johan