Hi Corbin,

On Wed, 25 Nov 2020 at 00:05, Bruno Turcksin <[email protected]>
wrote:

> deal.II has some limited support for python mainly for mesh manipulation.
> We have some python notebooks here
> <https://github.com/dealii/dealii/blob/master/contrib/python-bindings/notebooks/index.ipynb>.
> I think what you want to do is similar to the step-62 notebook. Right now,
> the only way to interact with numpy is to print the data to a file and then
> load it (see here
> <https://dealii.org/current/doxygen/deal.II/classLinearAlgebra_1_1Vector.html#a2fadcc595d3e7e9ba44de8c85fd7595c>
> and here
> <https://dealii.org/current/doxygen/deal.II/classSparseMatrix.html#a3141075e3ad6362fce005d2f1c8da699>).
> If you want to manipulate the mesh directly in python, you need
> boost.python and you need to configure deal.II with
> -DDEAL_II_COMPONENT_PYTHON_BINDING=ON. It's sometimes a little bit tricky
> to enable the python binding so don't hesitate to ask any question on the
> mailing list if you need help.
>
> On Tuesday, November 24, 2020 at 12:16:18 AM UTC-5 [email protected]
> wrote:
>
>>
>>    - what is the best practice for exporting deal.ii solution data in a
>>    way that Python / numpy can interact with it?
>>
>> Depending on what you want from the data, another option might be to
export the data as .vtu (*not* .vtk) and read it with VTKPython.  For
example, you can use VTKPython to grid it, and then work with the gridded
data with numpy.

If I/O turns out to be a bottleneck, you could also consider writing the
data as HDF5
https://www.dealii.org/current/doxygen/deal.II/namespaceHDF5.html
and then accessing the HDF5 file from Python (using h5py, for example).  I
haven't used deal.II's HDF5 export but HDF5 can sometimes vastly improve
I/O performance compared to text files or even other binary formats (e.g.,
with blosc compression).

>
>>    -  Is there a good way for external software to 'hook' into the
>>    deal.ii pipeline? Something like:
>>       - initialize a triangulation / grid
>>       - run the solver
>>       - make a call like: new_data = external_software(deal_ii_output,
>>       grid)
>>       - reinitialize the grid based on new_data
>>       - loop
>>
>> Have you used Cython at all?
https://cython.org/
It is my favorite way to use C and C++ libraries from Python (compared to
binding generators, or writing extensions by hand, or cffi).  It provides a
very natural way to transfer data to and from C or C++ library code using
typed numpy arrays.  It can take some patience to get what you want from
the documentation, but if you are already used to Python and have some
familiarity with C and C++ it makes it very easy to migrate code between C
/ C++ and Python.  So, for example, you can prototype in Python and
gradually shift functionality over to C or C++.

What I have found easiest is to put the heavy-lifting code in a static C++
library, building from the (awesome) deal.II tutorials and documentation,
and then wrap that C++ library into a loadable Python extension module
using Cython.  Then you can pass arguments from Python to your solver using
the extension module.

In my experience, the trickiest part of this is not Cython per se, but
getting testing and continuous integration working with the mix of
languages: C++, Cython, Python, and your build system (CMake?)
mini-language.

If you choose this route, another option for controlling your solver from
Python (possibly with less pain / dependencies than Boost.Python?) might be
pybind11 (disclaimer: haven't tried it myself).

Best

Alex

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