Implementation¶
If you have a cool new idea for a better method, and you want to optimise it,
you can easily plug it in the current tool. This section explains how the
package is setup internally, and how you can extend it. Most of this concerns
C++
, and python
only comes in when exposing the resulting classes.
Method¶
All methods in the end derive from MutableVertexPartition
, which
implements almost all necessary details, such as moving actual nodes while
maintaining the internal administration. Similarly, it provides all the
necessary functionality for initialising a partition. Additionally, there are
two abstract classes that derive from this base class:
ResolutionParameterVertexPartition
and
LinearResolutionParameterVertexPartition
(which in turn derives from
the former class). If you want a method with a resolution parameter, you should
derive from one of these two classes, otherwise, simply from the base class
MutableVertexPartition
.
There are two functions that you need to implement yourself: diff_move()
and quality()
. Note that they should always be consistent, so that we can
double check the internal consistency. You should also ensure that the
diff_move function can be correctly used on any aggregate graph (i.e. moving a
node in the aggregate graph indeed corresponds to moving a set of nodes in the
individual graph).
That’s it. In principle, you could now use and test the method in C++
.
Python¶
Exposing the method to python
takes a bit more effort. There are various
places in which you need to change/add things. In the following, we assume you
created a new class called CoolVertexPartition
. In order of dependencies, it
goes as follows:
Your own new VertexPartition class should add some specific methods. In particular, you need to ensure you create a method
CoolVertexPartition* CoolVertexPartition::create(Graph* graph) { return new CoolVertexPartition(graph); }
and
CoolVertexPartition* CoolVertexPartition::create(Graph* graph, vector<size_t> const& membership) { return new CoolVertexPartition(graph, membership); }
These methods ensure that based on a current partition, we can create a new partition (without knowing its type).
In
python_partition_interface.cpp
some methods need to be added. In particularPyObject* _new_CoolVertexPartition(PyObject *self, PyObject *args, PyObject *keywds)
You should be able to simply copy an existing method, and adapt it to your own needs.
These methods need to be exposed in
pynterface.h
. In particular, you need to add the method you created in step (2) tolouvain_funcs[]
. Again, you should be able to simply copy an existing line.You can then finally create the Python class in
VertexPartition.py
. The base class derives from theVertexClustering
fromigraph
, so that it is compatible with all operations inigraph
. You should add the method as follows:class CoolVertexPartition(MutableVertexPartition): def __init__(self, ... ): ...
Again, you should be able to copy the outline for another class and adapt it to your own needs. Don’t forget to change to
docstring
to update the documentation so that everybody knows how your new cool method works.Expose your newly created
python
class directly in__init__.py
by importing it:from .VertexPartition import CoolVertexPartition
That’s it! You’re done and should now be able to find communities using your
new CoolVertexPartition
:
>>> louvain.find_partition(G, louvain.CoolVertexPartition);