feat: expose voronoi to python

[BeaMarton13]

I used Cody for the functions.

• By submitting this pull request, I assign the copyright of my contribution to The igraph development team.

[ntamas]

Try to avoid re-formatting the .py files even if your IDE insists on reformatting. It makes it much harder to go through the PR and separate pure formatting-only modifications from the "real" part of the PR.

[szhorvat]

Only a few comments, not an exhaustive review.

[ntamas]

Not a full review yet, I haven't checked the unit test and the Python side in detail. From a bird's eye view the Python side looks good.

[Copilot]

Pull Request Overview

This pull request exposes a new Voronoi community detection algorithm to Python.

• Adds new test cases in tests/test_decomposition.py to validate the Voronoi clustering implementation.
• Implements the _community_voronoi function in src/igraph/community.py with detailed documentation.
• Updates the Python API and C extension bindings in src/igraph/init.py and src/_igraph/graphobject.c respectively.

Reviewed Changes

Copilot reviewed 4 out of 4 changed files in this pull request and generated 2 comments.

File	Description
tests/test_decomposition.py	Introduces tests for the community_voronoi method using multiple graph scenarios.
src/igraph/community.py	Implements the Voronoi clustering algorithm with comprehensive documentation.
src/igraph/init.py	Exposes the new community_voronoi function through the public API.
src/_igraph/graphobject.c	Adds the C extension binding for community_voronoi, handling Python–C argument conversion and result packaging.

[szhorvat]

I think modularity should not be a parameter. Instead, let modularity be computed unconditionally. This takes little time compared to the rest of the algorithm.