Article companion¶
What these are
These notebooks accompany the survey article Community Detection with the Map Equation and Infomap: Theory and Applications (doi:10.1145/3779648), section by section. They are more academic and article-aligned than the rest of this site. For a gentler, Python-first path, start with the chapters: Concepts, Working with Infomap, Flow models, Workflows, and Robustness. Treat these notebooks as deeper companion reading.
The notebooks live in the Infomap repository under
examples/notebooks/
and their numbers match the survey’s sections. Some require additional
research code or data-processing packages, so the documentation build does not
execute them.
Foundations¶
3.1 The two-level map equation: the core objective. Gentler path: The map equation.
4.1 The two-level phase: the search algorithm. Related: Running Infomap.
4.3 Solution landscape: degenerate solutions and reliability. Related: Reading results and iterating.
Higher-order representations¶
5.1 Memory networks. See also: Memory and state networks.
5.2 Multilayer networks. See also: Multilayer networks.
5.3 Modeling temporal data. See also: Temporal networks.
Metadata, bipartite, and incomplete data¶
6.1 Networks with metadata. See also: Networks with metadata.
6.2 Bipartite networks. See also: Bipartite networks.
7 Networks with incomplete data. See also: Incomplete data and regularization.
Applications¶
Not yet covered by a narrative chapter
These four application topics do not have a dedicated chapter on this site yet. For now, the companion notebooks below are the best Python starting point.
9.1 Map equation centrality: a community-aware centrality from the map equation’s coding scheme.
9.2 Map equation similarity: MapSim node similarity and link prediction.
9.3 Infomap bioregions: delineating biogeographical regions from species occurrences.
9.4 Model selection with correlational data: choosing a correlation threshold by codelength savings.
Citing this work¶
If you use Infomap, cite the 2008 PNAS paper and the MapEquation software package. See How to cite Infomap. To cite the survey itself, use doi:10.1145/3779648.