Result of the igraph multi-level community detection algorithm. More...

#include <ClusterSnnGraph.hpp>

Public Attributes
int	status = 0

size_t	max = 0

std::vector< std::vector< int > >	membership

std::vector< double >	modularity

Detailed Description

Result of the igraph multi-level community detection algorithm.

Instances should be constructed using the ClusterSnnGraphMultiLevel::run() methods. A separate set of clustering results are reported for each level. The level providing the highest modularity is also reported; the clustering at this level is usually a good default choice.

Member Data Documentation

◆ status

int scran::ClusterSnnGraphMultiLevel::Results::status = 0

Output status. A value of zero indicates that the algorithm completed successfully.

◆ max

size_t scran::ClusterSnnGraphMultiLevel::Results::max = 0

The level that maximizes the modularity. This can be used to index a particular result in membership and modularity.

◆ membership

std::vector<std::vector<int> > scran::ClusterSnnGraphMultiLevel::Results::membership

Each vector contains the clustering result for a particular level. Each vector is of length equal to the number of cells and contains 0-indexed cluster identities.

◆ modularity

std::vector<double> scran::ClusterSnnGraphMultiLevel::Results::modularity

Modularity scores at each level. This is of the same length as membership.

The documentation for this struct was generated from the following file: