Function py_raphtory::algorithms::local_triangle_count

pub fn local_triangle_count(
    g: &PyGraphView,
    v: &PyAny
) -> PyResult<Option<usize>>

Local triangle count - calculates the number of triangles (a cycle of length 3) for a node. It measures the local clustering of a graph.

This is useful for understanding the level of connectivity and the likelihood of information or influence spreading through a network.

For example, in a social network, the local triangle count of a user’s profile can reveal the number of mutual friends they have and the level of interconnectivity between those friends. A high local triangle count for a user indicates that they are part of a tightly-knit group of people, which can be useful for targeted advertising or identifying key influencers within a network.

Local triangle count can also be used in other domains such as biology, where it can be used to analyze protein interaction networks, or in transportation networks, where it can be used to identify critical junctions or potential traffic bottlenecks.