# Local Clustering Coefficient¶

Local Clustering Coefficient for vertex tells us howe close its neighbors are. It’s number of existing connections in neighborhood divided by number of all possible connections.

$$LC(x)=\sum_{v \in N(x)}{\frac{|N(x) \cap N(v)|}{|N(x)|*(|N(x)|-1)}}$$

Where $$N(x)$$ is set of neighbours of vertex $$x$$

For further informations please refer to [Watts].

import ml.sparkling.graph.operators.OperatorsDSL._
import org.apache.spark.SparkContext
import org.apache.spark.graphx.Graph

implicit ctx:SparkContext=???
// initialize your SparkContext as implicit value
val graph =???

val centralityGraph: Graph[Double, _] = graph.localClustering()
// Graph where each vertex is associated with its local clustering coefficient


You can also compute local clustering coefficient for graph treating it as undirected one:

import ml.sparkling.graph.operators.OperatorsDSL._
import org.apache.spark.SparkContext
import ml.sparkling.graph.api.operators.measures.VertexMeasureConfiguration
import org.apache.spark.graphx.Graph

implicit ctx:SparkContext=???
// initialize your SparkContext as implicit value
val graph =???