Package edu.cmu.tetrad.graph

Class RandomGraph

java.lang.Object

edu.cmu.tetrad.graph.RandomGraph

public class RandomGraph
extends Object

The RandomGraph class provides methods for generating random graphs. It includes methods for generating random directed acyclic graphs (DAGs), random graphs with arbitrary edges, and random scale-free graphs.

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static final class	RandomGraph.UniformGraphGenerator	Generates random DAGs uniformly with certain classes of DAGs using variants of Markov chain algorithm by Malancon, Dutour, and Philippe.

Method Summary

Modifier and Type	Method	Description
static void	addTwoCycles(Graph graph, int numTwoCycles)	addTwoCycles.
static void	fixLatents1(int numLatentConfounders, Graph graph)	fixLatents1.
static void	fixLatents4(int numLatentConfounders, Graph graph)	fixLatents4.
static Graph	randomCyclicGraph2(int numNodes, int numEdges, int maxDegree)	Makes a cyclic graph by repeatedly adding cycles of length of 3, 4, or 5 to the graph, then finally adding two cycles.
static Graph	randomCyclicGraph3(int numNodes, int numEdges, int maxDegree, double probCycle, double probTwoCycle)	Makes a cyclic graph by repeatedly adding cycles of length of 3, 4, or 5 to the graph, then finally adding two cycles.
static Graph	randomDag(int numNodes, int numLatentConfounders, int maxNumEdges, int maxDegree, int maxIndegree, int maxOutdegree, boolean connected)	Generates a random Directed Acyclic Graph (DAG) with the specified parameters.
static Dag	randomDag(List<Node> nodes, int numLatentConfounders, int maxNumEdges, int maxDegree, int maxIndegree, int maxOutdegree, boolean connected)	Generates a random Directed Acyclic Graph (DAG).
static Graph	randomGraph(int numMeasures, int numLatentConfounders, int numEdges, int maxDegree, int maxIndegree, int maxOutdegree, boolean connected)	Generates a random graph based on the given parameters.
static Graph	randomGraph(List<Node> nodes, int numLatentConfounders, int maxNumEdges, int maxDegree, int maxIndegree, int maxOutdegree, boolean connected)	Generates a random graph based on the given parameters.
static Graph	randomGraphRandomForwardEdges(int numNodes, int numLatentConfounders, int numEdges, int maxDegree, int maxIndegree, int maxOutdegree, boolean connected)	Generates a random graph with the given parameters and random forward edges.
static Graph	randomGraphRandomForwardEdges(List<Node> nodes, int numLatentConfounders, int numEdges, int maxDegree, int maxIndegree, int maxOutdegree, boolean connected)	Generates a random graph with forward edges.
static Graph	randomGraphRandomForwardEdges(List<Node> nodes, int numLatentConfounders, int numEdges, int maxDegree, int maxIndegree, int maxOutdegree, boolean connected, boolean layoutAsCircle)	Generates a random graph with forward edges.
static Graph	randomGraphUniform(List<Node> nodes, int numLatentConfounders, int maxNumEdges, int maxDegree, int maxIndegree, int maxOutdegree, boolean connected, int numIterations)	Generates a random graph using UniformGraphGenerator with the specified parameters.
static Graph	randomScaleFreeGraph(int numNodes, int numLatentConfounders, double alpha, double beta, double delta_in, double delta_out)	Generates a random scale-free graph.

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Details

randomDag

public static Graph randomDag(int numNodes,
 int numLatentConfounders,
 int maxNumEdges,
 int maxDegree,
 int maxIndegree,
 int maxOutdegree,
 boolean connected)

Generates a random Directed Acyclic Graph (DAG) with the specified parameters.

Parameters:

numNodes - The number of nodes in the DAG.

numLatentConfounders - The number of latent confounders in the DAG.

maxNumEdges - The maximum number of edges in the DAG.

maxDegree - The maximum degree of each node in the DAG.

maxIndegree - The maximum indegree of each node in the DAG.

maxOutdegree - The maximum outdegree of each node in the DAG.

connected - Specifies whether the DAG should be connected.

Returns:

The randomly generated DAG.

randomDag

public static Dag randomDag(List<Node> nodes,
 int numLatentConfounders,
 int maxNumEdges,
 int maxDegree,
 int maxIndegree,
 int maxOutdegree,
 boolean connected)

Generates a random Directed Acyclic Graph (DAG).

Parameters:

nodes - the list of nodes in the graph

numLatentConfounders - the number of latent confounders (unobserved variables) in the graph

maxNumEdges - the maximum number of edges in the graph

maxDegree - the maximum number of edges incident to a single node in the graph

maxIndegree - the maximum number of incoming edges for a single node in the graph

maxOutdegree - the maximum number of outgoing edges for a single node in the graph

connected - whether the graph should be connected or not

Returns:

a randomly generated DAG representing the causal relationships between the nodes

randomGraph

public static Graph randomGraph(int numMeasures,
 int numLatentConfounders,
 int numEdges,
 int maxDegree,
 int maxIndegree,
 int maxOutdegree,
 boolean connected)

Generates a random graph based on the given parameters.

Parameters:

numMeasures - the number of nodes in the graph

numLatentConfounders - the number of latent confounders in the graph

numEdges - the number of edges in the graph

maxDegree - the maximum degree of each node in the graph

maxIndegree - the maximum indegree of each node in the graph

maxOutdegree - the maximum outdegree of each node in the graph

connected - indicates whether the graph should be connected or not

Returns:

a randomly generated graph

randomGraph

public static Graph randomGraph(List<Node> nodes,
 int numLatentConfounders,
 int maxNumEdges,
 int maxDegree,
 int maxIndegree,
 int maxOutdegree,
 boolean connected)

Generates a random graph based on the given parameters.

Parameters:

nodes - the list of nodes to create the graph with

numLatentConfounders - the number of latent confounders in the graph

maxNumEdges - the maximum number of edges in the graph

maxDegree - the maximum total degree (in-degree + out-degree) of each node

maxIndegree - the maximum in-degree of each node

maxOutdegree - the maximum out-degree of each node

connected - boolean flag indicating whether the generated graph should be connected or not

Returns:

the randomly generated graph

randomGraphUniform

public static Graph randomGraphUniform(List<Node> nodes,
 int numLatentConfounders,
 int maxNumEdges,
 int maxDegree,
 int maxIndegree,
 int maxOutdegree,
 boolean connected,
 int numIterations)

Generates a random graph using UniformGraphGenerator with the specified parameters.

Parameters:

nodes - The list of nodes to be included in the graph

numLatentConfounders - The maximum number of latent confounders to be added to the graph

maxNumEdges - The maximum number of edges to be added to the graph

maxDegree - The maximum degree of each node in the graph

maxIndegree - The maximum indegree of each node in the graph

maxOutdegree - The maximum outdegree of each node in the graph

connected - A flag indicating whether the graph should be a connected directed acyclic graph (DAG)

numIterations - The number of iterations to generate the graph

Returns:

The generated random graph

Throws:

IllegalArgumentException - if the given number of nodes is 0, or the maximum number of edges is out of range, or the maximum number of latent confounders is out of range

randomGraphRandomForwardEdges

public static Graph randomGraphRandomForwardEdges(int numNodes,
 int numLatentConfounders,
 int numEdges,
 int maxDegree,
 int maxIndegree,
 int maxOutdegree,
 boolean connected)

Generates a random graph with the given parameters and random forward edges.

Parameters:

numNodes - the number of nodes in the graph

numLatentConfounders - the number of latent confounders in the graph

numEdges - the number of edges in the graph

maxDegree - the maximum degree of a node in the graph

maxIndegree - the maximum indegree of a node in the graph

maxOutdegree - the maximum outdegree of a node in the graph

connected - indicates whether the graph should be connected

Returns:

a random graph object

randomGraphRandomForwardEdges

public static Graph randomGraphRandomForwardEdges(List<Node> nodes,
 int numLatentConfounders,
 int numEdges,
 int maxDegree,
 int maxIndegree,
 int maxOutdegree,
 boolean connected)

Generates a random graph with forward edges.

Parameters:

nodes - the list of nodes in the graph

numLatentConfounders - the number of latent confounders in the graph

numEdges - the total number of edges in the graph

maxDegree - the maximum number of edges connected to each node

maxIndegree - the maximum in-degree of each node

maxOutdegree - the maximum out-degree of each node

connected - if true, ensures that the generated graph is connected

Returns:

the random graph with forward edges

randomGraphRandomForwardEdges

public static Graph randomGraphRandomForwardEdges(List<Node> nodes,
 int numLatentConfounders,
 int numEdges,
 int maxDegree,
 int maxIndegree,
 int maxOutdegree,
 boolean connected,
 boolean layoutAsCircle)

Generates a random graph with forward edges.

Parameters:

nodes - a list of nodes to create the graph with

numLatentConfounders - the maximum number of latent confounders to include

numEdges - the desired number of edges in the graph

maxDegree - the maximum degree of a node in the graph

maxIndegree - the maximum indegree of a node in the graph

maxOutdegree - the maximum outdegree of a node in the graph

connected - indicates if the graph should be connected

layoutAsCircle - indicates if the graph should be laid out in a circular pattern

Returns:

a randomly generated graph with forward edges

Throws:

IllegalArgumentException - if the number of nodes is less than or equal to 0, the number of edges is negative or exceeds the possible maximum, or the number of latent confounders is negative or exceeds the number of nodes

randomScaleFreeGraph

public static Graph randomScaleFreeGraph(int numNodes,
 int numLatentConfounders,
 double alpha,
 double beta,
 double delta_in,
 double delta_out)

Generates a random scale-free graph.

Parameters:

numNodes - The number of nodes in the graph.

numLatentConfounders - The number of latent confounders in the graph.

alpha - The parameter alpha for generating node degrees in the graph.

beta - The parameter beta for generating node degrees in the graph.

delta_in - The parameter delta_in for generating node degrees in the graph.

delta_out - The parameter delta_out for generating node degrees in the graph.

Returns:

A randomly generated scale-free graph.

fixLatents1

public static void fixLatents1(int numLatentConfounders,
 Graph graph)

fixLatents1.

Parameters:

numLatentConfounders - a int

graph - a Graph object

fixLatents4

public static void fixLatents4(int numLatentConfounders,
 Graph graph)

fixLatents4.

Parameters:

numLatentConfounders - a int

graph - a Graph object

randomCyclicGraph2

public static Graph randomCyclicGraph2(int numNodes,
 int numEdges,
 int maxDegree)

Makes a cyclic graph by repeatedly adding cycles of length of 3, 4, or 5 to the graph, then finally adding two cycles.

Parameters:

numNodes - a int

numEdges - a int

maxDegree - a int

Returns:

a Graph object

randomCyclicGraph3

public static Graph randomCyclicGraph3(int numNodes,
 int numEdges,
 int maxDegree,
 double probCycle,
 double probTwoCycle)

Makes a cyclic graph by repeatedly adding cycles of length of 3, 4, or 5 to the graph, then finally adding two cycles.

Parameters:

numNodes - a int

numEdges - a int

maxDegree - a int

probCycle - a double

probTwoCycle - a double

Returns:

a Graph object

addTwoCycles

public static void addTwoCycles(Graph graph,
 int numTwoCycles)

addTwoCycles.

Parameters:

graph - a Graph object

numTwoCycles - a int