edu.cmu.tetrad.algcomparison.algorithm.pairwise.R1 Maven / Gradle / Ivy
package edu.cmu.tetrad.algcomparison.algorithm.pairwise;
import edu.cmu.tetrad.algcomparison.algorithm.Algorithm;
import edu.cmu.tetrad.algcomparison.utils.TakesExternalGraph;
import edu.cmu.tetrad.annotation.Bootstrapping;
import edu.cmu.tetrad.data.DataModel;
import edu.cmu.tetrad.data.DataSet;
import edu.cmu.tetrad.data.DataType;
import edu.cmu.tetrad.data.SimpleDataLoader;
import edu.cmu.tetrad.graph.EdgeListGraph;
import edu.cmu.tetrad.graph.Graph;
import edu.cmu.tetrad.search.Lofs;
import edu.cmu.tetrad.util.Parameters;
import edu.cmu.tetrad.util.Params;
import edu.pitt.dbmi.algo.resampling.GeneralResamplingTest;
import java.util.ArrayList;
import java.util.LinkedList;
import java.util.List;
/**
* R1.
*
* @author josephramsey
*/
//@Experimental
//@edu.cmu.tetrad.annotation.Algorithm(
// name = "R1",
// command = "r1",
// algoType = AlgType.orient_pairwise
//)
@Bootstrapping
public class R1 implements Algorithm, TakesExternalGraph {
private static final long serialVersionUID = 23L;
private Algorithm algorithm;
private Graph externalGraph;
public R1() {
}
public R1(Algorithm algorithm) {
this.algorithm = algorithm;
}
@Override
public Graph search(DataModel dataSet, Parameters parameters) {
if (parameters.getInt(Params.NUMBER_RESAMPLING) < 1) {
Graph graph = this.algorithm.search(dataSet, parameters);
if (graph != null) {
this.externalGraph = graph;
} else {
throw new IllegalArgumentException("This R1 algorithm needs both data and a graph source as inputs; it \n"
+ "will orient the edges in the input graph using the data");
}
List dataSets = new ArrayList<>();
dataSets.add(SimpleDataLoader.getContinuousDataSet(dataSet));
Lofs lofs = new Lofs(this.externalGraph, dataSets);
lofs.setRule(Lofs.Rule.R1);
return lofs.orient();
} else {
R1 r1 = new R1(this.algorithm);
if (this.externalGraph != null) {
r1.setExternalGraph(this.algorithm);
}
DataSet data = (DataSet) dataSet;
GeneralResamplingTest search = new GeneralResamplingTest(data, r1, parameters.getInt(Params.NUMBER_RESAMPLING), parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
search.setParameters(parameters);
search.setVerbose(parameters.getBoolean(Params.VERBOSE));
return search.search();
}
}
@Override
public Graph getComparisonGraph(Graph graph) {
return new EdgeListGraph(graph);
}
@Override
public String getDescription() {
return "R1, entropy based pairwise orientation" + (this.algorithm != null ? " with initial graph from "
+ this.algorithm.getDescription() : "");
}
@Override
public DataType getDataType() {
return DataType.Continuous;
}
@Override
public List getParameters() {
List parameters = new LinkedList<>();
if (this.algorithm != null && !this.algorithm.getParameters().isEmpty()) {
parameters.addAll(this.algorithm.getParameters());
}
parameters.add(Params.VERBOSE);
return parameters;
}
@Override
public void setExternalGraph(Algorithm algorithm) {
if (algorithm == null) {
throw new IllegalArgumentException("This R1 algorithm needs both data and a graph source as inputs; it \n"
+ "will orient the edges in the input graph using the data.");
}
this.algorithm = algorithm;
}
}