public Graph search(IFas fas, List<Node> nodes) { long beginTime = System.currentTimeMillis(); logger.log("info", "Starting FCI algorithm."); logger.log("info", "Independence test = " + getIndependenceTest() + "."); setMaxPathLength(maxPathLength); this.graph = new EdgeListGraph(nodes); long start1 = System.currentTimeMillis(); fas.setKnowledge(getKnowledge()); fas.setDepth(depth); fas.setVerbose(verbose); // fas.setFci(true); graph = fas.search(); graph.reorientAllWith(Endpoint.CIRCLE); this.sepsets = fas.getSepsets(); long stop1 = System.currentTimeMillis(); long start2 = System.currentTimeMillis(); // The original FCI, with or without JiJi Zhang's orientation rules fciOrientbk(getKnowledge(), graph, variables); ruleR0_RFCI(getRTuples()); // RFCI Algorithm 4.4 doFinalOrientation(); long endTime = System.currentTimeMillis(); this.elapsedTime = endTime - beginTime; logger.log("graph", "Returning graph: " + graph); long stop2 = System.currentTimeMillis(); logger.log("info", "Elapsed time adjacency search = " + (stop1 - start1) / 1000L + "s"); logger.log("info", "Elapsed time orientation search = " + (stop2 - start2) / 1000L + "s"); return graph; }
/** * Runs PC starting with a commplete graph over the given list of nodes, using the given * independence test and knowledge and returns the resultant graph. The returned graph will be a * pattern if the independence information is consistent with the hypothesis that there are no * latent common causes. It may, however, contain cycles or bidirected edges if this assumption is * not born out, either due to the actual presence of latent common causes, or due to statistical * errors in conditional independence judgments. * * <p>All of the given nodes must be in the domain of the given conditional independence test. */ public Graph search(List<Node> nodes) { this.logger.log("info", "Starting PC algorithm"); this.logger.log("info", "Independence test = " + getIndependenceTest() + "."); if (trueDag != null) { this.dsep = new IndTestDSep(trueDag); } long startTime = System.currentTimeMillis(); if (getIndependenceTest() == null) { throw new NullPointerException(); } List<Node> allNodes = getIndependenceTest().getVariables(); if (!allNodes.containsAll(nodes)) { throw new IllegalArgumentException( "All of the given nodes must " + "be in the domain of the independence test provided."); } IFas fas = new Fas2(getIndependenceTest()); fas.setInitialGraph(initialGraph); fas.setKnowledge(getKnowledge()); fas.setDepth(getDepth()); fas.setVerbose(verbose); graph = fas.search(); SearchGraphUtils.pcOrientbk(knowledge, graph, nodes); // independenceTest = new ProbabilisticMAPIndependence((DataSet) // independenceTest.getData()); SepsetsMaxPValue sepsetProducer = new SepsetsMaxPValue(graph, independenceTest, null, getDepth()); sepsetProducer.setDsep(dsep); addColliders(graph, sepsetProducer, knowledge); MeekRules rules = new MeekRules(); rules.setKnowledge(knowledge); rules.orientImplied(graph); // Graph pattern = new EdgeListGraphSingleConnections(graph); // // for (Node x : getNodes()) { // for (Node y : getNodes()) { // if (x == y) continue; // // if (!localMarkovIndep(x, y, pattern, independenceTest)) { // graph.addUndirectedEdge(x, y); // } // } // } // // fas = new FasStableConcurrent(getIndependenceTest()); // fas.setInitialGraph(new EdgeListGraphSingleConnections(graph)); // fas.setKnowledge(getKnowledge()); // fas.setDepth(getDepth()); // fas.setVerbose(verbose); // graph = fas.search(); // // sepsetProducer = new SepsetsMaxPValue(graph, independenceTest, null, getDepth()); // // addColliders(graph, sepsetProducer, knowledge); // // rules = new MeekRules(); // rules.setKnowledge(knowledge); // rules.orientImplied(graph); this.logger.log("graph", "\nReturning this graph: " + graph); this.elapsedTime = System.currentTimeMillis() - startTime; this.logger.log("info", "Elapsed time = " + (elapsedTime) / 1000. + " s"); this.logger.log("info", "Finishing PC Algorithm."); this.logger.flush(); return graph; }