@Test
public void test3() {
RandomUtil.getInstance().setSeed(49293843L);
List<Node> variableNodes = new ArrayList<>();
ContinuousVariable x1 = new ContinuousVariable("X1");
ContinuousVariable x2 = new ContinuousVariable("X2");
ContinuousVariable x3 = new ContinuousVariable("X3");
ContinuousVariable x4 = new ContinuousVariable("X4");
ContinuousVariable x5 = new ContinuousVariable("X5");
variableNodes.add(x1);
variableNodes.add(x2);
variableNodes.add(x3);
variableNodes.add(x4);
variableNodes.add(x5);
Graph _graph = new EdgeListGraph(variableNodes);
SemGraph graph = new SemGraph(_graph);
graph.setShowErrorTerms(true);
Node e1 = graph.getExogenous(x1);
Node e2 = graph.getExogenous(x2);
Node e3 = graph.getExogenous(x3);
Node e4 = graph.getExogenous(x4);
Node e5 = graph.getExogenous(x5);
graph.addDirectedEdge(x1, x3);
graph.addDirectedEdge(x1, x2);
graph.addDirectedEdge(x2, x3);
graph.addDirectedEdge(x3, x4);
graph.addDirectedEdge(x2, x4);
graph.addDirectedEdge(x4, x5);
graph.addDirectedEdge(x2, x5);
graph.addDirectedEdge(x5, x1);
GeneralizedSemPm pm = new GeneralizedSemPm(graph);
List<Node> variablesNodes = pm.getVariableNodes();
print(variablesNodes);
List<Node> errorNodes = pm.getErrorNodes();
print(errorNodes);
try {
pm.setNodeExpression(x1, "cos(b1) + a1 * X5 + E_X1");
pm.setNodeExpression(x2, "a2 * X1 + E_X2");
pm.setNodeExpression(x3, "tan(a3*X2 + a4*X1) + E_X3");
pm.setNodeExpression(x4, "0.1 * E^X2 + X3 + E_X4");
pm.setNodeExpression(x5, "0.1 * E^X4 + a6* X2 + E_X5");
pm.setNodeExpression(e1, "U(0, 1)");
pm.setNodeExpression(e2, "U(0, 1)");
pm.setNodeExpression(e3, "U(0, 1)");
pm.setNodeExpression(e4, "U(0, 1)");
pm.setNodeExpression(e5, "U(0, 1)");
GeneralizedSemIm im = new GeneralizedSemIm(pm);
print(im);
DataSet dataSet = im.simulateDataNSteps(1000, false);
// System.out.println(dataSet);
double[] d1 = dataSet.getDoubleData().getColumn(0).toArray();
double[] d2 = dataSet.getDoubleData().getColumn(1).toArray();
double cov = StatUtils.covariance(d1, d2);
assertEquals(-0.002, cov, 0.001);
} catch (ParseException e) {
e.printStackTrace();
}
}
@Test
public void test1() {
GeneralizedSemPm pm = makeTypicalPm();
print(pm);
Node x1 = pm.getNode("X1");
Node x2 = pm.getNode("X2");
Node x3 = pm.getNode("X3");
Node x4 = pm.getNode("X4");
Node x5 = pm.getNode("X5");
SemGraph graph = pm.getGraph();
List<Node> variablesNodes = pm.getVariableNodes();
print(variablesNodes);
List<Node> errorNodes = pm.getErrorNodes();
print(errorNodes);
try {
pm.setNodeExpression(x1, "cos(B1) + E_X1");
print(pm);
String b1 = "B1";
String b2 = "B2";
String b3 = "B3";
Set<Node> nodes = pm.getReferencingNodes(b1);
assertTrue(nodes.contains(x1));
assertTrue(!nodes.contains(x2) && !nodes.contains(x2));
Set<String> referencedParameters = pm.getReferencedParameters(x3);
print("Parameters referenced by X3 are: " + referencedParameters);
assertTrue(referencedParameters.contains(b1) && referencedParameters.contains(b2));
assertTrue(!(referencedParameters.contains(b1) && referencedParameters.contains(b3)));
Node e_x3 = pm.getNode("E_X3");
//
for (Node node : pm.getNodes()) {
Set<Node> referencingNodes = pm.getReferencingNodes(node);
print("Nodes referencing " + node + " are: " + referencingNodes);
}
for (Node node : pm.getVariableNodes()) {
Set<Node> referencingNodes = pm.getReferencedNodes(node);
print("Nodes referenced by " + node + " are: " + referencingNodes);
}
Set<Node> referencingX3 = pm.getReferencingNodes(x3);
assertTrue(referencingX3.contains(x4));
assertTrue(!referencingX3.contains(x5));
Set<Node> referencedByX3 = pm.getReferencedNodes(x3);
assertTrue(
referencedByX3.contains(x1)
&& referencedByX3.contains(x2)
&& referencedByX3.contains(e_x3)
&& !referencedByX3.contains(x4));
pm.setNodeExpression(x5, "a * E^X2 + X4 + E_X5");
Node e_x5 = pm.getErrorNode(x5);
graph.setShowErrorTerms(true);
assertTrue(e_x5.equals(graph.getExogenous(x5)));
pm.setNodeExpression(e_x5, "Beta(3, 5)");
print(pm);
assertEquals("Split(-1.5,-.5,.5,1.5)", pm.getParameterExpressionString(b1));
pm.setParameterExpression(b1, "N(0, 2)");
assertEquals("N(0, 2)", pm.getParameterExpressionString(b1));
GeneralizedSemIm im = new GeneralizedSemIm(pm);
print(im);
DataSet dataSet = im.simulateDataAvoidInfinity(10, false);
print(dataSet);
} catch (ParseException e) {
e.printStackTrace();
}
}
/**
* Constructs a new standardized SEM IM from the freeParameters in the given SEM IM.
*
* @param im Stop asking me for these things! The given SEM IM!!!
* @param initialization CALCULATE_FROM_SEM if the initial values will be calculated from the
* given SEM IM; INITIALIZE_FROM_DATA if data will be simulated from the given SEM,
* standardized, and estimated.
*/
public StandardizedSemIm(SemIm im, Initialization initialization) {
this.semPm = new SemPm(im.getSemPm());
this.semGraph = new SemGraph(semPm.getGraph());
semGraph.setShowErrorTerms(true);
if (semGraph.existsDirectedCycle()) {
throw new IllegalArgumentException("The cyclic case is not handled.");
}
if (initialization == Initialization.CALCULATE_FROM_SEM) {
// This code calculates the new coefficients directly from the old ones.
edgeParameters = new HashMap<Edge, Double>();
List<Node> nodes = im.getVariableNodes();
TetradMatrix impliedCovar = im.getImplCovar(true);
for (Parameter parameter : im.getSemPm().getParameters()) {
if (parameter.getType() == ParamType.COEF) {
Node a = parameter.getNodeA();
Node b = parameter.getNodeB();
int aindex = nodes.indexOf(a);
int bindex = nodes.indexOf(b);
double vara = impliedCovar.get(aindex, aindex);
double stda = Math.sqrt(vara);
double varb = impliedCovar.get(bindex, bindex);
double stdb = Math.sqrt(varb);
double oldCoef = im.getEdgeCoef(a, b);
double newCoef = (stda / stdb) * oldCoef;
edgeParameters.put(Edges.directedEdge(a, b), newCoef);
} else if (parameter.getType() == ParamType.COVAR) {
Node a = parameter.getNodeA();
Node b = parameter.getNodeB();
Node exoa = semGraph.getExogenous(a);
Node exob = semGraph.getExogenous(b);
double covar = im.getErrCovar(a, b) / Math.sqrt(im.getErrVar(a) * im.getErrVar(b));
edgeParameters.put(Edges.bidirectedEdge(exoa, exob), covar);
}
}
} else {
// This code estimates the new coefficients from simulated data from the old model.
DataSet dataSet = im.simulateData(1000, false);
TetradMatrix _dataSet = dataSet.getDoubleData();
_dataSet = DataUtils.standardizeData(_dataSet);
DataSet dataSetStandardized = ColtDataSet.makeData(dataSet.getVariables(), _dataSet);
SemEstimator estimator = new SemEstimator(dataSetStandardized, im.getSemPm());
SemIm imStandardized = estimator.estimate();
edgeParameters = new HashMap<Edge, Double>();
for (Parameter parameter : imStandardized.getSemPm().getParameters()) {
if (parameter.getType() == ParamType.COEF) {
Node a = parameter.getNodeA();
Node b = parameter.getNodeB();
double coef = imStandardized.getEdgeCoef(a, b);
edgeParameters.put(Edges.directedEdge(a, b), coef);
} else if (parameter.getType() == ParamType.COVAR) {
Node a = parameter.getNodeA();
Node b = parameter.getNodeB();
Node exoa = semGraph.getExogenous(a);
Node exob = semGraph.getExogenous(b);
double covar = -im.getErrCovar(a, b) / Math.sqrt(im.getErrVar(a) * im.getErrVar(b));
edgeParameters.put(Edges.bidirectedEdge(exoa, exob), covar);
}
}
}
this.measuredNodes = Collections.unmodifiableList(semPm.getMeasuredNodes());
}