@Test
public void test8() {
RandomUtil.getInstance().setSeed(29999483L);
Node x = new GraphNode("X");
Node y = new GraphNode("Y");
List<Node> nodes = new ArrayList<>();
nodes.add(x);
nodes.add(y);
Graph graph = new EdgeListGraphSingleConnections(nodes);
graph.addDirectedEdge(x, y);
SemPm spm = new SemPm(graph);
SemIm sim = new SemIm(spm);
sim.setEdgeCoef(x, y, 20);
sim.setErrVar(x, 1);
sim.setErrVar(y, 1);
GeneralizedSemPm pm = new GeneralizedSemPm(spm);
GeneralizedSemIm im = new GeneralizedSemIm(pm, sim);
print(im);
try {
pm.setParameterEstimationInitializationExpression("b1", "U(10, 30)");
pm.setParameterEstimationInitializationExpression("T1", "U(.1, 3)");
pm.setParameterEstimationInitializationExpression("T2", "U(.1, 3)");
} catch (ParseException e) {
e.printStackTrace();
}
DataSet data = im.simulateDataRecursive(1000, false);
GeneralizedSemEstimator estimator = new GeneralizedSemEstimator();
GeneralizedSemIm estIm = estimator.estimate(pm, data);
print(estIm);
// System.out.println(estimator.getReport());
double aSquaredStar = estimator.getaSquaredStar();
assertEquals(0.69, aSquaredStar, 0.01);
}
@Test
public void test15() {
RandomUtil.getInstance().setSeed(29999483L);
try {
Node x1 = new GraphNode("X1");
Node x2 = new GraphNode("X2");
Node x3 = new GraphNode("X3");
Node x4 = new GraphNode("X4");
Graph g = new EdgeListGraphSingleConnections();
g.addNode(x1);
g.addNode(x2);
g.addNode(x3);
g.addNode(x4);
g.addDirectedEdge(x1, x2);
g.addDirectedEdge(x2, x3);
g.addDirectedEdge(x3, x4);
g.addDirectedEdge(x1, x4);
GeneralizedSemPm pm = new GeneralizedSemPm(g);
pm.setNodeExpression(x1, "E_X1");
pm.setNodeExpression(x2, "a1 * X1 + E_X2");
pm.setNodeExpression(x3, "a2 * X2 + E_X3");
pm.setNodeExpression(x4, "a3 * X1 + a4 * X3 ^ 2 + E_X4");
pm.setNodeExpression(pm.getErrorNode(x1), "Gamma(c1, c2)");
pm.setNodeExpression(pm.getErrorNode(x2), "ChiSquare(c3)");
pm.setNodeExpression(pm.getErrorNode(x3), "ChiSquare(c4)");
pm.setNodeExpression(pm.getErrorNode(x4), "ChiSquare(c5)");
pm.setParameterExpression("c1", "5");
pm.setParameterExpression("c2", "2");
pm.setParameterExpression("c3", "10");
pm.setParameterExpression("c4", "10");
pm.setParameterExpression("c5", "10");
pm.setParameterEstimationInitializationExpression("c1", "U(1, 5)");
pm.setParameterEstimationInitializationExpression("c2", "U(1, 5)");
pm.setParameterEstimationInitializationExpression("c3", "U(1, 5)");
pm.setParameterEstimationInitializationExpression("c4", "U(1, 5)");
pm.setParameterEstimationInitializationExpression("c5", "U(1, 5)");
GeneralizedSemIm im = new GeneralizedSemIm(pm);
print("True model: ");
print(im);
DataSet data = im.simulateDataRecursive(1000, false);
GeneralizedSemEstimator estimator = new GeneralizedSemEstimator();
GeneralizedSemIm estIm = estimator.estimate(pm, data);
print("\n\n\nEstimated model: ");
print(estIm);
print(estimator.getReport());
double aSquaredStar = estimator.getaSquaredStar();
assertEquals(.79, aSquaredStar, 0.01);
} catch (ParseException e) {
e.printStackTrace();
}
}
@Test
public void test14() {
RandomUtil.getInstance().setSeed(29999483L);
try {
Node x1 = new GraphNode("X1");
Node x2 = new GraphNode("X2");
Node x3 = new GraphNode("X3");
Node x4 = new GraphNode("X4");
Graph g = new EdgeListGraphSingleConnections();
g.addNode(x1);
g.addNode(x2);
g.addNode(x3);
g.addNode(x4);
g.addDirectedEdge(x1, x2);
g.addDirectedEdge(x2, x3);
g.addDirectedEdge(x3, x4);
g.addDirectedEdge(x1, x4);
GeneralizedSemPm pm = new GeneralizedSemPm(g);
pm.setNodeExpression(x1, "E_X1");
pm.setNodeExpression(x2, "a1 * tan(X1) + E_X2");
pm.setNodeExpression(x3, "a2 * tan(X2) + E_X3");
pm.setNodeExpression(x4, "a3 * tan(X1) + a4 * tan(X3) ^ 2 + E_X4");
pm.setNodeExpression(pm.getErrorNode(x1), "N(0, c1)");
pm.setNodeExpression(pm.getErrorNode(x2), "N(0, c2)");
pm.setNodeExpression(pm.getErrorNode(x3), "N(0, c3)");
pm.setNodeExpression(pm.getErrorNode(x4), "N(0, c4)");
pm.setParameterExpression("a1", "1");
pm.setParameterExpression("a2", "1");
pm.setParameterExpression("a3", "1");
pm.setParameterExpression("a4", "1");
pm.setParameterExpression("c1", "4");
pm.setParameterExpression("c2", "4");
pm.setParameterExpression("c3", "4");
pm.setParameterExpression("c4", "4");
GeneralizedSemIm im = new GeneralizedSemIm(pm);
print("True model: ");
print(im);
DataSet data = im.simulateDataRecursive(1000, false);
GeneralizedSemIm imInit = new GeneralizedSemIm(pm);
imInit.setParameterValue("c1", 8);
imInit.setParameterValue("c2", 8);
imInit.setParameterValue("c3", 8);
imInit.setParameterValue("c4", 8);
GeneralizedSemEstimator estimator = new GeneralizedSemEstimator();
GeneralizedSemIm estIm = estimator.estimate(pm, data);
print("\n\n\nEstimated model: ");
print(estIm);
print(estimator.getReport());
double aSquaredStar = estimator.getaSquaredStar();
assertEquals(71.25, aSquaredStar, 0.01);
} 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();
}
}
@Test
public void test4() {
// For X3
Map<String, String[]> templates = new HashMap<>();
templates.put(
"NEW(b) + NEW(b) + NEW(c) + NEW(c) + NEW(c)", new String[] {"X1", "X2", "X3", "X4", "X5"});
templates.put("NEW(X1) + NEW(b) + NEW(c) + NEW(c) + NEW(c)", new String[] {});
templates.put("$", new String[] {});
templates.put("TSUM($)", new String[] {"X1", "X2", "X3", "X4", "X5"});
templates.put("TPROD($)", new String[] {"X1", "X2", "X3", "X4", "X5"});
templates.put("TPROD($) + X2", new String[] {"X1", "X2", "X3", "X4", "X5"});
templates.put("TPROD($) + TSUM($)", new String[] {"X1", "X2", "X3", "X4", "X5"});
templates.put("tan(TSUM(NEW(a)*$))", new String[] {"X1", "X2", "X3", "X4", "X5"});
templates.put("Normal(0, 1)", new String[] {"X1", "X2", "X3", "X4", "X5"});
templates.put("Normal(m, s)", new String[] {"X1", "X2", "X3", "X4", "X5"});
templates.put("Normal(NEW(m), s)", new String[] {"X1", "X2", "X3", "X4", "X5"});
templates.put("Normal(NEW(m), NEW(s)) + m1 + s6", new String[] {"X1", "X2", "X3", "X4", "X5"});
templates.put("TSUM($) + a", new String[] {"X1", "X2", "X3", "X4", "X5"});
templates.put("TSUM($) + TSUM($) + TSUM($) + 1", new String[] {"X1", "X2", "X3", "X4", "X5"});
for (String template : templates.keySet()) {
GeneralizedSemPm semPm = makeTypicalPm();
print(semPm.getGraph().toString());
Set<Node> shouldWork = new HashSet<>();
for (String name : templates.get(template)) {
shouldWork.add(semPm.getNode(name));
}
Set<Node> works = new HashSet<>();
for (int i = 0; i < semPm.getNodes().size(); i++) {
print("-----------");
print(semPm.getNodes().get(i).toString());
print("Trying template: " + template);
String _template = template;
Node node = semPm.getNodes().get(i);
try {
_template = TemplateExpander.getInstance().expandTemplate(_template, semPm, node);
} catch (Exception e) {
print("Couldn't expand template: " + template);
continue;
}
try {
semPm.setNodeExpression(node, _template);
print("Set formula " + _template + " for " + node);
if (semPm.getVariableNodes().contains(node)) {
works.add(node);
}
} catch (Exception e) {
print("Couldn't set formula " + _template + " for " + node);
}
}
for (String parameter : semPm.getParameters()) {
print("-----------");
print(parameter);
print("Trying template: " + template);
String _template = template;
try {
_template = TemplateExpander.getInstance().expandTemplate(_template, semPm, null);
} catch (Exception e) {
print("Couldn't expand template: " + template);
continue;
}
try {
semPm.setParameterExpression(parameter, _template);
print("Set formula " + _template + " for " + parameter);
} catch (Exception e) {
print("Couldn't set formula " + _template + " for " + parameter);
}
}
assertEquals(shouldWork, works);
}
}
@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();
}
}