Examples with ContinuousVariable edu.cmu.tetrad.data.ContinuousVariable used on opensource projects

Example 46 with ContinuousVariable

use of edu.cmu.tetrad.data.ContinuousVariable in project tetrad by cmu-phil.

the class TestDataWrapper method testDataModelList.

@Test
public void testDataModelList() {
    DataModelList modelList = new DataModelList();
    List<Node> variables1 = new ArrayList<>();
    for (int i = 0; i < 10; i++) {
        variables1.add(new ContinuousVariable("X" + i));
    }
    List<Node> variables2 = new ArrayList<>();
    for (int i = 0; i < 10; i++) {
        variables2.add(new ContinuousVariable("X" + i));
    }
    DataSet first = new ColtDataSet(10, variables1);
    first.setName("first");
    DataSet second = new ColtDataSet(10, variables2);
    second.setName("second");
    modelList.add(first);
    modelList.add(second);
    assertTrue(modelList.contains(first));
    assertTrue(modelList.contains(second));
    modelList.setSelectedModel(second);
    try {
        DataModelList modelList2 = new MarshalledObject<>(modelList).get();
        assertEquals("second", modelList2.getSelectedModel().getName());
    } catch (Exception e) {
        e.printStackTrace();
    }
}

Example 47 with ContinuousVariable

use of edu.cmu.tetrad.data.ContinuousVariable in project tetrad by cmu-phil.

the class MNLRLikelihood method getLik.

public double getLik(int child_index, int[] parents) {
    double lik = 0;
    Node c = variables.get(child_index);
    List<ContinuousVariable> continuous_parents = new ArrayList<>();
    List<DiscreteVariable> discrete_parents = new ArrayList<>();
    for (int p : parents) {
        Node parent = variables.get(p);
        if (parent instanceof ContinuousVariable) {
            continuous_parents.add((ContinuousVariable) parent);
        } else {
            discrete_parents.add((DiscreteVariable) parent);
        }
    }
    int p = continuous_parents.size();
    List<List<Integer>> cells = adTree.getCellLeaves(discrete_parents);
    // List<List<Integer>> cells = partition(discrete_parents);
    int[] continuousCols = new int[p];
    for (int j = 0; j < p; j++) continuousCols[j] = nodesHash.get(continuous_parents.get(j));
    for (List<Integer> cell : cells) {
        int r = cell.size();
        if (r > 1) {
            double[] mean = new double[p];
            double[] var = new double[p];
            for (int i = 0; i < p; i++) {
                for (int j = 0; j < r; j++) {
                    mean[i] += continuousData[continuousCols[i]][cell.get(j)];
                    var[i] += Math.pow(continuousData[continuousCols[i]][cell.get(j)], 2);
                }
                mean[i] /= r;
                var[i] /= r;
                var[i] -= Math.pow(mean[i], 2);
                var[i] = Math.sqrt(var[i]);
                if (Double.isNaN(var[i])) {
                    System.out.println(var[i]);
                }
            }
            int degree = fDegree;
            if (fDegree < 1) {
                degree = (int) Math.floor(Math.log(r));
            }
            TetradMatrix subset = new TetradMatrix(r, p * degree + 1);
            for (int i = 0; i < r; i++) {
                subset.set(i, p * degree, 1);
                for (int j = 0; j < p; j++) {
                    for (int d = 0; d < degree; d++) {
                        subset.set(i, p * d + j, Math.pow((continuousData[continuousCols[j]][cell.get(i)] - mean[j]) / var[j], d + 1));
                    }
                }
            }
            if (c instanceof ContinuousVariable) {
                TetradVector target = new TetradVector(r);
                for (int i = 0; i < r; i++) {
                    target.set(i, continuousData[child_index][cell.get(i)]);
                }
                lik += multipleRegression(target, subset);
            } else {
                ArrayList<Integer> temp = new ArrayList<>();
                TetradMatrix target = new TetradMatrix(r, ((DiscreteVariable) c).getNumCategories());
                for (int i = 0; i < r; i++) {
                    for (int j = 0; j < ((DiscreteVariable) c).getNumCategories(); j++) {
                        target.set(i, j, -1);
                    }
                    target.set(i, discreteData[child_index][cell.get(i)], 1);
                }
                lik += MultinomialLogisticRegression(target, subset);
            }
        }
    }
    return lik;
}

Example 48 with ContinuousVariable

use of edu.cmu.tetrad.data.ContinuousVariable in project tetrad by cmu-phil.

the class TestHistogram method test1.

public void test1() {
    List<Node> nodes = new LinkedList<>();
    Node x1 = new ContinuousVariable("X1");
    Node x2 = new ContinuousVariable("X2");
    nodes.add(x1);
    nodes.add(x2);
    TetradMatrix dataMatrix = new TetradMatrix(10, 2);
    dataMatrix.set(0, 0, 0);
    dataMatrix.set(1, 0, 0);
    dataMatrix.set(2, 0, 0);
    dataMatrix.set(3, 0, 0);
    dataMatrix.set(4, 0, 0);
    dataMatrix.set(5, 0, 1);
    dataMatrix.set(6, 0, 1);
    dataMatrix.set(7, 0, 1);
    dataMatrix.set(8, 0, 1);
    dataMatrix.set(9, 0, 1);
    dataMatrix.set(0, 1, 0);
    dataMatrix.set(1, 1, 1);
    dataMatrix.set(2, 1, 1);
    dataMatrix.set(3, 1, 1);
    dataMatrix.set(4, 1, 1);
    dataMatrix.set(5, 1, 0);
    dataMatrix.set(6, 1, 0);
    dataMatrix.set(7, 1, 0);
    dataMatrix.set(8, 1, 0);
    dataMatrix.set(9, 1, 1);
    DataSet dataSet = ColtDataSet.makeContinuousData(nodes, dataMatrix);
// Histogram histogram = new Histogram(dataSet, );
}

Example 49 with ContinuousVariable

use of edu.cmu.tetrad.data.ContinuousVariable in project tetrad by cmu-phil.

the class TabularDataTable method addColumnsOutTo.

/**
 * Col index here is JTable index.
 */
private void addColumnsOutTo(int col) {
    for (int i = dataSet.getNumColumns() + getNumLeadingCols(); i <= col; i++) {
        ContinuousVariable var = new ContinuousVariable("");
        dataSet.addVariable(var);
        System.out.println("Adding " + var + " col " + dataSet.getColumn(var));
    }
    pcs.firePropertyChange("modelChanged", null, null);
}

Example 50 with ContinuousVariable

use of edu.cmu.tetrad.data.ContinuousVariable in project tetrad by cmu-phil.

the class TimeLagGraphEditor method createGraphMenu.

private JMenu createGraphMenu() {
    JMenu graph = new JMenu("Graph");
    graph.add(new GraphPropertiesAction(getWorkbench()));
    graph.add(new PathsAction(getWorkbench()));
    // graph.add(new DirectedPathsAction(getWorkbench()));
    // graph.add(new TreksAction(getWorkbench()));
    // graph.add(new AllPathsAction(getWorkbench()));
    // graph.add(new NeighborhoodsAction(getWorkbench()));
    graph.addSeparator();
    JMenuItem correlateExogenous = new JMenuItem("Correlate Exogenous Variables");
    JMenuItem uncorrelateExogenous = new JMenuItem("Uncorrelate Exogenous Variables");
    graph.add(correlateExogenous);
    graph.add(uncorrelateExogenous);
    graph.addSeparator();
    correlateExogenous.addActionListener(new ActionListener() {

        public void actionPerformed(ActionEvent e) {
            correlateExogenousVariables();
            getWorkbench().invalidate();
            getWorkbench().repaint();
        }
    });
    uncorrelateExogenous.addActionListener(new ActionListener() {

        public void actionPerformed(ActionEvent e) {
            uncorrelationExogenousVariables();
            getWorkbench().invalidate();
            getWorkbench().repaint();
        }
    });
    JMenuItem randomGraph = new JMenuItem("Random Graph");
    graph.add(randomGraph);
    randomGraph.addActionListener(new ActionListener() {

        public void actionPerformed(ActionEvent e) {
            RandomGraphEditor editor = new RandomGraphEditor(workbench.getGraph(), true, parameters);
            int ret = JOptionPane.showConfirmDialog(TimeLagGraphEditor.this, editor, "Edit Random DAG Parameters", JOptionPane.PLAIN_MESSAGE);
            if (ret == JOptionPane.OK_OPTION) {
                Graph graph = null;
                Graph dag = new Dag();
                int numTrials = 0;
                while (graph == null && ++numTrials < 100) {
                    if (editor.isRandomForward()) {
                        dag = GraphUtils.randomGraphRandomForwardEdges(getGraph().getNodes(), editor.getNumLatents(), editor.getMaxEdges(), 30, 15, 15, false, true);
                        GraphUtils.arrangeBySourceGraph(dag, getWorkbench().getGraph());
                        HashMap<String, PointXy> layout = GraphUtils.grabLayout(workbench.getGraph().getNodes());
                        GraphUtils.arrangeByLayout(dag, layout);
                    } else if (editor.isUniformlySelected()) {
                        if (getGraph().getNumNodes() == editor.getNumNodes()) {
                            HashMap<String, PointXy> layout = GraphUtils.grabLayout(workbench.getGraph().getNodes());
                            dag = GraphUtils.randomGraph(getGraph().getNodes(), editor.getNumLatents(), editor.getMaxEdges(), editor.getMaxDegree(), editor.getMaxIndegree(), editor.getMaxOutdegree(), editor.isConnected());
                            GraphUtils.arrangeBySourceGraph(dag, getWorkbench().getGraph());
                            GraphUtils.arrangeByLayout(dag, layout);
                        } else {
                            List<Node> nodes = new ArrayList<>();
                            for (int i = 0; i < editor.getNumNodes(); i++) {
                                nodes.add(new ContinuousVariable("X" + (i + 1)));
                            }
                            dag = GraphUtils.randomGraph(nodes, editor.getNumLatents(), editor.getMaxEdges(), editor.getMaxDegree(), editor.getMaxIndegree(), editor.getMaxOutdegree(), editor.isConnected());
                        }
                    } else {
                        do {
                            if (getGraph().getNumNodes() == editor.getNumNodes()) {
                                HashMap<String, PointXy> layout = GraphUtils.grabLayout(workbench.getGraph().getNodes());
                                dag = GraphUtils.randomDag(getGraph().getNodes(), editor.getNumLatents(), editor.getMaxEdges(), 30, 15, 15, editor.isConnected());
                                GraphUtils.arrangeByLayout(dag, layout);
                            } else {
                                List<Node> nodes = new ArrayList<>();
                                for (int i = 0; i < editor.getNumNodes(); i++) {
                                    nodes.add(new ContinuousVariable("X" + (i + 1)));
                                }
                                dag = GraphUtils.randomGraph(nodes, editor.getNumLatents(), editor.getMaxEdges(), 30, 15, 15, editor.isConnected());
                            }
                        } while (dag.getNumEdges() < editor.getMaxEdges());
                    }
                    boolean addCycles = editor.isAddCycles();
                    if (addCycles) {
                        int minNumCycles = editor.getMinNumCycles();
                        int minCycleLength = editor.getMinCycleLength();
                        // graph = DataGraphUtils.addCycles2(dag, minNumCycles, minCycleLength);
                        graph = GraphUtils.cyclicGraph2(editor.getNumNodes(), editor.getMaxEdges(), 8);
                        GraphUtils.addTwoCycles(graph, editor.getMinNumCycles());
                    } else {
                        graph = new EdgeListGraph(dag);
                    }
                }
                if (graph == null) {
                    JOptionPane.showMessageDialog(TimeLagGraphEditor.this, "Could not find a graph that fits those constrains.");
                    getWorkbench().setGraph(new EdgeListGraph(dag));
                } else {
                    getWorkbench().setGraph(graph);
                }
            // getWorkbench().setGraph(new EdgeListGraph(dag));
            // getWorkbench().setGraph(graph);
            }
        }
    });
    JMenuItem randomIndicatorModel = new JMenuItem("Random Multiple Indicator Model");
    graph.add(randomIndicatorModel);
    randomIndicatorModel.addActionListener(new ActionListener() {

        public void actionPerformed(ActionEvent e) {
            RandomMimParamsEditor editor = new RandomMimParamsEditor(parameters);
            int ret = JOptionPane.showConfirmDialog(JOptionUtils.centeringComp(), editor, "Edit Random MIM Parameters", JOptionPane.OK_CANCEL_OPTION, JOptionPane.PLAIN_MESSAGE);
            if (ret == JOptionPane.OK_OPTION) {
                int numFactors = Preferences.userRoot().getInt("randomMimNumFactors", 1);
                int numStructuralNodes = Preferences.userRoot().getInt("numStructuralNodes", 3);
                int maxStructuralEdges = Preferences.userRoot().getInt("numStructuralEdges", 3);
                int measurementModelDegree = Preferences.userRoot().getInt("measurementModelDegree", 3);
                int numLatentMeasuredImpureParents = Preferences.userRoot().getInt("latentMeasuredImpureParents", 0);
                int numMeasuredMeasuredImpureParents = Preferences.userRoot().getInt("measuredMeasuredImpureParents", 0);
                int numMeasuredMeasuredImpureAssociations = Preferences.userRoot().getInt("measuredMeasuredImpureAssociations", 0);
                Graph graph;
                if (numFactors == 1) {
                    graph = DataGraphUtils.randomSingleFactorModel(numStructuralNodes, maxStructuralEdges, measurementModelDegree, numLatentMeasuredImpureParents, numMeasuredMeasuredImpureParents, numMeasuredMeasuredImpureAssociations);
                } else if (numFactors == 2) {
                    graph = DataGraphUtils.randomBifactorModel(numStructuralNodes, maxStructuralEdges, measurementModelDegree, numLatentMeasuredImpureParents, numMeasuredMeasuredImpureParents, numMeasuredMeasuredImpureAssociations);
                } else {
                    throw new IllegalArgumentException("Can only make random MIMs for 1 or 2 factors, " + "sorry dude.");
                }
                getWorkbench().setGraph(graph);
            }
        }
    });
    graph.addSeparator();
    graph.add(new JMenuItem(new SelectBidirectedAction(getWorkbench())));
    graph.add(new JMenuItem(new SelectUndirectedAction(getWorkbench())));
    // graph.add(action);
    return graph;
}