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

Example 66 with DataSet

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

the class MGM method runTests2.

/**
 * test non penalty use cases
 */
private static void runTests2() {
    Graph g = GraphConverter.convert("X1-->X2,X3-->X2,X4-->X5");
    // simple graph pm im gen example
    HashMap<String, Integer> nd = new HashMap<>();
    nd.put("X1", 0);
    nd.put("X2", 0);
    nd.put("X3", 4);
    nd.put("X4", 4);
    nd.put("X5", 4);
    g = MixedUtils.makeMixedGraph(g, nd);
    GeneralizedSemPm pm = MixedUtils.GaussianCategoricalPm(g, "Split(-1.5,-.5,.5,1.5)");
    System.out.println(pm);
    GeneralizedSemIm im = MixedUtils.GaussianCategoricalIm(pm);
    System.out.println(im);
    int samps = 1000;
    DataSet ds = im.simulateDataFisher(samps);
    ds = MixedUtils.makeMixedData(ds, nd);
    // System.out.println(ds);
    double lambda = 0;
    MGM model = new MGM(ds, new double[] { lambda, lambda, lambda });
    System.out.println("Init nll: " + model.smoothValue(model.params.toMatrix1D()));
    System.out.println("Init reg term: " + model.nonSmoothValue(model.params.toMatrix1D()));
    model.learn(1e-8, 1000);
    System.out.println("Learned nll: " + model.smoothValue(model.params.toMatrix1D()));
    System.out.println("Learned reg term: " + model.nonSmoothValue(model.params.toMatrix1D()));
    System.out.println("params:\n" + model.params);
    System.out.println("adjMat:\n" + model.adjMatFromMGM());
}

Example 67 with DataSet

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

the class GeneralBootstrapSearchAction method compute.

@Override
public void compute() {
    if (workLoad < 2) {
        long start, stop;
        start = System.currentTimeMillis();
        if (verbose) {
            out.println("thread started ... ");
        }
        DataSet data = generalBootstrapSearch.getData();
        DataSet dataSet = DataUtils.getBootstrapSample(data, data.getNumRows());
        Graph graph = algorithm.search(dataSet, parameters);
        stop = System.currentTimeMillis();
        if (verbose) {
            out.println("processing time of bootstrap for thread id : " + dataSetId + " was: " + (stop - start) / 1000.0 + " sec");
        }
        generalBootstrapSearch.addPAG(graph);
    } else {
        GeneralBootstrapSearchAction task1 = new GeneralBootstrapSearchAction(dataSetId, workLoad / 2, algorithm, parameters, generalBootstrapSearch, verbose);
        GeneralBootstrapSearchAction task2 = new GeneralBootstrapSearchAction(dataSetId + workLoad / 2, workLoad - workLoad / 2, algorithm, parameters, generalBootstrapSearch, verbose);
        List<GeneralBootstrapSearchAction> tasks = new ArrayList<>();
        tasks.add(task1);
        tasks.add(task2);
        invokeAll(tasks);
    }
}

Example 68 with DataSet

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

the class ADTreeTest method main.

public static void main(String[] args) throws Exception {
    int columns = 40;
    int numEdges = 40;
    int rows = 500;
    List<Node> variables = new ArrayList<>();
    List<String> varNames = new ArrayList<>();
    for (int i = 0; i < columns; i++) {
        final String name = "X" + (i + 1);
        varNames.add(name);
        variables.add(new ContinuousVariable(name));
    }
    Graph graph = GraphUtils.randomGraphRandomForwardEdges(variables, 0, numEdges, 30, 15, 15, false, true);
    BayesPm pm = new BayesPm(graph);
    BayesIm im = new MlBayesIm(pm, MlBayesIm.RANDOM);
    DataSet data = im.simulateData(rows, false);
    // This implementation uses a DataTable to represent the data
    // The first type parameter is the type for the variables
    // The second type parameter is the type for the values of the variables
    DataTableImpl<Node, Short> dataTable = new DataTableImpl<>(variables);
    for (int i = 0; i < rows; i++) {
        ArrayList<Short> intArray = new ArrayList<>();
        for (int j = 0; j < columns; j++) {
            intArray.add((short) data.getInt(i, j));
        }
        dataTable.addRow(intArray);
    }
    // create the tree
    long start = System.currentTimeMillis();
    ADTree<Node, Short> adTree = new ADTree<>(dataTable);
    System.out.println(String.format("Generated tree in %s millis", System.currentTimeMillis() - start));
    // the query is an arbitrary map of vars and their values
    TreeMap<Node, Short> query = new TreeMap<>();
    query.put(node(pm, "X1"), (short) 1);
    query.put(node(pm, "X5"), (short) 0);
    start = System.currentTimeMillis();
    System.out.println(String.format("Count is %d", adTree.count(query)));
    System.out.println(String.format("Query in %s ms", System.currentTimeMillis() - start));
    query.clear();
    query.put(node(pm, "X1"), (short) 1);
    query.put(node(pm, "X2"), (short) 1);
    query.put(node(pm, "X5"), (short) 0);
    query.put(node(pm, "X10"), (short) 1);
    start = System.currentTimeMillis();
    System.out.println(String.format("Count is %d", adTree.count(query)));
    System.out.println(String.format("Query in %s ms", System.currentTimeMillis() - start));
}

Example 69 with DataSet

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

the class HistogramAction method actionPerformed.

public void actionPerformed(ActionEvent e) {
    DataSet dataSet = (DataSet) dataEditor.getSelectedDataModel();
    if (dataSet == null || dataSet.getNumColumns() == 0) {
        JOptionPane.showMessageDialog(findOwner(), "Cannot display a histogram for an empty data set.");
        return;
    }
    int[] selected = dataSet.getSelectedIndices();
    // if more then one column is selected then open up more than one histogram
    if (selected != null && selected.length >= 1) {
        // warn user if they selected more than 10
        if (selected.length > 10) {
            int option = JOptionPane.showConfirmDialog(findOwner(), "You are about to open " + selected.length + " histograms, are you sure you want to proceed?", "Histogram Warning", JOptionPane.YES_NO_OPTION);
            // if selected no, return
            if (option == JOptionPane.NO_OPTION) {
                return;
            }
        }
        for (int index : selected) {
            JPanel component = createHistogramPanel(dataSet.getVariable(index));
            EditorWindow editorWindow = new EditorWindow(component, "Histogram", "Close", false, dataEditor);
            DesktopController.getInstance().addEditorWindow(editorWindow, JLayeredPane.PALETTE_LAYER);
            editorWindow.pack();
            setLocation(editorWindow, index);
            editorWindow.setVisible(true);
        }
    } else {
        // No selected variable--just show a histogram for the first variable.
        JPanel component = createHistogramPanel(null);
        EditorWindow editorWindow = new EditorWindow(component, "Histogram", "Close", false, dataEditor);
        DesktopController.getInstance().addEditorWindow(editorWindow, JLayeredPane.PALETTE_LAYER);
        editorWindow.pack();
        editorWindow.setVisible(true);
    }
}

Example 70 with DataSet

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

the class GdistanceApply method main.

public static void main(String... args) {
    double xdist = 2.4;
    double ydist = 2.4;
    double zdist = 2;
    long timestart = System.nanoTime();
    System.out.println("Loading first graph");
    Graph graph1 = GraphUtils.loadGraphTxt(new File("Motion_Corrected_Graphs/singlesub_motion_graph_025_04.txt"));
    long timegraph1 = System.nanoTime();
    // System.out.println(graph1);
    System.out.println("Done loading first graph. Elapsed time: " + (timegraph1 - timestart) / 1000000000 + "s");
    System.out.println("Loading second graph");
    Graph graph2 = GraphUtils.loadGraphTxt(new File("Motion_Corrected_Graphs/singlesub_motion_graph_027_04.txt"));
    long timegraph2 = System.nanoTime();
    System.out.println("Done loading second graph. Elapsed time: " + (timegraph2 - timegraph1) / 1000000000 + "s");
    // +++++++++ these steps are specifically for the motion corrected fMRI graphs ++++++++++++
    graph1.removeNode(graph1.getNode("Motion_1"));
    graph1.removeNode(graph1.getNode("Motion_2"));
    graph1.removeNode(graph1.getNode("Motion_3"));
    graph1.removeNode(graph1.getNode("Motion_4"));
    graph1.removeNode(graph1.getNode("Motion_5"));
    graph1.removeNode(graph1.getNode("Motion_6"));
    graph2.removeNode(graph2.getNode("Motion_1"));
    graph2.removeNode(graph2.getNode("Motion_2"));
    graph2.removeNode(graph2.getNode("Motion_3"));
    graph2.removeNode(graph2.getNode("Motion_4"));
    graph2.removeNode(graph2.getNode("Motion_5"));
    graph2.removeNode(graph2.getNode("Motion_6"));
    // load the location map
    String workingDirectory = System.getProperty("user.dir");
    System.out.println(workingDirectory);
    Path mapPath = Paths.get("coords.txt");
    System.out.println(mapPath);
    TabularDataReader dataReaderMap = new ContinuousTabularDataFileReader(mapPath.toFile(), Delimiter.COMMA);
    try {
        DataSet locationMap = (DataSet) DataConvertUtils.toDataModel(dataReaderMap.readInData());
        long timegraph3 = System.nanoTime();
        System.out.println("Done loading location map. Elapsed time: " + (timegraph3 - timegraph2) / 1000000000 + "s");
        System.out.println("Running Gdistance");
        Gdistance gdist = new Gdistance(locationMap, xdist, ydist, zdist);
        List<Double> distance = gdist.distances(graph1, graph2);
        System.out.println(distance);
        System.out.println("Done running Distance. Elapsed time: " + (System.nanoTime() - timegraph3) / 1000000000 + "s");
        System.out.println("Total elapsed time: " + (System.nanoTime() - timestart) / 1000000000 + "s");
        PrintWriter writer = new PrintWriter("Gdistances.txt", "UTF-8");
        writer.println(distance);
        writer.close();
    } catch (Exception IOException) {
        IOException.printStackTrace();
    }
}