/** Performs the action of loading a session from a file. */
public void actionPerformed(ActionEvent e) {
DataModel dataModel = getDataEditor().getSelectedDataModel();
if (dataModel instanceof DataSet) {
DataSet dataSet = (DataSet) dataModel;
DataFilter interpolator = new ModeInterpolator();
DataSet newDataSet = interpolator.filter(dataSet);
DataModelList list = new DataModelList();
list.add(newDataSet);
getDataEditor().reset(list);
getDataEditor().selectFirstTab();
} else if (dataModel instanceof ICovarianceMatrix) {
JOptionPane.showMessageDialog(JOptionUtils.centeringComp(), "Must be a tabular data set.");
}
}
private void createDiscreteTimeSeriesData() {
// GIVEN: Continuous data set D, maximum lag m.
Node[] dataVars = dataSet.getVariables().toArray(new Node[0]);
int n = dataVars.length;
int m = getNumLags();
// LetXi, i = 0,...,n-1, be the variables from the data. Let Xi(t) be
// the variable Xi at time lag t (before 0), t = 0,...,m.
Node[][] laggedVars = new Node[m + 1][n];
Knowledge knowledge = new Knowledge();
for (int s = 0; s <= m; s++) {
for (int j = 0; j < n; j++) {
String name1 = dataVars[j].getName();
String name2 = name1 + "." + (s + 1);
laggedVars[s][j] = new DiscreteVariable((DiscreteVariable) dataVars[j]);
laggedVars[s][j].setName(name2);
laggedVars[s][j].setCenter(80 * j + 50, 80 * (m - s) + 50);
knowledge.addToTier(s, laggedVars[s][j].getName());
}
}
// 2. Prepare the data the way you did.
List<Node> variables = new LinkedList<Node>();
for (int s = 0; s <= m; s++) {
for (int i = 0; i < n; i++) {
int[] rawData = new int[dataSet.getNumRows()];
for (int j = 0; j < dataSet.getNumRows(); j++) {
rawData[j] = dataSet.getInt(j, i);
}
int size = dataSet.getNumRows();
int[] laggedRaw = new int[size - m + 1];
System.arraycopy(rawData, m - s, laggedRaw, 0, size - m + 1);
variables.add(laggedVars[s][i]);
}
}
DataSet _laggedData = new ColtDataSet(dataSet.getNumRows() - m + 1, variables);
for (int s = 0; s <= m; s++) {
for (int i = 0; i < n; i++) {
int[] rawData = new int[dataSet.getNumRows()];
for (int j = 0; j < dataSet.getNumRows(); j++) {
rawData[j] = dataSet.getInt(j, i);
}
int size = dataSet.getNumRows();
int[] laggedRaw = new int[size - m + 1];
System.arraycopy(rawData, m - s, laggedRaw, 0, size - m + 1);
int _col = _laggedData.getColumn(laggedVars[s][i]);
for (int j = 0; j < dataSet.getNumRows(); j++) {
_laggedData.setInt(j, _col, laggedRaw[j]);
}
}
}
knowledge.setDefaultToKnowledgeLayout(true);
_laggedData.setKnowledge(knowledge);
DataModelList list = new DataModelList();
list.add(_laggedData);
getDataEditor().reset(list);
getDataEditor().selectLastTab();
}