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///////////////////////////////////////////////////////////////////////////////
// For information as to what this class does, see the Javadoc, below. //
// Copyright (C) 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, //
// 2007, 2008, 2009, 2010, 2014, 2015, 2022 by Peter Spirtes, Richard //
// Scheines, Joseph Ramsey, and Clark Glymour. //
// //
// This program is free software; you can redistribute it and/or modify //
// it under the terms of the GNU General Public License as published by //
// the Free Software Foundation; either version 2 of the License, or //
// (at your option) any later version. //
// //
// This program is distributed in the hope that it will be useful, //
// but WITHOUT ANY WARRANTY; without even the implied warranty of //
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the //
// GNU General Public License for more details. //
// //
// You should have received a copy of the GNU General Public License //
// along with this program; if not, write to the Free Software //
// Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA //
///////////////////////////////////////////////////////////////////////////////
package edu.cmu.tetrad.bayes;
import edu.cmu.tetrad.data.*;
import edu.cmu.tetrad.graph.Node;
import java.util.LinkedList;
import java.util.List;
/**
* Returns a data set in variables for columns with missing values are augmented with an extra category that represents
* the missing values, with missing values being reported as belong this category.
*
* @author josephramsey
*/
public final class ExtraCategoryInterpolator implements DataFilter {
public DataSet filter(DataSet dataSet) {
// Why does it have to be discrete? Why can't we simply expand
// whatever discrete columns are there and leave the continuous
// ones untouched? jdramsey 7/4/2005
List variables = new LinkedList<>();
// Add all of the variables to the new data set.
for (int j = 0; j < dataSet.getNumColumns(); j++) {
Node _var = dataSet.getVariable(j);
if (!(_var instanceof DiscreteVariable)) {
variables.add(_var);
continue;
}
DiscreteVariable variable = (DiscreteVariable) _var;
String oldName = variable.getName();
List oldCategories = variable.getCategories();
List newCategories = new LinkedList<>(oldCategories);
String newCategory = "Missing";
int _j = 0;
while (oldCategories.contains(newCategory)) {
newCategory = "Missing" + (++_j);
}
newCategories.add(newCategory);
String newName = oldName + "+";
DiscreteVariable newVariable = new DiscreteVariable(newName, newCategories);
variables.add(newVariable);
}
DataSet newDataSet = new BoxDataSet(new DoubleDataBox(dataSet.getNumRows(), variables.size()), variables);
// Copy old values to new data set, replacing missing values with new
// "MissingValue" categories.
for (int j = 0; j < dataSet.getNumColumns(); j++) {
Node _var = dataSet.getVariable(j);
if (_var instanceof ContinuousVariable) {
for (int i = 0; i < dataSet.getNumRows(); i++) {
newDataSet.setDouble(i, j, dataSet.getDouble(i, j));
}
} else if (_var instanceof DiscreteVariable) {
DiscreteVariable variable = (DiscreteVariable) _var;
int numCategories = variable.getNumCategories();
for (int i = 0; i < dataSet.getNumRows(); i++) {
int value = dataSet.getInt(i, j);
if (value == DiscreteVariable.MISSING_VALUE) {
newDataSet.setInt(i, j, numCategories);
} else {
newDataSet.setInt(i, j, value);
}
}
}
}
return newDataSet;
}
}
