edu.cmu.tetradapp.model.datamanip.InvertCovMatrixWrapper Maven / Gradle / Ivy
///////////////////////////////////////////////////////////////////////////////
// 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.tetradapp.model.datamanip;
import edu.cmu.tetrad.data.*;
import edu.cmu.tetrad.util.Matrix;
import edu.cmu.tetrad.util.TetradSerializableUtils;
import edu.cmu.tetradapp.model.DataWrapper;
import edu.cmu.tetradapp.model.PcRunner;
/**
* Splits continuous data sets by collinear columns.
*
* @author Tyler Gibson
*/
public class InvertCovMatrixWrapper extends DataWrapper {
private static final long serialVersionUID = 23L;
/**
* Splits the given data set by collinear columns.
*/
public InvertCovMatrixWrapper(DataWrapper wrapper) {
if (wrapper == null) {
throw new NullPointerException("The given data must not be null");
}
DataModel model = wrapper.getSelectedDataModel();
if (model instanceof ICovarianceMatrix) {
ICovarianceMatrix dataSet = (ICovarianceMatrix) model;
Matrix data = dataSet.getMatrix();
Matrix inverse = data.inverse();
String[] varNames = dataSet.getVariableNames().toArray(new String[0]);
ICovarianceMatrix covarianceMatrix = new CovarianceMatrix(DataUtils.createContinuousVariables(varNames), inverse,
((ICovarianceMatrix) model).getSampleSize());
setDataModel(covarianceMatrix);
setSourceGraph(wrapper.getSourceGraph());
} else {
throw new IllegalArgumentException("Must be a covariance matrix");
}
LogDataUtils.logDataModelList("Inverts a parent covaraince matrix.", getDataModelList());
}
/**
* Generates a simple exemplar of this class to test serialization.
*
* @see TetradSerializableUtils
*/
public static PcRunner serializableInstance() {
return PcRunner.serializableInstance();
}
}
© 2015 - 2025 Weber Informatics LLC | Privacy Policy