/*
* ConstrainedGaussianProcess.java
*
* Copyright (c) 2002-2016 Alexei Drummond, Andrew Rambaut and Marc Suchard
*
* This file is part of BEAST.
* See the NOTICE file distributed with this work for additional
* information regarding copyright ownership and licensing.
*
* BEAST is free software; you can redistribute it and/or modify
* it under the terms of the GNU Lesser General Public License as
* published by the Free Software Foundation; either version 2
* of the License, or (at your option) any later version.
*
* BEAST 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 Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public
* License along with BEAST; if not, write to the
* Free Software Foundation, Inc., 51 Franklin St, Fifth Floor,
* Boston, MA 02110-1301 USA
*/
package dr.evomodel.continuous;
import dr.evolution.tree.NodeRef;
import dr.inference.model.Likelihood;
import dr.inference.model.Parameter;
import dr.inference.operators.EllipticalSliceOperator;
import dr.inferencexml.operators.EllipticalSliceOperatorParser;
import dr.math.KroneckerOperation;
import dr.math.distributions.GaussianProcessRandomGenerator;
import dr.math.distributions.MultivariateNormalDistribution;
import dr.math.matrixAlgebra.CholeskyDecomposition;
import dr.math.matrixAlgebra.IllegalDimension;
import dr.math.matrixAlgebra.Matrix;
import dr.math.matrixAlgebra.SymmetricMatrix;
import dr.xml.*;
/**
* @author Marc A. Suchard
* @author Max R. Tolkoff
*/
public class ConstrainedGaussianProcessRandomGenerator implements GaussianProcessRandomGenerator {
private final GaussianProcessRandomGenerator generator;
private final boolean translationInvariant;
private final boolean rotationInvariant;
public ConstrainedGaussianProcessRandomGenerator(GaussianProcessRandomGenerator generator,
boolean translationInvariant, boolean rotationInvariant) {
this.generator = generator;
this.translationInvariant = translationInvariant;
this.rotationInvariant = rotationInvariant;
}
@Override
public Likelihood getLikelihood() {
throw new RuntimeException("Not yet implemented");
// return generator.getLikelihood();
}
@Override
public int getDimension() {
return generator.getDimension();
}
@Override
public double[][] getPrecisionMatrix() {
throw new RuntimeException("Not yet implemented");
// return generator.getPrecisionMatrix();
}
@Override
public Object nextRandom() {
double[] draw = (double[]) generator.nextRandom();
EllipticalSliceOperator.transformPoint(draw, translationInvariant, rotationInvariant,
2); // TODO Generalize for dim != 2
return draw;
}
@Override
public double logPdf(Object x) {
throw new RuntimeException("Not yet implemented");
// return generator.logPdf(x);
}
public boolean isTranslationInvariant() {
return translationInvariant;
}
public static XMLObjectParser PARSER = new AbstractXMLObjectParser() {
public static final String CONSTAINED_GAUSSIAN_PROCESS = "constrainedGaussianProcess";
public static final String TRANSLATION_INVARIANT = EllipticalSliceOperatorParser.TRANSLATION_INVARIANT;
public static final String ROTATION_INVARIANT = EllipticalSliceOperatorParser.ROTATION_INVARIANT;
private XMLSyntaxRule[] rules = new XMLSyntaxRule[]{
new ElementRule(GaussianProcessRandomGenerator.class),
AttributeRule.newBooleanRule(TRANSLATION_INVARIANT, true),
AttributeRule.newBooleanRule(ROTATION_INVARIANT, true),
};
@Override
public Object parseXMLObject(XMLObject xo) throws XMLParseException {
boolean translationInvariant = xo.getAttribute(TRANSLATION_INVARIANT, false);
boolean rotationInvariant = xo.getAttribute(ROTATION_INVARIANT, false);
GaussianProcessRandomGenerator generator =
(GaussianProcessRandomGenerator) xo.getChild(GaussianProcessRandomGenerator.class);
return new ConstrainedGaussianProcessRandomGenerator(generator, translationInvariant, rotationInvariant);
}
@Override
public XMLSyntaxRule[] getSyntaxRules() {
return rules;
}
@Override
public String getParserDescription() {
return "Returns a random draw of traits given a trait model and a prior";
}
@Override
public Class getReturnType() {
return ConstrainedGaussianProcessRandomGenerator.class;
}
@Override
public String getParserName() {
return CONSTAINED_GAUSSIAN_PROCESS;
}
};
}