/*
* MarkovRandomFieldMatrix.java
*
* Copyright (c) 2002-2015 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.inference.model;
import dr.util.Transform;
/**
* @author Marc Suchard
*/
public class MarkovRandomFieldMatrix extends MatrixParameter {
private Parameter diagonalParameter;
private Parameter offDiagonalParameter;
private final Parameter nuggetParameter;
private final Transform diagonalTransform;
private final Transform offDiagonalTransform;
private boolean asCorrelation = false;
private int dim;
// public MarkovRandomFieldMatrix(String name, int dim, Parameter diagonals, Parameter offDiagonal,
// Parameter nugget,
// boolean asCorrelation) {
// this(name, dim, diagonals, offDiagonal, nugget, asCorrelation, null, null);
// }
public MarkovRandomFieldMatrix(String name, int dim, Parameter diagonals, Parameter offDiagonal,
Parameter nugget,
boolean asCorrelation,
Transform diagonalTransform, Transform offDiagonalTransform) {
super(name);
diagonalParameter = diagonals;
offDiagonalParameter = offDiagonal;
nuggetParameter = nugget;
addParameter(diagonalParameter);
addParameter(offDiagonalParameter);
addParameter(nuggetParameter);
this.dim = dim;
this.asCorrelation = asCorrelation;
this.diagonalTransform = (diagonalTransform != null) ? diagonalTransform : Transform.NONE;
this.offDiagonalTransform = (offDiagonalTransform != null) ? offDiagonalTransform : Transform.NONE;
}
// public void variableChangedEvent(Variable variable, int index, Parameter.ChangeType type) {
// if (variable == diagonalParameter || variable == offDiagonalParameter || variable == nuggetParameter) {
// fireParameterChangedEvent(-1, ChangeType.ALL_VALUES_CHANGED);
// } else {
// throw new IllegalArgumentException("Unknown variable '" + variable.getVariableName() + "'");
// }
// }
// public double[] getAttributeValue() {
// double[] stats = new double[dim * dim];
// int index = 0;
// for (int i = 0; i < dim; i++) {
// for (int j = 0; j < dim; j++) {
// stats[index] = getParameterValue(i, j);
// index++;
// }
// }
// return stats;
// }
//
public int getDimension() {
return dim * dim;
}
public String getDimensionName(int i) {
int row = i / dim;
int col = i % dim;
return getParameterName() + "_" + (row + 1) + "_" + (col + 1);
}
private double getDiagonalParameterValue(int i) {
return diagonalTransform.inverse(diagonalParameter.getParameterValue(i));
}
private double getOffDiagonalParameterValue(int i) {
return offDiagonalTransform.inverse(offDiagonalParameter.getParameterValue(i));
}
private double getNuggetValue(int i) {
return nuggetParameter.getParameterValue(i);
}
public double getParameterValue(int i) {
int row = i / dim;
int col = i % dim;
return getParameterValue(row, col);
}
public double getParameterValue(int row, int col) {
if (row == col) {
double diag = getDiagonalParameterValue(0);
if (row > 0 && row < (dim - 1)) {
diag *= 2; // TODO Assumes RW-1 model
}
diag += getNuggetValue(0);
return diag;
// return getDiagonalParameterValue(row);
} else if (row == (col - 1) || row == (col + 1)) {
if (asCorrelation) {
return -getOffDiagonalParameterValue(0) *
Math.sqrt(getDiagonalParameterValue(0) * getDiagonalParameterValue(0));
}
return getOffDiagonalParameterValue(0);
}
return 0.0;
}
// public double[][] getParameterAsMatrix() {
// final int I = dim;
// double[][] parameterAsMatrix = new double[I][I];
// for (int i = 0; i < I; i++) {
// parameterAsMatrix[i][i] = getParameterValue(i, i);
// for (int j = i + 1; j < I; j++) {
// parameterAsMatrix[j][i] = parameterAsMatrix[i][j] = getParameterValue(i, j);
// }
// }
// return parameterAsMatrix;
// }
public int getColumnDimension() {
return dim;
}
public int getRowDimension() {
return dim;
}
}