/* * 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; } }