/* * AntigenicTraitLikelihood.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.evomodel.antigenic; import dr.inference.model.*; import dr.math.MathUtils; import dr.util.Author; import dr.util.Citable; import dr.util.Citation; import dr.util.DataTable; import dr.xml.*; import java.io.BufferedReader; import java.io.FileReader; import java.io.IOException; import java.util.*; import java.util.logging.Logger; /** * @author Andrew Rambaut * @author Marc Suchard * @version $Id$ */ @Deprecated // for the moment at least public abstract class AntigenicTraitLikelihood extends MultidimensionalScalingLikelihood implements Citable { public AntigenicTraitLikelihood(String name) { super(name); } protected void initalizeTable(DataTable<String[]> dataTable, double[][] observationValueTable, ObservationType[][] observationTypeTable, boolean log2Transform) { // the largest measured value for any given column of data double[] maxColumnValue = new double[dataTable.getColumnCount()]; // the largest measured value over all double maxAssayValue = 0.0; for (int i = 0; i < dataTable.getRowCount(); i++) { String[] dataRow = dataTable.getRow(i); for (int j = 0; j < dataTable.getColumnCount(); j++) { Double value = null; ObservationType type = null; if (dataRow[j].startsWith("<")) { // is a lower bound value = convertString(dataRow[j].substring(1)); if (Double.isNaN(value)) { throw new RuntimeException("Illegal value in table as a threshold"); } type = ObservationType.LOWER_BOUND; } else if (dataRow[j].startsWith(">")) { // is a lower bound value = convertString(dataRow[j].substring(1)); if (Double.isNaN(value)) { throw new RuntimeException("Illegal value in table as a threshold"); } type = ObservationType.UPPER_BOUND; } else { value = convertString(dataRow[j]); type = Double.isNaN(value) ? ObservationType.MISSING : ObservationType.POINT; } observationValueTable[i][j] = value; observationTypeTable[i][j] = type; if (!Double.isNaN(value)) { if (value > maxColumnValue[j]) { maxColumnValue[j] = value; } if (value > maxAssayValue) { maxAssayValue = value; } } } } if (log2Transform) { // transform and normalize the data... for (int i = 0; i < dataTable.getRowCount(); i++) { for (int j = 0; j < dataTable.getColumnCount(); j++) { observationValueTable[i][j] = transform(observationValueTable[i][j], maxColumnValue[j], 2); // the transformation reverses the bounds if (observationTypeTable[i][j] == ObservationType.UPPER_BOUND) { observationTypeTable[i][j] = ObservationType.LOWER_BOUND; } else if (observationTypeTable[i][j] == ObservationType.LOWER_BOUND) { observationTypeTable[i][j] = ObservationType.UPPER_BOUND; } } } } } private double convertString(String value) { try { return java.lang.Double.valueOf(value); } catch (NumberFormatException nfe) { return java.lang.Double.NaN; } } protected double transform(final double value, final double maxValue, final double base) { // log2(maxValue / value) return (Math.log(maxValue) - Math.log(value)) / Math.log(base); } }