use of dr.inference.trace.TraceException in project beast-mcmc by beast-dev.
the class AICMAnalysisParser method parseXMLObject.
public Object parseXMLObject(XMLObject xo) throws XMLParseException {
String fileName = xo.getStringAttribute(FILE_NAME);
try {
// Open file
File file = new File(fileName);
String name = file.getName();
String parent = file.getParent();
if (!file.isAbsolute()) {
parent = System.getProperty("user.dir");
}
file = new File(parent, name);
fileName = file.getAbsolutePath();
// Set analysisType
String analysisType = "aicm";
// Set bootstrapLength
int bootstrapLength = xo.getAttribute(BOOTSTRAP_LENGTH, 1000);
// Load traces and remove burnin
LogFileTraces traces = new LogFileTraces(fileName, file);
traces.loadTraces();
long maxState = traces.getMaxState();
long burnin = xo.getAttribute(BURN_IN, maxState / 10);
if (burnin < 0 || burnin >= maxState) {
burnin = maxState / 10;
System.out.println("WARNING: Burn-in larger than total number of states - using to 10%");
}
traces.setBurnIn(burnin);
// Find likelihood column
XMLObject cxo = xo.getChild(COLUMN_NAME);
String likelihoodName = cxo.getStringAttribute(Attribute.NAME);
int traceIndex = -1;
for (int i = 0; i < traces.getTraceCount(); i++) {
String traceName = traces.getTraceName(i);
if (traceName.equals(likelihoodName)) {
traceIndex = i;
break;
}
}
if (traceIndex == -1) {
throw new XMLParseException("Column '" + likelihoodName + "' can not be found for " + getParserName() + " element.");
}
// Get samples and perform analysis
List<Double> sample = traces.getValues(traceIndex);
MarginalLikelihoodAnalysis analysis = new MarginalLikelihoodAnalysis(sample, traces.getTraceName(traceIndex), (int) burnin, analysisType, bootstrapLength);
System.out.println(analysis.toString());
return analysis;
} catch (FileNotFoundException fnfe) {
throw new XMLParseException("File '" + fileName + "' can not be opened for " + getParserName() + " element.");
} catch (java.io.IOException ioe) {
throw new XMLParseException(ioe.getMessage());
} catch (TraceException e) {
throw new XMLParseException(e.getMessage());
}
}
use of dr.inference.trace.TraceException in project beast-mcmc by beast-dev.
the class ArithmeticMeanAnalysisParser method parseXMLObject.
public Object parseXMLObject(XMLObject xo) throws XMLParseException {
String fileName = xo.getStringAttribute(FILE_NAME);
try {
// Open file
File file = new File(fileName);
String name = file.getName();
String parent = file.getParent();
if (!file.isAbsolute()) {
parent = System.getProperty("user.dir");
}
file = new File(parent, name);
fileName = file.getAbsolutePath();
// Set analysisType
String analysisType = "arithmetic";
// Set bootstrapLength
int bootstrapLength = xo.getAttribute(BOOTSTRAP_LENGTH, 1000);
// Load traces and remove burnin
LogFileTraces traces = new LogFileTraces(fileName, file);
traces.loadTraces();
long maxState = traces.getMaxState();
long burnin = xo.getAttribute(BURN_IN, maxState / 10);
if (burnin < 0 || burnin >= maxState) {
burnin = maxState / 10;
System.out.println("WARNING: Burn-in larger than total number of states - using to 10%");
}
traces.setBurnIn(burnin);
// Find likelihood column
XMLObject cxo = xo.getChild(COLUMN_NAME);
String likelihoodName = cxo.getStringAttribute(Attribute.NAME);
int traceIndex = -1;
for (int i = 0; i < traces.getTraceCount(); i++) {
String traceName = traces.getTraceName(i);
if (traceName.equals(likelihoodName)) {
traceIndex = i;
break;
}
}
if (traceIndex == -1) {
throw new XMLParseException("Column '" + likelihoodName + "' can not be found for " + getParserName() + " element.");
}
// Get samples and perform analysis
List<Double> sample = traces.getValues(traceIndex);
MarginalLikelihoodAnalysis analysis = new MarginalLikelihoodAnalysis(sample, traces.getTraceName(traceIndex), (int) burnin, analysisType, bootstrapLength);
System.out.println(analysis.toString());
return analysis;
} catch (FileNotFoundException fnfe) {
throw new XMLParseException("File '" + fileName + "' can not be opened for " + getParserName() + " element.");
} catch (java.io.IOException ioe) {
throw new XMLParseException(ioe.getMessage());
} catch (TraceException e) {
throw new XMLParseException(e.getMessage());
}
}
use of dr.inference.trace.TraceException in project beast-mcmc by beast-dev.
the class HarmonicMeanAnalysisParser method parseXMLObject.
public Object parseXMLObject(XMLObject xo) throws XMLParseException {
String fileName = xo.getStringAttribute(FILE_NAME);
try {
// Open file
File file = new File(fileName);
String name = file.getName();
String parent = file.getParent();
if (!file.isAbsolute()) {
parent = System.getProperty("user.dir");
}
file = new File(parent, name);
fileName = file.getAbsolutePath();
// Set analysisType
String analysisType = "harmonic";
boolean smoothedEstimate = false;
if (xo.hasAttribute(SMOOTHED_ESTIMATE))
smoothedEstimate = xo.getBooleanAttribute(SMOOTHED_ESTIMATE);
if (smoothedEstimate)
analysisType = "smoothed";
// Set bootstrapLength
int bootstrapLength = xo.getAttribute(BOOTSTRAP_LENGTH, 1000);
// Load traces and remove burnin
LogFileTraces traces = new LogFileTraces(fileName, file);
traces.loadTraces();
long maxState = traces.getMaxState();
long burnin = xo.getAttribute(BURN_IN, maxState / 10);
if (burnin < 0 || burnin >= maxState) {
burnin = (int) (maxState / 10);
System.out.println("WARNING: Burn-in larger than total number of states - using to 10%");
}
traces.setBurnIn(burnin);
// Find likelihood column
XMLObject cxo = xo.getChild(COLUMN_NAME);
String likelihoodName = cxo.getStringAttribute(Attribute.NAME);
int traceIndex = -1;
for (int i = 0; i < traces.getTraceCount(); i++) {
String traceName = traces.getTraceName(i);
if (traceName.equals(likelihoodName)) {
traceIndex = i;
break;
}
}
if (traceIndex == -1) {
throw new XMLParseException("Column '" + likelihoodName + "' can not be found for " + getParserName() + " element.");
}
// Get samples and perform analysis
List<Double> sample = traces.getValues(traceIndex);
MarginalLikelihoodAnalysis analysis = new MarginalLikelihoodAnalysis(sample, traces.getTraceName(traceIndex), (int) burnin, analysisType, bootstrapLength);
System.out.println(analysis.toString());
return analysis;
} catch (FileNotFoundException fnfe) {
throw new XMLParseException("File '" + fileName + "' can not be opened for " + getParserName() + " element.");
} catch (java.io.IOException ioe) {
throw new XMLParseException(ioe.getMessage());
} catch (TraceException e) {
throw new XMLParseException(e.getMessage());
}
}
use of dr.inference.trace.TraceException in project beast-mcmc by beast-dev.
the class ParameterParser method parseXMLObject.
public Object parseXMLObject(XMLObject xo) throws XMLParseException {
double[] values = null;
double[] uppers;
double[] lowers;
if (xo.hasAttribute(DIMENSION)) {
values = new double[xo.getIntegerAttribute(DIMENSION)];
}
if (xo.hasAttribute(FILENAME)) {
//read samples from a file (used for a reference prior) and calculate the mean
String fileName = xo.getStringAttribute(FILENAME);
File file = new File(fileName);
fileName = file.getName();
String parent = file.getParent();
if (!file.isAbsolute()) {
parent = System.getProperty("user.dir");
}
file = new File(parent, fileName);
fileName = file.getAbsolutePath();
String columnName = "";
if (xo.hasAttribute(PARAMETERCOLUMN)) {
columnName = xo.getStringAttribute(PARAMETERCOLUMN);
} else {
throw new XMLParseException("when providing a file name you must provide a parameter column as well");
}
//if a number for the burnin is not given, use 0 ...
int burnin;
if (xo.hasAttribute(BURNIN)) {
burnin = xo.getIntegerAttribute(BURNIN);
} else {
burnin = 0;
}
LogFileTraces traces = new LogFileTraces(fileName, file);
List parameterSamples = null;
try {
traces.loadTraces();
traces.setBurnIn(burnin);
int traceIndexParameter = -1;
for (int i = 0; i < traces.getTraceCount(); i++) {
String traceName = traces.getTraceName(i);
if (traceName.trim().equals(columnName)) {
traceIndexParameter = i;
}
}
if (traceIndexParameter == -1) {
throw new XMLParseException("Column '" + columnName + "' can not be found for " + getParserName() + " element.");
}
parameterSamples = traces.getValues(traceIndexParameter);
} catch (TraceException e) {
throw new XMLParseException(e.getMessage());
} catch (IOException ioe) {
throw new XMLParseException(ioe.getMessage());
}
values = new double[1];
for (int i = 0, stop = parameterSamples.size(); i < stop; i++) {
values[0] += ((Double) parameterSamples.get(i)) / ((double) stop);
}
System.out.println("Number of samples: " + parameterSamples.size());
System.out.println("Parameter mean: " + values[0]);
} else if (xo.hasAttribute(VALUE)) {
if (values == null) {
values = xo.getDoubleArrayAttribute(VALUE);
} else {
double[] v = xo.getDoubleArrayAttribute(VALUE);
if (v.length == values.length) {
System.arraycopy(v, 0, values, 0, v.length);
} else if (v.length == 1) {
for (int i = 0; i < values.length; i++) {
values[i] = v[0];
}
} else {
throw new XMLParseException("value string must have 1 value or dimension values");
}
}
} else {
if (xo.hasAttribute(DIMENSION)) {
values = new double[xo.getIntegerAttribute(DIMENSION)];
} else {
// parameter dimension will get set correctly by TreeModel presumably.
if (!xo.hasChildNamed(RANDOMIZE)) {
return new Parameter.Default(1);
}
values = new double[1];
values[0] = 1.0;
}
}
uppers = new double[values.length];
for (int i = 0; i < values.length; i++) {
uppers[i] = Double.POSITIVE_INFINITY;
}
lowers = new double[values.length];
for (int i = 0; i < values.length; i++) {
lowers[i] = Double.NEGATIVE_INFINITY;
}
if (xo.hasAttribute(UPPER)) {
double[] v = xo.getDoubleArrayAttribute(UPPER);
if (v.length == uppers.length) {
System.arraycopy(v, 0, uppers, 0, v.length);
} else if (v.length == 1) {
for (int i = 0; i < uppers.length; i++) {
uppers[i] = v[0];
}
} else {
throw new XMLParseException("uppers string must have 1 value or dimension values");
}
}
if (xo.hasAttribute(LOWER)) {
double[] v = xo.getDoubleArrayAttribute(LOWER);
if (v.length == lowers.length) {
System.arraycopy(v, 0, lowers, 0, v.length);
} else if (v.length == 1) {
for (int i = 0; i < lowers.length; i++) {
lowers[i] = v[0];
}
} else {
throw new XMLParseException("lowers string must have 1 value or dimension values");
}
}
if ((uppers.length != values.length)) {
throw new XMLParseException("value and upper limit strings have different dimension, in parameter");
}
if ((lowers.length != values.length)) {
throw new XMLParseException("value and lower limit strings have different dimension, in parameter");
}
// check if uppers and lowers are consistent
for (int i = 0; i < values.length; i++) {
if (uppers[i] < lowers[i]) {
throw new XMLParseException("upper is lower than lower, in parameter");
}
}
if (xo.hasChildNamed(RANDOMIZE)) {
Distribution distribution = (Distribution) xo.getChild(RANDOMIZE).getChild(Distribution.class);
for (int i = 0; i < values.length; i++) {
do {
// Not an efficient way to draw random variables, but this is currently the only general interface
values[i] = distribution.quantile(MathUtils.nextDouble());
} while (values[i] < lowers[i] || values[i] > uppers[i]);
}
} else {
// make values consistent with bounds
for (int i = 0; i < values.length; i++) {
if (uppers[i] < values[i])
values[i] = uppers[i];
}
for (int i = 0; i < values.length; i++) {
if (lowers[i] > values[i])
values[i] = lowers[i];
}
}
Parameter param = new Parameter.Default(values.length);
for (int i = 0; i < values.length; i++) {
param.setParameterValue(i, values[i]);
}
param.addBounds(new Parameter.DefaultBounds(uppers, lowers));
return param;
}
use of dr.inference.trace.TraceException in project beast-mcmc by beast-dev.
the class EBSPAnalysisParser method parseXMLObject.
public Object parseXMLObject(XMLObject xo) throws XMLParseException {
try {
// 10% is brun-in default
final double burnin = xo.getAttribute(BURN_IN, 0.1);
if (burnin < 0) {
throw new XMLParseException("burnIn should be either between 0 and 1 or a positive number");
}
final double[] hpdLevels = xo.hasAttribute(HPD_LEVELS) ? xo.getDoubleArrayAttribute(HPD_LEVELS) : null;
final File log = FileHelpers.getFile(getElementText(xo, LOG_FILE_NAME));
final XMLObject treeFileNames = xo.getChild(TREE_FILE_NAMES);
final int nTrees = treeFileNames.getChildCount();
File[] treeFiles = new File[nTrees];
for (int k = 0; k < nTrees; ++k) {
treeFiles[k] = FileHelpers.getFile(((XMLObject) treeFileNames.getChild(k)).getStringChild(0));
}
String modelTypeName = getElementText(xo, MODEL_TYPE).trim().toUpperCase();
String populationFirstColumn = getElementText(xo, POPULATION_FIRST_COLUMN);
String indicatorsFirstColumn = getElementText(xo, INDICATORS_FIRST_COLUMN);
VariableDemographicModel.Type modelType = VariableDemographicModel.Type.valueOf(modelTypeName);
String rootHeightColumn = null;
int nBins = -1;
if (xo.hasAttribute(NBINS)) {
if (xo.getChild(ROOTHEIGHT_COLUMN) != null) {
rootHeightColumn = getElementText(xo, ROOTHEIGHT_COLUMN);
nBins = xo.getIntegerAttribute(NBINS);
}
}
PrintWriter allDemoWriter = null;
if (xo.getChild(ALLDEMO_COLUMN) != null) {
String fName = getElementText(xo, ALLDEMO_COLUMN);
allDemoWriter = new PrintWriter(new FileWriter(fName));
}
final boolean quantiles = xo.getAttribute(QUANTILES, false);
final boolean logSpace = xo.getAttribute(LOG_SPACE, false);
final boolean useMid = xo.getAttribute(USE_MIDDLE, false);
final int onlyNchanges = xo.getAttribute(N_CHANGES, -1);
return new EBSPAnalysis(log, treeFiles, modelType, populationFirstColumn, indicatorsFirstColumn, rootHeightColumn, nBins, burnin, hpdLevels, quantiles, logSpace, useMid, onlyNchanges, allDemoWriter);
} catch (java.io.IOException ioe) {
throw new XMLParseException(ioe.getMessage());
} catch (Importer.ImportException e) {
throw new XMLParseException(e.toString());
} catch (TraceException e) {
throw new XMLParseException(e.toString());
}
}
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