LibPeakaboo.md

LibPeakaboo

LibPeakaboo is the Java XRF analysis library behind Peakaboo. The goal is to create a library which can be used more broadly, rather than just as part of a Swing GUI.

Examples

These examples use the Display package from Peakaboo to render the output. This code is not included in the LibPeakaboo project for portability reasons.

Basic Plot

Below is a basic example of how to load an XRF dataset from a single file and produce a plot showing the averaged spectrum. The input file is in tsv (tab separated value) format.

private static void example1(Path inputFile, Path plotFile) throws Exception {
	
	//Load Data
	DataSource source = new PlainText();
	source.read(Collections.singletonList(inputFile));
	DataSet dataset = new StandardDataSet(source);
	
	//Build Plot of Averaged Spectrum
	PlotData data = new PlotData();
	data.calibration = new EnergyCalibration(0f, 20.58f, dataset.getAnalysis().channelsPerScan());
	data.dataset = dataset;
	data.filtered = dataset.getAnalysis().averagePlot();
	
	//Render & Write Plot
	Plotter plot = new Plotter();
	plot.write(data, null, SurfaceType.RASTER, new Dimension(1000, 400), plotFile);
	
}

Peak Fittings

This example builds off of the previous one, and adds both peak fitting and data filtering. In this case, it fits Iron and Zinc, and applies a weighted average smoothing filter.

private static void example2(Path inputFile, Path plotFile) throws Exception {
	
	//Load Data
	DataSource source = new PlainText();
	source.read(Collections.singletonList(inputFile));
	DataSet dataset = new StandardDataSet(source);
	
	
	//Add Peak Fittings
	EnergyCalibration calibration = new EnergyCalibration(0f, 20.58f, dataset.getAnalysis().channelsPerScan());
	FittingSet fittings = new FittingSet();
	fittings.getFittingParameters().setEscapeType(EscapePeakType.SILICON);
	fittings.getFittingParameters().setCalibration(calibration);
	fittings.addTransitionSeries(PeakTable.SYSTEM.get(Element.Fe, TransitionSeriesType.K));
	fittings.addTransitionSeries(PeakTable.SYSTEM.get(Element.Zn, TransitionSeriesType.K));
	
	
	//Add Data Filters
	FilterSet filters = new FilterSet();
	Filter filter = new WeightedAverageNoiseFilter();
	filter.initialize();
	filters.add(filter);
	
	
	//Apply Fittings to Filtered Average Plot
	CurveFitter fitter = new OptimizingCurveFitter();
	FittingSolver solver = new GreedyFittingSolver();
	ReadOnlySpectrum filtered = filters.applyFilters(dataset.getAnalysis().averagePlot());
	FittingResultSet fittingResults = solver.solve(filtered, fittings, fitter);
	
	
	//Build Plot of Averaged Spectrum
	PlotData data = new PlotData();
	data.calibration = calibration;
	data.dataset = dataset;
	data.filtered = filtered;
	data.selectionResults = fittingResults;
	
	
	//Render & Write Plot
	Plotter plot = new Plotter();
	plot.write(data, null, SurfaceType.RASTER, new Dimension(1000, 400), plotFile);
	
}