Java tutorial
package gdsc.smlm.ij.plugins; /*----------------------------------------------------------------------------- * GDSC SMLM Software * * Copyright (C) 2013 Alex Herbert * Genome Damage and Stability Centre * University of Sussex, UK * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 3 of the License, or * (at your option) any later version. *---------------------------------------------------------------------------*/ import gdsc.smlm.function.gaussian.Gaussian2DFunction; import gdsc.smlm.ij.plugins.ResultsManager.InputSource; import gdsc.smlm.ij.settings.FilterSettings; import gdsc.smlm.ij.settings.GlobalSettings; import gdsc.smlm.ij.settings.SettingsManager; import gdsc.smlm.model.MaskDistribution; import gdsc.smlm.results.MemoryPeakResults; import gdsc.smlm.results.PeakResult; import ij.IJ; import ij.ImagePlus; import ij.WindowManager; import ij.gui.GenericDialog; import ij.plugin.PlugIn; import ij.process.ByteProcessor; import java.util.ArrayList; import org.apache.commons.math3.util.FastMath; /** * Filters PeakFit results that are stored in memory using various fit criteria. */ public class FilterResults implements PlugIn { private static final String TITLE = "Filter Results"; private static String inputOption = ""; private MemoryPeakResults results; private FilterSettings filterSettings = new FilterSettings(); private double nmPerPixel, gain; private boolean emCCD; // Used to pass data from analyseResults() to checkLimits() private float minDrift = Float.MAX_VALUE; private float maxDrift = 0; private float minSignal = Float.MAX_VALUE; private float maxSignal = 0; private float minSNR = Float.MAX_VALUE; private float maxSNR = 0; private double minPrecision = Float.MAX_VALUE; private double maxPrecision = 0; private double averageWidth = 0; private float minWidth = Float.MAX_VALUE; private float maxWidth = 0; /* * (non-Javadoc) * * @see ij.plugin.PlugIn#run(java.lang.String) */ public void run(String arg) { if (MemoryPeakResults.countMemorySize() == 0) { IJ.error(TITLE, "There are no fitting results in memory"); return; } // Show a dialog allowing the results set to be filtered GenericDialog gd = new GenericDialog(TITLE); gd.addMessage("Select a dataset to filter"); ResultsManager.addInput(gd, inputOption, InputSource.MEMORY); gd.showDialog(); if (gd.wasCanceled()) return; inputOption = ResultsManager.getInputSource(gd); results = ResultsManager.loadInputResults(inputOption, false); if (results == null || results.size() == 0) { IJ.error(TITLE, "No results could be loaded"); IJ.showStatus(""); return; } analyseResults(); if (!showDialog()) return; filterResults(); } /** * Analyse the results and determine the range for each filter */ private void analyseResults() { IJ.showStatus("Analysing results ..."); nmPerPixel = results.getNmPerPixel(); gain = results.getGain(); emCCD = results.isEMCCD(); double maxVariance = maxPrecision * maxPrecision; double minVariance = minPrecision * minPrecision; int size = results.size(); int i = 0; for (PeakResult result : results.getResults()) { if (i % 64 == 0) IJ.showProgress(i, size); final float drift = getDrift(result); if (maxDrift < drift) maxDrift = drift; if (minDrift > drift) minDrift = drift; final float signal = result.getSignal(); if (maxSignal < signal) maxSignal = signal; if (minSignal > signal) minSignal = signal; final float snr = getSNR(result); if (maxSNR < snr) maxSNR = snr; if (minSNR > snr) minSNR = snr; // Use variance to avoid sqrt() final double variance = getVariance(result); if (maxVariance < variance) maxVariance = variance; if (minVariance > variance) minVariance = variance; final float width = getWidth(result); averageWidth += width; if (maxWidth < width) maxWidth = width; if (minWidth > width) minWidth = width; } averageWidth /= results.size(); maxPrecision = Math.sqrt(maxVariance); minPrecision = Math.sqrt(minVariance); IJ.showProgress(1); IJ.showStatus(""); } private float getDrift(PeakResult result) { float drift = FastMath.max(Math.abs(result.origX - result.params[Gaussian2DFunction.X_POSITION]), Math.abs(result.origY - result.params[Gaussian2DFunction.Y_POSITION])); return drift; } private float getSNR(PeakResult result) { if (result.noise <= 0) return 0; return result.getSignal() / result.noise; } private double getVariance(PeakResult result) { return PeakResult.getVariance(nmPerPixel, result.getSD() * nmPerPixel, result.getSignal() / gain, result.noise / gain, emCCD); } private float getWidth(PeakResult result) { // The X-width should be the largest (major axis) // Q. Should a filter be used for the Y-width too? return result.params[Gaussian2DFunction.X_SD]; } /** * Check that none of the filter values are outside the limits */ private void checkLimits() { if (filterSettings.maxDrift > maxDrift || filterSettings.maxDrift < minDrift) filterSettings.maxDrift = maxDrift; if (filterSettings.minSignal > maxSignal || filterSettings.minSignal < minSignal) filterSettings.minSignal = minSignal; if (filterSettings.minSNR > maxSNR || filterSettings.minSNR < minSNR) filterSettings.minSNR = minSNR; if (filterSettings.maxPrecision > maxPrecision || filterSettings.maxPrecision < minPrecision) filterSettings.maxPrecision = maxPrecision; if (filterSettings.minWidth > maxWidth || filterSettings.minWidth < minWidth) filterSettings.minWidth = minWidth; if (filterSettings.maxWidth > maxWidth || filterSettings.maxWidth < minWidth) filterSettings.maxWidth = maxWidth; if (filterSettings.minWidth > filterSettings.maxWidth) { float tmp = filterSettings.maxWidth; filterSettings.maxWidth = filterSettings.minWidth; filterSettings.minWidth = tmp; } } /** * Apply the filters to the data */ private void filterResults() { checkLimits(); MemoryPeakResults newResults = new MemoryPeakResults(); newResults.copySettings(results); newResults.setName(results.getName() + " Filtered"); // Initialise the mask ByteProcessor mask = getMask(filterSettings.maskTitle); MaskDistribution maskFilter = null; final float centreX = results.getBounds().width / 2.0f; final float centreY = results.getBounds().height / 2.0f; if (mask != null) { double scaleX = (double) results.getBounds().width / mask.getWidth(); double scaleY = (double) results.getBounds().height / mask.getHeight(); maskFilter = new MaskDistribution((byte[]) mask.getPixels(), mask.getWidth(), mask.getHeight(), 0, scaleX, scaleY); } int i = 0; final int size = results.size(); final double maxVariance = filterSettings.maxPrecision * filterSettings.maxPrecision; for (PeakResult result : results.getResults()) { if (i % 64 == 0) IJ.showProgress(i, size); if (getDrift(result) > filterSettings.maxDrift) continue; if (result.getSignal() < filterSettings.minSignal) continue; if (getSNR(result) < filterSettings.minSNR) continue; if (getVariance(result) > maxVariance) continue; final float width = getWidth(result); if (width < filterSettings.minWidth || width > filterSettings.maxWidth) continue; if (maskFilter != null) { // Check the coordinates are inside the mask double[] xy = new double[] { result.getXPosition() - centreX, result.getYPosition() - centreY }; if (!maskFilter.isWithinXY(xy)) continue; } // Passed all filters. Add to the results newResults.add(result); } IJ.showProgress(1); IJ.showStatus(newResults.size() + " Filtered localisations"); MemoryPeakResults.addResults(newResults); } private ByteProcessor getMask(String maskTitle) { ImagePlus imp = WindowManager.getImage(maskTitle); if (imp != null) { return (ByteProcessor) imp.getProcessor().convertToByte(false); } return null; } private boolean showDialog() { GenericDialog gd = new GenericDialog(TITLE); gd.addHelp(About.HELP_URL); GlobalSettings gs = SettingsManager.loadSettings(); filterSettings = gs.getFilterSettings(); checkLimits(); gd.addSlider("Max_drift", minDrift, maxDrift, filterSettings.maxDrift); gd.addSlider("Min_Signal", minSignal, maxSignal, filterSettings.minSignal); gd.addSlider("Min_SNR", minSNR, maxSNR, filterSettings.minSNR); gd.addSlider("Min_Precision", minPrecision, maxPrecision, filterSettings.maxPrecision); // TODO - If calibrated present the widths in nm gd.addMessage("Average Width = " + IJ.d2s(averageWidth, 3)); gd.addSlider("Min_Width", minWidth, maxWidth, filterSettings.minWidth); gd.addSlider("Max_Width", minWidth, maxWidth, filterSettings.maxWidth); // Get a list of potential mask images String[] items = getImageList(); gd.addChoice("Mask", items, filterSettings.maskTitle); gd.showDialog(); if (gd.wasCanceled()) return false; filterSettings.maxDrift = (float) gd.getNextNumber(); filterSettings.minSignal = (float) gd.getNextNumber(); filterSettings.minSNR = (float) gd.getNextNumber(); filterSettings.maxPrecision = (float) gd.getNextNumber(); filterSettings.minWidth = (float) gd.getNextNumber(); filterSettings.maxWidth = (float) gd.getNextNumber(); filterSettings.maskTitle = gd.getNextChoice(); return SettingsManager.saveSettings(gs); } /** * Build a list of all the image names. * * @return The list of images */ public static String[] getImageList() { ArrayList<String> newImageList = new ArrayList<String>(); newImageList.add("[None]"); for (int id : getIDList()) { ImagePlus imp = WindowManager.getImage(id); if (imp == null) continue; if (!imp.getProcessor().isBinary()) continue; newImageList.add(imp.getTitle()); } return newImageList.toArray(new String[0]); } public static int[] getIDList() { int[] list = WindowManager.getIDList(); return (list != null) ? list : new int[0]; } }