// default constructor
 SMLAnalysis() {
   ptable = ResultsTable.getResultsTable();
   ptable.setPrecision(5);
 }
  public void run(ImageProcessor ip) {
    String[] imageNames = getOpenImageNames();
    if (imageNames[0] == "None") {
      IJ.error("need at least 2 binary open images");
      return;
    }
    double previousMinOverlap = Prefs.get("BVTB.BinaryFeatureExtractor.minOverlap", 0);
    boolean previousCombine = Prefs.get("BVTB.BinaryFeatureExtractor.combine", false);

    GenericDialog gd = new GenericDialog("Binary Feature Extractor");
    gd.addChoice("Objects image", imageNames, imageNames[0]);
    gd.addChoice("Selector image", imageNames, imageNames[1]);
    gd.addNumericField("Object_overlap in % (0=off)", previousMinOverlap, 0, 9, "");
    gd.addCheckbox("Combine objects and selectors", previousCombine);
    gd.addCheckbox("Count output", true);
    gd.addCheckbox("Analysis tables", false);
    gd.showDialog();
    if (gd.wasCanceled()) {
      return;
    }
    String objectsImgTitle = gd.getNextChoice();
    String selectorsImgTitle = gd.getNextChoice();
    double minOverlap = gd.getNextNumber();
    boolean combineImages = gd.getNextBoolean();
    boolean showCountOutput = gd.getNextBoolean();
    boolean showAnalysis = gd.getNextBoolean();
    if (gd.invalidNumber() || minOverlap < 0 || minOverlap > 100) {
      IJ.error("invalid number");
      return;
    }
    Prefs.set("BVTB.BinaryFeatureExtractor.minOverlap", minOverlap);
    Prefs.set("BVTB.BinaryFeatureExtractor.combine", combineImages);

    if (objectsImgTitle.equals(selectorsImgTitle)) {
      IJ.error("images need to be different");
      return;
    }

    ImagePlus objectsImp = WindowManager.getImage(objectsImgTitle);
    ImageProcessor objectsIP = objectsImp.getProcessor();
    ImagePlus selectorsImp = WindowManager.getImage(selectorsImgTitle);
    ImageProcessor selectorsIP = selectorsImp.getProcessor();

    if (!objectsIP.isBinary() || !selectorsIP.isBinary()) {
      IJ.error("works with 8-bit binary images only");
      return;
    }

    if ((objectsImp.getWidth() != selectorsImp.getWidth())
        || objectsImp.getHeight() != selectorsImp.getHeight()) {
      IJ.error("images need to be of the same size");
      return;
    }

    // close any existing RoiManager before instantiating a new one for this analysis
    RoiManager oldRM = RoiManager.getInstance2();
    if (oldRM != null) {
      oldRM.close();
    }

    RoiManager objectsRM = new RoiManager(true);
    ResultsTable objectsRT = new ResultsTable();
    ParticleAnalyzer analyzeObjects =
        new ParticleAnalyzer(analyzerOptions, measurementFlags, objectsRT, 0.0, 999999999.9);
    analyzeObjects.setRoiManager(objectsRM);

    analyzeObjects.analyze(objectsImp);
    objectsRM.runCommand("Show None");
    int objectNumber = objectsRT.getCounter();

    Roi[] objectRoi = objectsRM.getRoisAsArray();

    ResultsTable measureSelectorsRT = new ResultsTable();
    Analyzer overlapAnalyzer = new Analyzer(selectorsImp, measurementFlags, measureSelectorsRT);

    ImagePlus outputImp =
        IJ.createImage("output", "8-bit black", objectsImp.getWidth(), objectsImp.getHeight(), 1);
    ImageProcessor outputIP = outputImp.getProcessor();

    double[] measuredOverlap = new double[objectNumber];

    outputIP.setValue(255.0);
    for (int o = 0; o < objectNumber; o++) {
      selectorsImp.killRoi();
      selectorsImp.setRoi(objectRoi[o]);
      overlapAnalyzer.measure();
      measuredOverlap[o] = measureSelectorsRT.getValue("%Area", o);
      if (minOverlap != 0.0 && measuredOverlap[o] >= minOverlap) {
        outputIP.fill(objectRoi[o]);
        finalCount++;
      } else if (minOverlap == 0.0 && measuredOverlap[o] > 0.0) {
        outputIP.fill(objectRoi[o]);
        finalCount++;
      }
    }
    // measureSelectorsRT.show("Objects");

    selectorsImp.killRoi();
    RoiManager selectorRM = new RoiManager(true);
    ResultsTable selectorRT = new ResultsTable();
    ParticleAnalyzer.setRoiManager(selectorRM);
    ParticleAnalyzer analyzeSelectors =
        new ParticleAnalyzer(analyzerOptions, measurementFlags, selectorRT, 0.0, 999999999.9);
    analyzeSelectors.analyze(selectorsImp);
    selectorRM.runCommand("Show None");
    int selectorNumber = selectorRT.getCounter();

    if (combineImages) {
      outputImp.updateAndDraw();
      Roi[] selectorRoi = selectorRM.getRoisAsArray();

      ResultsTable measureObjectsRT = new ResultsTable();
      Analyzer selectorAnalyzer = new Analyzer(outputImp, measurementFlags, measureObjectsRT);

      double[] selectorOverlap = new double[selectorNumber];
      outputIP.setValue(255.0);
      for (int s = 0; s < selectorNumber; s++) {
        outputImp.killRoi();
        outputImp.setRoi(selectorRoi[s]);
        selectorAnalyzer.measure();
        selectorOverlap[s] = measureObjectsRT.getValue("%Area", s);
        if (selectorOverlap[s] > 0.0d) {
          outputIP.fill(selectorRoi[s]);
        }
      }
      selectorRoi = null;
      selectorAnalyzer = null;
      measureObjectsRT = null;
    }
    // selectorRT.show("Selectors");
    outputImp.killRoi();
    String outputImageTitle = WindowManager.getUniqueName("Extracted_" + objectsImgTitle);
    outputImp.setTitle(outputImageTitle);
    outputImp.show();
    outputImp.changes = true;

    if (showCountOutput) {
      String[] openTextWindows = WindowManager.getNonImageTitles();
      boolean makeNewTable = true;
      for (int w = 0; w < openTextWindows.length; w++) {
        if (openTextWindows[w].equals("BFE_Results")) {
          makeNewTable = false;
        }
      }

      TextWindow existingCountTable = ResultsTable.getResultsWindow();
      if (makeNewTable) {
        countTable = new ResultsTable();
        countTable.setPrecision(0);
        countTable.setValue("Image", 0, outputImageTitle);
        countTable.setValue("Objects", 0, objectNumber);
        countTable.setValue("Selectors", 0, selectorNumber);
        countTable.setValue("Extracted", 0, finalCount);
        countTable.show("BFE_Results");
      } else {
        IJ.renameResults("BFE_Results", "Results");
        countTable = ResultsTable.getResultsTable();
        countTable.setPrecision(0);
        countTable.incrementCounter();
        countTable.addValue("Image", outputImageTitle);
        countTable.addValue("Objects", objectNumber);
        countTable.addValue("Selectors", selectorNumber);
        countTable.addValue("Extracted", finalCount);
        IJ.renameResults("Results", "BFE_Results");
        countTable.show("BFE_Results");
      }
    }

    if (showAnalysis) {
      ResultsTable extractedRT = new ResultsTable();
      ParticleAnalyzer analyzeExtracted =
          new ParticleAnalyzer(
              ParticleAnalyzer.CLEAR_WORKSHEET | ParticleAnalyzer.RECORD_STARTS,
              measurementFlags,
              extractedRT,
              0.0,
              999999999.9);
      analyzeExtracted.analyze(outputImp);
      objectsRT.show("Objects");
      selectorRT.show("Selectors");
      extractedRT.show("Extracted");
    } else {
      objectsRT = null;
      selectorRT = null;
    }

    objectsRM = null;
    measureSelectorsRT = null;
    analyzeObjects = null;
    overlapAnalyzer = null;
    objectRoi = null;
    selectorRM = null;

    objectsImp.killRoi();
    objectsImp.changes = false;
    selectorsImp.changes = false;
  }
Exemple #3
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  public int setup(String arg, ImagePlus imp) {
    // IJ.register(Average_Oversampled.class);

    if (IJ.versionLessThan("1.32c")) return DONE;

    if (this.pre) { // before finding means

      imp.unlock();
      this.imp = imp;
      this.nslices = imp.getNSlices();
      this.width = imp.getWidth();
      this.height = imp.getHeight();
      this.slicecols = new float[nslices][width];
      this.pre = false;
      return (DOES_ALL + DOES_STACKS + FINAL_PROCESSING);

    } else { // find SD after finding means of columns
      float sum; // sum of pixel values column
      float avg; // average pixel value of a column
      double devsum; // sum of deviations
      double devavg; // standard deviation
      double[] columns = new double[width]; // x-axis of plot
      double[] sdevs = new double[width]; // y-axis of plot

      for (int i = 0; i < width; i += 1) {
        sum = 0; // reset with each column
        avg = 0; // reset with each column
        devsum = 0; // reset with each column
        devavg = 0; // reset with each column
        columns[i] = i; // building x-axis

        for (int s = 0; s < nslices; s += 1) { // sum of column means
          sum = sum + slicecols[s][i];
        }
        avg = sum / nslices; // mean of one column across all slices

        for (int s = 0; s < nslices; s += 1) { // standard deviation
          devsum = devsum + Math.pow((slicecols[s][i] - avg), 2); // square diff
        }
        devavg = Math.sqrt(devsum / nslices);

        sdevs[i] = devavg; // building y-axis
      }

      Plot plot = new Plot("Average SD by Column", "Columns", "Standard Deviation", columns, sdevs);
      plot.show();

      // calculate CTN
      double ctn;
      double sdevssum = 0;
      for (double sd : sdevs) {
        sdevssum = sdevssum + sd;
      }
      ctn = sdevssum / width;

      // display CTN on results table
      ResultsTable rt = ResultsTable.getResultsTable();
      // rt.incrementCounter();
      rt.addValue("Column Temporal Noise", ctn);
      rt.show("Results");

      this.pre = false;

      return DONE;
    }
  }