void loadTransformation(String filename, ResultsTable res) {
try {
String line;
FileReader fr = new FileReader(filename);
BufferedReader br = new BufferedReader(fr);
if (!br.readLine().equals(" Z-Step Raw Width minus Heigh Calibration Width minus Height")) {
IJ.error("File does not seam to be an Astigmatism calibration file");
return;
}
// java.lang.String [] elements = new java.lang.String [3];
java.lang.String[] elements;
int counter = 1;
res.reset();
while ((line = br.readLine()) != null) {
IJ.showStatus("Loading element " + counter + "... sit back and relax.");
counter++;
line.trim();
elements = line.split("\t");
res.incrementCounter();
res.addValue("Z-Step", Double.parseDouble(elements[1]));
res.addValue("Raw Width minus Heigh", Double.parseDouble(elements[2]));
res.addValue("Calibration Width minus Height", Double.parseDouble(elements[3]));
}
fr.close();
} catch (FileNotFoundException e) {
IJ.error("File not found exception" + e);
return;
} catch (IOException e) {
IJ.error("IOException exception" + e);
return;
} catch (NumberFormatException e) {
IJ.error("Number format exception" + e);
return;
}
}
/**
* Saves statistics for one particle in a results table. This is a method subclasses may want to
* override.
*/
protected void saveResults(ImageStatistics stats, Roi roi) {
analyzer.saveResults(stats, roi);
if (recordStarts) {
rt.addValue("XStart", stats.xstart);
rt.addValue("YStart", stats.ystart);
}
if (addToManager) {
if (roiManager == null) {
if (Macro.getOptions() != null && Interpreter.isBatchMode())
roiManager = Interpreter.getBatchModeRoiManager();
if (roiManager == null) {
Frame frame = WindowManager.getFrame("ROI Manager");
if (frame == null) IJ.run("ROI Manager...");
frame = WindowManager.getFrame("ROI Manager");
if (frame == null || !(frame instanceof RoiManager)) {
addToManager = false;
return;
}
roiManager = (RoiManager) frame;
}
if (resetCounter) roiManager.runCommand("reset");
}
if (imp.getStackSize() > 1) roi.setPosition(imp.getCurrentSlice());
if (lineWidth != 1) roi.setStrokeWidth(lineWidth);
roiManager.add(imp, roi, rt.getCounter());
}
if (showResults) rt.addResults();
}
public void run() {
line.trim();
elements = line.split("\t");
if (elements.length < 14) return;
lock.lock();
res.incrementCounter();
res.addValue("Intensity", Double.parseDouble(elements[1]));
res.addValue("X (px)", Double.parseDouble(elements[2]));
res.addValue("Y (px)", Double.parseDouble(elements[3]));
res.addValue("X (nm)", Double.parseDouble(elements[4]));
res.addValue("Y (nm)", Double.parseDouble(elements[5]));
res.addValue("Z (nm)", Double.parseDouble(elements[6]));
res.addValue("Left-StdDev (px)", Double.parseDouble(elements[7]));
res.addValue("Right-StdDev (px)", Double.parseDouble(elements[8]));
res.addValue("Up-StdDev (px)", Double.parseDouble(elements[9]));
res.addValue("Down-StdDev (px)", Double.parseDouble(elements[10]));
res.addValue("X Symmetry (%)", Double.parseDouble(elements[11]));
res.addValue("Y Symmetry (%)", Double.parseDouble(elements[12]));
res.addValue("Width minus Height (px)", Double.parseDouble(elements[13]));
res.addValue("Frame Number", Double.parseDouble(elements[14]));
lock.unlock();
}
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;
}
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;
}
}