use of ij.process.ImageProcessor in project GDSC-SMLM by aherbert.
the class PulseActivationAnalysis method displayComposite.
private void displayComposite(ImageProcessor[] images, String name) {
// We do not yet know the size
ImageStack stack = null;
for (int i = 0; i < images.length; i++) {
ImageProcessor ip = images[i];
if (stack == null)
stack = new ImageStack(ip.getWidth(), ip.getHeight());
ip.setColorModel(null);
stack.addSlice("C" + (i + 1), ip);
}
// Create a composite
ImagePlus imp = new ImagePlus(name, stack);
imp.setDimensions(images.length, 1, 1);
CompositeImage ci = new CompositeImage(imp, IJ.COMPOSITE);
// Make it easier to see
//ij.plugin.ContrastEnhancerce = new ij.plugin.ContrastEnhancer();
//double saturated = 0.35;
//ce.stretchHistogram(ci, saturated);
autoAdjust(ci, ci.getProcessor());
imp = WindowManager.getImage(name);
if (imp != null && imp.isComposite()) {
ci.setMode(imp.getCompositeMode());
imp.setImage(ci);
imp.getWindow().toFront();
} else {
ci.show();
imp = ci;
}
if (WindowManager.getWindow("Channels") == null) {
IJ.run("Channels Tool...");
Window w = WindowManager.getWindow("Channels");
if (w == null)
return;
Window w2 = imp.getWindow();
if (w2 == null)
return;
java.awt.Point p = w2.getLocation();
p.x += w2.getWidth();
w.setLocation(p);
}
}
use of ij.process.ImageProcessor in project GDSC-SMLM by aherbert.
the class FRCTest method canComputeMirrored.
@Test
public void canComputeMirrored() {
// Sample lines through an image to create a structure.
int size = 1024;
double[][] data = new double[size * 2][];
RandomGenerator r = new Well19937c(30051977);
for (int x = 0, y = 0, y2 = size, i = 0; x < size; x++, y++, y2--) {
data[i++] = new double[] { x + r.nextGaussian() * 5, y + r.nextGaussian() * 5 };
data[i++] = new double[] { x + r.nextGaussian() * 5, y2 + r.nextGaussian() * 5 };
}
// Create 2 images
Rectangle bounds = new Rectangle(0, 0, size, size);
IJImagePeakResults i1 = createImage(bounds);
IJImagePeakResults i2 = createImage(bounds);
int[] indices = Utils.newArray(data.length, 0, 1);
MathArrays.shuffle(indices, r);
for (int i : indices) {
IJImagePeakResults image = i1;
i1 = i2;
i2 = image;
image.add((float) data[i][0], (float) data[i][1], 1);
}
i1.end();
i2.end();
ImageProcessor ip1 = i1.getImagePlus().getProcessor();
ImageProcessor ip2 = i2.getImagePlus().getProcessor();
// Test
FRC frc = new FRC();
FloatProcessor[] fft1, fft2;
fft1 = frc.getComplexFFT(ip1);
fft2 = frc.getComplexFFT(ip2);
float[] dataA1 = (float[]) fft1[0].getPixels();
float[] dataB1 = (float[]) fft1[1].getPixels();
float[] dataA2 = (float[]) fft2[0].getPixels();
float[] dataB2 = (float[]) fft2[1].getPixels();
float[] numeratorE = new float[dataA1.length];
float[] absFFT1E = new float[dataA1.length];
float[] absFFT2E = new float[dataA1.length];
FRC.compute(numeratorE, absFFT1E, absFFT2E, dataA1, dataB1, dataA2, dataB2);
Assert.assertTrue("numeratorE", FRC.checkSymmetry(numeratorE, size));
Assert.assertTrue("absFFT1E", FRC.checkSymmetry(absFFT1E, size));
Assert.assertTrue("absFFT2E", FRC.checkSymmetry(absFFT2E, size));
float[] numeratorA = new float[dataA1.length];
float[] absFFT1A = new float[dataA1.length];
float[] absFFT2A = new float[dataA1.length];
FRC.computeMirrored(size, numeratorA, absFFT1A, absFFT2A, dataA1, dataB1, dataA2, dataB2);
//for (int y=0, i=0; y<size; y++)
// for (int x=0; x<size; x++, i++)
// {
// System.out.printf("[%d,%d = %d] %f ?= %f\n", x, y, i, numeratorE[i], numeratorA[i]);
// }
Assert.assertArrayEquals("numerator", numeratorE, numeratorA, 0);
Assert.assertArrayEquals("absFFT1", absFFT1E, absFFT1A, 0);
Assert.assertArrayEquals("absFFT2", absFFT2E, absFFT2A, 0);
FRC.computeMirroredFast(size, numeratorA, absFFT1A, absFFT2A, dataA1, dataB1, dataA2, dataB2);
// Check this.
for (int y = 1; y < size; y++) for (int x = 1, i = y * size + 1; x < size; x++, i++) {
Assert.assertEquals("numerator", numeratorE[i], numeratorA[i], 0);
Assert.assertEquals("absFFT1", absFFT1E[i], absFFT1A[i], 0);
Assert.assertEquals("absFFT2", absFFT2E[i], absFFT2A[i], 0);
}
}
use of ij.process.ImageProcessor in project GDSC-SMLM by aherbert.
the class FRCTest method computeMirroredIsFaster.
@Test
public void computeMirroredIsFaster() {
// Sample lines through an image to create a structure.
final int size = 2048;
double[][] data = new double[size * 2][];
RandomGenerator r = new Well19937c(30051977);
for (int x = 0, y = 0, y2 = size, i = 0; x < size; x++, y++, y2--) {
data[i++] = new double[] { x + r.nextGaussian() * 5, y + r.nextGaussian() * 5 };
data[i++] = new double[] { x + r.nextGaussian() * 5, y2 + r.nextGaussian() * 5 };
}
// Create 2 images
Rectangle bounds = new Rectangle(0, 0, size, size);
IJImagePeakResults i1 = createImage(bounds);
IJImagePeakResults i2 = createImage(bounds);
int[] indices = Utils.newArray(data.length, 0, 1);
MathArrays.shuffle(indices, r);
for (int i : indices) {
IJImagePeakResults image = i1;
i1 = i2;
i2 = image;
image.add((float) data[i][0], (float) data[i][1], 1);
}
i1.end();
i2.end();
ImageProcessor ip1 = i1.getImagePlus().getProcessor();
ImageProcessor ip2 = i2.getImagePlus().getProcessor();
// Test
FRC frc = new FRC();
FloatProcessor[] fft1, fft2;
fft1 = frc.getComplexFFT(ip1);
fft2 = frc.getComplexFFT(ip2);
final float[] dataA1 = (float[]) fft1[0].getPixels();
final float[] dataB1 = (float[]) fft1[1].getPixels();
final float[] dataA2 = (float[]) fft2[0].getPixels();
final float[] dataB2 = (float[]) fft2[1].getPixels();
final float[] numerator = new float[dataA1.length];
final float[] absFFT1 = new float[dataA1.length];
final float[] absFFT2 = new float[dataA1.length];
TimingService ts = new TimingService(10);
ts.execute(new MyTimingTask("compute") {
public Object run(Object data) {
FRC.compute(numerator, absFFT1, absFFT2, dataA1, dataB1, dataA2, dataB2);
return null;
}
});
ts.execute(new MyTimingTask("computeMirrored") {
public Object run(Object data) {
FRC.computeMirrored(size, numerator, absFFT1, absFFT2, dataA1, dataB1, dataA2, dataB2);
return null;
}
});
ts.execute(new MyTimingTask("computeMirroredFast") {
public Object run(Object data) {
FRC.computeMirroredFast(size, numerator, absFFT1, absFFT2, dataA1, dataB1, dataA2, dataB2);
return null;
}
});
ts.repeat(ts.getSize());
ts.report();
}
use of ij.process.ImageProcessor in project GDSC-SMLM by aherbert.
the class SpotInspector method run.
/*
* (non-Javadoc)
*
* @see ij.plugin.PlugIn#run(java.lang.String)
*/
public void run(String arg) {
SMLMUsageTracker.recordPlugin(this.getClass(), arg);
if (MemoryPeakResults.isMemoryEmpty()) {
IJ.error(TITLE, "No localisations in memory");
return;
}
if (!showDialog())
return;
// Load the results
results = ResultsManager.loadInputResults(inputOption, false);
if (results == null || results.size() == 0) {
IJ.error(TITLE, "No results could be loaded");
IJ.showStatus("");
return;
}
// Check if the original image is open
ImageSource source = results.getSource();
if (source == null) {
IJ.error(TITLE, "Unknown original source image");
return;
}
source = source.getOriginal();
if (!source.open()) {
IJ.error(TITLE, "Cannot open original source image: " + source.toString());
return;
}
final float stdDevMax = getStandardDeviation(results);
if (stdDevMax < 0) {
// TODO - Add dialog to get the initial peak width
IJ.error(TITLE, "Fitting configuration (for initial peak width) is not available");
return;
}
// Rank spots
rankedResults = new ArrayList<PeakResultRank>(results.size());
final double a = results.getNmPerPixel();
final double gain = results.getGain();
final boolean emCCD = results.isEMCCD();
for (PeakResult r : results.getResults()) {
float[] score = getScore(r, a, gain, emCCD, stdDevMax);
rankedResults.add(new PeakResultRank(r, score[0], score[1]));
}
Collections.sort(rankedResults);
// Prepare results table. Get bias if necessary
if (showCalibratedValues) {
// Get a bias if required
Calibration calibration = results.getCalibration();
if (calibration.getBias() == 0) {
ExtendedGenericDialog gd = new ExtendedGenericDialog(TITLE);
gd.addMessage("Calibrated results requires a camera bias");
gd.addNumericField("Camera_bias (ADUs)", calibration.getBias(), 2);
gd.showDialog();
if (!gd.wasCanceled()) {
calibration.setBias(Math.abs(gd.getNextNumber()));
}
}
}
IJTablePeakResults table = new IJTablePeakResults(false, results.getName(), true);
table.copySettings(results);
table.setTableTitle(TITLE);
table.setAddCounter(true);
table.setShowCalibratedValues(showCalibratedValues);
table.begin();
// Add a mouse listener to jump to the frame for the clicked line
textPanel = table.getResultsWindow().getTextPanel();
// We must ignore old instances of this class from the mouse listeners
id = ++currentId;
textPanel.addMouseListener(this);
// Add results to the table
int n = 0;
for (PeakResultRank rank : rankedResults) {
rank.rank = n++;
PeakResult r = rank.peakResult;
table.add(r.getFrame(), r.origX, r.origY, r.origValue, r.error, r.noise, r.params, r.paramsStdDev);
}
table.end();
if (plotScore || plotHistogram) {
// Get values for the plots
float[] xValues = null, yValues = null;
double yMin, yMax;
int spotNumber = 0;
xValues = new float[rankedResults.size()];
yValues = new float[xValues.length];
for (PeakResultRank rank : rankedResults) {
xValues[spotNumber] = spotNumber + 1;
yValues[spotNumber++] = recoverScore(rank.score);
}
// Set the min and max y-values using 1.5 x IQR
DescriptiveStatistics stats = new DescriptiveStatistics();
for (float v : yValues) stats.addValue(v);
if (removeOutliers) {
double lower = stats.getPercentile(25);
double upper = stats.getPercentile(75);
double iqr = upper - lower;
yMin = FastMath.max(lower - iqr, stats.getMin());
yMax = FastMath.min(upper + iqr, stats.getMax());
IJ.log(String.format("Data range: %f - %f. Plotting 1.5x IQR: %f - %f", stats.getMin(), stats.getMax(), yMin, yMax));
} else {
yMin = stats.getMin();
yMax = stats.getMax();
IJ.log(String.format("Data range: %f - %f", yMin, yMax));
}
plotScore(xValues, yValues, yMin, yMax);
plotHistogram(yValues, yMin, yMax);
}
// Extract spots into a stack
final int w = source.getWidth();
final int h = source.getHeight();
final int size = 2 * radius + 1;
ImageStack spots = new ImageStack(size, size, rankedResults.size());
// To assist the extraction of data from the image source, process them in time order to allow
// frame caching. Then set the appropriate slice in the result stack
Collections.sort(rankedResults, new Comparator<PeakResultRank>() {
public int compare(PeakResultRank o1, PeakResultRank o2) {
if (o1.peakResult.getFrame() < o2.peakResult.getFrame())
return -1;
if (o1.peakResult.getFrame() > o2.peakResult.getFrame())
return 1;
return 0;
}
});
for (PeakResultRank rank : rankedResults) {
PeakResult r = rank.peakResult;
// Extract image
// Note that the coordinates are relative to the middle of the pixel (0.5 offset)
// so do not round but simply convert to int
final int x = (int) (r.params[Gaussian2DFunction.X_POSITION]);
final int y = (int) (r.params[Gaussian2DFunction.Y_POSITION]);
// Extract a region but crop to the image bounds
int minX = x - radius;
int minY = y - radius;
int maxX = FastMath.min(x + radius + 1, w);
int maxY = FastMath.min(y + radius + 1, h);
int padX = 0, padY = 0;
if (minX < 0) {
padX = -minX;
minX = 0;
}
if (minY < 0) {
padY = -minY;
minY = 0;
}
int sizeX = maxX - minX;
int sizeY = maxY - minY;
float[] data = source.get(r.getFrame(), new Rectangle(minX, minY, sizeX, sizeY));
// Prevent errors with missing data
if (data == null)
data = new float[sizeX * sizeY];
ImageProcessor spotIp = new FloatProcessor(sizeX, sizeY, data, null);
// Pad if necessary, i.e. the crop is too small for the stack
if (padX > 0 || padY > 0 || sizeX < size || sizeY < size) {
ImageProcessor spotIp2 = spotIp.createProcessor(size, size);
spotIp2.insert(spotIp, padX, padY);
spotIp = spotIp2;
}
int slice = rank.rank + 1;
spots.setPixels(spotIp.getPixels(), slice);
spots.setSliceLabel(Utils.rounded(rank.originalScore), slice);
}
source.close();
ImagePlus imp = Utils.display(TITLE, spots);
imp.setRoi((PointRoi) null);
// Make bigger
for (int i = 10; i-- > 0; ) imp.getWindow().getCanvas().zoomIn(imp.getWidth() / 2, imp.getHeight() / 2);
}
use of ij.process.ImageProcessor in project GDSC-SMLM by aherbert.
the class SplitResults method splitResults.
private void splitResults(MemoryPeakResults results, ImageProcessor ip) {
IJ.showStatus("Splitting " + Utils.pleural(results.size(), "result"));
// Create an object mask
ObjectAnalyzer objectAnalyzer = new ObjectAnalyzer(ip, false);
final int maxx = ip.getWidth();
final int maxy = ip.getHeight();
final float scaleX = (float) results.getBounds().width / maxx;
final float scaleY = (float) results.getBounds().height / maxy;
// Create a results set for each object
final int maxObject = objectAnalyzer.getMaxObject();
MemoryPeakResults[] resultsSet = new MemoryPeakResults[maxObject + 1];
for (int object = 0; object <= maxObject; object++) {
MemoryPeakResults newResults = new MemoryPeakResults();
newResults.copySettings(results);
newResults.setName(results.getName() + " " + object);
resultsSet[object] = newResults;
}
final int[] mask = objectAnalyzer.getObjectMask();
if (showObjectMask) {
ImageProcessor objectIp = (maxObject <= 255) ? new ByteProcessor(maxx, maxy) : new ShortProcessor(maxx, maxy);
for (int i = 0; i < mask.length; i++) objectIp.set(i, mask[i]);
ImagePlus imp = Utils.display(objectMask + " Objects", objectIp);
imp.setDisplayRange(0, maxObject);
imp.updateAndDraw();
}
// Process the results mapping them to their objects
int i = 0;
final int size = results.size();
final int step = Utils.getProgressInterval(size);
for (PeakResult result : results.getResults()) {
if (++i % step == 0)
IJ.showProgress(i, size);
// Map to the mask objects
final int object;
int x = (int) (result.getXPosition() / scaleX);
int y = (int) (result.getYPosition() / scaleY);
if (x < 0 || x >= maxx || y < 0 || y >= maxy) {
object = 0;
} else {
final int index = y * maxx + x;
if (index < 0 || index >= mask.length)
object = 0;
else
object = mask[index];
}
resultsSet[object].add(result);
}
IJ.showProgress(1);
// Add the new results sets to memory
i = 0;
for (int object = (nonMaskDataset) ? 0 : 1; object <= maxObject; object++) {
if (!resultsSet[object].isEmpty()) {
MemoryPeakResults.addResults(resultsSet[object]);
i++;
}
}
IJ.showStatus("Split " + Utils.pleural(results.size(), "result") + " into " + Utils.pleural(i, "set"));
}
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