use of net.imglib2.RandomAccessibleInterval in project vcell by virtualcell.
the class ConstructTIRFGeometry method run.
@Override
public void run() {
// Calculate constant d in TIRF exponential decay function
// Angle of incidence in radians
theta = theta * 2 * Math.PI / 360;
// Refractive index of glass
final double n1 = 1.52;
// Refractive index of cytosol
final double n2 = 1.38;
final double d = lambda * Math.pow((Math.pow(n1, 2) * Math.pow(Math.sin(theta), 2) - Math.pow(n2, 2)), -0.5) / (4 * Math.PI);
System.out.println("d: " + d);
final double fluorPerMolecule = 250;
// Get frame of interest to define geometry
long maxX = data.dimension(0) - 1;
long maxY = data.dimension(1) - 1;
Interval interval = Intervals.createMinMax(0, 0, sliceIndex, maxX, maxY, sliceIndex);
RandomAccessibleInterval<T> croppedRAI = ops.transform().crop(data, interval, true);
// Subtract lowest pixel value
IterableInterval<T> dataII = Views.iterable(croppedRAI);
double min = ops.stats().min(dataII).getRealDouble();
Cursor<T> dataCursor = dataII.cursor();
while (dataCursor.hasNext()) {
double val = dataCursor.next().getRealDouble();
dataCursor.get().setReal(val - min);
}
// Perform Gaussian blur
RandomAccessibleInterval<T> blurredRAI = ops.filter().gauss(croppedRAI, 2);
IterableInterval<T> blurredII = Views.iterable(blurredRAI);
// Segment slice by threshold and fill holes
IterableInterval<BitType> thresholded = ops.threshold().huang(blurredII);
Img<BitType> thresholdedImg = ops.convert().bit(thresholded);
RandomAccessibleInterval<BitType> thresholdedRAI = ops.morphology().fillHoles(thresholdedImg);
// Get the largest region
RandomAccessibleInterval<LabelingType<ByteType>> labeling = ops.labeling().cca(thresholdedRAI, ConnectedComponents.StructuringElement.EIGHT_CONNECTED);
LabelRegions<ByteType> labelRegions = new LabelRegions<>(labeling);
Iterator<LabelRegion<ByteType>> iterator = labelRegions.iterator();
LabelRegion<ByteType> maxRegion = iterator.next();
while (iterator.hasNext()) {
LabelRegion<ByteType> currRegion = iterator.next();
if (currRegion.size() > maxRegion.size()) {
maxRegion = currRegion;
}
}
// Generate z index map
double iMax = ops.stats().max(dataII).getRealDouble();
Img<UnsignedShortType> dataImg = ops.convert().uint16(dataII);
Img<UnsignedShortType> zMap = ops.convert().uint16(ops.create().img(dataII));
LabelRegionCursor cursor = maxRegion.localizingCursor();
RandomAccess<UnsignedShortType> zMapRA = zMap.randomAccess();
RandomAccess<UnsignedShortType> dataRA = dataImg.randomAccess();
while (cursor.hasNext()) {
cursor.fwd();
zMapRA.setPosition(cursor);
dataRA.setPosition(cursor);
double val = dataRA.get().getRealDouble();
// Log of 0 is undefined
if (val < 1) {
val = 1;
}
int z = (int) Math.round(-d * Math.log(val / iMax) / zRes);
zMapRA.get().set(z);
}
System.out.println("6");
// Use map to construct 3D geometry
// Add 5 slices of padding on top
int maxZ = (int) ops.stats().max(zMap).getRealDouble() + 5;
long[] resultDimensions = { maxX + 1, maxY + 1, maxZ };
Img<BitType> result = new ArrayImgFactory<BitType>().create(resultDimensions, new BitType());
RandomAccess<BitType> resultRA = result.randomAccess();
System.out.println(maxZ);
cursor.reset();
while (cursor.hasNext()) {
cursor.fwd();
zMapRA.setPosition(cursor);
int zIndex = zMapRA.get().get();
int[] position = { cursor.getIntPosition(0), cursor.getIntPosition(1), zIndex };
while (position[2] < maxZ) {
resultRA.setPosition(position);
resultRA.get().set(true);
position[2]++;
}
}
output = datasetService.create(result);
CalibratedAxis[] axes = new DefaultLinearAxis[] { new DefaultLinearAxis(Axes.X), new DefaultLinearAxis(Axes.Y), new DefaultLinearAxis(Axes.Z) };
output.setAxes(axes);
System.out.println("Done constructing geometry");
}
use of net.imglib2.RandomAccessibleInterval in project vcell by virtualcell.
the class ImageStatsForPlotting method computeMean.
/**
* Computes the mean of each XY slice along the 3rd dimension
* TODO: Currently assumes only 3 dimensions, must handle time series of z stacks and multiple channels
* @param data
* @return Pair containing A) the 3rd dimension index, and B) the mean value of the XY slice
*/
private Pair<double[], double[]> computeMean(RandomAccessibleInterval<T> data, IterableInterval<BitType> mask) {
double[] indices = new double[(int) data.dimension(2)];
double[] means = new double[indices.length];
for (int z = 0; z < indices.length; z++) {
FinalInterval interval = Intervals.createMinMax(0, 0, z, data.dimension(0) - 1, data.dimension(1) - 1, z);
double mean = 0.0;
RandomAccessibleInterval<T> cropped = ops.transform().crop(data, interval);
if (mask == null) {
mean = ops.stats().mean(Views.iterable(cropped)).getRealDouble();
} else {
Cursor<BitType> maskCursor = mask.localizingCursor();
RandomAccess<T> dataRA = cropped.randomAccess();
RealSum sum = new RealSum();
int size = 0;
maskCursor.reset();
while (maskCursor.hasNext()) {
maskCursor.fwd();
if (maskCursor.get().get()) {
dataRA.setPosition(maskCursor);
sum.add(dataRA.get().getRealDouble());
size++;
}
}
mean = sum.getSum() / size;
}
indices[z] = z;
means[z] = mean;
}
return new ValuePair<double[], double[]>(indices, means);
}
use of net.imglib2.RandomAccessibleInterval in project vcell by virtualcell.
the class LargestRegionSlice method run.
@Override
public void run() {
int maxArea = 0;
int zOfMaxArea = 0;
for (int z = 0; z < data.dimension(2); z++) {
FinalInterval interval = Intervals.createMinMax(0, 0, z, data.dimension(0) - 1, data.dimension(1) - 1, z);
RandomAccessibleInterval<BitType> croppedRAI = ops.transform().crop(data, interval);
IterableInterval<BitType> croppedII = Views.iterable(croppedRAI);
Cursor<BitType> cursor = croppedII.cursor();
int area = 0;
while (cursor.hasNext()) {
if (cursor.next().get()) {
area++;
}
}
if (area > maxArea) {
maxArea = area;
zOfMaxArea = z;
}
}
FinalInterval interval = Intervals.createMinMax(0, 0, zOfMaxArea, data.dimension(0) - 1, data.dimension(1) - 1, zOfMaxArea);
output = ops.transform().crop(data, interval);
}
use of net.imglib2.RandomAccessibleInterval in project vcell by virtualcell.
the class VCellService method runSimulation.
private static Task<List<Dataset>, SimulationState> runSimulation(final SimulationServiceImpl client, final VCellModel vCellModel, final SimulationSpec simSpec, final List<Species> outputSpecies, final boolean shouldCreateIndividualDatasets, final OpService opService, final DatasetService datasetService) throws IOException, XMLStreamException {
final Task<List<Dataset>, SimulationState> task = new Task<List<Dataset>, SimulationState>() {
@Override
protected List<Dataset> doInBackground() throws Exception {
setSubtask(SimulationState.notRun);
final File sbmlSpatialFile = new File(vCellModel.getName() + ".xml");
new SBMLWriter().write(vCellModel.getSbmlDocument(), sbmlSpatialFile);
final SBMLModel model = new SBMLModel();
model.setFilepath(sbmlSpatialFile.getAbsolutePath());
final SimulationInfo simulationInfo = client.computeModel(model, simSpec);
try {
Thread.sleep(500);
} catch (final InterruptedException e) {
e.printStackTrace();
}
setSubtask(SimulationState.running);
while (client.getStatus(simulationInfo).getSimState() == SimulationState.running) {
System.out.println("waiting for simulation results");
try {
Thread.sleep(500);
} catch (final InterruptedException e) {
e.printStackTrace();
}
}
if (client.getStatus(simulationInfo).getSimState() == SimulationState.failed) {
setSubtask(SimulationState.failed);
return null;
}
final List<Dataset> results = new ArrayList<>();
final List<VariableInfo> vars = client.getVariableList(simulationInfo);
final List<Double> times = client.getTimePoints(simulationInfo);
for (final VariableInfo var : vars) {
if (outputSpecies.stream().anyMatch(species -> species.getId().equals(var.getVariableVtuName()))) {
// Get data for first time point and determine dimensions
List<Double> data = client.getData(simulationInfo, var, 0);
final int[] dimensions = getDimensions(data, times);
final Img<DoubleType> img = opService.create().img(dimensions);
final RandomAccess<DoubleType> imgRA = img.randomAccess();
// Copy data to the ImgLib2 Img
for (int t = 0; t < times.size(); t++) {
data = client.getData(simulationInfo, var, t);
for (int d = 0; d < data.size(); d++) {
imgRA.setPosition(new int[] { d, t });
imgRA.get().set(data.get(d));
}
}
// Create ImageJ Dataset and add to results
final Dataset dataset = datasetService.create(img);
dataset.setName(var.getVariableVtuName());
results.add(dataset);
}
}
// If desired, add all datasets with the same dimensions
if (!shouldCreateIndividualDatasets && !results.isEmpty()) {
// First, group datasets according to dimensions
final List<List<Dataset>> datasetGroups = new ArrayList<>();
final List<Dataset> initialGroup = new ArrayList<>();
initialGroup.add(results.get(0));
datasetGroups.add(initialGroup);
for (int i = 1; i < results.size(); i++) {
final Dataset result = results.get(i);
for (final List<Dataset> datasetGroup : datasetGroups) {
final Dataset[] datasets = new Dataset[] { datasetGroup.get(0), result };
if (Datasets.areSameSize(datasets, 0, 1)) {
datasetGroup.add(result);
} else {
final List<Dataset> newGroup = new ArrayList<>();
newGroup.add(result);
datasetGroups.add(newGroup);
}
}
}
final List<Dataset> summedResults = new ArrayList<>();
for (final List<Dataset> datasetGroup : datasetGroups) {
final Img<DoubleType> sum = opService.create().img(datasetGroup.get(0));
for (final Dataset dataset : datasetGroup) {
@SuppressWarnings("unchecked") final RandomAccessibleInterval<DoubleType> current = (Img<DoubleType>) dataset.getImgPlus().getImg();
opService.math().add(sum, sum, current);
}
final Dataset result = datasetService.create(sum);
result.setName(datasetGroup.stream().map(d -> d.getName()).collect(Collectors.joining("+")));
summedResults.add(result);
}
return summedResults;
}
setSubtask(SimulationState.done);
return results;
}
};
return task;
}
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