/
StatisticsOfLabelledPixels.java
860 lines (706 loc) · 41.6 KB
/
StatisticsOfLabelledPixels.java
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package net.haesleinhuepf.clij2.plugins;
import ij.ImagePlus;
import ij.measure.ResultsTable;
import net.haesleinhuepf.clij.clearcl.ClearCLBuffer;
import net.haesleinhuepf.clij.coremem.enums.NativeTypeEnum;
import net.haesleinhuepf.clij.macro.CLIJMacroPlugin;
import net.haesleinhuepf.clij.macro.CLIJOpenCLProcessor;
import net.haesleinhuepf.clij.macro.documentation.OffersDocumentation;
import net.haesleinhuepf.clij2.AbstractCLIJ2Plugin;
import net.haesleinhuepf.clij2.CLIJ2;
import net.haesleinhuepf.clij2.utilities.IsCategorized;
import org.scijava.plugin.Plugin;
import java.nio.FloatBuffer;
import java.util.ArrayList;
/**
* Author: @haesleinhuepf
* September 2019 in Prague
*/
@Plugin(type = CLIJMacroPlugin.class, name = "CLIJ2_statisticsOfLabelledPixels")
public class StatisticsOfLabelledPixels extends AbstractCLIJ2Plugin implements CLIJMacroPlugin, CLIJOpenCLProcessor, OffersDocumentation, IsCategorized {
@Override
public String getCategories() {
return "Measurement";
}
public enum STATISTICS_ENTRY {
IDENTIFIER(0),
BOUNDING_BOX_X(1),
BOUNDING_BOX_Y(2),
BOUNDING_BOX_Z(3),
BOUNDING_BOX_END_X(4),
BOUNDING_BOX_END_Y(5),
BOUNDING_BOX_END_Z(6),
BOUNDING_BOX_WIDTH(7),
BOUNDING_BOX_HEIGHT(8),
BOUNDING_BOX_DEPTH(9),
MINIMUM_INTENSITY(10),
MAXIMUM_INTENSITY(11),
MEAN_INTENSITY(12),
SUM_INTENSITY(13),
STANDARD_DEVIATION_INTENSITY(14),
PIXEL_COUNT(15),
SUM_INTENSITY_TIMES_X(16),
SUM_INTENSITY_TIMES_Y(17),
SUM_INTENSITY_TIMES_Z(18),
MASS_CENTER_X(19),
MASS_CENTER_Y(20),
MASS_CENTER_Z(21),
SUM_X(22),
SUM_Y(23),
SUM_Z(24),
CENTROID_X(25),
CENTROID_Y(26),
CENTROID_Z(27),
SUM_DISTANCE_TO_MASS_CENTER(28),
MEAN_DISTANCE_TO_MASS_CENTER(29),
MAX_DISTANCE_TO_MASS_CENTER(30),
MAX_MEAN_DISTANCE_TO_MASS_CENTER_RATIO(31),
SUM_DISTANCE_TO_CENTROID(32),
MEAN_DISTANCE_TO_CENTROID(33),
MAX_DISTANCE_TO_CENTROID(34),
MAX_MEAN_DISTANCE_TO_CENTROID_RATIO(35);
static final int NUMBER_OF_ENTRIES = 36;
public final int value;
STATISTICS_ENTRY(int value) {
this.value = value;
}
}
@Override
public boolean executeCL() {
ClearCLBuffer inputImage = (ClearCLBuffer) args[0];
ClearCLBuffer inputLabelMap = (ClearCLBuffer) args[1];
ResultsTable resultsTable = ResultsTable.getResultsTable();
getCLIJ2().statisticsOfLabelledPixels(inputImage, inputLabelMap, resultsTable);
resultsTable.show("Results");
return true;
}
public static ResultsTable statisticsOfLabelledPixels(CLIJ2 clij2, ClearCLBuffer inputImage, ClearCLBuffer inputLabelMap, ResultsTable resultsTable) {
double[][] statistics = statisticsOfLabelledPixels(clij2, inputImage, inputLabelMap);
return statisticsArrayToResultsTable(statistics, resultsTable);
}
static ResultsTable statisticsArrayToResultsTable(double[][] statistics, ResultsTable resultsTable) {
ArrayList<STATISTICS_ENTRY> entries = new ArrayList<STATISTICS_ENTRY>();
entries.add(STATISTICS_ENTRY.IDENTIFIER);
entries.add(STATISTICS_ENTRY.BOUNDING_BOX_X);
entries.add(STATISTICS_ENTRY.BOUNDING_BOX_Y);
entries.add(STATISTICS_ENTRY.BOUNDING_BOX_Z);
entries.add(STATISTICS_ENTRY.BOUNDING_BOX_END_X);
entries.add(STATISTICS_ENTRY.BOUNDING_BOX_END_Y);
entries.add(STATISTICS_ENTRY.BOUNDING_BOX_END_Z);
entries.add(STATISTICS_ENTRY.BOUNDING_BOX_WIDTH);
entries.add(STATISTICS_ENTRY.BOUNDING_BOX_HEIGHT);
entries.add(STATISTICS_ENTRY.BOUNDING_BOX_DEPTH);
entries.add(STATISTICS_ENTRY.MINIMUM_INTENSITY);
entries.add(STATISTICS_ENTRY.MAXIMUM_INTENSITY);
entries.add(STATISTICS_ENTRY.MEAN_INTENSITY);
entries.add(STATISTICS_ENTRY.SUM_INTENSITY);
entries.add(STATISTICS_ENTRY.STANDARD_DEVIATION_INTENSITY);
entries.add(STATISTICS_ENTRY.PIXEL_COUNT);
entries.add(STATISTICS_ENTRY.SUM_INTENSITY_TIMES_X);
entries.add(STATISTICS_ENTRY.SUM_INTENSITY_TIMES_Y);
entries.add(STATISTICS_ENTRY.SUM_INTENSITY_TIMES_Z);
entries.add(STATISTICS_ENTRY.MASS_CENTER_X);
entries.add(STATISTICS_ENTRY.MASS_CENTER_Y);
entries.add(STATISTICS_ENTRY.MASS_CENTER_Z);
entries.add(STATISTICS_ENTRY.SUM_X);
entries.add(STATISTICS_ENTRY.SUM_Y);
entries.add(STATISTICS_ENTRY.SUM_Z);
entries.add(STATISTICS_ENTRY.CENTROID_X);
entries.add(STATISTICS_ENTRY.CENTROID_Y);
entries.add(STATISTICS_ENTRY.CENTROID_Z);
entries.add(STATISTICS_ENTRY.SUM_DISTANCE_TO_MASS_CENTER);
entries.add(STATISTICS_ENTRY.MEAN_DISTANCE_TO_MASS_CENTER);
entries.add(STATISTICS_ENTRY.MAX_DISTANCE_TO_MASS_CENTER);
entries.add(STATISTICS_ENTRY.MAX_MEAN_DISTANCE_TO_MASS_CENTER_RATIO);
entries.add(STATISTICS_ENTRY.SUM_DISTANCE_TO_CENTROID);
entries.add(STATISTICS_ENTRY.MEAN_DISTANCE_TO_CENTROID);
entries.add(STATISTICS_ENTRY.MAX_DISTANCE_TO_CENTROID);
entries.add(STATISTICS_ENTRY.MAX_MEAN_DISTANCE_TO_CENTROID_RATIO);
for (int line = 0; line < statistics.length; line++) {
resultsTable.incrementCounter();
for (STATISTICS_ENTRY entry : entries) {
resultsTable.addValue(entry.toString(), statistics[line][entry.value]);
}
}
return resultsTable;
}
public static double[][] statisticsOfLabelledPixels(CLIJ2 clij2, ClearCLBuffer inputImage, ClearCLBuffer inputLabelMap) {
int numberOfLabels = (int) clij2.maximumOfAllPixels(inputLabelMap);
return statisticsOfLabelledPixels(clij2, inputImage, inputLabelMap, 1, numberOfLabels);
}
public static double[] statisticsOfLabelledPixels(CLIJ2 clij2, ClearCLBuffer inputImage, ClearCLBuffer inputLabelMap, Integer labelIndex) {
return statisticsOfLabelledPixels(clij2, inputImage, inputLabelMap, labelIndex, labelIndex)[0];
}
private static class Statistician implements Runnable{
private double[][] statistics;
private final ClearCLBuffer inputImage;
private final ClearCLBuffer inputLabelMap;
private final int startLabelIndex;
private final int endLabelIndex;
private final int zPlane;
private final CLIJ2 clij2;
float[] pixels;
float[] labels;
Statistician(double[][] statistics, CLIJ2 clij2, ClearCLBuffer inputImage, ClearCLBuffer inputLabelMap, int startLabelIndex, int endLabelIndex, int zPlane) {
this.statistics = statistics;
this.inputImage = inputImage;
this.inputLabelMap = inputLabelMap;
this.startLabelIndex = startLabelIndex;
this.endLabelIndex = endLabelIndex;
this.zPlane = zPlane;
this.clij2 = clij2;
}
@Override
public void run() {
boolean[] initializedFlags = new boolean[statistics.length];
//ImagePlus imp = null;
//ImagePlus lab = null;
synchronized (clij2) {
ClearCLBuffer image = clij2.create(inputImage.getWidth(), inputImage.getHeight());
clij2.copySlice(inputImage, image, zPlane);
//inputImage;
ClearCLBuffer labelMap = null;
//inputLabelMap;
//if (inputImage.getNativeType() != NativeTypeEnum.Float) {
// image = clij2.create(inputImage.getDimensions(), NativeTypeEnum.Float);
// clij2.copy(inputImage, image);
//}
if (inputLabelMap != null) {
labelMap = clij2.create(inputLabelMap.getWidth(), inputLabelMap.getHeight());
clij2.copySlice(inputLabelMap, labelMap, zPlane);
//if (inputLabelMap.getNativeType() != NativeTypeEnum.Float) {
// labelMap = clij2.create(inputLabelMap.getDimensions(), NativeTypeEnum.Float);
// clij2.copy(inputLabelMap, labelMap);
//}
}
pixels = new float[(int) (image.getWidth() * image.getHeight())];
image.writeTo(FloatBuffer.wrap(pixels), true);
image.close();
if (labelMap != null) {
labels = new float[(int) (labelMap.getWidth() * labelMap.getHeight())];
labelMap.writeTo(FloatBuffer.wrap(labels), true);
// };
//imp = clij2.pull(image);
//lab = inputLabelMap != null ? clij2.pull(labelMap) : null;
// if (labelMap != null) {
labelMap.close();
}
}
int width = (int) inputImage.getWidth();
//for (int z = 0; z < imp.getNSlices(); z++) {
// imp.setZ(z + 1);
// if (lab != null) {
// lab.setZ(z + 1);
// }
//pixels = (float[]) imp.getProcessor().getPixels();
//labels = lab!=null?(float[]) lab.getProcessor().getPixels():null;
int x = 0;
int y = 0;
for (int i = 0; i < pixels.length; i++) {
int index = labels!=null?(int) labels[i]:0;
if (index >= startLabelIndex) {
int targetIndex = index - startLabelIndex;
double value = pixels[i];
boolean initialized = initializedFlags[targetIndex];
if (x < statistics[targetIndex][STATISTICS_ENTRY.BOUNDING_BOX_X.value] || !initialized) {
statistics[targetIndex][STATISTICS_ENTRY.BOUNDING_BOX_X.value] = x;
}
if (y < statistics[targetIndex][STATISTICS_ENTRY.BOUNDING_BOX_Y.value] || !initialized) {
statistics[targetIndex][STATISTICS_ENTRY.BOUNDING_BOX_Y.value] = y;
}
if (zPlane < statistics[targetIndex][STATISTICS_ENTRY.BOUNDING_BOX_Z.value] || !initialized) {
statistics[targetIndex][STATISTICS_ENTRY.BOUNDING_BOX_Z.value] = zPlane;
}
if (x > statistics[targetIndex][STATISTICS_ENTRY.BOUNDING_BOX_END_X.value] || !initialized) {
statistics[targetIndex][STATISTICS_ENTRY.BOUNDING_BOX_END_X.value] = x;
}
if (y > statistics[targetIndex][STATISTICS_ENTRY.BOUNDING_BOX_END_Y.value] || !initialized) {
statistics[targetIndex][STATISTICS_ENTRY.BOUNDING_BOX_END_Y.value] = y;
}
if (zPlane > statistics[targetIndex][STATISTICS_ENTRY.BOUNDING_BOX_END_Z.value] || !initialized) {
statistics[targetIndex][STATISTICS_ENTRY.BOUNDING_BOX_END_Z.value] = zPlane;
}
if (value > statistics[targetIndex][STATISTICS_ENTRY.MAXIMUM_INTENSITY.value] || !initialized) {
statistics[targetIndex][STATISTICS_ENTRY.MAXIMUM_INTENSITY.value] = value;
}
if (value < statistics[targetIndex][STATISTICS_ENTRY.MINIMUM_INTENSITY.value] || !initialized) {
statistics[targetIndex][STATISTICS_ENTRY.MINIMUM_INTENSITY.value] = value;
}
statistics[targetIndex][STATISTICS_ENTRY.SUM_INTENSITY.value] += value;
statistics[targetIndex][STATISTICS_ENTRY.SUM_INTENSITY_TIMES_X.value] += value * x;
statistics[targetIndex][STATISTICS_ENTRY.SUM_INTENSITY_TIMES_Y.value] += value * y;
statistics[targetIndex][STATISTICS_ENTRY.SUM_INTENSITY_TIMES_Z.value] += value * zPlane;
statistics[targetIndex][STATISTICS_ENTRY.SUM_X.value] += x;
statistics[targetIndex][STATISTICS_ENTRY.SUM_Y.value] += y;
statistics[targetIndex][STATISTICS_ENTRY.SUM_Z.value] += zPlane;
statistics[targetIndex][STATISTICS_ENTRY.PIXEL_COUNT.value] += 1;
initializedFlags[targetIndex] = true;
}
x++;
if (x >= width) {
x = 0;
y++;
}
}
//}
}
}
private static class SecondOrderStatistician implements Runnable {
private final float[] pixels;
private final float[] labels;
private final int startLabelIndex;
private final double[][] statistics;
private final double[] squaredDifferencesFromMean;
private final int width;
private final int z;
SecondOrderStatistician(float[] pixels, float[] labels, int startLabelIndex, int width, int z, double[][] statistics, double[] squaredDifferencesFromMean) {
this.pixels = pixels;
this.labels = labels;
this.startLabelIndex = startLabelIndex;
this.statistics = statistics;
this.squaredDifferencesFromMean = squaredDifferencesFromMean;
this.width = width;
this.z = z;
}
@Override
public void run() {
//for (int z = 0; z < imp.getNSlices(); z++) {
// imp.setZ(z + 1);
//if(lab != null) {
// lab.setZ(z + 1);
//}
//float[] pixels = (float[]) imp.getProcessor().getPixels();
//float[] labels = lab!=null?(float[]) lab.getProcessor().getPixels():null;
int x = 0;
int y = 0;
for (int i = 0; i < pixels.length; i ++) {
int index = labels!=null?(int) labels[i]:0;
if (index >= startLabelIndex) {
int targetIndex = index - startLabelIndex;
double value = pixels[i];
squaredDifferencesFromMean[targetIndex] += Math.pow(value - statistics[targetIndex][STATISTICS_ENTRY.MEAN_INTENSITY.value], 2);
double mass_center_x = statistics[targetIndex][STATISTICS_ENTRY.MASS_CENTER_X.value];
double mass_center_y = statistics[targetIndex][STATISTICS_ENTRY.MASS_CENTER_Y.value];
double mass_center_z = statistics[targetIndex][STATISTICS_ENTRY.MASS_CENTER_Z.value];
double distance = Math.sqrt(
Math.pow(mass_center_x - x, 2) +
Math.pow(mass_center_y - y, 2) +
Math.pow(mass_center_z - z, 2)
);
if (statistics[targetIndex][STATISTICS_ENTRY.MAX_DISTANCE_TO_MASS_CENTER.value] < distance) {
statistics[targetIndex][STATISTICS_ENTRY.MAX_DISTANCE_TO_MASS_CENTER.value] = distance;
}
statistics[targetIndex][STATISTICS_ENTRY.SUM_DISTANCE_TO_MASS_CENTER.value] += distance;
double center_x = statistics[targetIndex][STATISTICS_ENTRY.CENTROID_X.value];
double center_y = statistics[targetIndex][STATISTICS_ENTRY.CENTROID_Y.value];
double center_z = statistics[targetIndex][STATISTICS_ENTRY.CENTROID_Z.value];
distance = Math.sqrt(
Math.pow(center_x - x, 2) +
Math.pow(center_y - y, 2) +
Math.pow(center_z - z, 2)
);
if (statistics[targetIndex][STATISTICS_ENTRY.MAX_DISTANCE_TO_CENTROID.value] < distance) {
statistics[targetIndex][STATISTICS_ENTRY.MAX_DISTANCE_TO_CENTROID.value] = distance;
}
statistics[targetIndex][STATISTICS_ENTRY.SUM_DISTANCE_TO_CENTROID.value] += distance;
}
x++;
if (x >= width) {
x = 0;
y++;
}
}
// }
}
}
// as it's super slow on the GPU, let's do it on the CPU
public static double[][] statisticsOfLabelledPixels(CLIJ2 clij2, ClearCLBuffer inputImage, ClearCLBuffer inputLabelMap, Integer startLabelIndex, Integer endLabelIndex) {
int num_threads = (int) inputImage.getDepth();
STATISTICS_ENTRY[] indices_to_min_collect = {
STATISTICS_ENTRY.BOUNDING_BOX_X,
STATISTICS_ENTRY.BOUNDING_BOX_Y,
STATISTICS_ENTRY.BOUNDING_BOX_Z,
STATISTICS_ENTRY.MINIMUM_INTENSITY
};
STATISTICS_ENTRY[] indices_to_max_collect = {
STATISTICS_ENTRY.BOUNDING_BOX_END_X,
STATISTICS_ENTRY.BOUNDING_BOX_END_Y,
STATISTICS_ENTRY.BOUNDING_BOX_END_Z,
STATISTICS_ENTRY.MAXIMUM_INTENSITY
};
STATISTICS_ENTRY[] indices_to_sum_collect = {
STATISTICS_ENTRY.SUM_INTENSITY,
STATISTICS_ENTRY.PIXEL_COUNT,
STATISTICS_ENTRY.SUM_INTENSITY_TIMES_X,
STATISTICS_ENTRY.SUM_INTENSITY_TIMES_Y,
STATISTICS_ENTRY.SUM_INTENSITY_TIMES_Z,
STATISTICS_ENTRY.SUM_X,
STATISTICS_ENTRY.SUM_Y,
STATISTICS_ENTRY.SUM_Z
};
double[][][] statistics = new double[num_threads + 1][endLabelIndex - startLabelIndex + 1][STATISTICS_ENTRY.NUMBER_OF_ENTRIES];
for (int t = 0; t < num_threads; t++) {
for (int j = 0; j < statistics[0].length; j++) {
for (STATISTICS_ENTRY entry : indices_to_max_collect) {
statistics[t + 1][j][entry.value] = -Double.MAX_VALUE;
}
for (STATISTICS_ENTRY entry : indices_to_min_collect) {
statistics[t + 1][j][entry.value] = Double.MAX_VALUE;
}
}
}
Thread[] threads = new Thread[num_threads];
Statistician[] statisticians = new Statistician[num_threads];
for (int i = 0; i < num_threads; i++) {
statisticians[i] = new Statistician(statistics[i + 1], clij2, inputImage, inputLabelMap, startLabelIndex, endLabelIndex, i);
threads[i] = new Thread(statisticians[i]);
threads[i].start();
}
for (int i = 0; i < num_threads; i++) {
try {
threads[i].join();
} catch (InterruptedException e) {
e.printStackTrace();
}
}
for (int t = 0; t < num_threads; t++) {
for (int j = 0; j < statistics[0].length; j++) {
for (STATISTICS_ENTRY entry : indices_to_max_collect) {
if (t == 0) {
statistics[0][j][entry.value] = statistics[t + 1][j][entry.value];
} else {
statistics[0][j][entry.value] = Math.max(statistics[0][j][entry.value], statistics[t + 1][j][entry.value]);
}
}
for (STATISTICS_ENTRY entry : indices_to_min_collect) {
if (t == 0) {
statistics[0][j][entry.value] = statistics[t + 1][j][entry.value];
} else {
statistics[0][j][entry.value] = Math.min(statistics[0][j][entry.value], statistics[t + 1][j][entry.value]);
}
}
for (STATISTICS_ENTRY entry : indices_to_sum_collect) {
statistics[0][j][entry.value] += statistics[t + 1][j][entry.value];
}
}
}
for (int j = 0; j < statistics[0].length; j++) {
statistics[0][j][STATISTICS_ENTRY.MEAN_INTENSITY.value] =
statistics[0][j][STATISTICS_ENTRY.SUM_INTENSITY.value] /
statistics[0][j][STATISTICS_ENTRY.PIXEL_COUNT.value];
statistics[0][j][STATISTICS_ENTRY.BOUNDING_BOX_WIDTH.value] =
statistics[0][j][STATISTICS_ENTRY.BOUNDING_BOX_END_X.value] -
statistics[0][j][STATISTICS_ENTRY.BOUNDING_BOX_X.value] + 1;
statistics[0][j][STATISTICS_ENTRY.BOUNDING_BOX_HEIGHT.value] =
statistics[0][j][STATISTICS_ENTRY.BOUNDING_BOX_END_Y.value] -
statistics[0][j][STATISTICS_ENTRY.BOUNDING_BOX_Y.value] + 1;
statistics[0][j][STATISTICS_ENTRY.BOUNDING_BOX_DEPTH.value] =
statistics[0][j][STATISTICS_ENTRY.BOUNDING_BOX_END_Z.value] -
statistics[0][j][STATISTICS_ENTRY.BOUNDING_BOX_Z.value] + 1;
statistics[0][j][STATISTICS_ENTRY.IDENTIFIER.value] = j + startLabelIndex;
statistics[0][j][STATISTICS_ENTRY.MASS_CENTER_X.value] =
statistics[0][j][STATISTICS_ENTRY.SUM_INTENSITY_TIMES_X.value] /
statistics[0][j][STATISTICS_ENTRY.SUM_INTENSITY.value];
statistics[0][j][STATISTICS_ENTRY.MASS_CENTER_Y.value] =
statistics[0][j][STATISTICS_ENTRY.SUM_INTENSITY_TIMES_Y.value] /
statistics[0][j][STATISTICS_ENTRY.SUM_INTENSITY.value];
statistics[0][j][STATISTICS_ENTRY.MASS_CENTER_Z.value] =
statistics[0][j][STATISTICS_ENTRY.SUM_INTENSITY_TIMES_Z.value] /
statistics[0][j][STATISTICS_ENTRY.SUM_INTENSITY.value];
statistics[0][j][STATISTICS_ENTRY.CENTROID_X.value] =
statistics[0][j][STATISTICS_ENTRY.SUM_X.value] /
statistics[0][j][STATISTICS_ENTRY.PIXEL_COUNT.value];
statistics[0][j][STATISTICS_ENTRY.CENTROID_Y.value] =
statistics[0][j][STATISTICS_ENTRY.SUM_Y.value] /
statistics[0][j][STATISTICS_ENTRY.PIXEL_COUNT.value];
statistics[0][j][STATISTICS_ENTRY.CENTROID_Z.value] =
statistics[0][j][STATISTICS_ENTRY.SUM_Z.value] /
statistics[0][j][STATISTICS_ENTRY.PIXEL_COUNT.value];
}
for (int t = 0; t < num_threads; t++) {
for (int j = 0; j < statistics[0].length; j++) {
statistics[t + 1][j][STATISTICS_ENTRY.MEAN_INTENSITY.value] = statistics[0][j][STATISTICS_ENTRY.MEAN_INTENSITY.value];
statistics[t + 1][j][STATISTICS_ENTRY.MASS_CENTER_X.value] = statistics[0][j][STATISTICS_ENTRY.MASS_CENTER_X.value];
statistics[t + 1][j][STATISTICS_ENTRY.MASS_CENTER_Y.value] = statistics[0][j][STATISTICS_ENTRY.MASS_CENTER_Y.value];
statistics[t + 1][j][STATISTICS_ENTRY.MASS_CENTER_Z.value] = statistics[0][j][STATISTICS_ENTRY.MASS_CENTER_Z.value];
statistics[t + 1][j][STATISTICS_ENTRY.CENTROID_X.value] = statistics[0][j][STATISTICS_ENTRY.CENTROID_X.value];
statistics[t + 1][j][STATISTICS_ENTRY.CENTROID_Y.value] = statistics[0][j][STATISTICS_ENTRY.CENTROID_Y.value];
statistics[t + 1][j][STATISTICS_ENTRY.CENTROID_Z.value] = statistics[0][j][STATISTICS_ENTRY.CENTROID_Z.value];
statistics[t + 1][j][STATISTICS_ENTRY.MAX_DISTANCE_TO_MASS_CENTER.value] = 0;
statistics[t + 1][j][STATISTICS_ENTRY.MAX_DISTANCE_TO_CENTROID.value] = 0;
if (t == 0) {
statistics[0][j][STATISTICS_ENTRY.MAX_DISTANCE_TO_MASS_CENTER.value] = 0;
statistics[0][j][STATISTICS_ENTRY.MAX_DISTANCE_TO_CENTROID.value] = 0;
}
}
}
double[][] squaredDifferencesFromMean = new double[num_threads + 1][statistics[0].length];
Thread[] followUpThreads = new Thread[num_threads];
for (int t = 0; t < num_threads; t++) {
followUpThreads[t] = new Thread(new SecondOrderStatistician(
statisticians[t].pixels,
statisticians[t].labels,
startLabelIndex,
(int) inputImage.getWidth(),
t, // t corresponds to z-position
statistics[t + 1],
squaredDifferencesFromMean[t + 1]
));
followUpThreads[t].start();
}
for (int t = 0; t < num_threads; t++) {
try {
followUpThreads[t].join();
} catch (InterruptedException e) {
e.printStackTrace();
}
}
// if (inputImage != image) {
// image.close();
// }
// if (inputLabelMap != labelMap && labelMap != null) {
// labelMap.close();
// }
for (int t = 0; t < num_threads; t++) {
for (int j = 0; j < statistics[0].length; j++) {
squaredDifferencesFromMean[0][j] += squaredDifferencesFromMean[t+1][j];
statistics[0][j][STATISTICS_ENTRY.MAX_DISTANCE_TO_MASS_CENTER.value] = Math.max(statistics[0][j][STATISTICS_ENTRY.MAX_DISTANCE_TO_MASS_CENTER.value], statistics[t + 1][j][STATISTICS_ENTRY.MAX_DISTANCE_TO_MASS_CENTER.value]);
statistics[0][j][STATISTICS_ENTRY.MAX_DISTANCE_TO_CENTROID.value] = Math.max(statistics[0][j][STATISTICS_ENTRY.MAX_DISTANCE_TO_CENTROID.value], statistics[t + 1][j][STATISTICS_ENTRY.MAX_DISTANCE_TO_CENTROID.value]);
statistics[0][j][STATISTICS_ENTRY.SUM_DISTANCE_TO_MASS_CENTER.value] = statistics[0][j][STATISTICS_ENTRY.SUM_DISTANCE_TO_MASS_CENTER.value] + statistics[t + 1][j][STATISTICS_ENTRY.SUM_DISTANCE_TO_MASS_CENTER.value];
statistics[0][j][STATISTICS_ENTRY.SUM_DISTANCE_TO_CENTROID.value] = statistics[0][j][STATISTICS_ENTRY.SUM_DISTANCE_TO_CENTROID.value] + statistics[t + 1][j][STATISTICS_ENTRY.SUM_DISTANCE_TO_CENTROID.value];
}
}
for (int j = 0; j < statistics[0].length; j++) {
statistics[0][j][STATISTICS_ENTRY.STANDARD_DEVIATION_INTENSITY.value] =
Math.sqrt(squaredDifferencesFromMean[0][j] /
statistics[0][j][STATISTICS_ENTRY.PIXEL_COUNT.value]);
statistics[0][j][STATISTICS_ENTRY.MEAN_DISTANCE_TO_MASS_CENTER.value] = statistics[0][j][STATISTICS_ENTRY.SUM_DISTANCE_TO_MASS_CENTER.value] / statistics[0][j][STATISTICS_ENTRY.PIXEL_COUNT.value];
statistics[0][j][STATISTICS_ENTRY.MEAN_DISTANCE_TO_CENTROID.value] = statistics[0][j][STATISTICS_ENTRY.SUM_DISTANCE_TO_CENTROID.value] / statistics[0][j][STATISTICS_ENTRY.PIXEL_COUNT.value];
statistics[0][j][STATISTICS_ENTRY.MAX_MEAN_DISTANCE_TO_MASS_CENTER_RATIO.value] = statistics[0][j][STATISTICS_ENTRY.MAX_DISTANCE_TO_MASS_CENTER.value] / statistics[0][j][STATISTICS_ENTRY.MEAN_DISTANCE_TO_MASS_CENTER.value];
statistics[0][j][STATISTICS_ENTRY.MAX_MEAN_DISTANCE_TO_CENTROID_RATIO.value] = statistics[0][j][STATISTICS_ENTRY.MAX_DISTANCE_TO_CENTROID.value] / statistics[0][j][STATISTICS_ENTRY.MEAN_DISTANCE_TO_CENTROID.value];
}
return statistics[0];
}
public static double[][] statisticsOfLabelledPixels_single_threaded(CLIJ2 clij2, ClearCLBuffer inputImage, ClearCLBuffer inputLabelMap, Integer startLabelIndex, Integer endLabelIndex) {
double[][] statistics = new double[endLabelIndex - startLabelIndex + 1][STATISTICS_ENTRY.NUMBER_OF_ENTRIES];
boolean[] initializedFlags = new boolean[statistics.length];
ClearCLBuffer image = inputImage;
ClearCLBuffer labelMap = inputLabelMap;
if (inputImage.getNativeType() != NativeTypeEnum.Float) {
image = clij2.create(inputImage.getDimensions(), NativeTypeEnum.Float);
clij2.copy(inputImage, image);
}
if (inputLabelMap != null) {
if (inputLabelMap.getNativeType() != NativeTypeEnum.Float) {
labelMap = clij2.create(inputLabelMap.getDimensions(), NativeTypeEnum.Float);
clij2.copy(inputLabelMap, labelMap);
}
}
ImagePlus imp = clij2.pull(image);
ImagePlus lab = inputLabelMap!=null?clij2.pull(labelMap):null;
int width = imp.getWidth();
for (int z = 0; z < imp.getNSlices(); z++) {
imp.setZ(z + 1);
if (lab != null) {
lab.setZ(z + 1);
}
float[] pixels = (float[]) imp.getProcessor().getPixels();
float[] labels = lab!=null?(float[]) lab.getProcessor().getPixels():null;
int x = 0;
int y = 0;
for (int i = 0; i < pixels.length; i++) {
int index = labels!=null?(int) labels[i]:0;
if (index >= startLabelIndex) {
int targetIndex = index - startLabelIndex;
double value = pixels[i];
boolean initialized = initializedFlags[targetIndex];
if (x < statistics[targetIndex][STATISTICS_ENTRY.BOUNDING_BOX_X.value] || !initialized) {
statistics[targetIndex][STATISTICS_ENTRY.BOUNDING_BOX_X.value] = x;
}
if (y < statistics[targetIndex][STATISTICS_ENTRY.BOUNDING_BOX_Y.value] || !initialized) {
statistics[targetIndex][STATISTICS_ENTRY.BOUNDING_BOX_Y.value] = y;
}
if (z < statistics[targetIndex][STATISTICS_ENTRY.BOUNDING_BOX_Z.value] || !initialized) {
statistics[targetIndex][STATISTICS_ENTRY.BOUNDING_BOX_Z.value] = z;
}
if (x > statistics[targetIndex][STATISTICS_ENTRY.BOUNDING_BOX_END_X.value] || !initialized) {
statistics[targetIndex][STATISTICS_ENTRY.BOUNDING_BOX_END_X.value] = x;
}
if (y > statistics[targetIndex][STATISTICS_ENTRY.BOUNDING_BOX_END_Y.value] || !initialized) {
statistics[targetIndex][STATISTICS_ENTRY.BOUNDING_BOX_END_Y.value] = y;
}
if (z > statistics[targetIndex][STATISTICS_ENTRY.BOUNDING_BOX_END_Z.value] || !initialized) {
statistics[targetIndex][STATISTICS_ENTRY.BOUNDING_BOX_END_Z.value] = z;
}
if (value > statistics[targetIndex][STATISTICS_ENTRY.MAXIMUM_INTENSITY.value] || !initialized) {
statistics[targetIndex][STATISTICS_ENTRY.MAXIMUM_INTENSITY.value] = value;
}
if (value < statistics[targetIndex][STATISTICS_ENTRY.MINIMUM_INTENSITY.value] || !initialized) {
statistics[targetIndex][STATISTICS_ENTRY.MINIMUM_INTENSITY.value] = value;
}
statistics[targetIndex][STATISTICS_ENTRY.SUM_INTENSITY.value] += value;
statistics[targetIndex][STATISTICS_ENTRY.SUM_INTENSITY_TIMES_X.value] += value * x;
statistics[targetIndex][STATISTICS_ENTRY.SUM_INTENSITY_TIMES_Y.value] += value * y;
statistics[targetIndex][STATISTICS_ENTRY.SUM_INTENSITY_TIMES_Z.value] += value * z;
statistics[targetIndex][STATISTICS_ENTRY.SUM_X.value] += x;
statistics[targetIndex][STATISTICS_ENTRY.SUM_Y.value] += y;
statistics[targetIndex][STATISTICS_ENTRY.SUM_Z.value] += z;
statistics[targetIndex][STATISTICS_ENTRY.PIXEL_COUNT.value] += 1;
initializedFlags[targetIndex] = true;
}
x++;
if (x >= width) {
x = 0;
y++;
}
}
}
for (int j = 0; j < statistics.length; j++) {
statistics[j][STATISTICS_ENTRY.MEAN_INTENSITY.value] =
statistics[j][STATISTICS_ENTRY.SUM_INTENSITY.value] /
statistics[j][STATISTICS_ENTRY.PIXEL_COUNT.value];
statistics[j][STATISTICS_ENTRY.BOUNDING_BOX_WIDTH.value] =
statistics[j][STATISTICS_ENTRY.BOUNDING_BOX_END_X.value] -
statistics[j][STATISTICS_ENTRY.BOUNDING_BOX_X.value] + 1;
statistics[j][STATISTICS_ENTRY.BOUNDING_BOX_HEIGHT.value] =
statistics[j][STATISTICS_ENTRY.BOUNDING_BOX_END_Y.value] -
statistics[j][STATISTICS_ENTRY.BOUNDING_BOX_Y.value] + 1;
statistics[j][STATISTICS_ENTRY.BOUNDING_BOX_DEPTH.value] =
statistics[j][STATISTICS_ENTRY.BOUNDING_BOX_END_Z.value] -
statistics[j][STATISTICS_ENTRY.BOUNDING_BOX_Z.value] + 1;
statistics[j][STATISTICS_ENTRY.IDENTIFIER.value] = j + startLabelIndex;
statistics[j][STATISTICS_ENTRY.MASS_CENTER_X.value] =
statistics[j][STATISTICS_ENTRY.SUM_INTENSITY_TIMES_X.value] /
statistics[j][STATISTICS_ENTRY.SUM_INTENSITY.value];
statistics[j][STATISTICS_ENTRY.MASS_CENTER_Y.value] =
statistics[j][STATISTICS_ENTRY.SUM_INTENSITY_TIMES_Y.value] /
statistics[j][STATISTICS_ENTRY.SUM_INTENSITY.value];
statistics[j][STATISTICS_ENTRY.MASS_CENTER_Z.value] =
statistics[j][STATISTICS_ENTRY.SUM_INTENSITY_TIMES_Z.value] /
statistics[j][STATISTICS_ENTRY.SUM_INTENSITY.value];
statistics[j][STATISTICS_ENTRY.CENTROID_X.value] =
statistics[j][STATISTICS_ENTRY.SUM_X.value] /
statistics[j][STATISTICS_ENTRY.PIXEL_COUNT.value];
statistics[j][STATISTICS_ENTRY.CENTROID_Y.value] =
statistics[j][STATISTICS_ENTRY.SUM_Y.value] /
statistics[j][STATISTICS_ENTRY.PIXEL_COUNT.value];
statistics[j][STATISTICS_ENTRY.CENTROID_Z.value] =
statistics[j][STATISTICS_ENTRY.SUM_Z.value] /
statistics[j][STATISTICS_ENTRY.PIXEL_COUNT.value];
}
double[] squaredDifferencesFromMean = new double[statistics.length];
for (int z = 0; z < imp.getNSlices(); z++) {
imp.setZ(z + 1);
if(lab != null) {
lab.setZ(z + 1);
}
float[] pixels = (float[]) imp.getProcessor().getPixels();
float[] labels = lab!=null?(float[]) lab.getProcessor().getPixels():null;
for (int i = 0; i < pixels.length; i ++) {
int index = labels!=null?(int) labels[i]:0;
if (index >= startLabelIndex) {
int targetIndex = index - startLabelIndex;
double value = pixels[i];
squaredDifferencesFromMean[targetIndex] += Math.pow(value - statistics[targetIndex][STATISTICS_ENTRY.MEAN_INTENSITY.value], 2);
}
}
}
for (int j = 0; j < statistics.length; j++) {
statistics[j][STATISTICS_ENTRY.STANDARD_DEVIATION_INTENSITY.value] =
Math.sqrt(squaredDifferencesFromMean[j] /
statistics[j][STATISTICS_ENTRY.PIXEL_COUNT.value]);
}
if (inputImage != image) {
image.close();
}
if (inputLabelMap != labelMap && labelMap != null) {
labelMap.close();
}
return statistics;
}
/*
public static double[][] statisticsOfLabelledPixels(CLIJ clij, ClearCLBuffer inputImage, ClearCLBuffer inputLabelMap, int startLabelIndex, int endLabelIndex) {
if (endLabelIndex - startLabelIndex > 10) {
System.out.println("processing many labels");
return statisticsOfManyLabelledPixels(clij, inputImage, inputLabelMap, startLabelIndex, endLabelIndex);
}
double[][] statistics = new double[endLabelIndex - startLabelIndex + 1][STATISTICS_ENTRY.NUMBER_OF_ENTRIES];
ClearCLBuffer tempMask = clij.create(inputImage);
for (int i = startLabelIndex; i <= endLabelIndex; i++) {
System.out.println("Deriving stats from " + i);
LabelToMask.labelToMask(clij, inputLabelMap, tempMask, new Float(i));
double[] boundingBox = BoundingBox.boundingBox(clij, tempMask);
int numberOfPixels = (int)clij.op().sumPixels(tempMask);
double maximumIntensity = MaximumOfMaskedPixels.maximumOfMaskedPixels(clij, inputImage, tempMask);
double minimumIntensity = MinimumOfMaskedPixels.minimumOfMaskedPixels(clij, inputImage, tempMask);
double meanIntensity = MeanOfMaskedPixels.meanOfMaskedPixels(clij, inputImage, tempMask);
statistics[i - startLabelIndex][STATISTICS_ENTRY.BOUNDING_BOX_X.value] = boundingBox[STATISTICS_ENTRY.BOUNDING_BOX_X.value];
statistics[i - startLabelIndex][STATISTICS_ENTRY.BOUNDING_BOX_Y.value] = boundingBox[STATISTICS_ENTRY.BOUNDING_BOX_Y.value];
statistics[i - startLabelIndex][STATISTICS_ENTRY.BOUNDING_BOX_Z.value] = boundingBox[STATISTICS_ENTRY.BOUNDING_BOX_Z.value];
statistics[i - startLabelIndex][STATISTICS_ENTRY.BOUNDING_BOX_WIDTH.value] = boundingBox[STATISTICS_ENTRY.BOUNDING_BOX_WIDTH.value];
statistics[i - startLabelIndex][STATISTICS_ENTRY.BOUNDING_BOX_HEIGHT.value] = boundingBox[STATISTICS_ENTRY.BOUNDING_BOX_HEIGHT.value];
statistics[i - startLabelIndex][STATISTICS_ENTRY.BOUNDING_BOX_DEPTH.value] = boundingBox[STATISTICS_ENTRY.BOUNDING_BOX_DEPTH.value];
statistics[i - startLabelIndex][STATISTICS_ENTRY.MINIMUM_INTENSITY.value] = minimumIntensity;
statistics[i - startLabelIndex][STATISTICS_ENTRY.MAXIMUM_INTENSITY.value] = maximumIntensity;
statistics[i - startLabelIndex][STATISTICS_ENTRY.MEAN_INTENSITY.value] = meanIntensity;
statistics[i - startLabelIndex][STATISTICS_ENTRY.PIXEL_COUNT.value] = numberOfPixels;
}
tempMask.close();
return statistics;
}*/
// All the cropping doesn't work; we must recompile all the time; not good
// We can revive that code to speed stats up when image-size-specific re-compilation is no longer necessary
/*
private static double[][] statisticsOfManyLabelledPixels(CLIJ clij, ClearCLBuffer inputImage, ClearCLBuffer inputLabelMap, int startLabelIndex, int endLabelIndex) {
double[][] statistics = new double[endLabelIndex - startLabelIndex + 1][STATISTICS_ENTRY.NUMBER_OF_ENTRIES];
ClearCLBuffer tempMask = clij.create(inputImage);
for (int i = startLabelIndex; i <= endLabelIndex; i++) {
System.out.println("Deriving stats from " + i);
LabelToMask.labelToMask(clij, inputLabelMap, tempMask, new Float(i));
double[] boundingBox = BoundingBox.boundingBox(clij, tempMask);
long[] size = new long[3];
for (int d = 0; d < 3; d++) {
size[d] = (long)Math.max(((long)(boundingBox[d + 3] / 10)) * 10, 1);
}
ClearCLBuffer cropImage = clij.create(size, inputImage.getNativeType());
ClearCLBuffer cropMask = clij.create(size, tempMask.getNativeType());
clij.op().crop(inputImage, cropImage, (int)boundingBox[0], (int)boundingBox[1], (int)boundingBox[2]);
clij.op().crop(tempMask, cropMask, (int)boundingBox[0], (int)boundingBox[1], (int)boundingBox[2]);
int numberOfPixels = (int)clij.op().sumPixels(cropMask);
double maximumIntensity = MaximumOfMaskedPixels.maximumOfMaskedPixels(clij, cropImage, cropMask);
double minimumIntensity = MinimumOfMaskedPixels.minimumOfMaskedPixels(clij, cropImage, cropMask);
double meanIntensity = MeanOfMaskedPixels.meanOfMaskedPixels(clij, cropImage, cropMask);
statistics[i - startLabelIndex][STATISTICS_ENTRY.BOUNDING_BOX_X.value] = boundingBox[STATISTICS_ENTRY.BOUNDING_BOX_X.value];
statistics[i - startLabelIndex][STATISTICS_ENTRY.BOUNDING_BOX_Y.value] = boundingBox[STATISTICS_ENTRY.BOUNDING_BOX_Y.value];
statistics[i - startLabelIndex][STATISTICS_ENTRY.BOUNDING_BOX_Z.value] = boundingBox[STATISTICS_ENTRY.BOUNDING_BOX_Z.value];
statistics[i - startLabelIndex][STATISTICS_ENTRY.BOUNDING_BOX_WIDTH.value] = boundingBox[STATISTICS_ENTRY.BOUNDING_BOX_WIDTH.value];
statistics[i - startLabelIndex][STATISTICS_ENTRY.BOUNDING_BOX_HEIGHT.value] = boundingBox[STATISTICS_ENTRY.BOUNDING_BOX_HEIGHT.value];
statistics[i - startLabelIndex][STATISTICS_ENTRY.BOUNDING_BOX_DEPTH.value] = boundingBox[STATISTICS_ENTRY.BOUNDING_BOX_DEPTH.value];
statistics[i - startLabelIndex][STATISTICS_ENTRY.MINIMUM_INTENSITY.value] = minimumIntensity;
statistics[i - startLabelIndex][STATISTICS_ENTRY.MAXIMUM_INTENSITY.value] = maximumIntensity;
statistics[i - startLabelIndex][STATISTICS_ENTRY.MEAN_INTENSITY.value] = meanIntensity;
statistics[i - startLabelIndex][STATISTICS_ENTRY.PIXEL_COUNT.value] = numberOfPixels;
cropImage.close();
cropMask.close();
IJ.log("idx: " + i);
}
tempMask.close();
return statistics;
}
*/
@Override
public String getParameterHelpText() {
return "Image input, Image labelmap";
}
@Override
public String getDescription() {
return "Determines bounding box, area (in pixels/voxels), min, max and mean intensity \n" +
" of labelled objects in a label map and corresponding pixels in the original image. \n\n" +
"Instead of a label map, you can also use a binary image as a binary image is a label map with just one label." +
"\n\nThis method is executed on the CPU and not on the GPU/OpenCL device.";
}
@Override
public String getAvailableForDimensions() {
return "2D, 3D";
}
}