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ModularImageAnalysis (MIA) is an ImageJ plugin which provides a modular framework for assembling image and object analysis workflows. Detected objects can be transformed, filtered, measured and related. Analysis workflows are batch-enabled by default, allowing easy processing of high-content datasets.
//TODO: Once unit test is working, swap Vector3D calculation for angle calculation from SkeletonTools.FitSkeletonBreaks
package io.github.mianalysis.mia.process.analysis;
import org.apache.commons.math3.geometry.euclidean.threed.Vector3D;
import io.github.mianalysis.mia.process.math.CumStat;
/**
* Calculates the direction autocorrelation. Tested against results from DiPer.
*/
public class DirectionalPersistenceCalculator {
public static CumStat[] calculate(CumStat[] cumStat, int[] f, double[] x, double[] y, double[] z) {
for (int i = 0; i < f.length-1; i++) {
for (int j = i; j < f.length-1; j++) {
// Vectors must each take a single time step
if (f[i+1]-f[i] == 1 & f[j+1]-f[j] == 1) {
int df = f[j] - f[i];
Vector3D v1 = new Vector3D((x[i+1] - x[i]), (y[i+1] - y[i]), (z[i+1] - z[i]));
Vector3D v2 = new Vector3D((x[j+1] - x[j]), (y[j+1] - y[j]), (z[j+1] - z[j]));
if (v1.getNorm() != 0 & v2.getNorm() != 0) {
if (cumStat[df] == null) cumStat[df] = new CumStat();
cumStat[df].addMeasure(Math.cos(Vector3D.angle(v1, v2)));
}
}
}
}
return cumStat;
}
public static CumStat[] calculate(int[] f, double[] x, double[] y, double[] z) {
int maxDf = f[f.length - 1] - f[0]; // Maximum frame separation
CumStat[] cumStat = new CumStat[maxDf];
calculate(cumStat,f,x,y,z);
return cumStat;
}
public static CumStat[] calculateContinuous(double[] x, double[] y, double[] z) {
int[] f = new int[x.length];
for (int i=0;i