io.github.mianalysis.mia.process.activecontour.minimisers.GreedyMinimiser Maven / Gradle / Ivy
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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: Add minimum and maximum node spacing. Beyond this, the node stays in its original place
package io.github.mianalysis.mia.process.activecontour.minimisers;
import java.util.Iterator;
import io.github.mianalysis.mia.process.activecontour.energies.EnergyCollection;
import io.github.mianalysis.mia.process.activecontour.physicalmodel.NodeCollection;
import io.github.mianalysis.mia.process.activecontour.physicalmodel.Vertex;
import io.github.mianalysis.mia.process.math.CumStat;
/**
* Created by Stephen on 16/09/2016.
*/
public class GreedyMinimiser {
public static final int RANDOM = 0; //Evaluate nodes as they come off the NodeCollection iterator
public static final int RIGHTDOWN = 1; //Start at top-left and work right, then down
public static final int CLOCKWISE = 2; //Start at the first node in NodeCollection and proceed to the right
int sequence = 0; //Defaults to random read
EnergyCollection energies;
double width = 100; //full width of window over which greedy minimiser checks
double sample_n = 25; //Number of samples in one dimension
public GreedyMinimiser(EnergyCollection energies) {
this.energies = energies;
}
public void evaluateGreedy(Vertex node) {
double x = node.getX();
double y = node.getY();
double x_min = x-width/2;
double y_min = y-width/2;
double spacing = width/(sample_n-1);
double min_energy = Double.POSITIVE_INFINITY;
CumStat cs_x = new CumStat();
CumStat cs_y = new CumStat();
//Iterating over all possible sites
for (int c=0;c iterator = nodes.iterator();
while (iterator.hasNext()) {
evaluateGreedy(iterator.next());
}
break;
case RIGHTDOWN:
Vertex node_row = nodes.getSpecialNode(Vertex.TOPLEFT); //The starting node
Vertex node_col = node_row;
while (node_row.getBottomNeighbour() != null) {
while (node_col.getRightNeighbour() != null) {
evaluateGreedy(node_col);
node_col = node_col.getRightNeighbour(); //Moving onto the next node in the row
}
evaluateGreedy(node_col);
node_row = node_row.getBottomNeighbour(); //Moving onto the next node in the row
node_col = node_row;
}
while (node_col.getRightNeighbour() != null) {
evaluateGreedy(node_col);
node_col = node_col.getRightNeighbour(); //Moving onto the next node in the row
}
break;
case CLOCKWISE:
iterator = nodes.iterator();
Vertex node = iterator.next();
evaluateGreedy(node);
int startNode = node.getID();
node = node.getRightNeighbour();
while (node.getID() != startNode) {
evaluateGreedy(node);
node = node.getRightNeighbour();
}
break;
}
}
public double getWidth() {
return width;
}
public double getSampleN() {
return sample_n;
}
public void setWidth(double width) {
this.width = width;
}
public void setSampleN(double sample_n) {
this.sample_n = sample_n;
}
public void setSequence(int sequence) {
this.sequence = sequence;
}
}