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| package systeme;
import java.applet.Applet;
import java.util.*;
import java.awt.*;
/**
* Dieses Applet implementiert das k-means Verfahren. Dieses ist ein unüberwachtes
* Klassifikationsverfahren (auch Clustering Verfahren genannt), mit dem sich
* Merkmalsvektoren im Merkmalsraum in Ballungszentren bzw. Cluster aufteilen
* lassen.
*
* @author Jens Spehr
*
*/
public class Kmeans extends Applet implements Runnable {
Vector CrossList; /** Enthält alle Merkmalsvektoren */
Vector Centroids; /** Enthält die Schwerpunkte der Cluster */
Choice SubsetChoice; /** Steuerelement */
Button StartButton,RestartButton,ResetButton,RunButton,DrawGButton; /** Buttons*/
Checkbox history; /** Checkbox */
Thread Go; /** Thread für den Run-Modus. */
int step; /** Aktueller Schritt, in dem sich der Algorithmus befindet. */
int subset; /** Anzahl der Cluster */
Random rand; /** Zufallsvariable*/
boolean abort; /** Abbruchkriterium */
/** Erstellt das Graphic User Interface (GUI). */
public void init() {
rand = new Random();
Centroids = new Vector();
StartButton = new Button("Start");
add(StartButton);
StartButton.setEnabled(false);
RestartButton = new Button("New Start");
add(RestartButton);
RestartButton.setEnabled(false);
ResetButton = new Button("Reset");
add(ResetButton);
ResetButton.setEnabled(false);
RunButton = new Button("Run");
add(RunButton);
RunButton.setEnabled(false);
DrawGButton = new Button("Draw Cluster");
add(DrawGButton);
CrossList = new Vector();
SubsetChoice = new Choice();
SubsetChoice.addItem("2");
SubsetChoice.addItem("3");
SubsetChoice.addItem("4");
SubsetChoice.addItem("5");
SubsetChoice.addItem("6");
SubsetChoice.addItem("7");
SubsetChoice.addItem("8");
add(SubsetChoice);
history = new Checkbox("Show History");
add(history);
subset = 2;
step = -1;
}
/** Zeichnet den Text, die Merkmalsvektoren und die Clusterschwerpunkte. */
public void paint(Graphics g)
{
g.setColor(Color.BLACK);
g.drawRect(0, 500, 499, 300);
StringBuffer buffer;
if (step == 1) g.setColor(Color.red);
else g.setColor(Color.black);
buffer = new StringBuffer("Step 1: Place ranomly initial group centroids into the 2d space.");
g.drawString(buffer.toString(),2, 370);
if (step == 2) g.setColor(Color.red);
else g.setColor(Color.black);
buffer = new StringBuffer("Step 2: Assign each object to the group that has the closest centroid.");
g.drawString(buffer.toString(),2, 385);
if (step == 3) g.setColor(Color.red);
else g.setColor(Color.black);
buffer = new StringBuffer("Step 3: Recalculate the positions of the centroids. ");
g.drawString(buffer.toString(),2, 400);
if (step == 4) g.setColor(Color.red);
else g.setColor(Color.black);
buffer = new StringBuffer("Step 4: If the positions of the centroids didn't change go to the next step, else go to Step 2.");
g.drawString(buffer.toString(),2, 415);
if (step == 5) g.setColor(Color.red);
else g.setColor(Color.black);
buffer = new StringBuffer("Step 5: End.");
g.drawString(buffer.toString(),2, 430);
// Zeichnet die Merkmalsvektoren
Cross s;
int numShapes = CrossList.size();
for (int i = 0; i < numShapes; i++)
{
s = (Cross) CrossList.elementAt(i);
s.draw(g);
}
// Zeichnet die Clusterschwerpunkte
if (step != -1)
{
Quad t = new Quad();
int numCent = Centroids.size();
for (int i = 0; i < numCent; i++)
{
t = (Quad) Centroids.elementAt(i);
t.hist = history.getState();
t.draw(g);
}
}
}
/** Erzeugt einen neuen Merkmalsvektor durch einen Mausklick. */
public boolean mouseUp(Event e, int x, int y) {
if ((step == -1) && (allowedMousePosition(x,y)== true))
{
ResetButton.setEnabled(true);
StartButton.setEnabled(true);
RunButton.setEnabled(true);
Cross s = new Cross();
s.color = Color.black;
s.x = x;
s.y = y;
CrossList.addElement(s);
repaint();
}
return true;
}
/** Überprüfung, ob die aktuelle Mausposition erlaubt ist. */
public boolean allowedMousePosition(int x, int y)
{
if ((x>=5)&&(y>=55)&&(x<595)&&(y<345)) return true;
else return false;
}
/** Automatisches Durchlaufen des k-means Verfahrens. In einem Schritt wird
* für ca. 100ms verweilt. */
public void run() {
while (true) {
if (step ==-1) this.step1();
else if (step == 1) this.step2();
else if (step == 2) this.step3();
else if (step == 3) step = 4;
else if ((step == 4) && (abort==true))
{
RestartButton.setEnabled(true);
ResetButton.setEnabled(true);
step = 5;
repaint();
Go.stop();
}
else if ((step == 4) && (abort==false)) this.step2();
repaint();
try { // Thread erfordert Ausnahme-Handler (try-catch-Klausel)
Thread.sleep(100);
}
catch (InterruptedException e) {
}
}
}
/** Managen der Button Ereignisse. */
public boolean action(Event event, Object eventobject)
{
if ((event.target==StartButton))
{
StartButton.setLabel("Step");
RestartButton.setEnabled(true);
if (step ==-1) this.step1();
else if (step == 1) this.step2();
else if (step == 2) this.step3();
else if (step == 3) step = 4;
else if ((step == 4) && (abort==true))
{
StartButton.setEnabled(false);
RunButton.setEnabled(false);
step = 5;
}
else if ((step == 4) && (abort==false)) this.step2();
repaint();
return true;
}
if ((event.target==RunButton))
{
Go = new Thread(this);
Go.start();
StartButton.setEnabled(false);
RestartButton.setEnabled(false);
ResetButton.setEnabled(false);
RunButton.setEnabled(false);
return true;
}
if ((event.target==DrawGButton))
{
if (CrossList.size()>0) Reset();
String SubsetString = SubsetChoice.getSelectedItem();
if (SubsetString.equals("2")) subset = 2;
if (SubsetString.equals("3")) subset = 3;
if (SubsetString.equals("4")) subset = 4;
if (SubsetString.equals("5")) subset = 5;
if (SubsetString.equals("6")) subset = 6;
if (SubsetString.equals("7")) subset = 7;
if (SubsetString.equals("8")) subset = 8;
// Erstelle Gausverteilungen
Vector GaussianList;
GaussianList = new Vector();
for (int i = 0; i<subset;i++)
{
Gaussian gaus = new Gaussian();
// Initialisiere Erwartungswert
gaus.mux = 50 + Math.abs(rand.nextInt() % 450);
gaus.muy = 75 + Math.abs(rand.nextInt() % 275);
// Initialisiere Standardabweichung
gaus.sigma = 10 + Math.abs(30 * rand.nextDouble());
GaussianList.addElement(gaus);
}
ResetButton.setEnabled(true);
StartButton.setEnabled(true);
RunButton.setEnabled(true);
// Erzeuge die Merkmalsvektoren
for (int i = 0; i<subset;i++)
{
// Wähle Gausverteilung
Gaussian gaus;
gaus = (Gaussian) GaussianList.elementAt(i);
// Erzeuge die Merkmalsvektoren für das ausgewählte Cluster
for (int j = 0;j<2800/subset;j++)
{
// Zur Performance-Steigerung wird hier keine "echte"
// Gausskurve verwendet.
double r = 5*gaus.sigma*Math.pow(rand.nextDouble(),2);
double alpha = 2*Math.PI*rand.nextDouble();
int x = gaus.mux + (int) Math.round(r*Math.cos(alpha));
int y = gaus.muy + (int) Math.round(r*Math.sin(alpha));
// Überprüfung, ob Position erlaubt ist...
if (allowedMousePosition(x,y)==true)
{
// Füge den Merkmalvektor der CrossList hinzu.
Cross s = new Cross();
s.color = Color.black;
s.x = x;
s.y = y;
CrossList.addElement(s);
}
}
}
repaint();
return true;
}
if ((event.target==RestartButton) && (step !=-1))
{
step = -1;
abort = false;
Centroids.removeAllElements();
int numShapes = CrossList.size();
Cross s;
for (int i = 0; i < numShapes; i++)
{
s = (Cross) CrossList.elementAt(i);
s.color = Color.black;
}
StartButton.setLabel("Start");
StartButton.setEnabled(true);
ResetButton.setEnabled(true);
RunButton.setEnabled(true);
this.repaint();
return true;
}
if ((event.target==ResetButton))
{
Reset();
return true;
}
return true;
}
/** Zurücksetzen des Applet durch Löschen von allen Merkmalsvektoren und
* Clusterschwerpunkten. */
public void Reset()
{
step = -1;
abort = false;
Centroids.removeAllElements();
int numShapes = CrossList.size();
Cross s;
for (int i = 0; i < numShapes; i++)
{
s = (Cross) CrossList.elementAt(i);
s.color = Color.white;
}
StartButton.setLabel("Start");
StartButton.setEnabled(false);
RestartButton.setEnabled(false);
ResetButton.setEnabled(false);
RunButton.setEnabled(false);
CrossList.removeAllElements();
this.repaint();
}
/** Verteilt zufällig die Clusterschwerpunkte im 2d Merkmalsraum. */
public void step1()
{
abort = false;
String SubsetString = SubsetChoice.getSelectedItem();
if (SubsetString.equals("2")) subset = 2;
if (SubsetString.equals("3")) subset = 3;
if (SubsetString.equals("4")) subset = 4;
if (SubsetString.equals("5")) subset = 5;
if (SubsetString.equals("6")) subset = 6;
if (SubsetString.equals("7")) subset = 7;
if (SubsetString.equals("8")) subset = 8;
int numShapes = CrossList.size();
boolean ch[] = new boolean[numShapes];
for (int i = 0; i<numShapes;i++) ch[i]=false;
for (int i = 0; i<subset;)
{
Cross s;
Quad p = new Quad();
int r = Math.abs(rand.nextInt() % numShapes);
if (ch[r]==false)
{
s = (Cross) CrossList.elementAt(r);
p.x = s.x;
p.y = s.y;
if (i == 0) p.color = Color.green;
else if (i == 1) p.color = Color.red;
else if (i == 2) p.color = Color.blue;
else if (i == 3) p.color = Color.yellow;
else if (i == 4) p.color = Color.orange;
else if (i == 5) p.color = Color.magenta;
else if (i == 6) p.color = Color.cyan;
else if (i == 7) p.color = Color.lightGray;
else if (i == 8) p.color = Color.darkGray;
p.History = new Vector();
Centroids.addElement(p);
ch[r] = true;
i++;
}
}
step = 1;
}
/** Zuordnung von jedem Merkmalsvektore zum jeweils nächsten Clusterschwerpunkt */
public void step2()
{
Cross s;
Quad p;
int numShapes = CrossList.size();
for (int i = 0; i < numShapes; i++)
{
s = (Cross) CrossList.elementAt(i);
int numCent = Centroids.size();
int min = 0;
double dist_min = 99999999.9;
for (int j = 0; j < numCent; j++)
{
p = (Quad) Centroids.elementAt(j);
double dist = Point.distance(s.x, s.y, p.x, p.y);
if (dist < dist_min)
{
dist_min = dist;
min = j;
}
}
p = (Quad) Centroids.elementAt(min);
s.color = p.color;
}
step = 2;
}
/** Neuberechnung der Clusterschwerpunkte. */
public void step3()
{
Quad p;
Cross s;
Point m = new Point();
double changes = 0.0;
int numCent = Centroids.size();
for (int j = 0; j < numCent; j++)
{
p = (Quad) Centroids.elementAt(j);
m.x = 0;
m.y = 0;
int Count = 0;
int numShapes = CrossList.size();
for (int i = 0; i < numShapes; i++)
{
s = (Cross) CrossList.elementAt(i);
if (s.color == p.color)
{
m.x += s.x;
m.y += s.y;
Count++;
}
}
if (Count>0)
{
changes += Point.distance(p.x,p.y,m.x/Count, m.y/Count);
Point pt = new Point();
pt.x = p.x;
pt.y = p.y;
p.History.addElement(pt);
p.x = m.x / Count;
p.y = m.y / Count;
}
}
if (changes<0.1) abort = true;
step = 3;
}
} |
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