public void writeMap(Cluster cluster, float yBar) {
Set<Submission> subSet = new HashSet<Submission>(cluster.size());
String documents = "";
for (int i = 0; i < cluster.size(); i++) {
Submission sub = submissions.elementAt(cluster.getSubmissionAt(i));
documents += sub.name + " ";
subSet.add(sub);
}
documents = documents.trim();
String theme =
ThemeGenerator.generateThemes(subSet, this.program.get_themewords(), false, this.program);
mapString +=
"<area shape=\"rect\" coords=\""
+ (cluster.x - 2)
+ ","
+ (yBar)
+ ","
+ (cluster.x + 2)
+ ","
+ (cluster.y + 2)
+ "\" onMouseover=\"set('"
+ cluster.size()
+ "','"
+ trimStringToLength(String.valueOf(cluster.getSimilarity()), 6)
+ "','"
+ trimStringToLength(documents, 50)
+ "','"
+ theme
+ "')\" ";
// if (cluster.size() == 1)
// mapString += "href=\"submission"+cluster.getSubmissionAt(0)+".html\">\n";
// else
mapString += "nohref>\n";
}
public static int[] calculateVectorSpace(BufferedImage image) {
clusters = createClusters(image);
int[] vectorSpace = new int[IMAGE_WIDTH * IMAGE_HEIGHT];
Arrays.fill(vectorSpace, -1);
boolean refineNeeded = true;
int loops = 0;
while (refineNeeded) {
refineNeeded = false;
loops++;
for (int y = 0; y < IMAGE_HEIGHT; y++) {
for (int x = 0; x < IMAGE_WIDTH; x++) {
int pixel = image.getRGB(x, y);
Cluster cluster = getMinCluster(pixel);
if (vectorSpace[IMAGE_WIDTH * y + x] != cluster.getId()) {
if (vectorSpace[IMAGE_WIDTH * y + x] != -1) {
clusters[vectorSpace[IMAGE_WIDTH * y + x]].removePixel(pixel);
}
cluster.addPixel(pixel);
refineNeeded = true;
vectorSpace[IMAGE_WIDTH * y + x] = cluster.getId();
}
}
}
}
System.out.println("Took " + loops + " loops.");
return vectorSpace;
}
public void drawCluster(Cluster cluster) {
int index = clusters.indexOf(cluster);
if (index != -1) {
cluster.y = maxY;
cluster.x = minX + index * factor;
if (cluster.size() > 1) g.setColor(Color.RED);
else g.setColor(Color.BLACK);
g.drawRect(cluster.x - 1, cluster.y - cluster.size(), 2, 1 + cluster.size());
} else {
Cluster left = cluster.getLeft();
Cluster right = cluster.getRight();
drawCluster(left);
drawCluster(right);
int yBar = minY + (int) ((maxY - minY) * (cluster.getSimilarity() / threshold));
g.setColor(Color.DARK_GRAY);
if (left.y > yBar) {
g.drawLine(left.x, left.y - 1, left.x, yBar);
writeMap(left, yBar);
}
if (right.y > yBar) {
g.drawLine(right.x, right.y - 1, right.x, yBar);
writeMap(right, yBar);
}
g.setColor(Color.BLACK);
g.drawLine(left.x, yBar, right.x, yBar);
cluster.x = (right.x + left.x) / 2;
cluster.y = yBar;
}
}
/** Print it! */
public String printClusters(Cluster clustering, float threshold, HTMLFile f) {
int maxSize = 0;
ArrayList<Cluster> clusters = getClusters(clustering, threshold);
for (Iterator<Cluster> i = clusters.iterator(); i.hasNext(); ) {
Cluster cluster = i.next();
if (cluster.size() > maxSize) maxSize = cluster.size();
}
TreeSet<Cluster> sorted = new TreeSet<Cluster>(clusters);
clusters = null;
// Now print them:
return outputClustering(f, sorted, maxSize);
}
/** Min clustering... */
public Cluster minMaxAvrClustering() {
int nrOfSubmissions = submissions.size();
boolean minClustering = (Options.MIN_CLUSTER == this.program.get_clusterType());
boolean maxClustering = (Options.MAX_CLUSTER == this.program.get_clusterType());
SimilarityMatrix simMatrix = this.program.get_similarity();
ArrayList<Cluster> clusters = new ArrayList<Cluster>(submissions.size());
for (int i = 0; i < nrOfSubmissions; i++) clusters.add(new Cluster(i, this));
while (clusters.size() > 1) {
int indexA = -1, indexB = -1;
float maxSim = -1;
int nrOfClusters = clusters.size();
// find similarity
for (int a = 0; a < (nrOfClusters - 1); a++) {
Cluster cluster = clusters.get(a);
for (int b = a + 1; b < nrOfClusters; b++) {
float sim;
if (minClustering) sim = cluster.maxSimilarity(clusters.get(b), simMatrix);
else if (maxClustering) sim = cluster.minSimilarity(clusters.get(b), simMatrix);
else sim = cluster.avrSimilarity(clusters.get(b), simMatrix);
if (sim > maxSim) {
maxSim = sim;
indexA = a;
indexB = b;
}
}
}
if (maxSim > maxMergeValue) maxMergeValue = maxSim;
// now merge these clusters
Cluster clusterA = clusters.get(indexA);
Cluster clusterB = clusters.get(indexB);
clusters.remove(clusterA);
clusters.remove(clusterB);
clusters.add(new Cluster(clusterA, clusterB, maxSim, this));
}
return clusters.get(0);
}
private ArrayList<Cluster> getClusters(Cluster clustering, float threshold) {
ArrayList<Cluster> clusters = new ArrayList<Cluster>();
// First determine the clusters
Stack<Cluster> stack = new Stack<Cluster>();
stack.push(clustering);
while (!stack.empty()) {
Cluster current = stack.pop();
if (current.size() == 1) {
clusters.add(current); // singleton clusters
} else {
if (current.getSimilarity() >= threshold) {
clusters.add(current);
} else {
// current.size() != 1 !!!
stack.push(current.getLeft());
stack.push(current.getRight());
}
}
}
return clusters;
}
/** This method returns the distribution HTML code as a string */
private String outputClustering(HTMLFile f, Collection<Cluster> allClusters, int maxSize) {
int[] distribution = new int[maxSize + 1];
int max = 0;
for (int i = 0; i <= maxSize; i++) distribution[i] = 0;
// Now output the clustering:
f.println("<TABLE CELLPADDING=2 CELLSPACING=2>");
f.println(
"<TR><TH ALIGN=center BGCOLOR=#8080ff>"
+ msg.getString("Clusters.Cluster_number")
+ "<TH ALIGN=center BGCOLOR=#8080ff>"
+ msg.getString("Clusters.Size")
+ "<TH ALIGN=center BGCOLOR=#8080ff>"
+ msg.getString("Clusters.Threshold")
+ "<TH ALIGN=center BGCOLOR=#8080ff>"
+ msg.getString("Clusters.Cluster_members")
+ "<TH ALIGN=center BGCOLOR=#8080ff>"
+ msg.getString("Clusters.Most_frequent_words")
+ "</TR>");
Iterator<Cluster> clusterI = allClusters.iterator();
for (int i = 1; clusterI.hasNext(); i++) {
Cluster cluster = clusterI.next();
if (max < ++distribution[cluster.size()]) max = distribution[cluster.size()];
// no singleton clusters
if (cluster.size() == 1) continue;
f.print(
"<TR><TD ALIGN=center BGCOLOR=#8080ff>"
+ i
+ "<TD ALIGN=center BGCOLOR=#c0c0ff>"
+ cluster.size()
+ "<TD ALIGN=center BGCOLOR=#c0c0ff>"
+ cluster.getSimilarity()
+ "<TD ALIGN=left BGCOLOR=#c0c0ff>");
// sort names
TreeSet<Submission> sortedSubmissions = new TreeSet<Submission>();
for (int x = 0; x < cluster.size(); x++) {
sortedSubmissions.add(submissions.elementAt(cluster.getSubmissionAt(x)));
}
for (Iterator<Submission> iter = sortedSubmissions.iterator(); iter.hasNext(); ) {
Submission sub = iter.next();
int index = submissions.indexOf(sub);
f.print("<A HREF=\"submission" + index + ".html\">" + sub.name + "</A>");
if (iter.hasNext()) f.print(", ");
neededSubmissions.add(sub); // write files for these.
}
if (this.program.get_language() instanceof jplag.text.Language) {
f.println(
"<TD ALIGN=left BGCOLOR=#c0c0ff>"
+ ThemeGenerator.generateThemes(
sortedSubmissions, this.program.get_themewords(), true, this.program));
} else {
f.println("<TD ALIGN=left BGCOLOR=#c0c0ff>-");
}
f.println("</TR>");
}
f.println("</TABLE>\n<P>\n");
f.println("<H5>" + msg.getString("Clusters.Distribution_of_cluster_size") + ":</H5>");
String text;
text = "<TABLE CELLPADDING=1 CELLSPACING=1>\n";
text +=
"<TR><TH ALIGN=center BGCOLOR=#8080ff>"
+ msg.getString("Clusters.Cluster_size")
+ "<TH ALIGN=center BGCOLOR=#8080ff>"
+ msg.getString("Clusters.Number_of_clusters")
+ "<TH ALIGN=center BGCOLOR=#8080ff>.</TR>\n";
for (int i = 0; i <= maxSize; i++) {
if (distribution[i] == 0) continue;
text +=
"<TR><TD ALIGN=center BGCOLOR=#c0c0ff>"
+ i
+ "<TD ALIGN=right BGCOLOR=#c0c0ff>"
+ distribution[i]
+ "<TD BGCOLOR=#c0c0ff>\n";
for (int j = (distribution[i] * barLength / max); j > 0; j--) text += ("#");
if (distribution[i] * barLength / max == 0) {
if (distribution[i] == 0) text += (".");
else text += ("#");
}
text += ("</TR>\n");
}
text += ("</TABLE>\n");
f.print(text);
return text;
}