/**
* Computes and plots correlation functions
*
* @param tauMax is the maximum time for correlation functions
*/
public void computeCorrelation(int tauMax) {
plotFrame.clearData();
double energyAccumulator = 0, magnetizationAccumulator = 0;
double energySquaredAccumulator = 0, magnetizationSquaredAccumulator = 0;
for (int t = 0; t < numberOfPoints; t++) {
energyAccumulator += energy[t];
magnetizationAccumulator += magnetization[t];
energySquaredAccumulator += energy[t] * energy[t];
magnetizationSquaredAccumulator += magnetization[t] * magnetization[t];
}
double averageEnergySquared = Math.pow(energyAccumulator / numberOfPoints, 2);
double averageMagnetizationSquared = Math.pow(magnetizationAccumulator / numberOfPoints, 2);
// compute normalization factors
double normE = (energySquaredAccumulator / numberOfPoints) - averageEnergySquared;
double normM = (magnetizationSquaredAccumulator / numberOfPoints) - averageMagnetizationSquared;
for (int tau = 1; tau <= tauMax; tau++) {
double c_MAccumulator = 0;
double c_EAccumulator = 0;
int counter = 0;
for (int t = 0; t < numberOfPoints - tau; t++) {
c_MAccumulator += magnetization[t] * magnetization[t + tau];
c_EAccumulator += energy[t] * energy[t + tau];
counter++;
}
// correlation function defined so that c(0) = 1 and c(infinity) -> 0
plotFrame.append(0, tau, ((c_MAccumulator / counter) - averageMagnetizationSquared) / normM);
plotFrame.append(1, tau, ((c_EAccumulator / counter) - averageEnergySquared) / normE);
}
plotFrame.setVisible(true);
}
/** initializes site lattice with single particle clusters randomly placed on the lattice */
public void initialize() {
site = new int[L][L];
for (int i = 0; i < L; i++) {
for (int j = 0; j < L; j++) {
site[i][j] = -1; // site not occupied
}
}
x = new int[numberOfParticles];
y = new int[numberOfParticles];
firstParticle = new int[numberOfParticles];
nextParticle = new int[numberOfParticles];
lastParticle = new int[numberOfParticles];
mass = new int[numberOfParticles + 1];
numberOfClusters = 0;
for (int i = 0; i < numberOfParticles; i++) {
do {
x[i] = (int) (Math.random() * L);
y[i] = (int) (Math.random() * L);
} while (site[x[i]][y[i]] != -1);
site[x[i]][y[i]] = numberOfClusters;
firstParticle[numberOfClusters] = i;
mass[numberOfClusters] = 1;
nextParticle[i] = -1; // no more particles in cluster
lastParticle[numberOfClusters] = i;
numberOfClusters++;
checkNeighbors(x[i], y[i]);
}
}
/**
* Constructs OscillatorsMode with the given mode and number of particles.
*
* <p>The particle separation is one in this model.
*
* @param mode int
* @param N int
*/
OscillatorsMode(int mode, int N) {
amplitude = Math.sqrt(2.0 / (N + 1));
omega = 2 * Math.sqrt(OMEGA_SQUARED) * Math.abs(Math.sin(mode * Math.PI / N / 2));
wavenumber = Math.PI * mode / (N + 1);
functionDrawer = new FunctionDrawer(this);
functionDrawer.initialize(0, N + 1, 300, false); // draws the initial displacement
functionDrawer.color = Color.LIGHT_GRAY;
}
/** Draws clusters */
public void draw(DrawingPanel panel, Graphics g) {
if (site == null) {
return;
}
int sizeX = Math.abs(panel.xToPix(1.0) - panel.xToPix(0));
int sizeY = Math.abs(panel.yToPix(1.0) - panel.yToPix(0));
for (int i = 0; i < numberOfParticles; i++) {
int xpix = panel.xToPix(x[i]) - sizeX;
int ypix = panel.yToPix(y[i]) - sizeY;
g.fillRect(xpix + sizeX / 2, ypix + sizeY / 2, sizeX, sizeY);
}
}
/**
* Overrides TPoint showCoordinates method.
*
* @param vidPanel the video panel
*/
public void showCoordinates(VideoPanel vidPanel) {
// put values into pointmass x and y fields
Point2D p = getWorldPosition(vidPanel);
track.xField.setValue(p.getX());
track.yField.setValue(p.getY());
track.magField.setValue(p.distance(0, 0));
double theta = Math.atan2(p.getY(), p.getX());
track.angleField.setValue(theta);
super.showCoordinates(vidPanel);
}
/**
* Gets the dimension of the lattice in pixel units.
*
* @param panel
* @return the dimension
*/
public Dimension getInterior(DrawingPanel panel) {
float availableWidth = panel.getWidth() - panel.getLeftGutter() - panel.getRightGutter() - 1;
float availableHeight = panel.getHeight() - panel.getTopGutter() - panel.getBottomGutter() - 1;
scaleFactor = Math.min(availableWidth / dimension.width, availableHeight / dimension.height);
if (scaleFactor > 1) {
scaleFactor = 1;
return dimension;
}
return new Dimension((int) (scaleFactor * ncol), (int) (scaleFactor * nrow));
}
public ScientificRenderer(int sigfigs) {
sigfigs = Math.min(sigfigs, 6);
if (format instanceof DecimalFormat) {
String pattern = "0.0"; // $NON-NLS-1$
for (int i = 0; i < sigfigs - 1; i++) {
pattern += "0"; // $NON-NLS-1$
}
pattern += "E0"; // $NON-NLS-1$
((DecimalFormat) format).applyPattern(pattern);
}
}
/**
* Calculates statistical values for a data array.
*
* @param data the data array
* @return the max, min, mean, SD, SE and non-NaN data count
*/
private double[] getStatistics(double[] data) {
double max = -Double.MAX_VALUE;
double min = Double.MAX_VALUE;
double sum = 0.0;
double squareSum = 0.0;
int count = 0;
for (int i = 0; i < data.length; i++) {
if (Double.isNaN(data[i])) {
continue;
}
count++;
max = Math.max(max, data[i]);
min = Math.min(min, data[i]);
sum += data[i];
squareSum += data[i] * data[i];
}
double mean = sum / count;
double sd = count < 2 ? Double.NaN : Math.sqrt((squareSum - count * mean * mean) / (count - 1));
if (max == -Double.MAX_VALUE) max = Double.NaN;
if (min == Double.MAX_VALUE) min = Double.NaN;
return new double[] {max, min, mean, sd, sd / Math.sqrt(count), count};
}
/** Moves a cluster chosen at random in a random direction */
public void step() {
int cluster = (int) (Math.random() * numberOfClusters);
int direction = (int) (Math.random() * 4);
int dx = nnx[direction];
int dy = nny[direction];
int particle = firstParticle[cluster];
do {
site[x[particle]][y[particle]] = -1;
x[particle] = PBC.position(x[particle] + dx, L);
y[particle] = PBC.position(y[particle] + dy, L);
particle = nextParticle[particle];
} while (particle != -1);
particle = firstParticle[cluster];
do {
site[x[particle]][y[particle]] = cluster; // labels new sites occupied by cluster
particle = nextParticle[particle];
} while (particle != -1);
particle = firstParticle[cluster];
do {
checkNeighbors(x[particle], y[particle]); // checks for merger
particle = nextParticle[particle];
} while (particle != -1);
}
/**
* Evaluates the displacement for an oscillator at postion x
*
* @param x postion along chain
* @return the displacement
*/
public double evaluate(double x) {
return amplitude * Math.sin(x * wavenumber);
}
/**
* Sets the default point index. This defines the index of the points array used to get the point
* initially selected when the step is created.
*
* @param index the index
*/
public void setDefaultPointIndex(int index) {
index = Math.min(index, points.length - 1);
defaultIndex = Math.max(0, index);
}
/**
* Gets a list of Point2D objects that lie within pixels in a rectangle and along a line.
*
* @param searchRect the rectangle
* @param x0 the x-component of a point on the line
* @param y0 the y-component of a point on the line
* @param slope the slope of the line
* @return a list of Point2D
*/
public ArrayList<Point2D> getSearchPoints(
Rectangle searchRect, double x0, double y0, double theta) {
double slope = -Math.tan(theta);
// create line to search along
Line2D line = new Line2D.Double();
if (slope > LARGE_NUMBER) {
line.setLine(x0, y0, x0, y0 + 1);
} else if (slope < 1 / LARGE_NUMBER) {
line.setLine(x0, y0, x0 + 1, y0);
} else {
line.setLine(x0, y0, x0 + 1, y0 + slope);
}
// create intersection points (to set line ends)
Point2D p1 = new Point2D.Double();
Point2D p2 = new Point2D.Double(Double.NaN, Double.NaN);
Point2D p = p1;
boolean foundBoth = false;
double d = searchRect.x;
Object[] data = getDistanceAndPointAtX(line, d);
if (data != null) {
p.setLocation((Point2D) data[1]);
if (p.getY() >= searchRect.y && p.getY() <= searchRect.y + searchRect.height) {
// line end is left edge
p = p2;
}
}
d += searchRect.width;
data = getDistanceAndPointAtX(line, d);
if (data != null) {
p.setLocation((Point2D) data[1]);
if (p.getY() >= searchRect.y && p.getY() <= searchRect.y + searchRect.height) {
// line end is right edge
if (p == p1) p = p2;
else foundBoth = true;
}
}
if (!foundBoth) {
d = searchRect.y;
data = getDistanceAndPointAtY(line, d);
if (data != null) {
p.setLocation((Point2D) data[1]);
if (p.getX() >= searchRect.x && p.getX() <= searchRect.x + searchRect.width) {
// line end is top edge
if (p == p1) p = p2;
else if (!p1.equals(p2)) foundBoth = true;
}
}
}
if (!foundBoth) {
d += searchRect.height;
data = getDistanceAndPointAtY(line, d);
if (data != null) {
p.setLocation((Point2D) data[1]);
if (p.getX() >= searchRect.x && p.getX() <= searchRect.x + searchRect.width) {
// line end is bottom edge
if (p == p2 && !p1.equals(p2)) foundBoth = true;
}
}
}
// if both line ends have been found, use line to find pixels to search
if (foundBoth) {
// set line ends to intersections
line.setLine(p1, p2);
if (p1.getX() > p2.getX()) {
line.setLine(p2, p1);
}
// find pixel intersections that fall along the line
int xMin = (int) Math.ceil(Math.min(p1.getX(), p2.getX()));
int xMax = (int) Math.floor(Math.max(p1.getX(), p2.getX()));
int yMin = (int) Math.ceil(Math.min(p1.getY(), p2.getY()));
int yMax = (int) Math.floor(Math.max(p1.getY(), p2.getY()));
// collect intersections in TreeMap sorted by position along line
TreeMap<Double, Point2D> intersections = new TreeMap<Double, Point2D>();
for (int x = xMin; x <= xMax; x++) {
Object[] next = getDistanceAndPointAtX(line, x);
intersections.put((Double) next[0], (Point2D) next[1]);
}
for (int y = yMin; y <= yMax; y++) {
Object[] next = getDistanceAndPointAtY(line, y);
intersections.put((Double) next[0], (Point2D) next[1]);
}
p = null;
// create array of search points that are midway between intersections
ArrayList<Point2D> searchPts = new ArrayList<Point2D>();
for (Double key : intersections.keySet()) {
Point2D next = intersections.get(key);
if (p != null) {
double x = (p.getX() + next.getX()) / 2 - searchRect.x;
double y = (p.getY() + next.getY()) / 2 - searchRect.y;
p.setLocation(x, y);
searchPts.add(p);
}
p = next;
}
return searchPts;
}
return null;
}
/**
* Gets the template location at which the best match occurs in a rectangle and along a line. May
* return null.
*
* @param target the image to search
* @param searchRect the rectangle to search within the target image
* @param x0 the x-component of a point on the line
* @param y0 the y-component of a point on the line
* @param slope the slope of the line
* @param spread the spread of the line (line width = 1+2*spread)
* @return the optimized template location of the best match, if any
*/
public TPoint getMatchLocation(
BufferedImage target, Rectangle searchRect, double x0, double y0, double theta, int spread) {
wTarget = target.getWidth();
hTarget = target.getHeight();
// determine insets needed to accommodate template
int left = wTemplate / 2, right = left;
if (wTemplate % 2 > 0) right++;
int top = hTemplate / 2, bottom = top;
if (hTemplate % 2 > 0) bottom++;
// trim search rectangle if necessary
searchRect.x = Math.max(left, Math.min(wTarget - right, searchRect.x));
searchRect.y = Math.max(top, Math.min(hTarget - bottom, searchRect.y));
searchRect.width = Math.min(wTarget - searchRect.x - right, searchRect.width);
searchRect.height = Math.min(hTarget - searchRect.y - bottom, searchRect.height);
if (searchRect.width <= 0 || searchRect.height <= 0) {
peakHeight = Double.NaN;
peakWidth = Double.NaN;
return null;
}
// set up test pixels to search (rectangle plus template)
int xMin = Math.max(0, searchRect.x - left);
int xMax = Math.min(wTarget, searchRect.x + searchRect.width + right);
int yMin = Math.max(0, searchRect.y - top);
int yMax = Math.min(hTarget, searchRect.y + searchRect.height + bottom);
wTest = xMax - xMin;
hTest = yMax - yMin;
if (target.getType() != BufferedImage.TYPE_INT_RGB) {
BufferedImage image = new BufferedImage(wTarget, hTarget, BufferedImage.TYPE_INT_RGB);
image.createGraphics().drawImage(target, 0, 0, null);
target = image;
}
targetPixels = new int[wTest * hTest];
target.getRaster().getDataElements(xMin, yMin, wTest, hTest, targetPixels);
// get the points to search along the line
ArrayList<Point2D> searchPts = getSearchPoints(searchRect, x0, y0, theta);
if (searchPts == null) {
peakHeight = Double.NaN;
peakWidth = Double.NaN;
return null;
}
// collect differences in a map as they are measured
HashMap<Point2D, Double> diffs = new HashMap<Point2D, Double>();
// find the point with the minimum difference from template
double matchDiff = largeNumber; // larger than typical differences
int xMatch = 0, yMatch = 0;
double avgDiff = 0;
Point2D matchPt = null;
for (Point2D pt : searchPts) {
int x = (int) pt.getX();
int y = (int) pt.getY();
double diff = getDifferenceAtTestPoint(x, y);
diffs.put(pt, diff);
avgDiff += diff;
if (diff < matchDiff) {
matchDiff = diff;
xMatch = x;
yMatch = y;
matchPt = pt;
}
}
avgDiff /= searchPts.size();
peakHeight = avgDiff / matchDiff - 1;
peakWidth = Double.NaN;
double dl = 0;
int matchIndex = searchPts.indexOf(matchPt);
// if match is not exact, fit a Gaussian and find peak
if (!Double.isInfinite(peakHeight) && matchIndex > 0 && matchIndex < searchPts.size() - 1) {
// fill data arrays
Point2D pt = searchPts.get(matchIndex - 1);
double diff = diffs.get(pt);
xValues[0] = -pt.distance(matchPt);
yValues[0] = avgDiff / diff - 1;
xValues[1] = 0;
yValues[1] = peakHeight;
pt = searchPts.get(matchIndex + 1);
diff = diffs.get(pt);
xValues[2] = pt.distance(matchPt);
yValues[2] = avgDiff / diff - 1;
// determine approximate offset (dl) and width (w) values
double pull = -xValues[0] / (yValues[1] - yValues[0]);
double push = xValues[2] / (yValues[1] - yValues[2]);
if (Double.isNaN(pull)) pull = LARGE_NUMBER;
if (Double.isNaN(push)) push = LARGE_NUMBER;
dl = 0.3 * (xValues[2] - xValues[0]) * (push - pull) / (push + pull);
double ratio = dl > 0 ? peakHeight / yValues[0] : peakHeight / yValues[2];
double w = dl > 0 ? dl - xValues[0] : dl - xValues[2];
w = w * w / Math.log(ratio);
// set parameters and fit to x data
dataset.clear();
dataset.append(xValues, yValues);
double rmsDev = 1;
for (int k = 0; k < 3; k++) {
double c = k == 0 ? w : k == 1 ? w / 3 : w * 3;
f.setParameterValue(0, peakHeight);
f.setParameterValue(1, dl);
f.setParameterValue(2, c);
rmsDev = fitter.fit(f);
if (rmsDev < 0.01) { // fitter succeeded (3-point fit should be exact)
dl = f.getParameterValue(1);
peakWidth = f.getParameterValue(2);
break;
}
}
}
double dx = dl * Math.cos(theta);
double dy = dl * Math.sin(theta);
double xImage = xMatch + searchRect.x - left - trimLeft + dx;
double yImage = yMatch + searchRect.y - top - trimTop + dy;
return new TPoint(xImage, yImage);
}
/**
* Gets the template location at which the best match occurs in a rectangle. May return null.
*
* @param target the image to search
* @param searchRect the rectangle to search within the target image
* @return the optimized template location at which the best match, if any, is found
*/
public TPoint getMatchLocation(BufferedImage target, Rectangle searchRect) {
wTarget = target.getWidth();
hTarget = target.getHeight();
// determine insets needed to accommodate template
int left = wTemplate / 2, right = left;
if (wTemplate % 2 > 0) right++;
int top = hTemplate / 2, bottom = top;
if (hTemplate % 2 > 0) bottom++;
// trim search rectangle if necessary
searchRect.x = Math.max(left, Math.min(wTarget - right, searchRect.x));
searchRect.y = Math.max(top, Math.min(hTarget - bottom, searchRect.y));
searchRect.width = Math.min(wTarget - searchRect.x - right, searchRect.width);
searchRect.height = Math.min(hTarget - searchRect.y - bottom, searchRect.height);
if (searchRect.width <= 0 || searchRect.height <= 0) {
peakHeight = Double.NaN;
peakWidth = Double.NaN;
return null;
}
// set up test pixels to search (rectangle plus template)
int xMin = Math.max(0, searchRect.x - left);
int xMax = Math.min(wTarget, searchRect.x + searchRect.width + right);
int yMin = Math.max(0, searchRect.y - top);
int yMax = Math.min(hTarget, searchRect.y + searchRect.height + bottom);
wTest = xMax - xMin;
hTest = yMax - yMin;
if (target.getType() != BufferedImage.TYPE_INT_RGB) {
BufferedImage image = new BufferedImage(wTarget, hTarget, BufferedImage.TYPE_INT_RGB);
image.createGraphics().drawImage(target, 0, 0, null);
target = image;
}
targetPixels = new int[wTest * hTest];
target.getRaster().getDataElements(xMin, yMin, wTest, hTest, targetPixels);
// find the rectangle point with the minimum difference
double matchDiff = largeNumber; // larger than typical differences
int xMatch = 0, yMatch = 0;
double avgDiff = 0;
for (int x = 0; x <= searchRect.width; x++) {
for (int y = 0; y <= searchRect.height; y++) {
double diff = getDifferenceAtTestPoint(x, y);
avgDiff += diff;
if (diff < matchDiff) {
matchDiff = diff;
xMatch = x;
yMatch = y;
}
}
}
avgDiff /= (searchRect.width * searchRect.height);
peakHeight = avgDiff / matchDiff - 1;
peakWidth = Double.NaN;
double dx = 0, dy = 0;
// if match is not exact, fit a Gaussian and find peak
if (!Double.isInfinite(peakHeight)) {
// fill data arrays
xValues[1] = yValues[1] = peakHeight;
for (int i = -1; i < 2; i++) {
if (i == 0) continue;
double diff = getDifferenceAtTestPoint(xMatch + i, yMatch);
xValues[i + 1] = avgDiff / diff - 1;
diff = getDifferenceAtTestPoint(xMatch, yMatch + i);
yValues[i + 1] = avgDiff / diff - 1;
}
// estimate peakHeight = peak of gaussian
// estimate offset dx of gaussian
double pull = 1 / (xValues[1] - xValues[0]);
double push = 1 / (xValues[1] - xValues[2]);
if (Double.isNaN(pull)) pull = LARGE_NUMBER;
if (Double.isNaN(push)) push = LARGE_NUMBER;
dx = 0.6 * (push - pull) / (push + pull);
// estimate width wx of gaussian
double ratio = dx > 0 ? peakHeight / xValues[0] : peakHeight / xValues[2];
double wx = dx > 0 ? dx + 1 : dx - 1;
wx = wx * wx / Math.log(ratio);
// estimate offset dy of gaussian
pull = 1 / (yValues[1] - yValues[0]);
push = 1 / (yValues[1] - yValues[2]);
if (Double.isNaN(pull)) pull = LARGE_NUMBER;
if (Double.isNaN(push)) push = LARGE_NUMBER;
dy = 0.6 * (push - pull) / (push + pull);
// estimate width wy of gaussian
ratio = dy > 0 ? peakHeight / yValues[0] : peakHeight / yValues[2];
double wy = dy > 0 ? dy + 1 : dy - 1;
wy = wy * wy / Math.log(ratio);
// set x parameters and fit to x data
dataset.clear();
dataset.append(pixelOffsets, xValues);
double rmsDev = 1;
for (int k = 0; k < 3; k++) {
double c = k == 0 ? wx : k == 1 ? wx / 3 : wx * 3;
f.setParameterValue(0, peakHeight);
f.setParameterValue(1, dx);
f.setParameterValue(2, c);
rmsDev = fitter.fit(f);
if (rmsDev < 0.01) { // fitter succeeded (3-point fit should be exact)
dx = f.getParameterValue(1);
peakWidth = f.getParameterValue(2);
break;
}
}
if (!Double.isNaN(peakWidth)) {
// set y parameters and fit to y data
dataset.clear();
dataset.append(pixelOffsets, yValues);
for (int k = 0; k < 3; k++) {
double c = k == 0 ? wy : k == 1 ? wy / 3 : wy * 3;
f.setParameterValue(0, peakHeight);
f.setParameterValue(1, dx);
f.setParameterValue(2, c);
rmsDev = fitter.fit(f);
if (rmsDev < 0.01) { // fitter succeeded (3-point fit should be exact)
dy = f.getParameterValue(1);
peakWidth = (peakWidth + f.getParameterValue(2)) / 2;
break;
}
}
if (rmsDev > 0.01) peakWidth = Double.NaN;
}
}
double xImage = xMatch + searchRect.x - left - trimLeft + dx;
double yImage = yMatch + searchRect.y - top - trimTop + dy;
return new TPoint(xImage, yImage);
}
/**
* Rebuilds the template from an input image. The input image dimensions must match the original.
* The input and original are overlaid onto the existing template, if any. Pixels that fall
* outside the mask are ignored in the final template.
*
* @param image the input image
* @param alphaInput the opacity with which the input image is overlaid
* @param alphaOriginal the opacity with which the original image is overlaid
*/
public void rebuildTemplate(BufferedImage image, int alphaInput, int alphaOriginal) {
int w = image.getWidth();
int h = image.getHeight();
// return if image dimensions do not match original image
if (original.getWidth() != w || original.getHeight() != h) return;
// return if both alphas are zero
if (alphaInput == 0 && alphaOriginal == 0) return;
// draw image onto argb input
BufferedImage input = new BufferedImage(w, h, BufferedImage.TYPE_INT_ARGB);
input.createGraphics().drawImage(image, 0, 0, null);
// create working image if needed
if (working == null) {
working = new BufferedImage(w, h, BufferedImage.TYPE_INT_ARGB);
}
// reset template dimensions and create new template if needed
if (template == null || w != wTemplate || h != hTemplate) {
wTemplate = w;
hTemplate = h;
int len = w * h;
template = new BufferedImage(w, h, BufferedImage.TYPE_INT_ARGB);
pixels = new int[len];
templateR = new int[len];
templateG = new int[len];
templateB = new int[len];
isPixelTransparent = new boolean[len];
}
// set alpha of input and draw onto working
Graphics2D gWorking = working.createGraphics();
alphaInput = Math.max(0, Math.min(255, alphaInput));
if (alphaInput > 0) { // overlay only if not transparent
gWorking.setComposite(getComposite(alphaInput));
input.getRaster().getDataElements(0, 0, w, h, pixels);
gWorking.drawImage(input, 0, 0, null);
}
// set alpha of original and draw onto working
alphaOriginal = Math.max(0, Math.min(255, alphaOriginal));
if (alphaOriginal > 0) { // overlay only if not transparent
gWorking.setComposite(getComposite(alphaOriginal));
original.getRaster().getDataElements(0, 0, w, h, pixels);
gWorking.drawImage(original, 0, 0, null);
}
// read pixels from working raster
working.getRaster().getDataElements(0, 0, wTemplate, hTemplate, pixels);
if (mask != null) {
// set pixels outside mask to transparent
for (int i = 0; i < pixels.length; i++) {
boolean inside = true;
// pixel is inside only if all corners are inside
int x = i % wTemplate, y = i / wTemplate;
for (int j = 0; j < 2; j++) {
for (int k = 0; k < 2; k++) {
p.setLocation(x + j, y + k);
inside = inside && mask.contains(p);
}
}
if (!inside) pixels[i] = pixels[i] & (0 << 24); // set alpha to zero (transparent)
}
}
// write pixels to template raster
template.getRaster().setDataElements(0, 0, wTemplate, hTemplate, pixels);
// trim transparent edges from template
int trimRight = 0, trimBottom = 0;
trimLeft = trimTop = 0;
// left edge
boolean transparentEdge = true;
while (transparentEdge && trimLeft < wTemplate) {
for (int line = 0; line < hTemplate; line++) {
int i = line * wTemplate + trimLeft;
transparentEdge = transparentEdge && getAlpha(pixels[i]) == 0;
}
if (transparentEdge) trimLeft++;
}
// right edge
transparentEdge = true;
while (transparentEdge && (trimLeft + trimRight) < wTemplate) {
for (int line = 0; line < hTemplate; line++) {
int i = (line + 1) * wTemplate - 1 - trimRight;
transparentEdge = transparentEdge && getAlpha(pixels[i]) == 0;
}
if (transparentEdge) trimRight++;
}
// top edge
transparentEdge = true;
while (transparentEdge && trimTop < hTemplate) {
for (int col = 0; col < wTemplate; col++) {
int i = trimTop * wTemplate + col;
transparentEdge = transparentEdge && getAlpha(pixels[i]) == 0;
}
if (transparentEdge) trimTop++;
}
// bottom edge
transparentEdge = true;
while (transparentEdge && (trimTop + trimBottom) < hTemplate) {
for (int col = 0; col < wTemplate; col++) {
int i = (hTemplate - 1 - trimBottom) * wTemplate + col;
transparentEdge = transparentEdge && getAlpha(pixels[i]) == 0;
}
if (transparentEdge) trimBottom++;
}
// reduce size of template if needed
if (trimLeft + trimRight + trimTop + trimBottom > 0) {
wTemplate -= (trimLeft + trimRight);
hTemplate -= (trimTop + trimBottom);
pixels = new int[wTemplate * hTemplate];
templateR = new int[wTemplate * hTemplate];
templateG = new int[wTemplate * hTemplate];
templateB = new int[wTemplate * hTemplate];
isPixelTransparent = new boolean[wTemplate * hTemplate];
BufferedImage bi = new BufferedImage(wTemplate, hTemplate, BufferedImage.TYPE_INT_ARGB);
bi.createGraphics().drawImage(template, -trimLeft, -trimTop, null);
template = bi;
template.getRaster().getDataElements(0, 0, wTemplate, hTemplate, pixels);
}
// set up rgb and transparency arrays for faster matching
for (int i = 0; i < pixels.length; i++) {
int val = pixels[i];
templateR[i] = getRed(val); // red
templateG[i] = getGreen(val); // green
templateB[i] = getBlue(val); // blue
isPixelTransparent[i] = getAlpha(val) == 0; // alpha
}
}