private void getintbright() {
weights = new float[ncurves][xpts][ypts];
for (int i = 0; i < ncurves; i++) {
nmeas[i] = 0;
for (int j = 0; j < xpts; j++) {
for (int k = 0; k < ypts; k++) {
nmeas[i] += (int) pch[i][j][k];
}
}
double tempavg = 0.0;
double tempavg2 = 0.0;
double temp2avg = 0.0;
double temp2avg2 = 0.0;
double tempccavg = 0.0;
for (int j = 0; j < xpts; j++) {
for (int k = 0; k < ypts; k++) {
double normed = (double) pch[i][j][k] / (double) nmeas[i];
if (pch[i][j][k] > 0.0f) {
weights[i][j][k] = (float) ((double) nmeas[i] / (normed * (1.0f - normed)));
} else {
weights[i][j][k] = 1.0f;
}
tempavg += normed * (double) j;
tempavg2 += normed * (double) j * (double) j;
temp2avg += normed * (double) k;
temp2avg2 += normed * (double) k * (double) k;
tempccavg += normed * (double) k * (double) j;
}
}
tempccavg -= tempavg * temp2avg;
brightcc[i] = tempccavg / Math.sqrt(tempavg * temp2avg);
tempavg2 -= tempavg * tempavg;
tempavg2 /= tempavg;
bright1[i] = (tempavg2 - 1.0);
temp2avg2 -= temp2avg * temp2avg;
temp2avg2 /= temp2avg;
bright2[i] = (temp2avg2 - 1.0);
intensity1[i] = tempavg;
intensity2[i] = temp2avg;
if (psfflag == 0) {
bright1[i] /= 0.3536;
bright2[i] /= 0.3536;
brightcc[i] /= 0.3536;
} else {
if (psfflag == 1) {
bright1[i] /= 0.078;
bright2[i] /= 0.078;
brightcc[i] /= 0.078;
} else {
bright1[i] /= 0.5;
bright2[i] /= 0.5;
brightcc[i] /= 0.5;
}
}
number1[i] = intensity1[i] / bright1[i];
number2[i] = intensity2[i] / bright2[i];
brightmincc[i] = (bright1[i] * beta) * Math.sqrt(intensity1[i] / intensity2[i]);
}
}
/* Creates a spline fitted polygon with one pixel segment lengths
that can be retrieved using the getFloatPolygon() method. */
public void fitSplineForStraightening() {
fitSpline((int) getUncalibratedLength() * 2);
if (splinePoints == 0) return;
float[] xpoints = new float[splinePoints * 2];
float[] ypoints = new float[splinePoints * 2];
xpoints[0] = xSpline[0];
ypoints[0] = ySpline[0];
int n = 1, n2;
double inc = 0.01;
double distance = 0.0, distance2 = 0.0, dx = 0.0, dy = 0.0, xinc, yinc;
double x, y, lastx, lasty, x1, y1, x2 = xSpline[0], y2 = ySpline[0];
for (int i = 1; i < splinePoints; i++) {
x1 = x2;
y1 = y2;
x = x1;
y = y1;
x2 = xSpline[i];
y2 = ySpline[i];
dx = x2 - x1;
dy = y2 - y1;
distance = Math.sqrt(dx * dx + dy * dy);
xinc = dx * inc / distance;
yinc = dy * inc / distance;
lastx = xpoints[n - 1];
lasty = ypoints[n - 1];
// n2 = (int)(dx/xinc);
n2 = (int) (distance / inc);
if (splinePoints == 2) n2++;
do {
dx = x - lastx;
dy = y - lasty;
distance2 = Math.sqrt(dx * dx + dy * dy);
// IJ.log(i+" "+IJ.d2s(xinc,5)+" "+IJ.d2s(yinc,5)+" "+IJ.d2s(distance,2)+"
// "+IJ.d2s(distance2,2)+" "+IJ.d2s(x,2)+" "+IJ.d2s(y,2)+" "+IJ.d2s(lastx,2)+"
// "+IJ.d2s(lasty,2)+" "+n+" "+n2);
if (distance2 >= 1.0 - inc / 2.0 && n < xpoints.length - 1) {
xpoints[n] = (float) x;
ypoints[n] = (float) y;
// IJ.log("--- "+IJ.d2s(x,2)+" "+IJ.d2s(y,2)+" "+n);
n++;
lastx = x;
lasty = y;
}
x += xinc;
y += yinc;
} while (--n2 > 0);
}
xSpline = xpoints;
ySpline = ypoints;
splinePoints = n;
}
/**
* Returns the perimeter length of ROIs created using the wand tool and the particle analyzer. The
* algorithm counts edge pixels as 1 and corner pixels as sqrt(2). It does this by calculating the
* total length of the ROI boundary and subtracting 2-sqrt(2) for each non-adjacent corner. For
* example, a 1x1 pixel ROI has a boundary length of 4 and 2 non-adjacent edges so the perimeter
* is 4-2*(2-sqrt(2)). A 2x2 pixel ROI has a boundary length of 8 and 4 non-adjacent edges so the
* perimeter is 8-4*(2-sqrt(2)).
*/
double getTracedPerimeter() {
int sumdx = 0;
int sumdy = 0;
int nCorners = 0;
int dx1 = xp[0] - xp[nPoints - 1];
int dy1 = yp[0] - yp[nPoints - 1];
int side1 = Math.abs(dx1) + Math.abs(dy1); // one of these is 0
boolean corner = false;
int nexti, dx2, dy2, side2;
for (int i = 0; i < nPoints; i++) {
nexti = i + 1;
if (nexti == nPoints) nexti = 0;
dx2 = xp[nexti] - xp[i];
dy2 = yp[nexti] - yp[i];
sumdx += Math.abs(dx1);
sumdy += Math.abs(dy1);
side2 = Math.abs(dx2) + Math.abs(dy2);
if (side1 > 1 || !corner) {
corner = true;
nCorners++;
} else corner = false;
dx1 = dx2;
dy1 = dy2;
side1 = side2;
}
double w = 1.0, h = 1.0;
if (imp != null) {
Calibration cal = imp.getCalibration();
w = cal.pixelWidth;
h = cal.pixelHeight;
}
return sumdx * w + sumdy * h - (nCorners * ((w + h) - Math.sqrt(w * w + h * h)));
}
void handleMouseMove(int sx, int sy) {
// Do rubber banding
int tool = Toolbar.getToolId();
if (!(tool == Toolbar.POLYGON || tool == Toolbar.POLYLINE || tool == Toolbar.ANGLE)) {
imp.deleteRoi();
imp.draw();
return;
}
drawRubberBand(sx, sy);
degrees = Double.NaN;
double len = -1;
if (nPoints > 1) {
double x1, y1, x2, y2;
if (xpf != null) {
x1 = xpf[nPoints - 2];
y1 = ypf[nPoints - 2];
x2 = xpf[nPoints - 1];
y2 = ypf[nPoints - 1];
} else {
x1 = xp[nPoints - 2];
y1 = yp[nPoints - 2];
x2 = xp[nPoints - 1];
y2 = yp[nPoints - 1];
}
degrees =
getAngle(
(int) Math.round(x1),
(int) Math.round(y1),
(int) Math.round(x2),
(int) Math.round(y2));
if (tool != Toolbar.ANGLE) {
Calibration cal = imp.getCalibration();
double pw = cal.pixelWidth, ph = cal.pixelHeight;
if (IJ.altKeyDown()) {
pw = 1.0;
ph = 1.0;
}
len = Math.sqrt((x2 - x1) * pw * (x2 - x1) * pw + (y2 - y1) * ph * (y2 - y1) * ph);
}
}
if (tool == Toolbar.ANGLE) {
if (nPoints == 2) angle1 = degrees;
else if (nPoints == 3) {
double angle2 = getAngle(xp[1], yp[1], xp[2], yp[2]);
degrees = Math.abs(180 - Math.abs(angle1 - angle2));
if (degrees > 180.0) degrees = 360.0 - degrees;
}
}
String length = len != -1 ? ", length=" + IJ.d2s(len) : "";
double degrees2 =
tool == Toolbar.ANGLE && nPoints == 3 && Prefs.reflexAngle ? 360.0 - degrees : degrees;
String angle = !Double.isNaN(degrees) ? ", angle=" + IJ.d2s(degrees2) : "";
int ox = ic != null ? ic.offScreenX(sx) : sx;
int oy = ic != null ? ic.offScreenY(sy) : sy;
IJ.showStatus(imp.getLocationAsString(ox, oy) + length + angle);
}
PolygonRoi trimPolygon(PolygonRoi roi, double length) {
int[] x = roi.getXCoordinates();
int[] y = roi.getYCoordinates();
int n = roi.getNCoordinates();
x = smooth(x, n);
y = smooth(y, n);
float[] curvature = getCurvature(x, y, n);
Rectangle r = roi.getBounds();
double threshold = rodbard(length);
// IJ.log("trim: "+length+" "+threshold);
double distance = Math.sqrt((x[1] - x[0]) * (x[1] - x[0]) + (y[1] - y[0]) * (y[1] - y[0]));
x[0] += r.x;
y[0] += r.y;
int i2 = 1;
int x1, y1, x2 = 0, y2 = 0;
for (int i = 1; i < n - 1; i++) {
x1 = x[i];
y1 = y[i];
x2 = x[i + 1];
y2 = y[i + 1];
distance += Math.sqrt((x2 - x1) * (x2 - x1) + (y2 - y1) * (y2 - y1)) + 1;
distance += curvature[i] * 2;
if (distance >= threshold) {
x[i2] = x2 + r.x;
y[i2] = y2 + r.y;
i2++;
distance = 0.0;
}
}
int type = roi.getType() == Roi.FREELINE ? Roi.POLYLINE : Roi.POLYGON;
if (type == Roi.POLYLINE && distance > 0.0) {
x[i2] = x2 + r.x;
y[i2] = y2 + r.y;
i2++;
}
PolygonRoi p = new PolygonRoi(x, y, i2, type);
if (roi.getStroke() != null) p.setStrokeWidth(roi.getStrokeWidth());
p.setStrokeColor(roi.getStrokeColor());
p.setName(roi.getName());
imp.setRoi(p);
return p;
}
public void postProcess() {
double stdDev;
double n = num;
for (int i = 0; i < len; i++) {
if (num > 1) {
stdDev = (n * sum2[i] - sum[i] * sum[i]) / n;
if (stdDev > 0.0) result[i] = (float) Math.sqrt(stdDev / (n - 1.0));
else result[i] = 0f;
} else result[i] = 0f;
}
}
PolygonRoi trimFloatPolygon(PolygonRoi roi, double length) {
FloatPolygon poly = roi.getFloatPolygon();
float[] x = poly.xpoints;
float[] y = poly.ypoints;
int n = poly.npoints;
x = smooth(x, n);
y = smooth(y, n);
float[] curvature = getCurvature(x, y, n);
double threshold = rodbard(length);
// IJ.log("trim: "+length+" "+threshold);
double distance = Math.sqrt((x[1] - x[0]) * (x[1] - x[0]) + (y[1] - y[0]) * (y[1] - y[0]));
int i2 = 1;
double x1, y1, x2 = 0, y2 = 0;
for (int i = 1; i < n - 1; i++) {
x1 = x[i];
y1 = y[i];
x2 = x[i + 1];
y2 = y[i + 1];
distance += Math.sqrt((x2 - x1) * (x2 - x1) + (y2 - y1) * (y2 - y1)) + 1;
distance += curvature[i] * 2;
if (distance >= threshold) {
x[i2] = (float) x2;
y[i2] = (float) y2;
i2++;
distance = 0.0;
}
}
int type = roi.getType() == Roi.FREELINE ? Roi.POLYLINE : Roi.POLYGON;
if (type == Roi.POLYLINE && distance > 0.0) {
x[i2] = (float) x2;
y[i2] = (float) y2;
i2++;
}
PolygonRoi p = new PolygonRoi(x, y, i2, type);
if (roi.getStroke() != null) p.setStrokeWidth(roi.getStrokeWidth());
p.setStrokeColor(roi.getStrokeColor());
p.setDrawOffset(roi.getDrawOffset());
p.setName(roi.getName());
imp.setRoi(p);
return p;
}
double getFloatSmoothedPerimeter() {
double length = getSmoothedLineLength();
double w2 = 1.0, h2 = 1.0;
if (imp != null) {
Calibration cal = imp.getCalibration();
w2 = cal.pixelWidth * cal.pixelWidth;
h2 = cal.pixelHeight * cal.pixelHeight;
}
double dx = xpf[nPoints - 1] - xpf[0];
double dy = ypf[nPoints - 1] - ypf[0];
length += Math.sqrt(dx * dx * w2 + dy * dy * h2);
return length;
}
double getFloatSmoothedLineLength() {
double length = 0.0;
double w2 = 1.0;
double h2 = 1.0;
double dx, dy;
if (imp != null) {
Calibration cal = imp.getCalibration();
w2 = cal.pixelWidth * cal.pixelWidth;
h2 = cal.pixelHeight * cal.pixelHeight;
}
dx = (xpf[0] + xpf[1] + xpf[2]) / 3.0 - xpf[0];
dy = (ypf[0] + ypf[1] + ypf[2]) / 3.0 - ypf[0];
length += Math.sqrt(dx * dx * w2 + dy * dy * h2);
for (int i = 1; i < nPoints - 2; i++) {
dx = (xpf[i + 2] - xpf[i - 1]) / 3.0;
dy = (ypf[i + 2] - ypf[i - 1]) / 3.0;
length += Math.sqrt(dx * dx * w2 + dy * dy * h2);
}
dx = xpf[nPoints - 1] - (xpf[nPoints - 3] + xpf[nPoints - 2] + xpf[nPoints - 1]) / 3.0;
dy = ypf[nPoints - 1] - (ypf[nPoints - 3] + ypf[nPoints - 2] + ypf[nPoints - 1]) / 3.0;
length += Math.sqrt(dx * dx * w2 + dy * dy * h2);
return length;
}
/*
* For a list of r² values, find the smallest r1² values such that a "ball"
* of radius r1 centered at (dx,dy,dz) includes a "ball" of radius r
* centered at the origin. "Ball" refers to a 3D integer grid.
*/
int[] scanCube(int dx, int dy, int dz, int[] distSqValues) {
final int numRadii = distSqValues.length;
int[] r1Sq = new int[numRadii];
if ((dx == 0) && (dy == 0) && (dz == 0)) {
for (int rSq = 0; rSq < numRadii; rSq++) {
r1Sq[rSq] = Integer.MAX_VALUE;
}
} else {
final int dxAbs = -(int) Math.abs(dx);
final int dyAbs = -(int) Math.abs(dy);
final int dzAbs = -(int) Math.abs(dz);
for (int rSqInd = 0; rSqInd < numRadii; rSqInd++) {
final int rSq = distSqValues[rSqInd];
int max = 0;
final int r = 1 + (int) Math.sqrt(rSq);
int scank, scankj;
int dk, dkji;
// int iBall;
int iPlus;
for (int k = 0; k <= r; k++) {
scank = k * k;
dk = (k - dzAbs) * (k - dzAbs);
for (int j = 0; j <= r; j++) {
scankj = scank + j * j;
if (scankj <= rSq) {
iPlus = ((int) Math.sqrt(rSq - scankj)) - dxAbs;
dkji = dk + (j - dyAbs) * (j - dyAbs) + iPlus * iPlus;
if (dkji > max) max = dkji;
}
}
}
r1Sq[rSqInd] = max;
}
}
return r1Sq;
}
/** Returns the perimeter (for ROIs) or length (for lines). */
public double getLength() {
if (type == TRACED_ROI) return getTracedPerimeter();
if (nPoints > 2) {
if (type == FREEROI) return getSmoothedPerimeter();
else if (type == FREELINE && !(width == 0 || height == 0)) return getSmoothedLineLength();
}
double length = 0.0;
int dx, dy;
double w2 = 1.0, h2 = 1.0;
if (imp != null) {
Calibration cal = imp.getCalibration();
w2 = cal.pixelWidth * cal.pixelWidth;
h2 = cal.pixelHeight * cal.pixelHeight;
}
if (xSpline != null) {
double fdx, fdy;
for (int i = 0; i < (splinePoints - 1); i++) {
fdx = xSpline[i + 1] - xSpline[i];
fdy = ySpline[i + 1] - ySpline[i];
length += Math.sqrt(fdx * fdx * w2 + fdy * fdy * h2);
}
if (type == POLYGON) {
fdx = xSpline[0] - xSpline[splinePoints - 1];
fdy = ySpline[0] - ySpline[splinePoints - 1];
length += Math.sqrt(fdx * fdx * w2 + fdy * fdy * h2);
}
} else if (xpf != null) {
double fdx, fdy;
for (int i = 0; i < (nPoints - 1); i++) {
fdx = xpf[i + 1] - xpf[i];
fdy = ypf[i + 1] - ypf[i];
length += Math.sqrt(fdx * fdx * w2 + fdy * fdy * h2);
}
if (type == POLYGON) {
fdx = xpf[0] - xpf[nPoints - 1];
fdy = ypf[0] - ypf[nPoints - 1];
length += Math.sqrt(fdx * fdx * w2 + fdy * fdy * h2);
}
} else {
for (int i = 0; i < (nPoints - 1); i++) {
dx = xp[i + 1] - xp[i];
dy = yp[i + 1] - yp[i];
length += Math.sqrt(dx * dx * w2 + dy * dy * h2);
}
if (type == POLYGON) {
dx = xp[0] - xp[nPoints - 1];
dy = yp[0] - yp[nPoints - 1];
length += Math.sqrt(dx * dx * w2 + dy * dy * h2);
}
}
return length;
}
float[] getCurvature(float[] x, float[] y, int n) {
float[] x2 = new float[n];
float[] y2 = new float[n];
for (int i = 0; i < n; i++) {
x2[i] = x[i];
y2[i] = y[i];
}
ImageProcessor ipx = new FloatProcessor(n, 1, x, null);
ImageProcessor ipy = new FloatProcessor(n, 1, y, null);
ipx.convolve(kernel, kernel.length, 1);
ipy.convolve(kernel, kernel.length, 1);
float[] indexes = new float[n];
float[] curvature = new float[n];
for (int i = 0; i < n; i++) {
indexes[i] = i;
curvature[i] =
(float) Math.sqrt((x2[i] - x[i]) * (x2[i] - x[i]) + (y2[i] - y[i]) * (y2[i] - y[i]));
}
return curvature;
}
/*------------------------------------------------------------------*/
void getSplineInterpolationCoefficients(double[] c, double tolerance) {
double z[] = {Math.sqrt(3.0) - 2.0};
double lambda = 1.0;
if (c.length == 1) {
return;
}
for (int k = 0; (k < z.length); k++) {
lambda = lambda * (1.0 - z[k]) * (1.0 - 1.0 / z[k]);
}
for (int n = 0; (n < c.length); n++) {
c[n] = c[n] * lambda;
}
for (int k = 0; (k < z.length); k++) {
c[0] = getInitialCausalCoefficientMirrorOnBounds(c, z[k], tolerance);
for (int n = 1; (n < c.length); n++) {
c[n] = c[n] + z[k] * c[n - 1];
}
c[c.length - 1] = getInitialAntiCausalCoefficientMirrorOnBounds(c, z[k], tolerance);
for (int n = c.length - 2; (0 <= n); n--) {
c[n] = z[k] * (c[n + 1] - c[n]);
}
}
} /* end getSplineInterpolationCoefficients */
public boolean dialogItemChanged(GenericDialog gd, AWTEvent e) {
int width = imp.getWidth();
int height = imp.getHeight();
type = gd.getNextChoice();
areaPerPoint = gd.getNextNumber();
color = gd.getNextChoice();
randomOffset = gd.getNextBoolean();
double minArea = (width * height) / 50000.0;
if (type.equals(types[1]) && minArea < 144.0) minArea = 144.0;
else if (minArea < 16) minArea = 16.0;
if (areaPerPoint / (pixelWidth * pixelHeight) < minArea) {
String err = "\"Area per Point\" too small";
if (gd.wasOKed()) IJ.error("Grid", err);
else IJ.showStatus(err);
return true;
}
double tileSize = Math.sqrt(areaPerPoint);
tileWidth = tileSize / pixelWidth;
tileHeight = tileSize / pixelHeight;
if (randomOffset) {
xstart = (int) (random.nextDouble() * tileWidth);
ystart = (int) (random.nextDouble() * tileHeight);
} else {
xstart = (int) (tileWidth / 2.0 + 0.5);
ystart = (int) (tileHeight / 2.0 + 0.5);
}
linesV = (int) ((width - xstart) / tileWidth) + 1;
linesH = (int) ((height - ystart) / tileHeight) + 1;
if (gd.invalidNumber()) return true;
if (type.equals(types[0])) drawLines();
else if (type.equals(types[1])) drawCrosses();
else if (type.equals(types[2])) drawPoints();
else showGrid(null);
return true;
}
String getInfo(ImagePlus imp, ImageProcessor ip) {
String s = new String("\n");
s += "Title: " + imp.getTitle() + "\n";
Calibration cal = imp.getCalibration();
int stackSize = imp.getStackSize();
int channels = imp.getNChannels();
int slices = imp.getNSlices();
int frames = imp.getNFrames();
int digits = imp.getBitDepth() == 32 ? 4 : 0;
if (cal.scaled()) {
String unit = cal.getUnit();
String units = cal.getUnits();
s +=
"Width: "
+ IJ.d2s(imp.getWidth() * cal.pixelWidth, 2)
+ " "
+ units
+ " ("
+ imp.getWidth()
+ ")\n";
s +=
"Height: "
+ IJ.d2s(imp.getHeight() * cal.pixelHeight, 2)
+ " "
+ units
+ " ("
+ imp.getHeight()
+ ")\n";
if (slices > 1)
s += "Depth: " + IJ.d2s(slices * cal.pixelDepth, 2) + " " + units + " (" + slices + ")\n";
double xResolution = 1.0 / cal.pixelWidth;
double yResolution = 1.0 / cal.pixelHeight;
int places = Tools.getDecimalPlaces(xResolution, yResolution);
if (xResolution == yResolution)
s += "Resolution: " + IJ.d2s(xResolution, places) + " pixels per " + unit + "\n";
else {
s += "X Resolution: " + IJ.d2s(xResolution, places) + " pixels per " + unit + "\n";
s += "Y Resolution: " + IJ.d2s(yResolution, places) + " pixels per " + unit + "\n";
}
} else {
s += "Width: " + imp.getWidth() + " pixels\n";
s += "Height: " + imp.getHeight() + " pixels\n";
if (stackSize > 1) s += "Depth: " + slices + " pixels\n";
}
if (stackSize > 1)
s +=
"Voxel size: "
+ d2s(cal.pixelWidth)
+ "x"
+ d2s(cal.pixelHeight)
+ "x"
+ d2s(cal.pixelDepth)
+ " "
+ cal.getUnit()
+ "\n";
else
s +=
"Pixel size: "
+ d2s(cal.pixelWidth)
+ "x"
+ d2s(cal.pixelHeight)
+ " "
+ cal.getUnit()
+ "\n";
s += "ID: " + imp.getID() + "\n";
String zOrigin = stackSize > 1 || cal.zOrigin != 0.0 ? "," + d2s(cal.zOrigin) : "";
s += "Coordinate origin: " + d2s(cal.xOrigin) + "," + d2s(cal.yOrigin) + zOrigin + "\n";
int type = imp.getType();
switch (type) {
case ImagePlus.GRAY8:
s += "Bits per pixel: 8 ";
String lut = "LUT";
if (imp.getProcessor().isColorLut()) lut = "color " + lut;
else lut = "grayscale " + lut;
if (imp.isInvertedLut()) lut = "inverting " + lut;
s += "(" + lut + ")\n";
if (imp.getNChannels() > 1) s += displayRanges(imp);
else s += "Display range: " + (int) ip.getMin() + "-" + (int) ip.getMax() + "\n";
break;
case ImagePlus.GRAY16:
case ImagePlus.GRAY32:
if (type == ImagePlus.GRAY16) {
String sign = cal.isSigned16Bit() ? "signed" : "unsigned";
s += "Bits per pixel: 16 (" + sign + ")\n";
} else s += "Bits per pixel: 32 (float)\n";
if (imp.getNChannels() > 1) s += displayRanges(imp);
else {
s += "Display range: ";
double min = ip.getMin();
double max = ip.getMax();
if (cal.calibrated()) {
min = cal.getCValue((int) min);
max = cal.getCValue((int) max);
}
s += IJ.d2s(min, digits) + " - " + IJ.d2s(max, digits) + "\n";
}
break;
case ImagePlus.COLOR_256:
s += "Bits per pixel: 8 (color LUT)\n";
break;
case ImagePlus.COLOR_RGB:
s += "Bits per pixel: 32 (RGB)\n";
break;
}
double interval = cal.frameInterval;
double fps = cal.fps;
if (stackSize > 1) {
ImageStack stack = imp.getStack();
int slice = imp.getCurrentSlice();
String number = slice + "/" + stackSize;
String label = stack.getShortSliceLabel(slice);
if (label != null && label.length() > 0) label = " (" + label + ")";
else label = "";
if (interval > 0.0 || fps != 0.0) {
s += "Frame: " + number + label + "\n";
if (fps != 0.0) {
String sRate =
Math.abs(fps - Math.round(fps)) < 0.00001 ? IJ.d2s(fps, 0) : IJ.d2s(fps, 5);
s += "Frame rate: " + sRate + " fps\n";
}
if (interval != 0.0)
s +=
"Frame interval: "
+ ((int) interval == interval ? IJ.d2s(interval, 0) : IJ.d2s(interval, 5))
+ " "
+ cal.getTimeUnit()
+ "\n";
} else s += "Image: " + number + label + "\n";
if (imp.isHyperStack()) {
if (channels > 1) s += " Channel: " + imp.getChannel() + "/" + channels + "\n";
if (slices > 1) s += " Slice: " + imp.getSlice() + "/" + slices + "\n";
if (frames > 1) s += " Frame: " + imp.getFrame() + "/" + frames + "\n";
}
if (imp.isComposite()) {
if (!imp.isHyperStack() && channels > 1) s += " Channels: " + channels + "\n";
String mode = ((CompositeImage) imp).getModeAsString();
s += " Composite mode: \"" + mode + "\"\n";
}
}
if (ip.getMinThreshold() == ImageProcessor.NO_THRESHOLD) s += "No Threshold\n";
else {
double lower = ip.getMinThreshold();
double upper = ip.getMaxThreshold();
int dp = digits;
if (cal.calibrated()) {
lower = cal.getCValue((int) lower);
upper = cal.getCValue((int) upper);
dp = cal.isSigned16Bit() ? 0 : 4;
}
s += "Threshold: " + IJ.d2s(lower, dp) + "-" + IJ.d2s(upper, dp) + "\n";
}
ImageCanvas ic = imp.getCanvas();
double mag = ic != null ? ic.getMagnification() : 1.0;
if (mag != 1.0) s += "Magnification: " + IJ.d2s(mag, 2) + "\n";
if (cal.calibrated()) {
s += " \n";
int curveFit = cal.getFunction();
s += "Calibration Function: ";
if (curveFit == Calibration.UNCALIBRATED_OD) s += "Uncalibrated OD\n";
else if (curveFit == Calibration.CUSTOM) s += "Custom lookup table\n";
else s += CurveFitter.fList[curveFit] + "\n";
double[] c = cal.getCoefficients();
if (c != null) {
s += " a: " + IJ.d2s(c[0], 6) + "\n";
s += " b: " + IJ.d2s(c[1], 6) + "\n";
if (c.length >= 3) s += " c: " + IJ.d2s(c[2], 6) + "\n";
if (c.length >= 4) s += " c: " + IJ.d2s(c[3], 6) + "\n";
if (c.length >= 5) s += " c: " + IJ.d2s(c[4], 6) + "\n";
}
s += " Unit: \"" + cal.getValueUnit() + "\"\n";
} else s += "Uncalibrated\n";
FileInfo fi = imp.getOriginalFileInfo();
if (fi != null) {
if (fi.url != null && !fi.url.equals("")) s += "URL: " + fi.url + "\n";
else if (fi.directory != null && fi.fileName != null)
s += "Path: " + fi.directory + fi.fileName + "\n";
}
ImageWindow win = imp.getWindow();
if (win != null) {
Point loc = win.getLocation();
Dimension screen = IJ.getScreenSize();
s +=
"Screen location: "
+ loc.x
+ ","
+ loc.y
+ " ("
+ screen.width
+ "x"
+ screen.height
+ ")\n";
}
Overlay overlay = imp.getOverlay();
if (overlay != null) {
String hidden = imp.getHideOverlay() ? " (hidden)" : " ";
int n = overlay.size();
String elements = n == 1 ? " element" : " elements";
s += "Overlay: " + n + elements + (imp.getHideOverlay() ? " (hidden)" : "") + "\n";
} else s += "No Overlay\n";
Roi roi = imp.getRoi();
if (roi == null) {
if (cal.calibrated()) s += " \n";
s += "No Selection\n";
} else if (roi instanceof EllipseRoi) {
s += "\nElliptical Selection\n";
double[] p = ((EllipseRoi) roi).getParams();
double dx = p[2] - p[0];
double dy = p[3] - p[1];
double major = Math.sqrt(dx * dx + dy * dy);
s += " Major: " + IJ.d2s(major, 2) + "\n";
s += " Minor: " + IJ.d2s(major * p[4], 2) + "\n";
s += " X1: " + IJ.d2s(p[0], 2) + "\n";
s += " Y1: " + IJ.d2s(p[1], 2) + "\n";
s += " X2: " + IJ.d2s(p[2], 2) + "\n";
s += " Y2: " + IJ.d2s(p[3], 2) + "\n";
s += " Aspect ratio: " + IJ.d2s(p[4], 2) + "\n";
} else {
s += " \n";
s += roi.getTypeAsString() + " Selection";
String points = null;
if (roi instanceof PointRoi) {
int npoints = ((PolygonRoi) roi).getNCoordinates();
String suffix = npoints > 1 ? "s)" : ")";
points = " (" + npoints + " point" + suffix;
}
String name = roi.getName();
if (name != null) {
s += " (\"" + name + "\")";
if (points != null) s += "\n " + points;
} else if (points != null) s += points;
s += "\n";
Rectangle r = roi.getBounds();
if (roi instanceof Line) {
Line line = (Line) roi;
s += " X1: " + IJ.d2s(line.x1d * cal.pixelWidth) + "\n";
s += " Y1: " + IJ.d2s(yy(line.y1d, imp) * cal.pixelHeight) + "\n";
s += " X2: " + IJ.d2s(line.x2d * cal.pixelWidth) + "\n";
s += " Y2: " + IJ.d2s(yy(line.y2d, imp) * cal.pixelHeight) + "\n";
} else if (cal.scaled()) {
s += " X: " + IJ.d2s(cal.getX(r.x)) + " (" + r.x + ")\n";
s += " Y: " + IJ.d2s(cal.getY(r.y, imp.getHeight())) + " (" + r.y + ")\n";
s += " Width: " + IJ.d2s(r.width * cal.pixelWidth) + " (" + r.width + ")\n";
s += " Height: " + IJ.d2s(r.height * cal.pixelHeight) + " (" + r.height + ")\n";
} else {
s += " X: " + r.x + "\n";
s += " Y: " + yy(r.y, imp) + "\n";
s += " Width: " + r.width + "\n";
s += " Height: " + r.height + "\n";
}
}
return s;
}
public void updatebeta() {
for (int i = 0; i <= ncurves; i++) {
brightmincc[i] = (bright1[i] * beta) / Math.sqrt(intensity1[i] / intensity2[i]);
eminccarray[i].setText("" + (float) brightmincc[i]);
}
}
private void updateavg() {
nmeas[ncurves] = 0;
avg = new float[xpts][ypts];
avgweights = new float[xpts][ypts];
for (int i = 0; i < ncurves; i++) {
if (include[i]) {
for (int j = 0; j < xpts; j++) {
for (int k = 0; k < ypts; k++) {
avg[j][k] += pch[i][j][k];
nmeas[ncurves] += (int) pch[i][j][k];
}
}
}
}
double tempavg = 0.0;
double tempavg2 = 0.0;
double temp2avg = 0.0;
double temp2avg2 = 0.0;
double tempccavg = 0.0;
for (int i = 0; i < xpts; i++) {
for (int j = 0; j < ypts; j++) {
double normed = (double) avg[i][j] / (double) nmeas[ncurves];
avgweights[i][j] = (float) ((double) nmeas[ncurves] / (normed * (1.0f - normed)));
if (avg[i][j] > 0.0f) {
avgweights[i][j] = (float) ((double) nmeas[ncurves] / (normed * (1.0f - normed)));
} else {
avgweights[i][j] = 1.0f;
}
tempavg += (double) i * normed;
tempavg2 += (double) i * (double) i * normed;
temp2avg += (double) j * normed;
temp2avg2 += (double) j * (double) j * normed;
tempccavg += (double) i * (double) j * normed;
}
}
tempccavg -= tempavg * temp2avg;
brightcc[ncurves] = tempccavg / Math.sqrt(tempavg * temp2avg);
tempavg2 -= tempavg * tempavg;
tempavg2 /= tempavg;
bright1[ncurves] = (tempavg2 - 1.0);
temp2avg2 -= temp2avg * temp2avg;
temp2avg2 /= temp2avg;
bright2[ncurves] = (temp2avg2 - 1.0);
intensity1[ncurves] = tempavg;
intensity2[ncurves] = temp2avg;
if (psfflag == 0) {
bright1[ncurves] /= 0.3536;
bright2[ncurves] /= 0.3536;
brightcc[ncurves] /= 0.3536;
} else {
if (psfflag == 1) {
bright1[ncurves] /= 0.078;
bright2[ncurves] /= 0.078;
brightcc[ncurves] /= 0.078;
} else {
bright1[ncurves] /= 0.5;
bright2[ncurves] /= 0.5;
brightcc[ncurves] /= 0.5;
}
}
number1[ncurves] = intensity1[ncurves] / bright1[ncurves];
number2[ncurves] = intensity2[ncurves] / bright2[ncurves];
brightmincc[ncurves] =
(bright1[ncurves] * beta) * Math.sqrt(intensity1[ncurves] / intensity2[ncurves]);
}
/**
* DistanceRidgetoLocalThickness
*
* <p>Input: Distance Ridge (32-bit stack) (Output from Distance Ridge.java) Output: Local
* Thickness. Overwrites the input.
*
* <ul>
* <li>Version 1: September 6, 2006.
* <li>Version 2: September 25, 2006. Fixed several bugs that resulted in non-symmetrical output
* from symmetrical input.
* <li>Version 2.1 Oct. 1, 2006. Fixed a rounding error that caused some points to be missed.
* <li>Version 3 July 31, 2007. Parallel processing version.
* <li>Version 3.1 Multiplies the output by 2 to conform with the definition of local thickness
* </ul>
*
* @param imp
*/
private void distanceRidgetoLocalThickness(ImagePlus imp, float[][] s) {
final int w = imp.getWidth();
final int h = imp.getHeight();
final int d = imp.getStackSize();
float[] sk;
// Count the distance ridge points on each slice
int[] nRidge = new int[d];
int ind, nr, iR;
IJ.showStatus("Local Thickness: scanning stack ");
for (int k = 0; k < d; k++) {
sk = s[k];
nr = 0;
for (int j = 0; j < h; j++) {
final int wj = w * j;
for (int i = 0; i < w; i++) {
ind = i + wj;
if (sk[ind] > 0) nr++;
}
}
nRidge[k] = nr;
}
int[][] iRidge = new int[d][];
int[][] jRidge = new int[d][];
float[][] rRidge = new float[d][];
// Pull out the distance ridge points
int[] iRidgeK, jRidgeK;
float[] rRidgeK;
float sMax = 0;
for (int k = 0; k < d; k++) {
nr = nRidge[k];
iRidge[k] = new int[nr];
jRidge[k] = new int[nr];
rRidge[k] = new float[nr];
sk = s[k];
iRidgeK = iRidge[k];
jRidgeK = jRidge[k];
rRidgeK = rRidge[k];
iR = 0;
for (int j = 0; j < h; j++) {
final int wj = w * j;
for (int i = 0; i < w; i++) {
ind = i + wj;
if (sk[ind] > 0) {;
iRidgeK[iR] = i;
jRidgeK[iR] = j;
rRidgeK[iR++] = sk[ind];
if (sk[ind] > sMax) sMax = sk[ind];
sk[ind] = 0;
}
}
}
}
int nThreads = Runtime.getRuntime().availableProcessors();
final Object[] resources = new Object[d]; // For synchronization
for (int k = 0; k < d; k++) {
resources[k] = new Object();
}
LTThread[] ltt = new LTThread[nThreads];
for (int thread = 0; thread < nThreads; thread++) {
ltt[thread] =
new LTThread(thread, nThreads, w, h, d, nRidge, s, iRidge, jRidge, rRidge, resources);
ltt[thread].start();
}
try {
for (int thread = 0; thread < nThreads; thread++) {
ltt[thread].join();
}
} catch (InterruptedException ie) {
IJ.error("A thread was interrupted .");
}
// Fix the square values and apply factor of 2
IJ.showStatus("Local Thickness: square root ");
for (int k = 0; k < d; k++) {
sk = s[k];
for (int j = 0; j < h; j++) {
final int wj = w * j;
for (int i = 0; i < w; i++) {
ind = i + wj;
sk[ind] = (float) (2 * Math.sqrt(sk[ind]));
}
}
}
IJ.showStatus("Local Thickness complete");
return;
}
/**
* Saito-Toriwaki algorithm for Euclidian Distance Transformation. Direct application of Algorithm
* 1. Bob Dougherty 8/8/2006
*
* <ul>
* <li>Version S1A: lower memory usage.
* <li>Version S1A.1 A fixed indexing bug for 666-bin data set
* <li>Version S1A.2 Aug. 9, 2006. Changed noResult value.
* <li>Version S1B Aug. 9, 2006. Faster.
* <li>Version S1B.1 Sept. 6, 2006. Changed comments.
* <li>Version S1C Oct. 1, 2006. Option for inverse case. <br>
* Fixed inverse behavior in y and z directions.
* <li>Version D July 30, 2007. Multithread processing for step 2.
* </ul>
*
* <p>This version assumes the input stack is already in memory, 8-bit, and outputs to a new
* 32-bit stack. Versions that are more stingy with memory may be forthcoming.
*
* @param imp 8-bit (binary) ImagePlus
*/
private float[][] geometryToDistanceMap(ImagePlus imp, boolean inv) {
final int w = imp.getWidth();
final int h = imp.getHeight();
final int d = imp.getStackSize();
int nThreads = Runtime.getRuntime().availableProcessors();
// Create references to input data
ImageStack stack = imp.getStack();
byte[][] data = new byte[d][];
for (int k = 0; k < d; k++) data[k] = (byte[]) stack.getPixels(k + 1);
// Create 32 bit floating point stack for output, s. Will also use it
// for g in Transformation 1.
float[][] s = new float[d][];
for (int k = 0; k < d; k++) {
ImageProcessor ipk = new FloatProcessor(w, h);
s[k] = (float[]) ipk.getPixels();
}
float[] sk;
// Transformation 1. Use s to store g.
IJ.showStatus("EDT transformation 1/3");
Step1Thread[] s1t = new Step1Thread[nThreads];
for (int thread = 0; thread < nThreads; thread++) {
s1t[thread] = new Step1Thread(thread, nThreads, w, h, d, inv, s, data);
s1t[thread].start();
}
try {
for (int thread = 0; thread < nThreads; thread++) {
s1t[thread].join();
}
} catch (InterruptedException ie) {
IJ.error("A thread was interrupted in step 1 .");
}
// Transformation 2. g (in s) -> h (in s)
IJ.showStatus("EDT transformation 2/3");
Step2Thread[] s2t = new Step2Thread[nThreads];
for (int thread = 0; thread < nThreads; thread++) {
s2t[thread] = new Step2Thread(thread, nThreads, w, h, d, s);
s2t[thread].start();
}
try {
for (int thread = 0; thread < nThreads; thread++) {
s2t[thread].join();
}
} catch (InterruptedException ie) {
IJ.error("A thread was interrupted in step 2 .");
}
// Transformation 3. h (in s) -> s
IJ.showStatus("EDT transformation 3/3");
Step3Thread[] s3t = new Step3Thread[nThreads];
for (int thread = 0; thread < nThreads; thread++) {
s3t[thread] = new Step3Thread(thread, nThreads, w, h, d, inv, s, data);
s3t[thread].start();
}
try {
for (int thread = 0; thread < nThreads; thread++) {
s3t[thread].join();
}
} catch (InterruptedException ie) {
IJ.error("A thread was interrupted in step 3 .");
}
// Find the largest distance for scaling
// Also fill in the background values.
float distMax = 0;
final int wh = w * h;
float dist;
for (int k = 0; k < d; k++) {
sk = s[k];
for (int ind = 0; ind < wh; ind++) {
if (((data[k][ind] & 255) < 128) ^ inv) {
sk[ind] = 0;
} else {
dist = (float) Math.sqrt(sk[ind]);
sk[ind] = dist;
distMax = (dist > distMax) ? dist : distMax;
}
}
}
IJ.showProgress(1.0);
IJ.showStatus("Done");
return s;
}
void Sauvola(ImagePlus imp, int radius, double par1, double par2, boolean doIwhite) {
// Sauvola recommends K_VALUE = 0.5 and R_VALUE = 128.
// This is a modification of Niblack's thresholding method.
// Sauvola J. and Pietaksinen M. (2000) "Adaptive Document Image Binarization"
// Pattern Recognition, 33(2): 225-236
// http://www.ee.oulu.fi/mvg/publications/show_pdf.php?ID=24
// Ported to ImageJ plugin from E Celebi's fourier_0.8 routines
// This version uses a circular local window, instead of a rectagular one
ImagePlus Meanimp, Varimp;
ImageProcessor ip = imp.getProcessor(), ipMean, ipVar;
double k_value = 0.5;
double r_value = 128;
byte object;
byte backg;
if (par1 != 0) {
IJ.log("Sauvola: changed k_value from :" + k_value + " to:" + par1);
k_value = par1;
}
if (par2 != 0) {
IJ.log("Sauvola: changed r_value from :" + r_value + " to:" + par2);
r_value = par2;
}
if (doIwhite) {
object = (byte) 0xff;
backg = (byte) 0;
} else {
object = (byte) 0;
backg = (byte) 0xff;
}
Meanimp = duplicateImage(ip);
ImageConverter ic = new ImageConverter(Meanimp);
ic.convertToGray32();
ipMean = Meanimp.getProcessor();
RankFilters rf = new RankFilters();
rf.rank(ipMean, radius, rf.MEAN); // Mean
// Meanimp.show();
Varimp = duplicateImage(ip);
ic = new ImageConverter(Varimp);
ic.convertToGray32();
ipVar = Varimp.getProcessor();
rf.rank(ipVar, radius, rf.VARIANCE); // Variance
// Varimp.show();
byte[] pixels = (byte[]) ip.getPixels();
float[] mean = (float[]) ipMean.getPixels();
float[] var = (float[]) ipVar.getPixels();
for (int i = 0; i < pixels.length; i++)
pixels[i] =
((int) (pixels[i] & 0xff)
> (int) (mean[i] * (1.0 + k_value * ((Math.sqrt(var[i]) / r_value) - 1.0))))
? object
: backg;
// imp.updateAndDraw();
return;
}
void jacobi(double[][] a, int n, double[] d, double[][] v)
/* a matrice de depart,
n taille du systeme,
d valeurs propres
v matrice de passage : vecteur propre normalises */
{
int j, iq, ip, i;
double tresh, theta, tau, t, sm, s, h, g, c;
double[] b = new double[3];
double[] z = new double[3];
for (ip = 0; ip < n; ip++) {
for (iq = 0; iq < n; iq++) {
v[ip][iq] = 0.0;
}
v[ip][ip] = 1.0;
}
for (ip = 0; ip < n; ip++) {
b[ip] = d[ip] = a[ip][ip];
z[ip] = 0.0;
}
// int nrot=0;
for (i = 1; i <= 50; i++) {
sm = 0.0;
for (ip = 0; ip < n - 1; ip++) {
for (iq = ip + 1; iq < n; iq++) sm += Math.abs(a[ip][iq]);
}
if (sm == 0.0) {
return;
}
if (i < 4) tresh = 0.2 * sm / (n * n);
else tresh = 0.0;
for (ip = 0; ip < n - 1; ip++) {
for (iq = ip + 1; iq < n; iq++) {
g = 100.0 * Math.abs(a[ip][iq]);
if (i > 4
&& Math.abs(d[ip]) + g == Math.abs(d[ip])
&& Math.abs(d[iq]) + g == Math.abs(d[iq])) a[ip][iq] = 0.0;
else if (Math.abs(a[ip][iq]) > tresh) {
h = d[iq] - d[ip];
if (Math.abs(h) + g == Math.abs(h)) t = (a[ip][iq]) / h;
else {
theta = 0.5 * h / (a[ip][iq]);
t = 1.0 / (Math.abs(theta) + Math.sqrt(1.0 + theta * theta));
if (theta < 0.0) t = -t;
}
c = 1.0 / Math.sqrt(1 + t * t);
s = t * c;
tau = s / (1.0 + c);
h = t * a[ip][iq];
z[ip] -= h;
z[iq] += h;
d[ip] -= h;
d[iq] += h;
a[ip][iq] = 0.0;
for (j = 0; j <= ip - 1; j++) {
ROTATE(a, j, ip, j, iq, tau, s);
}
for (j = ip + 1; j <= iq - 1; j++) {
ROTATE(a, ip, j, j, iq, tau, s);
}
for (j = iq + 1; j < n; j++) {
ROTATE(a, ip, j, iq, j, tau, s);
}
for (j = 0; j < n; j++) {
ROTATE(v, j, ip, j, iq, tau, s);
}
// ++nrot;
}
}
}
for (ip = 0; ip < n; ip++) {
b[ip] += z[ip];
d[ip] = b[ip];
z[ip] = 0.0;
}
}
}
/*
if selection is closed shape, create a circle with the same area and centroid, otherwise use<br>
the Pratt method to fit a circle to the points that define the line or multi-point selection.<br>
Reference: Pratt V., Direct least-squares fitting of algebraic surfaces", Computer Graphics, Vol. 21, pages 145-152 (1987).<br>
Original code: Nikolai Chernov's MATLAB script for Newton-based Pratt fit.<br>
(http://www.math.uab.edu/~chernov/cl/MATLABcircle.html)<br>
Java version: https://github.com/mdoube/BoneJ/blob/master/src/org/doube/geometry/FitCircle.java<br>
@authors Nikolai Chernov, Michael Doube, Ved Sharma
*/
void fitCircle(ImagePlus imp) {
Roi roi = imp.getRoi();
if (roi == null) {
noRoi("Fit Circle");
return;
}
if (roi.isArea()) { // create circle with the same area and centroid
ImageProcessor ip = imp.getProcessor();
ip.setRoi(roi);
ImageStatistics stats =
ImageStatistics.getStatistics(ip, Measurements.AREA + Measurements.CENTROID, null);
double r = Math.sqrt(stats.pixelCount / Math.PI);
imp.killRoi();
int d = (int) Math.round(2.0 * r);
IJ.makeOval(
(int) Math.round(stats.xCentroid - r), (int) Math.round(stats.yCentroid - r), d, d);
return;
}
Polygon poly = roi.getPolygon();
int n = poly.npoints;
int[] x = poly.xpoints;
int[] y = poly.ypoints;
if (n < 3) {
IJ.error("Fit Circle", "At least 3 points are required to fit a circle.");
return;
}
// calculate point centroid
double sumx = 0, sumy = 0;
for (int i = 0; i < n; i++) {
sumx = sumx + poly.xpoints[i];
sumy = sumy + poly.ypoints[i];
}
double meanx = sumx / n;
double meany = sumy / n;
// calculate moments
double[] X = new double[n], Y = new double[n];
double Mxx = 0, Myy = 0, Mxy = 0, Mxz = 0, Myz = 0, Mzz = 0;
for (int i = 0; i < n; i++) {
X[i] = x[i] - meanx;
Y[i] = y[i] - meany;
double Zi = X[i] * X[i] + Y[i] * Y[i];
Mxy = Mxy + X[i] * Y[i];
Mxx = Mxx + X[i] * X[i];
Myy = Myy + Y[i] * Y[i];
Mxz = Mxz + X[i] * Zi;
Myz = Myz + Y[i] * Zi;
Mzz = Mzz + Zi * Zi;
}
Mxx = Mxx / n;
Myy = Myy / n;
Mxy = Mxy / n;
Mxz = Mxz / n;
Myz = Myz / n;
Mzz = Mzz / n;
// calculate the coefficients of the characteristic polynomial
double Mz = Mxx + Myy;
double Cov_xy = Mxx * Myy - Mxy * Mxy;
double Mxz2 = Mxz * Mxz;
double Myz2 = Myz * Myz;
double A2 = 4 * Cov_xy - 3 * Mz * Mz - Mzz;
double A1 = Mzz * Mz + 4 * Cov_xy * Mz - Mxz2 - Myz2 - Mz * Mz * Mz;
double A0 = Mxz2 * Myy + Myz2 * Mxx - Mzz * Cov_xy - 2 * Mxz * Myz * Mxy + Mz * Mz * Cov_xy;
double A22 = A2 + A2;
double epsilon = 1e-12;
double ynew = 1e+20;
int IterMax = 20;
double xnew = 0;
int iterations = 0;
// Newton's method starting at x=0
for (int iter = 1; iter <= IterMax; iter++) {
iterations = iter;
double yold = ynew;
ynew = A0 + xnew * (A1 + xnew * (A2 + 4. * xnew * xnew));
if (Math.abs(ynew) > Math.abs(yold)) {
if (IJ.debugMode) IJ.log("Fit Circle: wrong direction: |ynew| > |yold|");
xnew = 0;
break;
}
double Dy = A1 + xnew * (A22 + 16 * xnew * xnew);
double xold = xnew;
xnew = xold - ynew / Dy;
if (Math.abs((xnew - xold) / xnew) < epsilon) break;
if (iter >= IterMax) {
if (IJ.debugMode) IJ.log("Fit Circle: will not converge");
xnew = 0;
}
if (xnew < 0) {
if (IJ.debugMode) IJ.log("Fit Circle: negative root: x = " + xnew);
xnew = 0;
}
}
if (IJ.debugMode)
IJ.log("Fit Circle: n=" + n + ", xnew=" + IJ.d2s(xnew, 2) + ", iterations=" + iterations);
// calculate the circle parameters
double DET = xnew * xnew - xnew * Mz + Cov_xy;
double CenterX = (Mxz * (Myy - xnew) - Myz * Mxy) / (2 * DET);
double CenterY = (Myz * (Mxx - xnew) - Mxz * Mxy) / (2 * DET);
double radius = Math.sqrt(CenterX * CenterX + CenterY * CenterY + Mz + 2 * xnew);
if (Double.isNaN(radius)) {
IJ.error("Fit Circle", "Points are collinear.");
return;
}
CenterX = CenterX + meanx;
CenterY = CenterY + meany;
imp.killRoi();
IJ.makeOval(
(int) Math.round(CenterX - radius),
(int) Math.round(CenterY - radius),
(int) Math.round(2 * radius),
(int) Math.round(2 * radius));
}
public void Calc_5Fr(ImagePlus imp1, ImagePlus imp2) {
if (imp1.getType() != imp2.getType()) {
error();
return;
}
if (imp1.getType() == 0) { // getType returns 0 for 8-bit, 1 for 16-bit
bitDepth = "8-bit";
Prefs.set("ps.bitDepth", bitDepth);
} else {
bitDepth = "16-bit";
Prefs.set("ps.bitDepth", bitDepth);
}
int width = imp1.getWidth();
int height = imp1.getHeight();
if (width != imp2.getWidth() || height != imp2.getHeight()) {
error();
return;
}
ImageStack stack1 = imp1.getStack();
// if (bgStackTitle != "NoBg") ImageStack stack2 = imp2.getStack();
ImageStack stack2 = imp2.getStack();
ImageProcessor ip = imp1.getProcessor();
int dimension = width * height;
byte[] pixB;
short[] pixS;
float[][] pixF = new float[5][dimension];
float[][] pixFBg = new float[5][dimension];
float a;
float b;
float den;
float aSmp;
float bSmp;
float denSmp;
float aBg;
float bBg;
float denBg;
float retF;
float azimF;
byte[] retB = new byte[dimension];
short[] retS = new short[dimension];
byte[] azimB = new byte[dimension];
short[] azimS = new short[dimension];
// Derived Variables:
float swingAngle = 2f * (float) Math.PI * swing;
float tanSwingAngleDiv2 = (float) Math.tan(swingAngle / 2.f);
float tanSwingAngleDiv2DivSqrt2 = (float) (Math.tan(swingAngle / 2.f) / Math.sqrt(2));
float wavelengthDiv2Pi = wavelength / (2f * (float) Math.PI);
// get the pixels of each slice in the stack and convert to float
for (int i = 0; i < 5; i++) {
if (bitDepth == "8-bit") {
pixB = (byte[]) stack1.getPixels(i + 3);
for (int j = 0; j < dimension; j++) pixF[i][j] = 0xff & pixB[j];
if (bgStackTitle != "NoBg") {
pixB = (byte[]) stack2.getPixels(i + 3);
for (int j = 0; j < dimension; j++) pixFBg[i][j] = 0xff & pixB[j];
}
} else {
pixS = (short[]) stack1.getPixels(i + 3);
for (int j = 0; j < dimension; j++) pixF[i][j] = (float) pixS[j];
if (bgStackTitle != "NoBg") {
pixS = (short[]) stack2.getPixels(i + 3);
for (int j = 0; j < dimension; j++) pixFBg[i][j] = (float) pixS[j];
}
}
}
// Algorithm
// terms a and b
for (int j = 0; j < dimension; j++) {
denSmp = (pixF[1][j] + pixF[2][j] + pixF[3][j] + pixF[4][j] - 4 * pixF[0][j]) / 2;
denBg = denSmp;
a = (pixF[4][j] - pixF[1][j]);
aSmp = a;
aBg = a;
b = (pixF[2][j] - pixF[3][j]);
bSmp = b;
bBg = b;
if (bgStackTitle != "NoBg") {
denBg = (pixFBg[1][j] + pixFBg[2][j] + pixFBg[3][j] + pixFBg[4][j] - 4 * pixFBg[0][j]) / 2;
aBg = pixFBg[4][j] - pixFBg[1][j];
bBg = pixFBg[2][j] - pixFBg[3][j];
}
// Special case of sample retardance half wave, denSmp = 0
if (denSmp == 0) {
retF = (float) wavelength / 4;
azimF =
(float) (a == 0 & b == 0 ? 0 : (azimRef + 90 + 90 * Math.atan2(a, b) / Math.PI) % 180);
} else {
// Retardance, the background correction can be improved by separately considering sample
// retardance values larger than a quarter wave
if (bgStackTitle != "NoBg") {
a = aSmp / denSmp - aBg / denBg;
b = bSmp / denSmp - bBg / denBg;
} else {
a = aSmp / denSmp;
b = bSmp / denSmp;
}
retF = (float) Math.atan(tanSwingAngleDiv2 * Math.sqrt(a * a + b * b));
if (denSmp < 0) retF = (float) Math.PI - retF;
retF = retF * wavelengthDiv2Pi; // convert to nm
if (retF > retCeiling) retF = retCeiling;
// Orientation
if ((bgStackTitle == "NoBg") || ((bgStackTitle != "NoBg") && (Math.abs(denSmp) < 1))) {
a = aSmp;
b = bSmp;
}
azimF =
(float) (a == 0 & b == 0 ? 0 : (azimRef + 90 + 90 * Math.atan2(a, b) / Math.PI) % 180);
}
if (bitDepth == "8-bit") retB[j] = (byte) (((int) (255 * retF / retCeiling)) & 0xff);
else retS[j] = (short) (4095 * retF / retCeiling);
if (mirror == "Yes") azimF = 180 - azimF;
if (bitDepth == "8-bit") azimB[j] = (byte) (((int) azimF) & 0xff);
else azimS[j] = (short) (azimF * 10f);
}
// show the resulting images in slice 1 and 2
imp1.setSlice(3);
if (bitDepth == "8-bit") {
stack1.setPixels(retB, 1);
stack1.setPixels(azimB, 2);
} else {
stack1.setPixels(retS, 1);
stack1.setPixels(azimS, 2);
}
imp1.setSlice(1);
IJ.selectWindow(imp1.getTitle());
Prefs.set("ps.sampleStackTitle", sampleStackTitle);
Prefs.set("ps.bgStackTitle", bgStackTitle);
Prefs.set("ps.mirror", mirror);
Prefs.set("ps.wavelength", wavelength);
Prefs.set("ps.swing", swing);
Prefs.set("ps.retCeiling", retCeiling);
Prefs.set("ps.azimRef", azimRef);
Prefs.savePreferences();
}
/*------------------------------------------------------------------*/
void doIt(ImageProcessor ip) {
int width = ip.getWidth();
int height = ip.getHeight();
double hLine[] = new double[width];
double vLine[] = new double[height];
if (!(ip.getPixels() instanceof float[])) {
throw new IllegalArgumentException("Float image required");
}
switch (operation) {
case GRADIENT_MAGNITUDE:
{
ImageProcessor h = ip.duplicate();
ImageProcessor v = ip.duplicate();
float[] floatPixels = (float[]) ip.getPixels();
float[] floatPixelsH = (float[]) h.getPixels();
float[] floatPixelsV = (float[]) v.getPixels();
getHorizontalGradient(h, FLT_EPSILON);
getVerticalGradient(v, FLT_EPSILON);
for (int y = 0, k = 0; (y < height); y++) {
for (int x = 0; (x < width); x++, k++) {
floatPixels[k] =
(float)
Math.sqrt(
floatPixelsH[k] * floatPixelsH[k] + floatPixelsV[k] * floatPixelsV[k]);
}
stepProgressBar();
}
}
break;
case GRADIENT_DIRECTION:
{
ImageProcessor h = ip.duplicate();
ImageProcessor v = ip.duplicate();
float[] floatPixels = (float[]) ip.getPixels();
float[] floatPixelsH = (float[]) h.getPixels();
float[] floatPixelsV = (float[]) v.getPixels();
getHorizontalGradient(h, FLT_EPSILON);
getVerticalGradient(v, FLT_EPSILON);
for (int y = 0, k = 0; (y < height); y++) {
for (int x = 0; (x < width); x++, k++) {
floatPixels[k] = (float) Math.atan2(floatPixelsH[k], floatPixelsV[k]);
}
stepProgressBar();
}
}
break;
case LAPLACIAN:
{
ImageProcessor hh = ip.duplicate();
ImageProcessor vv = ip.duplicate();
float[] floatPixels = (float[]) ip.getPixels();
float[] floatPixelsHH = (float[]) hh.getPixels();
float[] floatPixelsVV = (float[]) vv.getPixels();
getHorizontalHessian(hh, FLT_EPSILON);
getVerticalHessian(vv, FLT_EPSILON);
for (int y = 0, k = 0; (y < height); y++) {
for (int x = 0; (x < width); x++, k++) {
floatPixels[k] = (float) (floatPixelsHH[k] + floatPixelsVV[k]);
}
stepProgressBar();
}
}
break;
case LARGEST_HESSIAN:
{
ImageProcessor hh = ip.duplicate();
ImageProcessor vv = ip.duplicate();
ImageProcessor hv = ip.duplicate();
float[] floatPixels = (float[]) ip.getPixels();
float[] floatPixelsHH = (float[]) hh.getPixels();
float[] floatPixelsVV = (float[]) vv.getPixels();
float[] floatPixelsHV = (float[]) hv.getPixels();
getHorizontalHessian(hh, FLT_EPSILON);
getVerticalHessian(vv, FLT_EPSILON);
getCrossHessian(hv, FLT_EPSILON);
for (int y = 0, k = 0; (y < height); y++) {
for (int x = 0; (x < width); x++, k++) {
floatPixels[k] =
(float)
(0.5
* (floatPixelsHH[k]
+ floatPixelsVV[k]
+ Math.sqrt(
4.0 * floatPixelsHV[k] * floatPixelsHV[k]
+ (floatPixelsHH[k] - floatPixelsVV[k])
* (floatPixelsHH[k] - floatPixelsVV[k]))));
}
stepProgressBar();
}
}
break;
case SMALLEST_HESSIAN:
{
ImageProcessor hh = ip.duplicate();
ImageProcessor vv = ip.duplicate();
ImageProcessor hv = ip.duplicate();
float[] floatPixels = (float[]) ip.getPixels();
float[] floatPixelsHH = (float[]) hh.getPixels();
float[] floatPixelsVV = (float[]) vv.getPixels();
float[] floatPixelsHV = (float[]) hv.getPixels();
getHorizontalHessian(hh, FLT_EPSILON);
getVerticalHessian(vv, FLT_EPSILON);
getCrossHessian(hv, FLT_EPSILON);
for (int y = 0, k = 0; (y < height); y++) {
for (int x = 0; (x < width); x++, k++) {
floatPixels[k] =
(float)
(0.5
* (floatPixelsHH[k]
+ floatPixelsVV[k]
- Math.sqrt(
4.0 * floatPixelsHV[k] * floatPixelsHV[k]
+ (floatPixelsHH[k] - floatPixelsVV[k])
* (floatPixelsHH[k] - floatPixelsVV[k]))));
}
stepProgressBar();
}
}
break;
case HESSIAN_ORIENTATION:
{
ImageProcessor hh = ip.duplicate();
ImageProcessor vv = ip.duplicate();
ImageProcessor hv = ip.duplicate();
float[] floatPixels = (float[]) ip.getPixels();
float[] floatPixelsHH = (float[]) hh.getPixels();
float[] floatPixelsVV = (float[]) vv.getPixels();
float[] floatPixelsHV = (float[]) hv.getPixels();
getHorizontalHessian(hh, FLT_EPSILON);
getVerticalHessian(vv, FLT_EPSILON);
getCrossHessian(hv, FLT_EPSILON);
for (int y = 0, k = 0; (y < height); y++) {
for (int x = 0; (x < width); x++, k++) {
if (floatPixelsHV[k] < 0.0) {
floatPixels[k] =
(float)
(-0.5
* Math.acos(
(floatPixelsHH[k] - floatPixelsVV[k])
/ Math.sqrt(
4.0 * floatPixelsHV[k] * floatPixelsHV[k]
+ (floatPixelsHH[k] - floatPixelsVV[k])
* (floatPixelsHH[k] - floatPixelsVV[k]))));
} else {
floatPixels[k] =
(float)
(0.5
* Math.acos(
(floatPixelsHH[k] - floatPixelsVV[k])
/ Math.sqrt(
4.0 * floatPixelsHV[k] * floatPixelsHV[k]
+ (floatPixelsHH[k] - floatPixelsVV[k])
* (floatPixelsHH[k] - floatPixelsVV[k]))));
}
}
stepProgressBar();
}
}
break;
default:
throw new IllegalArgumentException("Invalid operation");
}
ip.resetMinAndMax();
imp.updateAndDraw();
} /* end doIt */
void Niblack(ImagePlus imp, int radius, double par1, double par2, boolean doIwhite) {
// Niblack recommends K_VALUE = -0.2 for images with black foreground
// objects, and K_VALUE = +0.2 for images with white foreground objects.
// Niblack W. (1986) "An introduction to Digital Image Processing" Prentice-Hall.
// Ported to ImageJ plugin from E Celebi's fourier_0.8 routines
// This version uses a circular local window, instead of a rectagular one
ImagePlus Meanimp, Varimp;
ImageProcessor ip = imp.getProcessor(), ipMean, ipVar;
double k_value;
int c_value = 0;
byte object;
byte backg;
if (doIwhite) {
k_value = 0.2;
object = (byte) 0xff;
backg = (byte) 0;
} else {
k_value = -0.2;
object = (byte) 0;
backg = (byte) 0xff;
}
if (par1 != 0) {
IJ.log("Niblack: changed k_value from :" + k_value + " to:" + par1);
k_value = par1;
}
if (par2 != 0) {
IJ.log(
"Niblack: changed c_value from :"
+ c_value
+ " to:"
+ par2); // requested feature, not in original
c_value = (int) par2;
}
Meanimp = duplicateImage(ip);
ImageConverter ic = new ImageConverter(Meanimp);
ic.convertToGray32();
ipMean = Meanimp.getProcessor();
RankFilters rf = new RankFilters();
rf.rank(ipMean, radius, rf.MEAN); // Mean
// Meanimp.show();
Varimp = duplicateImage(ip);
ic = new ImageConverter(Varimp);
ic.convertToGray32();
ipVar = Varimp.getProcessor();
rf.rank(ipVar, radius, rf.VARIANCE); // Variance
// Varimp.show();
byte[] pixels = (byte[]) ip.getPixels();
float[] mean = (float[]) ipMean.getPixels();
float[] var = (float[]) ipVar.getPixels();
for (int i = 0; i < pixels.length; i++)
pixels[i] =
((int) (pixels[i] & 0xff) > (int) (mean[i] + k_value * Math.sqrt(var[i]) - c_value))
? object
: backg;
// imp.updateAndDraw();
return;
}
public void run(String arg) {
int[] wList = WindowManager.getIDList();
if (wList==null) {
IJ.error("No images are open.");
return;
}
double kernel=3;
double kernelsum = 0;
double kernelvarsum =0;
double kernalvar = 0;
double sigmawidth = 2;
int kernelindex, minpixnumber;
String[] kernelsize = { "3�,"5�, "7�, "9�};
GenericDialog gd = new GenericDialog("Sigma Filter");
gd.addChoice("Kernel size", kernelsize, kernelsize[0]);
gd.addNumericField("Sigma width",sigmawidth , 2);
gd.addNumericField("Minimum number of pixels", 1, 0);
gd.addCheckbox("Keep source:",true);
gd.addCheckbox("Do all stack:",true);
gd.addCheckbox("Modified Lee's FIlter:",true);
gd.showDialog();
if (gd.wasCanceled()) return ;
kernelindex = gd.getNextChoiceIndex();
sigmawidth = gd.getNextNumber();
minpixnumber = ((int)gd.getNextNumber());
boolean keep = gd.getNextBoolean();
boolean doallstack = gd.getNextBoolean();
boolean modified = gd.getNextBoolean();
if (kernelindex==0) kernel = 3;
if (kernelindex==1) kernel = 5;
if (kernelindex==2) kernel = 7;
if (kernelindex==3) kernel = 9;
long start = System.currentTimeMillis();
if (minpixnumber> (kernel*kernel)){
IJ.showMessage("Sigma filter", "There must be more pixels in the kernel than+\n" + "the minimum number to be included");
return;
}
double v, midintensity;
int x, y, ix, iy;
double sum = 0;
double backupsum =0;
int count = 0;
int n = 0;
if (keep) {IJ.run("Select All"); IJ.run("Duplicate...", "title='Sigma filtered' duplicate");}
int radius = (int)(kernel-1)/2;
ImagePlus imp = WindowManager.getCurrentImage();
ImageStack stack1 = imp.getStack();
int width = imp.getWidth();
int height = imp.getHeight();
int nslices = stack1.getSize();
int cslice = imp.getCurrentSlice();
double status = width*height*nslices;
ImageProcessor ip = imp.getProcessor();
int sstart = 1;
if (!doallstack) {sstart = cslice; nslices=sstart;status = status/nslices;};
for (int i=sstart; i<=nslices; i++) {
imp.setSlice(i);
for (x=radius;x<width+radius;x++) {
for (y=radius;y<height+radius;y++) {
midintensity = ip.getPixelValue(x,y);
count = 0;
sum = 0;
kernelsum =0;
kernalvar =0;
kernelvarsum =0;
backupsum = 0;
//calculate mean of kernel value
for (ix=0;ix<kernel;ix++) {
for (iy=0;iy<kernel;iy++) {
v = ip.getPixelValue(x+ix-radius,y+iy-radius);
kernelsum = kernelsum+v;
}
}
double sigmacalcmean = (kernelsum/(kernel*kernel));
//calculate variance of kernel
for (ix=0;ix<kernel;ix++) {
for (iy=0;iy<kernel;iy++) {
v = ip.getPixelValue(x+ix-radius,y+iy-radius);
kernalvar = (v-sigmacalcmean)*(v-sigmacalcmean);
kernelvarsum = kernelvarsum + kernalvar;
}
}
//double variance = kernelvarsum/kernel;
double sigmacalcvar = kernelvarsum/((kernel*kernel)-1);
//calcuate sigma range = sqrt(variance/(mean^2)) � sigmawidth
double sigmarange = sigmawidth*(Math.sqrt((sigmacalcvar) /(sigmacalcmean*sigmacalcmean)));
//calulate sigma top value and bottom value
double sigmatop = midintensity*(1+sigmarange);
double sigmabottom = midintensity*(1-sigmarange);
//calculate mean of values that differ are in sigma range.
for (ix=0;ix<kernel;ix++) {
for (iy=0;iy<kernel;iy++) {
v = ip.getPixelValue(x+ix-radius,y+iy-radius);
if ((v>=sigmabottom)&&(v<=sigmatop)){
sum = sum+v;
count = count+1; }
backupsum = v+ backupsum;
}
}
//if there are too few pixels in the kernal that are within sigma range, the
//mean of the entire kernal is taken. My modification of Lee's filter is to exclude the central value
//from the calculation of the mean as I assume it to be spuriously high or low
if (!(count>(minpixnumber)))
{sum = (backupsum-midintensity);
count = (int)((kernel*kernel)-1);
if (!modified)
{sum = (backupsum);
count = (int)(kernel*kernel);}
}
double val = (sum/count);
ip.putPixelValue(x,y, val);
n = n+1;
double percentage = (((double)n/status)*100);
IJ.showStatus(IJ.d2s(percentage,0) +"% done");
}
// IJ.showProgress(i, status);
}}
imp.updateAndDraw();
IJ.showStatus(IJ.d2s((System.currentTimeMillis()-start)/1000.0, 2)+" seconds"); }
void sauvegarde(
int v1[],
double v2[],
double s[],
double s2[],
double xg[],
double yg[],
double zg[],
double[][] J,
double[][][] dir,
int n,
byte[] bord,
double[][] lmin,
double[][] lmax,
String directory,
String name) {
double sp;
PrintWriter pw = null;
try {
FileOutputStream fos = new FileOutputStream(directory + name);
BufferedOutputStream bos = new BufferedOutputStream(fos);
pw = new PrintWriter(bos);
} catch (IOException e) {
return;
}
pw.println(
"nb xg yg zg volpix volmarch surfacemarch surfacemarchnb sphericity I1 I2 I3 vI1x vI1y vI1z vI2x vI2y vI2z vI3x vI3y vI3z a b c Fab Fac Fbc xmin xmax ymin ymax zmin zmax dx dy dz border");
for (int i = 0; i < n; i++) {
pw.print(i + 1);
pw.print(" ");
pw.print(xg[i]);
pw.print(" ");
pw.print(yg[i]);
pw.print(" ");
pw.print(zg[i]);
pw.print(" ");
pw.print(v1[i]);
pw.print(" ");
pw.print(v2[i]);
pw.print(" ");
pw.print(s[i]);
pw.print(" ");
pw.print(s2[i]);
sp = 6 * v2[i] * Math.sqrt(3.14159265 / (s2[i] * s2[i] * s2[i]));
pw.print(" ");
pw.print(sp);
pw.print(" ");
pw.print(J[0][i]);
pw.print(" ");
pw.print(J[1][i]);
pw.print(" ");
pw.print(J[2][i]);
pw.print(" ");
pw.print(dir[0][0][i]);
pw.print(" ");
pw.print(dir[1][0][i]);
pw.print(" ");
pw.print(dir[2][0][i]);
pw.print(" ");
pw.print(dir[0][1][i]);
pw.print(" ");
pw.print(dir[1][1][i]);
pw.print(" ");
pw.print(dir[2][1][i]);
pw.print(" ");
pw.print(dir[0][2][i]);
pw.print(" ");
pw.print(dir[1][2][i]);
pw.print(" ");
pw.print(dir[2][2][i]);
pw.print(" ");
double ma = (J[0][i] + J[1][i] - J[2][i]);
double mb = (J[0][i] - J[1][i] + J[2][i]);
double mc = (-J[0][i] + J[1][i] + J[2][i]);
double b1 = (3 * mb * mb / (16 * Math.sqrt(ma * mc)));
b1 = Math.pow(b1, 0.2);
double a = b1 * Math.sqrt(ma / mb);
double b = b1;
double c = b * Math.sqrt(mc / mb);
double Fab = Math.sqrt((J[0][i] + J[1][i] - J[2][i]) / (J[0][i] - J[1][i] + J[2][i]));
double Fac = Math.sqrt((J[0][i] + J[1][i] - J[2][i]) / (-J[0][i] + J[1][i] + J[2][i]));
double Fbc = Math.sqrt((J[0][i] - J[1][i] + J[2][i]) / (-J[0][i] + J[1][i] + J[2][i]));
pw.print(a);
pw.print(" ");
pw.print(b);
pw.print(" ");
pw.print(c);
pw.print(" ");
pw.print(Fab);
pw.print(" ");
pw.print(Fac);
pw.print(" ");
pw.print(Fbc);
pw.print(" ");
pw.print(lmin[i][0] - 0.5);
pw.print(" ");
pw.print(lmax[i][0] + 0.5);
pw.print(" ");
pw.print(lmin[i][1] - 0.5);
pw.print(" ");
pw.print(lmax[i][1] + 0.5);
pw.print(" ");
pw.print(lmin[i][2] - 0.5);
pw.print(" ");
pw.print(lmax[i][2] + 0.5);
pw.print(" ");
double dx = lmax[i][0] - lmin[i][0] + 1;
double dy = lmax[i][1] - lmin[i][1] + 1;
double dz = lmax[i][2] - lmin[i][2] + 1;
double a1 = dx;
if (dy < a1) a1 = dy;
if (dz < a1) a1 = dz;
double a3 = dx;
if (dy > a3) a3 = dy;
if (dz > a3) a3 = dz;
double a2 = dx;
if (dx != a1 && dx != a3) a2 = dx;
if (dy != a1 && dy != a3) a2 = dy;
if (dz != a1 && dz != a3) a2 = dz;
pw.print(" ");
pw.print(a1);
pw.print(" ");
pw.print(a2);
pw.print(" ");
pw.print(a3);
pw.print(" ");
pw.println(bord[i]);
}
pw.close();
}