void loadParticleResults(String filename, ResultsTable res) {
try {
String line;
FileReader fr = new FileReader(filename);
BufferedReader br = new BufferedReader(fr);
java.lang.String header =
" Intensity X (px) Y (px) X (nm) Y (nm) Z (nm) Left-Width(px) Right-Width (px) Up-Height (px) Down-Height (px) X Symmetry (%) Y Symmetry (%) Width minus Height (px) Frame Number";
java.lang.String firstline = br.readLine();
if (!firstline.contains("X (px) Y (px) X (nm) Y (nm) Z (nm)")) {
IJ.error("File does not seam to be a Particles Table file");
IJ.log("Found header: " + firstline);
IJ.log("Expecting: " + header);
return;
}
res.reset();
int counter = 1;
java.util.concurrent.locks.Lock lock = new java.util.concurrent.locks.ReentrantLock();
ThreadedLoader tloader = new ThreadedLoader();
// java.lang.String txt = fr.read();
while ((line = br.readLine()) != null) {
tloader = new ThreadedLoader();
tloader.mysetup(res, lock, line);
tloader.start();
IJ.showStatus("Loading particle " + counter + "... sit back and relax.");
counter++;
}
try {
tloader.join();
} catch (Exception e) {
IJ.error("" + e);
}
if (res.getCounter() < 5000000) {
IJ.showStatus("Creating particle table, this should take a few seconds...");
res.show("Results");
} else
IJ.showMessage(
"Warning",
"Results table has too many particles, they will not be shown but the data still exists within it\nyou can still use all the plugin functionality or save table changes though the 'Save Particle Table' command.");
fr.close();
IJ.showStatus("Done loading table...");
} catch (FileNotFoundException e) {
IJ.error("File not found exception" + e);
return;
} catch (IOException e) {
IJ.error("IOException exception" + e);
return;
} catch (NumberFormatException e) {
IJ.error("Number format exception" + e);
return;
}
}
public void actionPerformed(ActionEvent e) {
Button b = (Button) e.getSource();
if (b == null) return;
boolean imageThere = checkImage();
if (imageThere) {
if (b == originalB) {
reset(imp, ip);
filteredB.setEnabled(true);
} else if (b == filteredB) {
apply(imp, ip);
} else if (b == sampleB) {
reset(imp, ip);
sample();
apply(imp, ip);
} else if (b == stackB) {
applyStack();
} else if (b == helpB) {
IJ.showMessage(
"Help",
"Threshold Colour v1.0\n \n"
+ "Modification of Bob Dougherty's BandPass2 plugin by G.Landini to\n"
+ "threshold 24 bit RGB images based on Hue, Saturation and Brightness\n"
+ "or Red, Green and Blue components.\n \n"
+ "Pass: Band-pass filter (anything within range is displayed).\n \n"
+ "Stop: Band-reject filter (anything within range is NOT displayed).\n \n"
+ "Original: Shows the original image and updates the buffer when\n"
+ " switching to another image.\n \n"
+ "Filtered: Shows the filtered image.\n \n"
+ "Stack: Processes the rest of the slices in the stack (if any)\n"
+ " using the current settings.\n \n"
+ "Threshold: Shows the object/background in the foreground and\n"
+ " background colours selected in the ImageJ toolbar.\n \n"
+ "Invert: Swaps the fore/background colours.\n \n"
+ "Sample: (experimental) Sets the ranges of the filters based on the\n"
+ " pixel value componentd in a rectangular, user-defined, ROI.\n \n"
+ "HSB RGB: Selects HSB or RGB space and resets all the filters.\n \n"
+ "Note that the \'thresholded\' image is RGB, not 8 bit grey.");
}
updatePlot();
updateLabels();
imp.updateAndDraw();
} else {
IJ.beep();
IJ.showStatus("No Image");
}
notify();
}
private void showioerror() {
IJ.showMessage("Error in file io");
}
private void geterrors() {
GenericDialog gd = new GenericDialog("Options");
float conf = 0.67f;
gd.addNumericField("Confidence Limit", (int) (conf * 100.0f), 5, 10, null);
gd.addChoice("Error Parameter", paramsnames, paramsnames[0]);
double spacing = 0.01;
gd.addNumericField("Chi^2 plot spacing (% of value)?", spacing * 100.0, 2, 10, null);
boolean globalerror = false;
gd.addCheckbox("Global Fit Error?", globalerror);
int dataset = 0;
gd.addNumericField("Data Set (for Global Error)", dataset, 0);
gd.showDialog();
if (gd.wasCanceled()) {
return;
}
conf = 0.01f * (float) gd.getNextNumber();
int paramindex = (int) gd.getNextChoiceIndex();
spacing = 0.01 * gd.getNextNumber();
globalerror = gd.getNextBoolean();
dataset = (int) gd.getNextNumber();
if (globalerror) {
support_plane_errors erclass = new support_plane_errors(this, 0.0001, 50, true, 0.1);
int[] erindeces = {paramindex, dataset};
// need to set up all the matrices
int nsel = 0;
int nparams = 11;
for (int i = 0; i < ncurves; i++) {
if (include[i]) {
nsel++;
}
}
double[][] params = new double[nsel][nparams];
String[][] tempformulas = new String[nsel][nparams];
double[][][] constraints = new double[2][nsel][nparams];
int[][] vflmatrix = new int[nsel][nparams];
float[][] tempdata = new float[nsel][xpts * ypts];
float[][] tempweights = new float[nsel][xpts * ypts];
int nfit = 0;
int counter = 0;
for (int i = 0; i < ncurves; i++) {
if (include[i]) {
for (int j = 0; j < nparams; j++) {
params[counter][j] = globalparams[i][j];
tempformulas[counter][j] = globalformulas[i][j];
constraints[0][counter][j] = globalconstraints[0][i][j];
constraints[1][counter][j] = globalconstraints[1][i][j];
vflmatrix[counter][j] = globalvflmatrix[i][j];
if (vflmatrix[counter][j] == 0 || (j == 0 && vflmatrix[counter][j] == 2)) {
nfit++;
}
}
for (int j = 0; j < xpts; j++) {
for (int k = 0; k < ypts; k++) {
tempdata[counter][j + k * xpts] = (float) ((double) pch[i][j][k] / (double) nmeas[i]);
tempweights[counter][j + k * xpts] = weights[i][j][k];
}
}
counter++;
}
}
int dofnum = xpts * ypts * nsel - (nfit - 1) - 1;
int dofden = xpts * ypts * nsel - nfit - 1;
// double flim=FLimit(dofnum,dofden,(double)conf);
double flim = (new jdist()).FLimit(dofnum, dofden, (double) conf);
IJ.log("FLimit = " + (float) flim);
if (flim == Double.NaN && flim < 1.0) {
IJ.showMessage("Invalid Limiting F Value");
return;
}
double truespacing = Math.abs(params[erindeces[1]][erindeces[0]] * spacing);
double[][] c2plot =
erclass.geterrorsglobal(
params,
vflmatrix,
tempformulas,
paramsnames,
constraints,
tempdata,
tempweights,
flim,
truespacing,
erindeces);
IJ.log("upper limit = " + c2plot[1][0] + " lower limit = " + c2plot[0][0]);
int templength = c2plot[0].length;
float[][] c2plotf = new float[2][templength - 1];
for (int i = 0; i < (templength - 1); i++) {
c2plotf[0][i] = (float) c2plot[0][i + 1];
c2plotf[1][i] = (float) c2plot[1][i + 1];
}
new PlotWindow4(
"c2 plot",
paramsnames[paramindex] + "[" + dataset + "]",
"Chi^2",
c2plotf[0],
c2plotf[1])
.draw();
} else {
support_plane_errors erclass = new support_plane_errors(this, 0.0001, 50, false, 0.1);
int errindex = paramindex;
float[] tempdata = new float[xpts * ypts];
float[] tempweights = new float[xpts * ypts];
for (int i = 0; i < xpts; i++) {
for (int j = 0; j < ypts; j++) {
tempdata[i + j * xpts] = (float) ((double) avg[i][j] / (double) nmeas[ncurves]);
tempweights[i + j * xpts] = avgweights[i][j];
}
}
int nfit = 0;
for (int i = 0; i < 7; i++) {
if (avgfixes[i] == 0) {
nfit++;
}
}
int dofnum = xpts * ypts - (nfit - 1) - 1;
int dofden = xpts * ypts - nfit - 1;
double flim = (new jdist()).FLimit(dofnum, dofden, (double) conf);
IJ.log("FLimit = " + (float) flim);
if (flim == Double.NaN && flim < 1.0) {
IJ.showMessage("Invalid Limiting F Value");
return;
}
double truespacing = Math.abs(avgparams[errindex] * spacing);
double[][] c2plot =
erclass.geterrors(
avgparams,
avgfixes,
avgconstraints,
tempdata,
tempweights,
flim,
truespacing,
errindex);
IJ.log("upper limit = " + c2plot[1][0] + " lower limit = " + c2plot[0][0]);
int templength = c2plot[0].length;
float[][] c2plotf = new float[2][templength - 1];
for (int i = 0; i < (templength - 1); i++) {
c2plotf[0][i] = (float) c2plot[0][i + 1];
c2plotf[1][i] = (float) c2plot[1][i + 1];
}
new PlotWindow4("c2 plot", paramsnames[errindex], "Chi^2", c2plotf[0], c2plotf[1]).draw();
}
}
public boolean get_errors(double[] params, int[] fixes) {
GenericDialog gd = new GenericDialog("Error Options");
String[] methods = {"Support Plane", "Monte Carlo"};
gd.addChoice("Method", methods, methods[0]);
float conf = 0.67f;
gd.addNumericField("SP_Confidence Limit (%)", (int) (conf * 100.0f), 5, 10, null);
String[] labels = {"P1", "P2", "P3", "P4", "P5", "P6", "P7", "P8", "P9", "P10"};
gd.addChoice("SP_Parameter", labels, labels[0]);
double spacing = 0.01;
gd.addNumericField("SP_Chi^2_plot_spacing (% of value)?", spacing * 100.0, 2, 10, null);
int ntrials = 100;
gd.addNumericField("MC_#_Trials", ntrials, 0);
gd.showDialog();
if (gd.wasCanceled()) {
return false;
}
int methodindex = gd.getNextChoiceIndex();
conf = 0.01f * (float) gd.getNextNumber();
int paramindex = gd.getNextChoiceIndex();
spacing = 0.01 * gd.getNextNumber();
ntrials = (int) gd.getNextNumber();
if (methodindex == 0) {
support_plane_errors_v2 erclass = new support_plane_errors_v2(this, 0.0001, 50, false, 0.1);
int errindex = paramindex;
int nfit = 0;
for (int i = 0; i < labels.length; i++) {
if (fixes[i] == 0) {
nfit++;
}
}
int npts = tempdata.length;
int dofnum = npts - (nfit - 1) - 1;
int dofden = npts - nfit - 1;
double flim = (new jdist()).FLimit(dofnum, dofden, (double) conf);
IJ.log("FLimit = " + (float) flim);
if (flim == Double.NaN && flim < 1.0) {
IJ.showMessage("Invalid Limiting F Value");
return false;
}
double truespacing = Math.abs(params[errindex] * spacing);
double[][] c2plot =
erclass.geterrors(
params, fixes, constraints, tempdata, weights, flim, truespacing, errindex);
IJ.log("upper limit = " + c2plot[1][0] + " lower limit = " + c2plot[0][0]);
IJ.log(
"upper error = "
+ (c2plot[1][0] - params[errindex])
+ " lower error = "
+ (params[errindex] - c2plot[0][0]));
int templength = c2plot[0].length;
float[][] c2plotf = new float[2][templength - 1];
for (int i = 0; i < (templength - 1); i++) {
c2plotf[0][i] = (float) c2plot[0][i + 1];
c2plotf[1][i] = (float) c2plot[1][i + 1];
}
new PlotWindow4("c2 plot", labels[errindex], "Chi^2", c2plotf[0], c2plotf[1]).draw();
} else {
StringBuffer sb = new StringBuffer();
sb.append("Trial\t");
for (int i = 0; i < labels.length; i++) {
if (fixes[i] == 0) sb.append(labels[i] + "\t");
}
sb.append("chi^2");
tw = new TextWindow("Monte Carlo Results", sb.toString(), "", 400, 400);
redirect = true;
monte_carlo_errors_v2 erclass = new monte_carlo_errors_v2(this, 0.0001, 50, false, 0.1);
double[][] errors = erclass.geterrors(params, fixes, constraints, tempdata, weights, ntrials);
sb = new StringBuffer();
sb.append("StDev\t");
for (int i = 0; i < errors.length; i++) {
float[] ferr = new float[errors[0].length];
for (int j = 0; j < ferr.length; j++) ferr[j] = (float) errors[i][j];
float stdev = jstatistics.getstatistic("StDev", ferr, null);
sb.append("" + stdev);
if (i < (errors.length - 1)) sb.append("\t");
}
tw.append(sb.toString());
redirect = false;
}
return true;
}
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"); }
public void run(String arg) {
Frame[] niframes = WindowManager.getNonImageWindows();
String[] titles = new String[niframes.length + 1];
for (int i = 0; i < niframes.length; i++) {
titles[i] = niframes[i].getTitle();
}
titles[niframes.length] = "Clipboard";
GenericDialog gd = new GenericDialog("Windows");
boolean importfile = false;
gd.addCheckbox("Import from file?", importfile);
gd.addChoice("Windows", titles, titles[0]);
boolean hasxvals = false;
gd.addCheckbox("X Vals Column?", hasxvals);
boolean multix = false;
gd.addCheckbox("Multi_X_Columns?", multix);
boolean skipendzeros = false;
gd.addCheckbox("Skip_end_zeros?", skipendzeros);
String[] delimiters = {"Tab", "Comma", "Space"};
gd.addChoice("Delimiter", delimiters, delimiters[0]);
gd.showDialog();
if (gd.wasCanceled()) {
return;
}
importfile = gd.getNextBoolean();
int index = gd.getNextChoiceIndex();
hasxvals = gd.getNextBoolean();
multix = gd.getNextBoolean();
skipendzeros = gd.getNextBoolean();
int delimindex = gd.getNextChoiceIndex();
if (multix) hasxvals = true;
String textdata = "";
if (importfile) {
OpenDialog od = new OpenDialog("Open File", "", ".txt");
String directory = od.getDirectory();
String name = od.getFileName();
if (name == null) {
return;
}
try {
File infile = new File(directory + name);
BufferedReader b = new BufferedReader(new FileReader(infile));
textdata = (new jdataio()).readstringfile(b);
b.close();
} catch (IOException e) {
return;
}
} else {
if (index == niframes.length) {
// here we get the data from the clipboard
Transferable t = Toolkit.getDefaultToolkit().getSystemClipboard().getContents(null);
try {
if (t != null && t.isDataFlavorSupported(DataFlavor.stringFlavor)) {
textdata = (String) t.getTransferData(DataFlavor.stringFlavor);
}
} catch (UnsupportedFlavorException e) {
} catch (IOException e) {
}
if (textdata.equals("")) {
IJ.error("Error copying from clipboard.");
return;
}
} else {
if (niframes[index] instanceof Editor) {
Editor tw = (Editor) niframes[index];
textdata = tw.getText();
} else {
if (niframes[index] instanceof TextWindow) {
TextWindow tw = (TextWindow) niframes[index];
textdata = tw.getTextPanel().getText();
} else {
IJ.showMessage("Not a valid text window");
return;
}
}
}
}
if (textdata == null) {
IJ.showMessage("Error in Obtaining String");
return;
}
if (textdata.indexOf("\r") >= 0) {
textdata = textdata.replace('\r', '\n');
}
char[] delims = {'\t', ',', ' '};
delimit_string ds = new delimit_string(delims[delimindex]);
String[] rows = ds.getrows(textdata);
int lines = rows.length;
int columns = ds.getnumcolumns(rows[0]);
int ycolumns = columns;
if (hasxvals) {
if (multix) {
ycolumns /= 2;
} else {
ycolumns--;
}
}
if (multix) {
float[][] ydata = new float[ycolumns][lines];
float[][] xdata = new float[ycolumns][lines];
for (int i = 0; i < lines; i++) {
float[] temp = ds.delim2float(rows[i], columns);
for (int j = 0; j < ycolumns; j++) {
ydata[j][i] = temp[2 * j + 1];
xdata[j][i] = temp[2 * j];
}
}
int[] npts = new int[ycolumns];
for (int i = 0; i < ycolumns; i++) {
npts[i] = lines;
}
if (skipendzeros) {
for (int i = 0; i < ycolumns; i++) {
int counter = lines - 1;
while ((xdata[i][counter] == 0.0f || Float.isNaN(xdata[i][counter])) && counter > 0) {
xdata[i][counter] = 0.0f;
ydata[i][counter] = 0.0f;
npts[i]--;
counter--;
}
}
}
(new PlotWindow4("Text Plot", "x", "y", xdata, ydata, npts)).draw();
} else {
float[][] tempydata = new float[ycolumns][lines];
float[] tempxdata = new float[lines];
float[][] xdata = null;
float[][] ydata = null;
int startcolumn = 0;
if (hasxvals) startcolumn = 1;
for (int i = 0; i < lines; i++) {
float[] temp = ds.delim2float(rows[i], columns);
if (hasxvals) {
tempxdata[i] = temp[0];
} else {
tempxdata[i] = (float) (i + 1);
}
for (int j = 0; j < ycolumns; j++) {
tempydata[j][i] = temp[j + startcolumn];
}
}
int[] npts = new int[ycolumns];
npts[0] = lines;
if (skipendzeros) {
int maxpts = 0;
for (int i = 0; i < ycolumns; i++) {
int counter = lines - 1;
npts[i] = lines;
while ((tempydata[i][counter] == 0.0f || Float.isNaN(tempydata[i][counter]))
&& counter > 0) {
npts[i]--;
counter--;
}
if (npts[i] > maxpts) maxpts = npts[i];
IJ.log("" + npts[i]);
}
ydata = new float[ycolumns][maxpts];
xdata = new float[ycolumns][maxpts];
for (int i = 0; i < ycolumns; i++) {
// npts[i]=npts[0];
System.arraycopy(tempxdata, 0, xdata[i], 0, npts[i]);
System.arraycopy(tempydata[i], 0, ydata[i], 0, npts[i]);
}
} else {
ydata = tempydata;
xdata = new float[ycolumns][];
for (int i = 0; i < ycolumns; i++) {
npts[i] = npts[0];
xdata[i] = tempxdata.clone();
}
}
(new PlotWindow4("Text Plot", "x", "y", xdata, ydata, npts)).draw();
}
}
/** Ask for parameters and then execute. */
public void run(String arg) {
// 1 - Obtain the currently active image:
ImagePlus imp = IJ.getImage();
if (null == imp) {
IJ.showMessage("There must be at least one image open");
return;
}
if (imp.getBitDepth() != 8) {
IJ.showMessage("Error", "Only 8-bit images are supported");
return;
}
// 2 - Ask for parameters:
GenericDialog gd = new GenericDialog("Auto Local Threshold");
String[] methods = {
"Try all",
"Bernsen",
"Contrast",
"Mean",
"Median",
"MidGrey",
"Niblack",
"Otsu",
"Phansalkar",
"Sauvola"
};
gd.addMessage("Auto Local Threshold v1.5");
gd.addChoice("Method", methods, methods[0]);
gd.addNumericField("Radius", 15, 0);
gd.addMessage("Special paramters (if different from default)");
gd.addNumericField("Parameter_1", 0, 0);
gd.addNumericField("Parameter_2", 0, 0);
gd.addCheckbox("White objects on black background", true);
if (imp.getStackSize() > 1) {
gd.addCheckbox("Stack", false);
}
gd.addMessage("Thresholded result is always shown in white [255].");
gd.showDialog();
if (gd.wasCanceled()) return;
// 3 - Retrieve parameters from the dialog
String myMethod = gd.getNextChoice();
int radius = (int) gd.getNextNumber();
double par1 = (double) gd.getNextNumber();
double par2 = (double) gd.getNextNumber();
boolean doIwhite = gd.getNextBoolean();
boolean doIstack = false;
int stackSize = imp.getStackSize();
if (stackSize > 1) doIstack = gd.getNextBoolean();
// 4 - Execute!
// long start = System.currentTimeMillis();
if (myMethod.equals("Try all")) {
ImageProcessor ip = imp.getProcessor();
int xe = ip.getWidth();
int ye = ip.getHeight();
int ml = methods.length;
ImagePlus imp2, imp3;
ImageStack tstack = null, stackNew;
if (stackSize > 1 && doIstack) {
boolean doItAnyway = true;
if (stackSize > 25) {
YesNoCancelDialog d =
new YesNoCancelDialog(
IJ.getInstance(),
"Auto Local Threshold",
"You might run out of memory.\n \nDisplay "
+ stackSize
+ " slices?\n \n \'No\' will process without display and\noutput results to the log window.");
if (!d.yesPressed()) {
// doIlog=true; //will show in the log window
doItAnyway = false;
}
if (d.cancelPressed()) return;
}
for (int j = 1; j <= stackSize; j++) {
imp.setSlice(j);
ip = imp.getProcessor();
tstack = new ImageStack(xe, ye);
for (int k = 1; k < ml; k++) tstack.addSlice(methods[k], ip.duplicate());
imp2 = new ImagePlus("Auto Threshold", tstack);
imp2.updateAndDraw();
for (int k = 1; k < ml; k++) {
imp2.setSlice(k);
Object[] result = exec(imp2, methods[k], radius, par1, par2, doIwhite);
}
// if (doItAnyway){
CanvasResizer cr = new CanvasResizer();
stackNew = cr.expandStack(tstack, (xe + 2), (ye + 18), 1, 1);
imp3 = new ImagePlus("Auto Threshold", stackNew);
imp3.updateAndDraw();
MontageMaker mm = new MontageMaker();
mm.makeMontage(imp3, 3, 3, 1.0, 1, (ml - 1), 1, 0, true); // 3 columns and 3 rows
}
imp.setSlice(1);
// if (doItAnyway)
IJ.run("Images to Stack", "method=[Copy (center)] title=Montage");
return;
} else { // single image try all
tstack = new ImageStack(xe, ye);
for (int k = 1; k < ml; k++) tstack.addSlice(methods[k], ip.duplicate());
imp2 = new ImagePlus("Auto Threshold", tstack);
imp2.updateAndDraw();
for (int k = 1; k < ml; k++) {
imp2.setSlice(k);
// IJ.log("analyzing slice with "+methods[k]);
Object[] result = exec(imp2, methods[k], radius, par1, par2, doIwhite);
}
// imp2.setSlice(1);
CanvasResizer cr = new CanvasResizer();
stackNew = cr.expandStack(tstack, (xe + 2), (ye + 18), 1, 1);
imp3 = new ImagePlus("Auto Threshold", stackNew);
imp3.updateAndDraw();
MontageMaker mm = new MontageMaker();
mm.makeMontage(imp3, 3, 3, 1.0, 1, (ml - 1), 1, 0, true);
return;
}
} else { // selected a method
if (stackSize > 1 && doIstack) { // whole stack
// if (doIstackHistogram) {// one global histogram
// Object[] result = exec(imp, myMethod, noWhite, noBlack, doIwhite, doIset, doIlog,
// doIstackHistogram );
// }
// else{ // slice by slice
for (int k = 1; k <= stackSize; k++) {
imp.setSlice(k);
Object[] result = exec(imp, myMethod, radius, par1, par2, doIwhite);
}
// }
imp.setSlice(1);
} else { // just one slice
Object[] result = exec(imp, myMethod, radius, par1, par2, doIwhite);
}
// 5 - If all went well, show the image:
// not needed here as the source image is binarised
}
}
void sample() {
byte[] hsSource, ssSource, bsSource;
// ImageProcessor ip2;
// ip2 = imp.getProcessor();
Rectangle myroi = ip.getRoi();
int swidth = myroi.width;
int sheight = myroi.height;
int sy = myroi.y;
int sx = myroi.x;
if (swidth == width && sheight == height) {
IJ.showMessage("Select a rectangular ROI");
IJ.beep();
return;
}
IJ.run("Select None");
int snumPixels = swidth * sheight;
hsSource = new byte[snumPixels];
ssSource = new byte[snumPixels];
bsSource = new byte[snumPixels];
int[] pixs = new int[snumPixels];
int[] bin = new int[256];
int counter = 0, pi = 0, rangePassH = 0, rangeStopH = 0, rangePassL = 0, rangeStopL = 0, i, j;
for (i = sy; i < sy + sheight; i++) {
for (j = sx; j < sx + swidth; j++) {
pixs[counter++] = ip.getPixel(j, i);
}
}
// Get hsb or rgb from roi.
ColorProcessor cp2 = new ColorProcessor(swidth, sheight, pixs);
int iminhue = 256, imaxhue = -1, iminsat = 256, imaxsat = -1, iminbri = 256, imaxbri = -1;
int iminred = 256, imaxred = -1, imingre = 256, imaxgre = -1, iminblu = 256, imaxblu = -1;
if (isRGB) cp2.getRGB(hsSource, ssSource, bsSource);
else cp2.getHSB(hsSource, ssSource, bsSource);
for (i = 0; i < snumPixels; i++) {
bin[hsSource[i] & 255] = 1;
if ((hsSource[i] & 255) > imaxhue) imaxhue = (hsSource[i] & 255);
if ((hsSource[i] & 255) < iminhue) iminhue = (hsSource[i] & 255);
if ((ssSource[i] & 255) > imaxsat) imaxsat = (ssSource[i] & 255);
if ((ssSource[i] & 255) < iminsat) iminsat = (ssSource[i] & 255);
if ((bsSource[i] & 255) > imaxbri) imaxbri = (bsSource[i] & 255);
if ((bsSource[i] & 255) < iminbri) iminbri = (bsSource[i] & 255);
// IJ.showMessage("h:"+minhue+"H:"+maxhue+"s:"+minsat+"S:"+maxsat+"b:"+minbri+"B:"+maxbri);
}
if (!isRGB) { // get pass or stop filter whichever has a narrower range
for (i = 0; i < 256; i++) {
if (bin[i] > 0) {
rangePassL = i;
break;
}
}
for (i = 255; i >= 0; i--) {
if (bin[i] > 0) {
rangePassH = i;
break;
}
}
for (i = 0; i < 256; i++) {
if (bin[i] == 0) {
rangeStopL = i;
break;
}
}
for (i = 255; i >= 0; i--) {
if (bin[i] == 0) {
rangeStopH = i;
break;
}
}
if ((rangePassH - rangePassL) < (rangeStopH - rangeStopL)) {
bandPassH.setState(true);
bandStopH.setState(false);
iminhue = rangePassL;
imaxhue = rangePassH;
} else {
bandPassH.setState(false);
bandStopH.setState(true);
iminhue = rangeStopL;
imaxhue = rangeStopH;
}
} else {
bandPassH.setState(true);
bandStopH.setState(false);
}
adjustMinHue(iminhue);
minSlider.setValue(iminhue);
adjustMaxHue(imaxhue);
maxSlider.setValue(imaxhue);
adjustMinSat(iminsat);
minSlider2.setValue(iminsat);
adjustMaxSat(imaxsat);
maxSlider2.setValue(imaxsat);
adjustMinBri(iminbri);
minSlider3.setValue(iminbri);
adjustMaxBri(imaxbri);
maxSlider3.setValue(imaxbri);
originalB.setEnabled(true);
// IJ.showStatus("done");
}
public int setup(String arg, ImagePlus imp) {
IJ.showMessage(arg);
return DOES_8G + DOES_16 + STACK_REQUIRED;
}
void error() {
IJ.showMessage(
"PolScope Calculator",
"This plugin requires one or two stacks (two for BG correcion) that have\n"
+ "the same width, height, data type and at least 6 slices each.");
}
