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 void run(String arg) {
GenericDialog gd = new GenericDialog("Options");
double sfreq = 20000.0;
gd.addNumericField("Sampling Frequency?", sfreq, 1, 10, null);
String[] psfchoice = {"3D Gaussian", "Gaus-Lorentz^2", "2D Gaussian"};
gd.addChoice("PSF Type?", psfchoice, psfchoice[0]);
String[] filetypechoice = {
"Confocor 3 raw", "Short binary trajectory", "PlotWindow trajectory", "Ascii Text File"
};
gd.addChoice("File Type?", filetypechoice, filetypechoice[0]);
boolean ch2green = true;
gd.addCheckbox("Ch2 is green?", ch2green);
gd.showDialog();
if (gd.wasCanceled()) {
return;
}
sfreq = gd.getNextNumber();
int psfflag = gd.getNextChoiceIndex();
int fileflag = gd.getNextChoiceIndex();
ch2green = gd.getNextBoolean();
int nfiles = 0;
Object[] histograms = null;
int xmax = 0;
int ymax = 0;
String[] names = null;
if (fileflag < 2) {
jdataio ioclass = new jdataio();
File[] filearray = ioclass.openfiles(OpenDialog.getDefaultDirectory(), IJ.getInstance());
if (filearray.length == 0) {
return;
}
String dir = filearray[0].getAbsolutePath();
int sepindex = dir.lastIndexOf(File.separator);
String newdir = dir.substring(0, sepindex + 1);
OpenDialog.setDefaultDirectory(newdir);
nfiles = filearray.length / 2;
if (nfiles > 25) {
nfiles = 25;
}
histograms = new Object[nfiles];
names = organize_c3_files(filearray);
for (int i = 0; i < nfiles; i++) {
try {
int length1 = (int) (((double) filearray[2 * i].length() - 128.0) / 4.0);
int length2 = (int) (((double) filearray[2 * i + 1].length() - 128.0) / 4.0);
int length3 = (int) (((double) filearray[2 * i].length()) / 2.0);
int length4 = (int) (((double) filearray[2 * i + 1].length()) / 2.0);
InputStream instream = new BufferedInputStream(new FileInputStream(filearray[2 * i]));
InputStream instream2 =
new BufferedInputStream(new FileInputStream(filearray[2 * i + 1]));
if (fileflag == 0) {
int[] pmdata = new int[length1];
int[] pmdata2 = new int[length2];
if (!ioclass.skipstreambytes(instream, 128)) {
showioerror();
instream.close();
return;
}
if (!ioclass.skipstreambytes(instream2, 128)) {
showioerror();
instream2.close();
return;
}
if (!ioclass.readintelintfile(instream, length1, pmdata)) {
showioerror();
instream.close();
return;
}
if (!ioclass.readintelintfile(instream2, length2, pmdata2)) {
showioerror();
instream2.close();
return;
}
if (ch2green) {
histograms[i] = (new pmodeconvert()).pm2pch(pmdata2, pmdata, sfreq, 20000000);
} else {
histograms[i] = (new pmodeconvert()).pm2pch(pmdata, pmdata2, sfreq, 20000000);
}
} else {
float[] tmdata = new float[length3];
float[] tmdata2 = new float[length4];
if (!ioclass.readintelshortfile(instream, length3, tmdata)) {
showioerror();
instream.close();
return;
}
if (!ioclass.readintelshortfile(instream2, length4, tmdata2)) {
showioerror();
instream2.close();
return;
}
if (ch2green) {
histograms[i] = (new pmodeconvert()).create_2Dhistogram(tmdata2, tmdata);
} else {
histograms[i] = (new pmodeconvert()).create_2Dhistogram(tmdata, tmdata2);
}
}
if (((float[][]) histograms[i]).length > xmax) {
xmax = ((float[][]) histograms[i]).length;
}
if (((float[][]) histograms[i])[0].length > ymax) {
ymax = ((float[][]) histograms[i])[0].length;
}
instream.close();
instream2.close();
} catch (IOException e) {
showioerror();
return;
}
}
} else {
if (fileflag == 2) {
ImageWindow iw = WindowManager.getCurrentWindow();
float[][] trajectories = (float[][]) jutils.runPW4VoidMethod(iw, "getYValues");
float[][] tempxvals = (float[][]) jutils.runPW4VoidMethod(iw, "getXValues");
sfreq = 1.0 / ((double) tempxvals[0][1]);
nfiles = trajectories.length / 2;
if (nfiles > 25) {
nfiles = 25;
}
names = new String[nfiles + 1];
names[nfiles] = "avg";
histograms = new Object[nfiles];
for (int i = 0; i < nfiles; i++) {
names[i] = "trajectory " + (i + 1);
if (ch2green) {
histograms[i] =
(new pmodeconvert())
.create_2Dhistogram(trajectories[2 * i + 1], trajectories[2 * i]);
} else {
histograms[i] =
(new pmodeconvert())
.create_2Dhistogram(trajectories[2 * i], trajectories[2 * i + 1]);
}
if (((float[][]) histograms[i]).length > xmax) {
xmax = ((float[][]) histograms[i]).length;
}
if (((float[][]) histograms[i])[0].length > ymax) {
ymax = ((float[][]) histograms[i])[0].length;
}
}
} else {
// here we read tab delimited lines from files
jdataio ioclass = new jdataio();
File[] filearray = ioclass.openfiles(OpenDialog.getDefaultDirectory(), IJ.getInstance());
if (filearray.length == 0) {
return;
}
String dir = filearray[0].getAbsolutePath();
int sepindex = dir.lastIndexOf(File.separator);
String newdir = dir.substring(0, sepindex + 1);
OpenDialog.setDefaultDirectory(newdir);
nfiles = filearray.length;
if (nfiles > 25) {
nfiles = 25;
}
histograms = new Object[nfiles];
names = new String[nfiles + 1];
names[nfiles] = "avg";
for (int i = 0; i < nfiles; i++) {
try {
names[i] = filearray[i].getName();
BufferedReader d = new BufferedReader(new FileReader(filearray[i]));
String[] lines = new String[256];
int counter = 0;
do {
lines[counter] = d.readLine();
counter++;
} while ((lines[counter - 1] != null && lines[counter - 1] != "") && counter < 256);
int numcolumns = 0;
for (int j = 0; j < counter - 1; j++) {
int temp = getncolumns(lines[j]);
if (temp > numcolumns) {
numcolumns = temp;
}
}
float[][] temphist2 = null;
if (ch2green) {
temphist2 = new float[numcolumns][counter - 1];
} else {
temphist2 = new float[counter - 1][numcolumns];
}
for (int k = 0; k < counter - 1; k++) {
float[] temp = tab_delim2float(lines[k]);
for (int j = 0; j < numcolumns; j++) {
if (ch2green) {
temphist2[j][k] = temp[j];
} else {
temphist2[k][j] = temp[j];
}
}
}
histograms[i] = temphist2;
d.close();
} catch (IOException e) {
showioerror();
return;
}
}
for (int i = 0; i < nfiles; i++) {
if (((float[][]) histograms[i]).length > xmax) {
xmax = ((float[][]) histograms[i]).length;
}
if (((float[][]) histograms[i])[0].length > ymax) {
ymax = ((float[][]) histograms[i])[0].length;
}
}
}
}
// note that here x is green and y is red
float[][][] pch = new float[nfiles][xmax][ymax];
for (int i = 0; i < nfiles; i++) {
for (int j = 0; j < ((float[][]) histograms[i]).length; j++) {
for (int k = 0; k < ((float[][]) histograms[i])[j].length; k++) {
pch[i][j][k] = ((float[][]) histograms[i])[j][k];
}
}
}
final PCH2DFitWindow cw = new PCH2DFitWindow();
cw.init(names, pch, psfflag);
final Frame f = new Frame("PCH 2D Analysis");
f.setLocation(10, 10);
f.addWindowListener(
new WindowAdapter() {
public void windowClosing(WindowEvent e) {
f.dispose();
}
});
f.add(cw);
f.pack();
f.setResizable(false);
Insets ins = f.getInsets();
cw.totalSize.height = PCH2DFitWindow.H + ins.bottom + ins.top + 65;
cw.totalSize.width = PCH2DFitWindow.WR + ins.left + ins.right;
f.setSize(cw.totalSize);
f.setVisible(true);
cw.requestFocus();
}
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;
}