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]);
}
}
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]);
}
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;
}
