public String toString() {
StringBuffer ret = new StringBuffer();
ret.append("Index : " + index + "\n");
ret.append("Mu : " + mu + "\n");
ret.append("Omega : " + omega + "\n");
/*for(int i=0; i<10; i++) {
ret.append( "\n" );
}*/
return ret.toString();
}
/** Returns a text file contained in ij.jar. */
public String openFromIJJar(String path) {
String text = null;
try {
InputStream is = this.getClass().getResourceAsStream(path);
// IJ.log(is+" "+path);
if (is == null) return null;
InputStreamReader isr = new InputStreamReader(is);
StringBuffer sb = new StringBuffer();
char[] b = new char[8192];
int n;
while ((n = isr.read(b)) > 0) sb.append(b, 0, n);
text = sb.toString();
} catch (IOException e) {
}
return text;
}
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;
}