public float[] fitdata(
double[] params,
int[] fixes1,
double[][] constraints,
float[] data,
float[] weights1,
double[] stats) {
// this function fits the array data to an arbitrary function denoted by
// the NLLSfitinterface
// the returned array is the fit
// stats returns the chisquared
// the weights are set to 1 if weights1 is null
// if fixes[i] is zero, the ith parameter is fit, if not, the ith
// parameter is fixed
// constraints is a 3 by nparams array containing the upper and lower
// bounds for each parameter
// and the parameter shift for the grid search
int nparams = params.length;
int npts = data.length;
int fitparams = nparams;
int[] fixes = new int[nparams];
if (fixes1 != null) {
for (int i = 0; i < nparams; i++) {
fitparams -= fixes1[i];
fixes[i] = fixes1[i];
}
}
for (int i = 0; i < nparams; i++) {
if (fixes[i] == 0) {
if (Math.abs(constraints[1][i] - constraints[0][i]) < constraints[2][i]) {
fixes[i] = 1;
params[i] = 0.5 * (constraints[0][i] + constraints[1][i]);
fitparams--;
}
}
}
double[] weights = new double[npts];
if (weights1 == null) {
for (int i = 0; i < npts; i++) {
weights[i] = 1.0;
}
} else {
for (int i = 0; i < npts; i++) {
weights[i] = weights1[i];
}
}
stats[1] = search_param(0, fitparams, params, fixes, constraints, data, weights);
StringBuffer resstring = new StringBuffer();
resstring.append("final minc2 =" + (float) stats[1]);
for (int i = 0; i < params.length; i++) {
resstring.append(" , " + (float) params[i]);
}
if (output) {
fitclass.showresults(resstring.toString());
}
double[] fit = fitclass.fitfunc(params);
float[] ffit = new float[fit.length];
for (int i = 0; i < fit.length; i++) {
ffit[i] = (float) fit[i];
}
return ffit;
}
public double calculate_c2_params(
double[] params, int numfit, float[] data, double[] weights, boolean[] fitmask) {
// this function calculates chisquared using the parameter array
double[] tempfit = fitclass.fitfunc(params);
return calculate_c2_fit(tempfit, numfit, data, weights, fitmask);
}
