public void Minimize()
{
int n_p = Coefficients.Length;
int m_dat = n_p;
// data and pameter arrays:
double[] p = new double[Coefficients.Length];
Coefficients.CopyTo(p, 0);
// auxiliary settings:
lmmin.lm_control_type control = new lmmin.lm_control_type();
lmmin.lm_initialize_control(control);
control.epsilon = 0.001;
lm_data_type data = new lm_data_type();
data.f = my_fit_function;
// perform the fit:
lmmin.lm_minimize(m_dat, n_p, p, lm_evaluate, lm_print,
data, control);
// print results:
Console.Write("status: {0} after {1} evaluations\n",
lmmin.lm_shortmsg[control.info], control.nfev);
Console.Write("Coefficients = new double[] {");
for (int i = 0; i < Coefficients.Length; i++)
{
if (i == 0 || i == 5)
{
Console.WriteLine();
Console.Write(" /* {0} */", i);
}
Console.Write(" {0:G10},", Coefficients[i]);
}
Console.WriteLine();
Console.WriteLine("};");
}
public void Minimize()
{
int n_p = Coefficients.Length;
int m_dat = n_p;
// data and pameter arrays:
double[] p = new double[Coefficients.Length];
Coefficients.CopyTo(p, 0);
// auxiliary settings:
lmmin.lm_control_type control = new lmmin.lm_control_type();
lmmin.lm_initialize_control(control);
control.epsilon = 0.001;
lm_data_type data = new lm_data_type();
data.f = my_fit_function;
// perform the fit:
lmmin.lm_minimize(m_dat, n_p, p, lm_evaluate, lm_print,
data, control);
// print results:
Console.Write("status: {0} after {1} evaluations\n",
lmmin.lm_shortmsg[control.info], control.nfev);
Console.Write("Coefficients = new double[] {");
for (int i = 0; i < Coefficients.Length; i++)
{
if (i == 0 || i == 5)
{
Console.WriteLine();
Console.Write(" /* {0} */", i);
}
Console.Write(" {0:G10},", Coefficients[i]);
}
Console.WriteLine();
Console.WriteLine("};");
}
