fminNCG#
- swordfish.function.fminNCG()#
Perform unconstrained minimization of a function using the Newton-CG method.
- Parameters:
func (Constant) – The function to minimize. The return value of the function must be numeric type.
X0 (Constant) – A numeric scalar or vector indicating the initial guess.
fprime (Constant) – The gradient of func.
fhess (Constant) – The function to compute the Hessian matrix of func.
xtol (Constant, optional) – A positive number. Convergence is assumed when the average relative error in the minimizer falls below this amount. The default value is 1e-5.
maxIter (Constant, optional) – A non-negative integer indicating the maximum number of iterations. The default value is 15000.
c1 (Constant, optional) – A number in (0,1) indicating the parameter for Armijo condition rule. The default value is 1e-4.
c2 (Constant, optional) – A number in (0,1) indicating the parameter for curvature condition rule. The default value is 0.9. Note that c2 must be greater than c1.
- Returns:
A dictionary with the following members:
xopt: A floating-point vector indicating the parameters of the minimum.
fopt: A floating-point scalar indicating the value of func at the minimum, i.e., fopt=func(xopt).
iterations: The number of iterations.
fcalls: The number of function calls made.
hcalls: The number of Hessian calls made.
warnFlag: An integer, which can be
0: Minimization performed.
1: Maximum number of iterations exceeded.
2: Line search failure (precision loss).
3: Null result encountered.
- Return type: