Minimize a function using a nonlinear conjugate gradient algorithm.
Parameters : | f : callable f(x,*args)
x0 : ndarray
fprime : callable f’(x,*args)
args : tuple
gtol : float
norm : float
epsilon : float or ndarray
callback : callable
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Returns : | xopt : ndarray
fopt : float
func_calls : int
grad_calls : int
warnflag : int
allvecs : ndarray
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Other Parameters: | |
maxiter : int
full_output : bool
disp : bool
retall : bool
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Notes
Optimize the function, f, whose gradient is given by fprime using the nonlinear conjugate gradient algorithm of Polak and Ribiere. See Wright & Nocedal, ‘Numerical Optimization’, 1999, pg. 120-122.