minimize(method=’CG’)

scipy.optimize.minimize(fun, x0, args=(), method='CG', jac=None, tol=None, callback=None, options={'gtol': 1e-05, 'norm': inf, 'eps': 1.4901161193847656e-08, 'maxiter': None, 'disp': False, 'return_all': False})

Minimization of scalar function of one or more variables using the conjugate gradient algorithm.

See also

For documentation for the rest of the parameters, see scipy.optimize.minimize

Options

dispbool

Set to True to print convergence messages.

maxiterint

Maximum number of iterations to perform.

gtolfloat

Gradient norm must be less than gtol before successful termination.

normfloat

Order of norm (Inf is max, -Inf is min).

epsfloat or ndarray

If jac is approximated, use this value for the step size.