minimize(method=’BFGS’)¶
- 
scipy.optimize.minimize(fun, x0, args=(), method='BFGS', 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 BFGS 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. 
 
 
