scipy.optimize.minimize(fun, x0, args=(), method='trust-krylov', jac=None, hess=None, hessp=None, tol=None, callback=None, options={'inexact': True})

Minimization of a scalar function of one or more variables using a nearly exact trust-region algorithm that only requires matrix vector products with the hessian matrix.

See also

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


inexact : bool, optional

Accuracy to solve subproblems. If True requires less nonlinear iterations, but more vector products.

.. versionadded:: 1.0.0