# minimize(method=’trust-krylov’)

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.

  New in version 1.0.0.

  See also

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

  Options
    inexact bool, optional

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

minimize(method=’trust-ncg’) minimize(method=’trust-exact’)