SciPy

minimize(method=’SLSQP’)

scipy.optimize.minimize(fun, x0, args=(), method='SLSQP', jac=None, bounds=None, constraints=(), tol=None, callback=None, options={'func': None, 'maxiter': 100, 'ftol': 1e-06, 'iprint': 1, 'disp': False, 'eps': 1.4901161193847656e-08})

Minimize a scalar function of one or more variables using Sequential Least SQuares Programming (SLSQP).

See also

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

Options
ftolfloat

Precision goal for the value of f in the stopping criterion.

epsfloat

Step size used for numerical approximation of the Jacobian.

dispbool

Set to True to print convergence messages. If False, verbosity is ignored and set to 0.

maxiterint

Maximum number of iterations.

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