_minimize_slsqp(func, x0, args=(), jac=None, bounds=None, constraints=(), maxiter=100, ftol=1e-06, iprint=1, disp=False, eps=1.4901161193847656e-08, callback=None, finite_diff_rel_step=None, **unknown_options)
Precision goal for the value of f in the stopping criterion.
Step size used for numerical approximation of the Jacobian.
Set to True to print convergence messages. If False, :None:None:`verbosity` is ignored and set to 0.
Maximum number of iterations.
If :None:None:`jac in ['2-point', '3-point', 'cs']` the relative step size to use for numerical approximation of :None:None:`jac`. The absolute step size is computed as h = rel_step * sign(x0) * max(1, abs(x0))
, possibly adjusted to fit into the bounds. For method='3-point'
the sign of :None:None:`h` is ignored. If None (default) then step is selected automatically.
Minimize a scalar function of one or more variables using Sequential Least Squares Programming (SLSQP).
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