`scipy.optimize._slsqplib:slsqp`

Signature

built-inslsqp(S, funx, gradx, C, d, sol, mult, xl, xu, buffer, indices)

Sequential Least Squares Programming solver.

Low-level interface to the SLSQP optimization algorithm. Performs a single iteration step.

S : dict: State dictionary containing algorithm parameters and internal state. Keys include: m (constraints), meq (equality constraints), n (variables), acc (accuracy), maxiter, mode, and internal state variables. Modified in-place.
funx : float: Current objective function value.
gradx : ndarray, shape (n,): Gradient of objective function at current point, float64.
C : ndarray, shape (m, n): Constraint Jacobian matrix, float64.
d : ndarray, shape (m,): Constraint values, float64.
sol : ndarray, shape (n,): Current solution vector, float64. Modified in-place.
mult : ndarray, shape (m + 2*n + 2,): Lagrange multipliers, float64.
xl : ndarray, shape (n,): Lower bounds on variables, float64. Use NaN for unbounded.
xu : ndarray, shape (n,): Upper bounds on variables, float64. Use NaN for unbounded.
buffer : ndarray: Workspace array for internal computations, float64.
indices : ndarray: Index array for internal computations, int32.