archimedes.optimize

Numerical optimization algorithms

Functions

implicit(func[, static_argnames, solver, name])	Construct an explicit function from an implicit relation.
least_squares(func, x0[, args, method, ...])	Solve nonlinear least squares problems
lm_solve(func, x0[, args, bounds, ftol, ...])	Solve nonlinear least squares using modified Levenberg-Marquardt algorithm.
minimize(obj, x0[, args, static_argnames, ...])	Minimize a scalar function with optional constraints and PyTree support.
nlp_solver(obj[, constr, static_argnames, ...])	Create a reusable solver for a nonlinear optimization problem.
qpsol(obj, constr, x0[, lba, uba, lam_a0, ...])	Solve a quadratic programming problem
root(func, x0[, args, static_argnames, ...])	Find a root of a nonlinear function.

Classes

LMResult	Result of Levenberg-Marquardt optimization.
LMStatus(*values)	Status codes for Levenberg-Marquardt optimization results.