nlopt-ocaml 0.5 · OCaml Package

OCaml interface to the NLopt optimization library

type 'a algorithm

Represent an algorithm, the parameter giving some properties of the algorithm.

val direct : [ `Global ] algorithm

val direct_l : [ `Global | `Ineq ] algorithm

val direct_l_rand : [ `Global ] algorithm

val direct_noscal : [ `Global ] algorithm

val direct_l_noscal : [ `Global ] algorithm

val direct_l_rand_noscal : [ `Global ] algorithm

val orig_direct : [ `Global | `Ineq ] algorithm

val orig_direct_l : [ `Global ] algorithm

val stogo : [ `Global | `Grad ] algorithm

val stogo_rand : [ `Global | `Grad ] algorithm

val lbfgs_nocedal : [ `Local | `Grad ] algorithm

val lbfgs : [ `Local | `Grad ] algorithm

val praxis : [ `Local ] algorithm

val var1 : [ `Local | `Grad ] algorithm

val var2 : [ `Local | `Grad ] algorithm

val tnewton : [ `Local | `Grad ] algorithm

val tnewton_restart : [ `Local | `Grad ] algorithm

val tnewton_precond : [ `Local | `Grad ] algorithm

val tnewton_precond_restart : [ `Local | `Grad ] algorithm

val crs2_lm : [ `Global ] algorithm

val mma : [ `Local | `Grad | `Ineq ] algorithm

val cobyla : [ `Local | `Ineq | `Eq ] algorithm

val newuoa : [ `Local ] algorithm

val newuoa_bound : [ `Local ] algorithm

val neldermead : [ `Local ] algorithm

val sbplx : [ `Local ] algorithm

val bobyqa : [ `Local ] algorithm

val isres : [ `Global | `Ineq | `Eq ] algorithm

val auglag : [ `Subsidiary | `Ineq | `Eq ] algorithm

val auglag_eq : [ `Subsidiary | `Ineq | `Eq ] algorithm

val mlsl : [ `Subsidiary | `Global ] algorithm

val mlsl_lds : [ `Subsidiary | `Global ] algorithm

val slsqp : [ `Local | `Grad | `Ineq | `Eq ] algorithm

type 'a t

A value containing the information about the optimization problem.

exception Roundoff_limited

exception Forced_stop

val create : 'a algorithm -> int -> 'a t

val set_min_objective : 
  'a t ->
  (float array -> float array option -> float) ->
  unit

val set_max_objective : 
  'a t ->
  (float array -> float array option -> float) ->
  unit

val optimize : 
  'a t ->
  float array ->
  [> `Success
  | `Stopval_reached
  | `Stopval_reached
  | `Ftol_reached
  | `Xtol_reached
  | `Maxeval_reached
  | `Maxtime_reached ]
  * float array
  * float

optimize opt x performs the optimization using x as an initial guess (it must be of size get_dimension opt). Returns a triple (result, xopt, fopt) where xopt is the optimzed value and fopt is the function value at that optimum.

raises Invalid_argument
x does not match the dimension of opt or NLopt returned NLOPT_INVALID_ARGS

raises Out_of_memory
NLopt returned NLOPT_OUT_OF_MEMORY

raises Failure
NLopt returned NLOPT_FAILURE

raises Roundoff_limited
NLopt returned NLOPT_ROUNDOFF_LIMITED

val get_dimension : 'a t -> int

Bound constraints

val set_lower_bounds : 'a t -> float array -> unit

val get_lower_bounds : 'a t -> float array

val set_upper_bounds : 'a t -> float array -> unit

val get_upper_bounds : 'a t -> float array

Nonlinear constraints

val add_inequality_constraint : 
  [> `Ineq ] t ->
  (float array -> float array option -> float) ->
  float ->
  unit

val add_equality_constraint : 
  [> `Eq ] t ->
  (float array -> float array option -> float) ->
  float ->
  unit

Stopping criteria

val set_stopval : 'a t -> float -> unit

val get_stopval : 'a t -> float

val set_ftol_rel : 'a t -> float -> unit

val get_ftol_rel : 'a t -> float

val set_ftol_abs : 'a t -> float -> unit

val get_ftol_abs : 'a t -> float

val set_xtol_rel : 'a t -> float -> unit

val get_xtol_rel : 'a t -> float

val set_xtol_abs : 'a t -> float array -> unit

val get_xtol_abs : 'a t -> float array

val set_maxeval : 'a t -> int -> unit

val get_maxeval : 'a t -> int

val set_maxtime : 'a t -> float -> unit

val get_maxtime : 'a t -> float

Local/subsidiary optimization algorithm

val set_local_optimizer : [> `Subsidiary ] t -> 'a t -> unit

Initial step size

val set_initial_step : 'a t -> float array -> unit

val get_initial_step : 'a t -> float array -> float array

Stochastic population

val set_population : 'a t -> int -> unit

Vector storage for limited-memory quasi-Newton algorithms

val set_vector_storage : 'a t -> int -> unit

val get_vector_storage : 'a t -> int

Utility functions

val version : unit -> int * int * int

val string_of_result : 
  [< `Success
  | `Stopval_reached
  | `Stopval_reached
  | `Ftol_reached
  | `Xtol_reached
  | `Maxeval_reached
  | `Maxtime_reached ] ->
  string

package nlopt-ocaml