package lbfgs

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in-package search v0.2.0

lbfgs
- Lbfgs
  - C
  - F

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Module
Module type
Parameter
Class
Class type

Fortran Layout.

type vec =
  (float, Bigarray.float64_elt, Bigarray.fortran_layout) Bigarray.Array1.t

Vectors.

val min : 
  ?print:print ->
  ?work:work ->
  ?nsteps:int ->
  ?stop:(state -> bool) ->
  ?corrections:int ->
  ?factr:float ->
  ?pgtol:float ->
  ?n:int ->
  ?ofsl:int ->
  ?l:vec ->
  ?ofsu:int ->
  ?u:vec ->
  (vec -> vec -> float) ->
  ?ofsx:int ->
  vec ->
  float

min f_df x compute the minimum of the function f given by f_df. x is an initial estimate of the solution vector. On termination, x will contain the best approximation found. f_df x df is a function that computes f(x) and its gradiant f'(x), returns f(x) and stores f'(x) in df. The x passed to f_df x df is physically equal to the x given in min f_df x. Can raise Abnormal.

parameter l
lower bound for each component of the vector x. Set l.(i) to neg_infinity to indicate that no lower bound is desired. Default: no lower bounds.

parameter u
upper bound for each component of the vector x. Set u.(i) to infinity to indicate that no upper bound is desired. Default: no upper bounds.

parameter n
the dimension of the space of unknowns. Default: dim x - ofsx + 1.

parameter ofsl
offset for the matrix l. Default: 1.

parameter ofsu
offset for the matrix u. Default: 1.

parameter ofsx
offset for the matrix x. Default: 1.

parameter factr
tolerance in the termination test for the algorithm. The iteration will stop when (f^k - f^{k+1})/max{ |f^k|,|f^{k+1}|, 1 } <= factr*epsilon_float. Set e.g. factr to 1e12 for low accuracy, 1e7 for moderate accuracy and 1e1 for extremely high accuracy. Setting factr to 0. suppresses this termination test. Default: 1e7.

parameter pgtol
The iteration will stop when max{ |proj g_i| : i = 1,..., n} <= pgtol where proj g_i is the ith component of the projected gradient. Setting pgtol to 0. suppresses this termination test. Default: 1e-5.

parameter corrections
maximum number of variable metric corrections used to define the limited memory matrix. Values < 3 are not recommended, and large values of corrections can result in excessive computing time. The range 3 <= corrections <= 20 is recommended. Default: 10.

parameter nsteps
maximum number of steps. Default: no limitation.

parameter stop
a function that tells whether we stop the computation after at the current approximation.

parameter print
Tells the amount of debugging information desired. Default: No.

val max : 
  ?print:print ->
  ?work:work ->
  ?nsteps:int ->
  ?stop:(state -> bool) ->
  ?corrections:int ->
  ?factr:float ->
  ?pgtol:float ->
  ?n:int ->
  ?ofsl:int ->
  ?l:vec ->
  ?ofsu:int ->
  ?u:vec ->
  (vec -> vec -> float) ->
  ?ofsx:int ->
  vec ->
  float

max f_df x computes the maximum of the function f given by f_df. x is an initial estimate of the solution vector. This function is provided for convenience and calls F.min to which the reader is referred for further explanations.