empire/lbfgs__sub_8f90_source.html

 !

 !  L-BFGS-B is released under the “New BSD License” (aka “Modified

 !  BSD License”

 !  or “3-clause license”)

 !  Please read attached file License.txt

 !

 !

 !                      DRIVER1 in Fortran 90

 !     --------------------------------------------------------------

 !     --------------------------------------------------------------

 !             DESCRIPTION OF THE VARIABLES IN L-BFGS-B

 !     --------------------------------------------------------------

 !

 !     n is an INTEGER variable that must be set by the user to the

 !       number of variables.  It is not altered by the routine.

 !

 !     m is an INTEGER variable that must be set by the user to the

 !       number of corrections used in the limited memory matrix.

 !       It is not altered by the routine.  Values of m < 3  are

 !       not recommended, and large values of m can result in excessive

 !       computing time. The range  3 <= m <= 20 is recommended.

 !

 !     x is a DOUBLE PRECISION array of length n.  On initial entry

 !       it must be set by the user to the values of the initial

 !       estimate of the solution vector.  Upon successful exit, it

 !       contains the values of the variables at the best point

 !       found (usually an approximate solution).

 !

 !     l is a DOUBLE PRECISION array of length n that must be set by

 !       the user to the values of the lower bounds on the variables. If

 !       the i-th variable has no lower bound, l(i) need not be defined.

 !

 !     u is a DOUBLE PRECISION array of length n that must be set by

 !       the user to the values of the upper bounds on the variables. If

 !       the i-th variable has no upper bound, u(i) need not be defined.

 !

 !     nbd is an INTEGER array of dimension n that must be set by the

 !       user to the type of bounds imposed on the variables:

 !       nbd(i)=0 if x(i) is unbounded,

 !              1 if x(i) has only a lower bound,

 !              2 if x(i) has both lower and upper bounds,

 !              3 if x(i) has only an upper bound.

 !

 !     f is a DOUBLE PRECISION variable.  If the routine setulb returns

 !       with task(1:2)= 'FG', then f must be set by the user to

 !       contain the value of the function at the point x.

 !

 !     g is a DOUBLE PRECISION array of length n.  If the routine setulb

 !       returns with taskb(1:2)= 'FG', then g must be set by the user to

 !       contain the components of the gradient at the point x.

 !

 !     factr is a DOUBLE PRECISION variable that must be set by the user.

 !       It is a 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*epsmch

 !

 !       where epsmch is the machine precision which is automatically

 !       generated by the code. Typical values for factr on a computer

 !       with 15 digits of accuracy in double precision are:

 !       factr=1.d+12 for low accuracy;

 !             1.d+7  for moderate accuracy;

 !             1.d+1  for extremely high accuracy.

 !       The user can suppress this termination test by setting factr=0.

 !

 !     pgtol is a double precision variable.

 !       On entry pgtol >= 0 is specified by the user.  The iteration

 !         will stop when

 !

 !                 max{|proj g_i | i = 1, ..., n} <= pgtol

 !

 !         where pg_i is the ith component of the projected gradient.

 !       The user can suppress this termination test by setting pgtol=0.

 !

 !     wa is a DOUBLE PRECISION  array of length

 !       (2mmax + 5)nmax + 11mmax^2 + 8mmax used as workspace.

 !       This array must not be altered by the user.

 !

 !     iwa is an INTEGER  array of length 3nmax used as

 !       workspace. This array must not be altered by the user.

 !

 !     task is a CHARACTER string of length 60.

 !       On first entry, it must be set to 'START'.

 !       On a return with task(1:2)='FG', the user must evaluate the

 !         function f and gradient g at the returned value of x.

 !       On a return with task(1:5)='NEW_X', an iteration of the

 !         algorithm has concluded, and f and g contain f(x) and g(x)

 !         respectively.  The user can decide whether to continue or stop

 !         the iteration.

 !       When

 !         task(1:4)='CONV', the termination test in L-BFGS-B has been

 !           satisfied;

 !         task(1:4)='ABNO', the routine has terminated abnormally

 !           without being able to satisfy the termination conditions,

 !           x contains the best approximation found,

 !           f and g contain f(x) and g(x) respectively;

 !         task(1:5)='ERROR', the routine has detected an error in the

 !           input parameters;

 !       On exit with task = 'CONV', 'ABNO' or 'ERROR', the variable task

 !         contains additional information that the user can print.

 !       This array should not be altered unless the user wants to

 !          stop the run for some reason.  See driver2 or driver3

 !          for a detailed explanation on how to stop the run

 !          by assigning task(1:4)='STOP' in the driver.

 !

 !     iprint is an INTEGER variable that must be set by the user.

 !       It controls the frequency and type of output generated:

 !        iprint<0    no output is generated;

 !        iprint=0    print only one line at the last iteration;

 !        0<iprint<99 print also f and |proj g| every iprint iterations;

 !        iprint=99   print details of every iteration except n-vectors;

 !        iprint=100  print also the changes of active set and final x;

 !        iprint>100  print details of every iteration including x and g;

 !       When iprint > 0, the file iterate.dat will be created to

 !                        summarize the iteration.

 !

 !     csave  is a CHARACTER working array of length 60.

 !

 !     lsave is a LOGICAL working array of dimension 4.

 !       On exit with task = 'NEW_X', the following information is

 !         available:

 !       lsave(1) = .true.  the initial x did not satisfy the bounds;

 !       lsave(2) = .true.  the problem contains bounds;

 !       lsave(3) = .true.  each variable has upper and lower bounds.

 !

 !     isave is an INTEGER working array of dimension 44.

 !       On exit with task = 'NEW_X', it contains information that

 !       the user may want to access:

 !         isave(30) = the current iteration number;

 !         isave(34) = the total number of function and gradient

 !                         evaluations;

 !         isave(36) = the number of function value or gradient

 !                                  evaluations in the current iteration;

 !         isave(38) = the number of free variables in the current

 !                         iteration;

 !         isave(39) = the number of active constraints at the current

 !                         iteration;

 !

 !         see the subroutine setulb.f for a description of other

 !         information contained in isave

 !

 !     dsave is a DOUBLE PRECISION working array of dimension 29.

 !       On exit with task = 'NEW_X', it contains information that

 !         the user may want to access:

 !         dsave(2)  = the value of f at the previous iteration;

 !         dsave(5)  = the machine precision epsmch generated by the code;

 !         dsave(13) = the infinity norm of the projected gradient;

 !

 !         see the subroutine setulb.f for a description of other

 !         information contained in dsave

 !

 !     --------------------------------------------------------------

 !           END OF THE DESCRIPTION OF THE VARIABLES IN L-BFGS-B

 !     --------------------------------------------------------------

 !

       subroutine lbfgs_sub(n,factr_in,pgtol_in,x)

 !

 !     This simple driver demonstrates how to call the L-BFGS-B code to

 !       solve a sample problem (the extended Rosenbrock function

 !       subject to bounds on the variables). The dimension n of this

 !       problem is variable.


       implicit none

 !

 !     Declare variables and parameters needed by the code.

 !       Note thar we wish to have output at every iteration.

 !          iprint=1

 !

 !       We also specify the tolerances in the stopping criteria.

 !          factr  = 1.0d+7, pgtol  = 1.0d-5

 !

 !       A description of all these variables is given at the beginning

 !       of  the driver

 !

       integer,  parameter    :: dp = kind(1.0d0)

       integer, intent(in) :: n

       real(kind=dp), intent(in) :: factr_in

       real(kind=dp), intent(in) :: pgtol_in

       real(kind=dp), dimension(n), intent(inout) :: x


       integer,  parameter    :: m = 5, iprint = 1


       real(dp)               :: factr  = 1.0d+7, pgtol  = 1.0d-5

 !

       character(len=60)      :: task, csave

       logical                :: lsave(4)

       integer                :: isave(44)

       real(dp)               :: f

       real(dp)               :: dsave(29)

       integer,  allocatable  :: nbd(:), iwa(:)

       real(dp), allocatable  :: l(:), u(:), g(:), wa(:)


 !     Set convergence parameters


       factr = factr_in

       pgtol = pgtol_in


 !     Allocate dynamic arrays


       allocate ( nbd(n), l(n), u(n), g(n) )

       allocate ( iwa(3*n) )

       allocate ( wa(2*m*n + 5*n + 11*m*m + 8*m) )

 !


       !there are no constraints so set all entries of nbd = 0

       nbd = 0


       write (6,16)

   16  format(/,5x, 'Solving sample problem.', &

              /,5x, ' (f = 0.0 at the optimal solution.)',/)


 !     We start the iteration by initializing task.


       task = 'START'


 !     The beginning of the loop


       do while(task(1:2).eq.'FG'.or.task.eq.'NEW_X'.or. &

                task.eq.'START')


 !     This is the call to the L-BFGS-B code.


          call setulb( n, m, x, l, u, nbd, f, g, factr, pgtol, &

                        wa, iwa, task, iprint,&

                        csave, lsave, isave, dsave )


          if (task(1:2) .eq. 'FG') then

             call fcn(n,x,f,g)

 !            call objective_function(n,x,f)

 !     Compute gradient g for the sample problem.

 !            call objective_gradient(n,x,g)

          end if

       end do


 !     end of loop do while


     end subroutine lbfgs_sub


fcn
subroutine fcn(n, x, f, g)
This is the subroutine which the optimization routines call to get the objective function value and i...
Definition: 4denvar_fcn.f90:31

lbfgs_sub
subroutine lbfgs_sub(n, factr_in, pgtol_in, x)
Limited memory BFGS unconstrained optimization code as callable subroutine.
Definition: lbfgs_sub.f90:198