Question

我试图使用NAG优化库来解决Fortran中的最大似然问题，但是我遇到了从外部子程序funct和hess访问主程序中的变量的问题（参见pseudo-代码如下）。将变量（例如b）从主程序传递给这样的例程的最佳方法是什么，因为我不能直接将它们作为参数传递（NAG库的限制）。我试图实现COMMON块，但没有太大的成功。

MODULE user_parameters
    ! Define the user parameters
    INTEGER, PARAMETER :: a = 100
    ... other parameters
END MODULE user_parameters


MODULE process_data
    USE user_parameters

    ! Define some other variables
    INTEGER :: b
    ... other variables

CONTAINS

    SUBROUTINE read_data
        ... read the data (e.g. alter value of b)
    END SUBROUTINE read_data

    SUBROUTINE clean_data
        ... clean the data (e.g. alter value of b)
    END SUBROUTINE clean_data
END MODULE process_data


MODULE maximum_likelihood
    USE user_parameters
    USE process_data

CONTAINS

    SUBROUTINE funct
        ... returns the LL's function value and gradient
    END SUBROUTINE funct

    SUBROUTINE hess
        ... returns the LL's hessian
    END SUBROUTINE hess
END MODULE maximum_likelihood


PROGRAM estimation
    USE user_parameters
    USE process_data
    USE maximum_likelihood
    EXTERNAL funct, hess

    CALL read_data
    CALL clean_data

    ! Call minimization routine
    CALL E04LBF(funct, hess)

END PROGRAM estimation

Answer 1

如何编写模块maximum_likelihood如下？

MODULE maximum_likelihood
    IMPLICIT NONE
    PRIVATE
    PUBLIC init, fin, funct, hess

    INTEGER, SAVE                         :: aa, bb
    REAL, DIMENSION(:), ALLOCATABLE, SAVE :: vv

CONTAINS

    SUBROUTINE init(aa_arg, bb_arg, vv_arg)
        ! set values module variables
    END SUBROUTINE init

    SUBROUTINE fin()
        deallocate(vv) 
    END SUBROUTINE fin

    SUBROUTINE funct
        ... returns the LL's function value and gradient
        ! using the values of aa, bb, and/or vv
    END SUBROUTINE funct

    SUBROUTINE hess
        ... returns the LL's hessian
        ! using the values of aa, bb, and/or vv
    END SUBROUTINE hess

END MODULE maximum_likelihood

然后，主程序看起来像

PROGRAM estimation
    USE maximum_likelihood, ONLY: init, fin, funct, hess

    ! read values for the parameters aaa, bbb, vvv

    ! set these values in the module variables in maximum_likelihood
    CALL init(aaa, bbb, vvv)

    ! Call minimization routine
    CALL E04LBF(funct, hess)

    ! clean up the module variables in maximum_likelihood
    CALL fin()

END PROGRAM estimation

从外部子程序访问主程序中的变量

1 个答案: