fdjac1 Subroutine

public subroutine fdjac1(fcn, n, x, Fvec, Fjac, Ldfjac, Iflag, Ml, Mu, Epsfcn, Wa1, Wa2)

this subroutine computes a forward-difference approximation to the n by n jacobian matrix associated with a specified problem of n functions in n variables. if the jacobian has a banded form, then function evaluations are saved by only approximating the nonzero terms.

Arguments

TypeIntentOptionalAttributesName
procedure(func) :: fcn

the user-supplied subroutine which calculates the functions.

integer, intent(in) :: n

a positive integer input variable set to the number of functions and variables.

real(kind=wp), intent(inout) :: x(n)

an input array of length n.

real(kind=wp), intent(in) :: Fvec(n)

an input array of length n which must contain the functions evaluated at x.

real(kind=wp), intent(out) :: Fjac(Ldfjac,n)

an output n by n array which contains the approximation to the jacobian matrix evaluated at x.

integer, intent(in) :: Ldfjac

a positive integer input variable not less than n which specifies the leading dimension of the array fjac.

integer, intent(inout) :: Iflag

an integer variable which can be used to terminate the execution of fdjac1. see description of func.

integer, intent(in) :: Ml

a nonnegative integer input variable which specifies the number of subdiagonals within the band of the jacobian matrix. if the jacobian is not banded, set ml to at least n - 1.

integer, intent(in) :: Mu

a nonnegative integer input variable which specifies the number of superdiagonals within the band of the jacobian matrix. if the jacobian is not banded, set mu to at least n - 1.

real(kind=wp), intent(in) :: Epsfcn

an input variable used in determining a suitable step length for the forward-difference approximation. this approximation assumes that the relative errors in the functions are of the order of epsfcn. if epsfcn is less than the machine precision, it is assumed that the relative errors in the functions are of the order of the machine precision.

real(kind=wp), intent(inout) :: Wa1(n)

work array of length n.

real(kind=wp), intent(inout) :: Wa2(n)

work array of length n. if ml + mu + 1 is at least n, then the jacobian is considered dense, and wa2 is not referenced.


Called by

proc~~fdjac1~~CalledByGraph proc~fdjac1 fdjac1 proc~hybrd hybrd proc~hybrd->proc~fdjac1 proc~minpack_hybrd minpack_hybrd proc~minpack_hybrd->proc~hybrd proc~hybrd1 hybrd1 proc~hybrd1->proc~hybrd proc~minpack_hybrd1 minpack_hybrd1 proc~minpack_hybrd1->proc~hybrd1

Contents

Source Code


Source Code

    subroutine fdjac1(fcn, n, x, Fvec, Fjac, Ldfjac, Iflag, Ml, Mu, Epsfcn, Wa1, Wa2)

        implicit none

        procedure(func) :: fcn !! the user-supplied subroutine which
                            !! calculates the functions.
        integer, intent(in) :: n !! a positive integer input variable set to the number
                            !! of functions and variables.
        integer, intent(in) :: Ldfjac !! a positive integer input variable not less than n
                                 !! which specifies the leading dimension of the array fjac.
        integer, intent(inout) :: Iflag !! an integer variable which can be used to terminate
                                 !! the execution of fdjac1. see description of [[func]].
        integer, intent(in) :: Ml !! a nonnegative integer input variable which specifies
                             !! the number of subdiagonals within the band of the
                             !! jacobian matrix. if the jacobian is not banded, set
                             !! ml to at least n - 1.
        integer, intent(in) :: Mu !! a nonnegative integer input variable which specifies
                             !! the number of superdiagonals within the band of the
                             !! jacobian matrix. if the jacobian is not banded, set
                             !! mu to at least n - 1.
        real(wp), intent(in) :: Epsfcn !! an input variable used in determining a suitable
                                  !! step length for the forward-difference approximation. this
                                  !! approximation assumes that the relative errors in the
                                  !! functions are of the order of epsfcn. if epsfcn is less
                                  !! than the machine precision, it is assumed that the relative
                                  !! errors in the functions are of the order of the machine
                                  !! precision.
        real(wp), intent(inout)  :: x(n) !! an input array of length n.
        real(wp), intent(in) :: Fvec(n) !! an input array of length n which must contain the
                                   !! functions evaluated at x.
        real(wp), intent(out) :: Fjac(Ldfjac, n) !! an output n by n array which contains the
                                            !! approximation to the jacobian matrix evaluated at x.
        real(wp), intent(inout) :: Wa1(n) !! work array of length n.
        real(wp), intent(inout) :: Wa2(n) !! work array of length n. if ml + mu + 1 is at
                                     !! least n, then the jacobian is considered dense, and wa2 is
                                     !! not referenced.

        integer :: i, j, k, msum
        real(wp) :: eps, h, temp

        eps = sqrt(max(Epsfcn, epsmch))
        msum = Ml + Mu + 1
        if (msum < n) then
            ! computation of banded approximate jacobian.
            do k = 1, msum
                do j = k, n, msum
                    Wa2(j) = x(j)
                    h = eps*abs(Wa2(j))
                    if (h == zero) h = eps
                    x(j) = Wa2(j) + h
                end do
                call fcn(n, x, Wa1, Iflag)
                if (Iflag < 0) return
                do j = k, n, msum
                    x(j) = Wa2(j)
                    h = eps*abs(Wa2(j))
                    if (h == zero) h = eps
                    do i = 1, n
                        Fjac(i, j) = zero
                        if (i >= j - Mu .and. i <= j + Ml) Fjac(i, j) = (Wa1(i) - Fvec(i))/h
                    end do
                end do
            end do
        else
            ! computation of dense approximate jacobian.
            do j = 1, n
                temp = x(j)
                h = eps*abs(temp)
                if (h == zero) h = eps
                x(j) = temp + h
                call fcn(n, x, Wa1, Iflag)
                if (Iflag < 0) return
                x(j) = temp
                do i = 1, n
                    Fjac(i, j) = (Wa1(i) - Fvec(i))/h
                end do
            end do
        end if

    end subroutine fdjac1