This question already has answers here:
Defining a function returning an array
(2 answers)
How to declare the type of a function that returns an array in Fortran?
(2 answers)
Closed 8 days ago.
I just started learning Fortran and I have this function called matrix_power
But I'm having difficulty trying to call the function. The file extension I'm using is .f and my compiler is gfortran.
Here is my code
function transpose_matrix(mat) result(mat_t)
implicit none
real, dimension(:,:), intent(in) :: mat
real, dimension(size(mat,2),size(mat,1)) :: mat_t
integer :: i, j
do i = 1, size(mat,1)
do j = 1, size(mat,2)
mat_t(j,i) = mat(i,j)
end do
end do
end function transpose_matrix
function matrix_power(mat, p) result(mat_p)
implicit none
integer, intent(in) :: p
real, dimension(:,:), intent(in) :: mat
real, dimension(size(mat,1),size(mat,2)) :: mat_p
integer :: i
mat_p = mat
do i = 2, p
mat_p = matmul(mat_p, mat)
end do
end function matrix_power
program matrix
implicit none
real, dimension(5, 5) :: matrix1 = reshape([2.0, 0.0, 0.0, 0.0, 0.0, &
0.0, 2.0, 0.0, 0.0, 0.0, &
0.0, 0.0, 2.0, 0.0, 0.0, &
0.0, 0.0, 0.0, 2.0, 0.0, &
2.0, 0.0, 0.0, 0.0, 2.0], (5, 5))
real, dimension(5, 5) :: mat_t, mat_p
integer :: i
mat_t = transpose_matrix(matrix1)
mat_p = matrix_power(matrix1, 3)
! Print the results
print *, "Matrix 1:"
print *, matrix1
print *, "Matrix 1 Transposed:"
print *, mat_t
print *, "Matrix 1 to the power of 3:"
print *, mat_p
end program matrix
I know that it's saying that there is a mismatch but it doesn't even make sense This is my definition of the mat_p
real, dimension(m,n) :: mat_t, mat_p
Here is the error I'm receiving
here is a text based error
Return type mismatch of function 'matrix_power' at (1) (UNKNOWN/REAL(4))
Function 'matrix_power' at (1) has no IMPLICIT type
As suspected by #VladimirFГероямслава in the comments, functions returning arrays must have explicit interfaces. Routines/functions with assumed shapes dummy arguments, or intent() attributes for the arguments, do also require explicit interfaces.
First of all , because you are using implicit none (which is a good practice) in the main program, you have to define the return type of all the non-intrinsic functions you are using. For instance if you had this function:
function matrix_trace(mat,n) result(t)
implicit none
real :: mat(n,n)
real :: t
integer :: i
t = 0.0
do i = 1, n
t = t + mat(i,i)
end do
end function
You would simply have to insert in your main program:
real, external :: matrix_trace
This is an implicit interface, because you don't describe how arguments are passed. The implicit interface is the legacy pre-Fortran 90 way.
In your case your have to define explicit interfaces, with two possibilities.
Interface blocks:
In your main program you insert this code:
INTERFACE
function transpose_matrix(mat) result(mat_t)
implicit none
real, dimension(:,:), intent(in) :: mat
real, dimension(size(mat,2),size(mat,1)) :: mat_t
end function transpose_matrix
function matrix_power(mat, p) result(mat_p)
implicit none
integer, intent(in) :: p
real, dimension(:,:), intent(in) :: mat
real, dimension(size(mat,1),size(mat,2)) :: mat_p
end function matrix_power
END INTERFACE
Modules
Much better, use modules to encapsulate your functions:
!*****************************************
MODULE mymatfuncs
CONTAINS
function transpose_matrix(mat) result(mat_t)
implicit none
real, dimension(:,:), intent(in) :: mat
real, dimension(size(mat,2),size(mat,1)) :: mat_t
integer :: i, j
do i = 1, size(mat,1)
do j = 1, size(mat,2)
mat_t(j,i) = mat(i,j)
end do
end do
end function transpose_matrix
function matrix_power(mat, p) result(mat_p)
implicit none
integer, intent(in) :: p
real, dimension(:,:), intent(in) :: mat
real, dimension(size(mat,1),size(mat,2)) :: mat_p
integer :: i
mat_p = mat
do i = 2, p
mat_p = matmul(mat_p, mat)
end do
end function matrix_power
END MODULE mymatfuncs
!*****************************************
program matrix
USE mymatfuncs, only: matrix_power, transpose_matrix
implicit none
real, dimension(5, 5) :: matrix1 = reshape([2.0, 0.0, 0.0, 0.0, 0.0, &
0.0, 2.0, 0.0, 0.0, 0.0, &
0.0, 0.0, 2.0, 0.0, 0.0, &
0.0, 0.0, 0.0, 2.0, 0.0, &
2.0, 0.0, 0.0, 0.0, 2.0], (5, 5))
real, dimension(5, 5) :: mat_t, mat_p
integer :: i
mat_t = transpose_matrix(matrix1)
mat_p = matrix_power(matrix1, 3)
! Print the results
print *, "Matrix 1:"
print *, matrix1
print *, "Matrix 1 Transposed:"
print *, mat_t
print *, "Matrix 1 to the power of 3:"
print *, mat_p
end program matrix
Related
I am currently implementing integrals in Fortran as subroutines. The subroutines on their own return the correct values. If i now call the e.g. same subroutine twice after each other, with the same input values, their returned value differs significantly?
The main program only calls the function like this:
program main
use types
use constants
use integrals
use basis
real(dp), dimension(2,3) :: molecule_coords
real(dp), dimension(2) :: z
type(primitive_gaussian), allocatable :: molecule(:,:)
molecule_coords(1,:) = (/0.,0.,0./)
molecule_coords(2,:) = (/0.,0.,1.6/)
molecule = def_molecule(molecule_coords)
z = (/1.0, 1.0/)
call overlap(molecule) ! Correct Value returned
call overlap(molecule) ! Wrong Value returned
end program main
My function for the overlap looks like this:
module integrals
use types
use constants
use basis
use stdlib_specialfunctions_gamma!, only: lig => lower_incomplete_gamma
contains
subroutine overlap(molecule)
implicit none
type(primitive_gaussian), intent(in) :: molecule(:,:)
integer :: nbasis, i, j, k, l
real(dp) :: norm, p, q, coeff, Kab
real(dp), dimension(3) :: Q_xyz
real(dp), dimension(INT(size(molecule,1)),INT(size(molecule,1))) :: S
nbasis = size(molecule,1)
do i = 1, nbasis
do j = 1, nbasis
! Iterate over l and m primitives in basis
do k = 1, size(molecule(i,:))
do l = 1, size(molecule(j,:))
norm = molecule(i, k)%norm() * molecule(j, l)%norm()
! Eq. 63
Q_xyz = (molecule(i, k)%coords - molecule(j, l)%coords)
! Eq. 64, 65
p = (molecule(i, k)%alpha + molecule(j, l)%alpha)
q = (molecule(i, k)%alpha * molecule(j, l)%alpha) / p
! Eq. 66
Kab = exp(-q * dot_product(Q_xyz,Q_xyz))
coeff = molecule(i, k)%coeff * molecule(j, l)%coeff
S(i,j) = S(i,j) + norm * coeff * Kab * (pi / p) ** (1.5)
end do
end do
end do
end do
print *, S
end subroutine overlap
end module integrals
I am a bit lost, why this would be the case, but I am also rather new to Fortran.
Any help is appreciated! Thanks!
I'd like to use Minpack (fortran) to estimate the D parameter in the following generalized form of the S-curve: y = (A - D) / (1 + (x**B/C)) + D
The idea is that in this application, the user provides A [which is always 0 to force passage through (0,0)], B, and C, and from there Minpack will find a value for D that forces passage through (1,y), where y is also supplied by the user but must be <= 1. I was able to accomplish this task with the code below, however, minpack is claiming it hasn't converged when in fact it appears that it has. For example, when running this code and entering the values 1 (at the first prompt) and 0 4 0.1 (at the second prompting), minpack returns info = 2, which according to the comments in lmdif means:
relative error between two consecutive iterates is at most xtol.
I'm tempted to comment out line 63, but am worried that's playing with fire...are there any seasoned minpack users out there who could comment on this? Line 63 is the one that reads:
if (info /= 1) stop "failed to converge"
Am I mis-using Minpack even though it appears to converge (based on my verifying the value in pars)?
module types
implicit none
private
public dp
integer, parameter :: dp=kind(0d0)
end module
module f_vals
DOUBLE PRECISION, SAVE, DIMENSION(:), POINTER:: fixed_vals
end module
module find_fit_module
! This module contains a general function find_fit() for a nonlinear least
! squares fitting. The function can fit any nonlinear expression to any data.
use minpack, only: lmdif1
use types, only: dp
implicit none
private
public find_fit
contains
subroutine find_fit(data_x, data_y, expr, pars)
! Fits the (data_x, data_y) arrays with the function expr(x, pars).
! The user can provide any nonlinear function 'expr' depending on any number of
! parameters 'pars' and it must return the evaluated expression on the
! array 'x'. The arrays 'data_x' and 'data_y' must have the same
! length.
real(dp), intent(in) :: data_x(:), data_y(:)
interface
function expr(x, pars) result(y)
use types, only: dp
implicit none
real(dp), intent(in) :: x(:), pars(:)
real(dp) :: y(size(x))
end function
end interface
real(dp), intent(inout) :: pars(:)
real(dp) :: tol, fvec(size(data_x))
integer :: iwa(size(pars)), info, m, n
real(dp), allocatable :: wa(:)
tol = sqrt(epsilon(1._dp))
!tol = 0.001
m = size(fvec)
n = size(pars)
allocate(wa(m*n + 5*n + m))
call lmdif1(fcn, m, n, pars, fvec, tol, info, iwa, wa, size(wa))
open(222, FILE='D_Value.txt')
write(222,4) pars(1)
4 format(E20.12)
close(222)
if (info /= 1) stop "failed to converge"
contains
subroutine fcn(m, n, x, fvec, iflag)
integer, intent(in) :: m, n, iflag
real(dp), intent(in) :: x(n)
real(dp), intent(out) :: fvec(m)
! Suppress compiler warning:
fvec(1) = iflag
fvec = data_y - expr(data_x, x)
end subroutine
end subroutine
end module
program snwdeplcrv
! Find a nonlinear fit of the form y = (A - D) / (1 + (x**B/C)) + D.
use find_fit_module, only: find_fit
use types, only: dp
use f_vals
implicit none
real(dp) :: pars(1), y_int_at_1
real(dp) :: y(1) = 1.0 ! Initialization of value to be reset by user (y: value of S-curve # x=1)
real(dp) :: A, B, C
integer :: i
allocate(fixed_vals(3)) ! A, B, C parameters
pars = [1._dp] ! D parameter in S-curve function
! Read PEST-specified parameters
write(*,*) ' Enter value that S-curve should equal when SWE=1 (must be <= 1)'
read(*,*) y_int_at_1
if(y_int_at_1 > 1.0) y_int_at_1 = 1
y = y_int_at_1
! Read PEST-specified parameters
write(*,*) ' Enter S-curve parameters: A, B, & C. D parameter to be estimated '
read(*,*) A, B, C
fixed_vals(1) = A
fixed_vals(2) = B
fixed_vals(3) = C
call find_fit([(real(i, dp), i=1,size(y))], y, expression, pars)
print *, pars
contains
function expression(x, pars) result(y)
use f_vals
real(dp), intent(in) :: x(:), pars(:)
real(dp) :: y(size(x))
real(dp) :: A, B, C, D
A = fixed_vals(1)
B = fixed_vals(2)
C = fixed_vals(3)
D = pars(1)
y = (A - D) / (1 + (x**B / C)) + D
end function
end program
This question already has an answer here:
Procedure with assumed-shape dummy argument must have an explicit interface [duplicate]
(1 answer)
Closed 4 years ago.
Im trying to write the code for a simple program that first asks for a number n, then creates an nxn matrix with 3s on its main diagonal, 1s over it and 0s under it and a vector (n) with 3 in the uneven positions and 2 in the even positions. It must then include a subroutine that multiplies both of them not using matmul()
program P13
implicit none
integer(4) :: n, i, j
integer, dimension(:), allocatable:: v
integer, dimension(:,:), allocatable :: m
integer, dimension(:), allocatable :: r
write(*,*) "Insert n"
read(*,*) n
allocate (v(1:n))
allocate (m(1:n,1:n))
v(1:n:2) = 3
v(2:n:2) = 2
m = 0
DO i=1,n,1
m (i,i:n)=1
END DO
Do i=1,n,1
m (i,i)=3
End do
call matrmul(n, m, v)
end program
subroutine matrmul(n, b, o, t)
implicit none
integer(4), intent(in) :: n
integer(4) :: i, j
integer, dimension(:), intent(in) :: b
integer, dimension(:,:),intent(in) :: o
integer, dimension(:), intent(out) :: t
DO i=1,n,1
t(i) = sum(b*o(:,i))
END DO
write(*,'(I2)') t
end subroutine
I get the error message Explicit interface required for ‘matrmul’ at (1): assumed-shape argument
How do I fix this?? Thanks
There are plenty examples here at stack overflow that will show you how to create explicit interfaces. However, since you allocate memory for all your arrays in the main program and you pass the size into the subroutine, just declare all your arrays in the subroutine with n.
subroutine matrmul(n, b, o, t)
implicit none
integer(4), intent(in) :: n
integer(4) :: i, j
integer, dimension(n), intent(in) :: b
integer, dimension(n,n),intent(in) :: o
integer, dimension(n), intent(out) :: t
I'm trying to use the MKL trust region algorithm to solve a nonlinear system of equations in a Fortran program. I started from the example provided online (ex_nlsqp_f90_x.f90 https://software.intel.com/en-us/node/501498) and everything works correctly. Now, because I have to use this in a much bigger program, I need the user defined objective function to be loaded from a separate module. Hence, I split the example into 2 separate files, but I'm not able to make it compile correctly.
So here is the code for module which contains user defined data structure and the objective function
module modFun
implicit none
private
public my_data, extended_powell
type :: my_data
integer a
integer sum
end type my_data
contains
subroutine extended_powell (m, n, x, f, user_data)
implicit none
integer, intent(in) :: m, n
real*8 , intent(in) :: x(n)
real*8, intent(out) :: f(m)
type(my_data) :: user_data
integer i
user_data%sum = user_data%sum + user_data%a
do i = 1, n/4
f(4*(i-1)+1) = x(4*(i-1)+1) + 10.0 * x(4*(i-1)+2)
f(4*(i-1)+2) = 2.2360679774998 * (x(4*(i-1)+3) - x(4*(i-1)+4))
f(4*(i-1)+3) = ( x(4*(i-1)+2) - 2.0 * x(4*(i-1)+3) )**2
f(4*(i-1)+4) = 3.1622776601684 * (x(4*(i-1)+1) - x(4*(i-1)+4))**2
end do
end subroutine extended_powell
end module modFun
and here the portion of the main program calling it
include 'mkl_rci.f90'
program EXAMPLE_EX_NLSQP_F90_X
use MKL_RCI
use MKL_RCI_type
use modFun
! user's objective function
! n - number of function variables
! m - dimension of function value
integer n, m
parameter (n = 4)
parameter (m = 4)
! precisions for stop-criteria (see manual for more details)
real*8 eps(6)
real*8 x(n)
real*8 fjac(m*n)
! number of iterations
integer fun
! Additional users data
type(my_data) :: m_data
m_data%a = 1
m_data%sum = 0
rs = 0.0
fun = djacobix(extended_powell,n,m,fjac,x,eps(1),%val(loc(m_data)))
end program EXAMPLE_EX_NLSQP_F90_X
Also djacobix code
INTERFACE
INTEGER FUNCTION DJACOBIX(fcn, n, m, fjac, x, eps, user_data)
USE, INTRINSIC :: ISO_C_BINDING
INTEGER, INTENT(IN) :: n
INTEGER, INTENT(IN) :: m
DOUBLE PRECISION, INTENT(IN) :: eps
DOUBLE PRECISION, INTENT(IN), DIMENSION(*) :: x
DOUBLE PRECISION, INTENT(OUT), DIMENSION(m, *) :: fjac
INTEGER(C_INTPTR_T) :: user_data
INTERFACE
SUBROUTINE fcn(m, n, x, f, user_data)
USE, INTRINSIC :: ISO_C_BINDING
INTEGER, INTENT(IN) :: n
INTEGER, INTENT(IN) :: m
DOUBLE PRECISION, INTENT(IN), DIMENSION(*) :: x
DOUBLE PRECISION, INTENT(OUT), DIMENSION(*) :: f
INTEGER(C_INTPTR_T), INTENT(IN) :: user_data
END SUBROUTINE
END INTERFACE
END FUNCTION
END INTERFACE
When i compile the following errors are generated:
mpiifort -g -t -mkl -I/apps/rhel6/intel/composer_xe_2015.3.187/mkl/include/intel64/lp64 -c modFun.f90
mpiifort -g -t -mkl -I/apps/rhel6/intel/composer_xe_2015.3.187/mkl/include/intel64/lp64 -c main.f90
main.f90(30): error #7065: The characteristics of dummy argument 5 of the associated actual procedure differ from the characteristics of dummy argument 5 of the dummy procedure. [EXTENDED_POWELL]
fun = djacobix(extended_powell,n,m,fjac,x,eps(1),%val(loc(m_data)))
-------------------^
I have the feeling I have to create an interface to override the check on the m_data, but I can't figure out where and how. Can anyone help me with this problem providing a working example?
I guess the reason is that the function djacobix passes the pointer instead of the true value of variable user_data.
You can check the manual at https://software.intel.com/content/www/us/en/develop/documentation/onemkl-developer-reference-c/top/nonlinear-optimization-problem-solvers/jacobian-matrix-calculation-routines/jacobix.html where a sentence shows that "You need to declare fcn as extern in the calling program."
I'm struggling with LAPACK's dgetrf and dgetri routines. Below is a subroutine I've created (the variable fit_coeffs is defined externally and is allocatable, it's not the problem). When I run I get memory allocation errors, that appear when I assign fit_coeffs, due to the matmul(ATA,AT) line. I know this from inserting a bunch of print statements. Also, both error checking statements after calls to LAPACK subroutines are printed, suggesting an error.
Does anyone understand where this comes from? I'm compiling using the command:
gfortran -Wall -cpp -std=f2003 -ffree-form -L/home/binningtont/lapack-3.4.0/ read_grib.f -llapack -lrefblas.
Thanks in advance!
subroutine polynomial_fit(x_array, y_array, D)
integer, intent(in) :: D
real, intent(in), dimension(:) :: x_array, y_array
real, allocatable, dimension(:,:) :: A, AT, ATA
real, allocatable, dimension(:) :: work
integer, dimension(:), allocatable :: pivot
integer :: l, m, n, lda, lwork, ok
l = D + 1
lda = l
lwork = l
allocate(fit_coeffs(l))
allocate(pivot(l))
allocate(work(l))
allocate(A(size(x_array),l))
allocate(AT(l,size(x_array)))
allocate(ATA(l,l))
do m = 1,size(x_array),1
do n = 1,l,1
A(m,n) = x_array(m)**(n-1)
end do
end do
AT = transpose(A)
ATA = matmul(AT,A)
call dgetrf(l, l, ATA, lda, pivot, ok)
! ATA is now represented as PLU (permutation, lower, upper)
if (ok /= 0) then
write(6,*) "HERE"
end if
call dgetri(l, ATA, lda, pivot, work, lwork, ok)
! ATA now contains the inverse of the matrix ATA
if (ok /= 0) then
write(6,*) "HERE"
end if
fit_coeffs = matmul(matmul(ATA,AT),y_array)
deallocate(pivot)
deallocate(fit_coeffs)
deallocate(work)
deallocate(A)
deallocate(AT)
deallocate(ATA)
end subroutine polynomial_fit
1) Where is fit_coeffs declared? I can't see how the above can even compile
1b) Implicit None is your friend!
2) You do have an interface in scope at the calling point, don't you?
3) dgertf and dgetri want "double precision" while you have single. So you need sgetrf and sgetri
"Fixing" all these and completeing the program I get
Program testit
Implicit None
Real, Dimension( 1:100 ) :: x, y
Integer :: D
Interface
subroutine polynomial_fit(x_array, y_array, D)
Implicit None ! Always use this!!
integer, intent(in) :: D
real, intent(in), dimension(:) :: x_array, y_array
End subroutine polynomial_fit
End Interface
Call Random_number( x )
Call Random_number( y )
D = 6
Call polynomial_fit( x, y, D )
End Program testit
subroutine polynomial_fit(x_array, y_array, D)
Implicit None ! Always use this!!
integer, intent(in) :: D
real, intent(in), dimension(:) :: x_array, y_array
real, allocatable, dimension(:,:) :: A, AT, ATA
real, allocatable, dimension(:) :: work, fit_coeffs
integer, dimension(:), allocatable :: pivot
integer :: l, m, n, lda, lwork, ok
l = D + 1
lda = l
lwork = l
allocate(fit_coeffs(l))
allocate(pivot(l))
allocate(work(l))
allocate(A(size(x_array),l))
allocate(AT(l,size(x_array)))
allocate(ATA(l,l))
do m = 1,size(x_array),1
do n = 1,l,1
A(m,n) = x_array(m)**(n-1)
end do
end do
AT = transpose(A)
ATA = matmul(AT,A)
call sgetrf(l, l, ATA, lda, pivot, ok)
! ATA is now represented as PLU (permutation, lower, upper)
if (ok /= 0) then
write(6,*) "HERE"
end if
call sgetri(l, ATA, lda, pivot, work, lwork, ok)
! ATA now contains the inverse of the matrix ATA
if (ok /= 0) then
write(6,*) "HERE"
end if
fit_coeffs = matmul(matmul(ATA,AT),y_array)
deallocate(pivot)
deallocate(fit_coeffs)
deallocate(work)
deallocate(A)
deallocate(AT)
deallocate(ATA)
end subroutine polynomial_fit
This runs to completion. If I omit the interface I get "HERE" printed twice. If I use the d versions I get seg faults.
Does this answer your question?