我想创建一个可变大小的数组来传递给Fortran DLL并获得结果（通过引用），这样我就可以直接获得值。
在Fortran代码中，我使用可分配的变量，我认为它就像指向分配地址的指针。
我可以做如下但我不知道如何在结构中做到这一点：
test = POINTER(c_double)()
sim.structtest(input, byref(test))
Fortran中test的定义是
real(kind=8), allocatable, dimension (:) :: test
allocate(test(1))
原始代码：
Python代码（structtest.py）：
from ctypes import *
import sys
import os
sim = cdll.LoadLibrary("struct.so")
class Input( Structure ):
_fields_ = [( "a", c_double * 1 ),
( "b", c_double )]
class Output( Structure ):
_fields_ = [( "a", c_double ),
( "b", POINTER(c_double) )] #-> don't know how to do
def main():
input = Input()
output = Output()
input.a[0] = 1
input.b = 2
sim.structtest(input, byref(output))
Fortran代码（struct.f90）：
subroutine structtest(input, output) bind(c, name='structtest')
USE ISO_C_BINDING
IMPLICIT NONE
!define input structure
TYPE T_INPUT
!real*8, allocatable :: a(:)
real(kind=8) :: a(1)
real(kind=8) :: b
END TYPE T_INPUT
!define output structure
TYPE T_OUTPUT
real(kind=8) :: a
real(kind=8), allocatable, dimension (:) :: b
END TYPE T_OUTPUT
!define a variable "input" with structure "INPUT"
TYPE (T_INPUT), value :: input
TYPE (T_OUTPUT) :: output
allocate(output%d(1))
output%b(1) = 5
PRINT *, output%d(1)
我将Fortran编译为DLL，如：
ifort -shared -fPIC -static-intel -o struct.so struct.f90
我执行Python：
python structtest.py
我得到了结果：
*** Error in `python': free(): corrupted unsorted chunks: 0x0000000001f7af00 ***
======= Backtrace: =========
/lib/x86_64-linux-gnu/libc.so.6(+0x777e5)[0x7fc9027f57e5]
/lib/x86_64-linux-gnu/libc.so.6(+0x8037a)[0x7fc9027fe37a]
/lib/x86_64-linux-gnu/libc.so.6(cfree+0x4c)[0x7fc90280253c]
/lib/x86_64-linux-gnu/libc.so.6(__open_catalog+0xe8)[0x7fc9027b2008]
/lib/x86_64-linux-gnu/libc.so.6(catopen+0x4c)[0x7fc9027b1c2c]
/home/mingster/simGeo.docker/simgeo/lib/struct.so(for__issue_diagnostic+0x11e)[0x7fc90147a77e]
/home/mingster/simGeo.docker/simgeo/lib/struct.so(for_allocate+0x303)[0x7fc90146b9a3]
/home/mingster/simGeo.docker/simgeo/lib/struct.so(structtest+0xae)[0x7fc90146b16e]
/usr/lib/x86_64-linux-gnu/libffi.so.6(ffi_call_unix64+0x4c)[0x7fc901757e40]
/usr/lib/x86_64-linux-gnu/libffi.so.6(ffi_call+0x2eb)[0x7fc9017578ab]
/usr/lib/python2.7/lib-dynload/_ctypes.x86_64-linux-gnu.so(_ctypes_callproc+0x48f)[0x7fc9019673df]
/usr/lib/python2.7/lib-dynload/_ctypes.x86_64-linux-gnu.so(+0x11d82)[0x7fc90196bd82]
python(PyObject_Call+0x43)[0x4b0c93]
python(PyEval_EvalFrameEx+0x602f)[0x4c9f9f]
python(PyEval_EvalFrameEx+0x5e0f)[0x4c9d7f]
python(PyEval_EvalCodeEx+0x255)[0x4c2705]
python(PyEval_EvalCode+0x19)[0x4c24a9]
python[0x4f19ef]
python(PyRun_FileExFlags+0x82)[0x4ec372]
python(PyRun_SimpleFileExFlags+0x191)[0x4eaaf1]
python(Py_Main+0x6c8)[0x49e208]
/lib/x86_64-linux-gnu/libc.so.6(__libc_start_main+0xf0)[0x7fc90279e830]
python(_start+0x29)[0x49da59]
======= Memory map: ========
00400000-006e9000 r-xp 00000000 08:01 525090 /usr/bin/python2.7
008e8000-008ea000 r--p 002e8000 08:01 525090 /usr/bin/python2.7
008ea000-00961000 rw-p 002ea000 08:01 525090 /usr/bin/python2.7
00961000-00984000 rw-p 00000000 00:00 0
01f10000-01ff6000 rw-p 00000000 00:00 0 [heap]
7fc8fc000000-7fc8fc021000 rw-p 00000000 00:00 0
7fc8fc021000-7fc900000000 ---p 00000000 00:00 0
7fc901246000-7fc90125c000 r-xp 00000000 08:01 38797837 /lib/x86_64-linux-gnu/libgcc_s.so.1
7fc90125c000-7fc90145b000 ---p 00016000 08:01 38797837 /lib/x86_64-linux-gnu/libgcc_s.so.1
7fc90145b000-7fc90145c000 rw-p 00015000 08:01 38797837 /lib/x86_64-linux-gnu/libgcc_s.so.1
7fc90145c000-7fc901504000 r-xp 00000000 08:01 51643749 /home/mingster/simGeo.docker/simgeo/lib/struct.so
7fc901504000-7fc901704000 ---p 000a8000 08:01 51643749 /home/mingster/simGeo.docker/simgeo/lib/struct.so
7fc901704000-7fc90170a000 rw-p 000a8000 08:01 51643749 /home/mingster/simGeo.docker/simgeo/lib/struct.so
7fc90170a000-7fc901752000 rw-p 00000000 00:00 0
7fc901752000-7fc901759000 r-xp 00000000 08:01 526635 /usr/lib/x86_64-linux-gnu/libffi.so.6.0.4
7fc901759000-7fc901958000 ---p 00007000 08:01 526635 /usr/lib/x86_64-linux-gnu/libffi.so.6.0.4
7fc901958000-7fc901959000 r--p 00006000 08:01 526635 /usr/lib/x86_64-linux-gnu/libffi.so.6.0.4
7fc901959000-7fc90195a000 rw-p 00007000 08:01 526635 /usr/lib/x86_64-linux-gnu/libffi.so.6.0.4
7fc90195a000-7fc901978000 r-xp 00000000 08:01 30543353 /usr/lib/python2.7/lib-dynload/_ctypes.x86_64-linux-gnu.so
7fc901978000-7fc901b77000 ---p 0001e000 08:01 30543353 /usr/lib/python2.7/lib-dynload/_ctypes.x86_64-linux-gnu.so
7fc901b77000-7fc901b78000 r--p 0001d000 08:01 30543353 /usr/lib/python2.7/lib-dynload/_ctypes.x86_64-linux-gnu.so
7fc901b78000-7fc901b7c000 rw-p 0001e000 08:01 30543353 /usr/lib/python2.7/lib-dynload/_ctypes.x86_64-linux-gnu.so
7fc901b7c000-7fc901e54000 r--p 00000000 08:01 529135 /usr/lib/locale/locale-archive
7fc901e54000-7fc901f5c000 r-xp 00000000 08:01 38797852 /lib/x86_64-linux-gnu/libm-2.23.so
7fc901f5c000-7fc90215b000 ---p 00108000 08:01 38797852 /lib/x86_64-linux-gnu/libm-2.23.so
7fc90215b000-7fc90215c000 r--p 00107000 08:01 38797852 /lib/x86_64-linux-gnu/libm-2.23.so
7fc90215c000-7fc90215d000 rw-p 00108000 08:01 38797852 /lib/x86_64-linux-gnu/libm-2.23.so
7fc90215d000-7fc902176000 r-xp 00000000 08:01 38797934 /lib/x86_64-linux-gnu/libz.so.1.2.8
7fc902176000-7fc902375000 ---p 00019000 08:01 38797934 /lib/x86_64-linux-gnu/libz.so.1.2.8
7fc902375000-7fc902376000 r--p 00018000 08:01 38797934 /lib/x86_64-linux-gnu/libz.so.1.2.8
7fc902376000-7fc902377000 rw-p 00019000 08:01 38797934 /lib/x86_64-linux-gnu/libz.so.1.2.8
7fc902377000-7fc902379000 r-xp 00000000 08:01 38797927 /lib/x86_64-linux-gnu/libutil-2.23.so
7fc902379000-7fc902578000 ---p 00002000 08:01 38797927 /lib/x86_64-linux-gnu/libutil-2.23.so
7fc902578000-7fc902579000 r--p 00001000 08:01 38797927 /lib/x86_64-linux-gnu/libutil-2.23.so
7fc902579000-7fc90257a000 rw-p 00002000 08:01 38797927 /lib/x86_64-linux-gnu/libutil-2.23.so
7fc90257a000-7fc90257d000 r-xp 00000000 08:01 38797825 /lib/x86_64-linux-gnu/libdl-2.23.so
7fc90257d000-7fc90277c000 ---p 00003000 08:01 38797825 /lib/x86_64-linux-gnu/libdl-2.23.so
7fc90277c000-7fc90277d000 r--p 00002000 08:01 38797825 /lib/x86_64-linux-gnu/libdl-2.23.so
7fc90277d000-7fc90277e000 rw-p 00003000 08:01 38797825 /lib/x86_64-linux-gnu/libdl-2.23.so
7fc90277e000-7fc90293e000 r-xp 00000000 08:01 38797811 /lib/x86_64-linux-gnu/libc-2.23.so
7fc90293e000-7fc902b3e000 ---p 001c0000 08:01 38797811 /lib/x86_64-linux-gnu/libc-2.23.so
7fc902b3e000-7fc902b42000 r--p 001c0000 08:01 38797811 /lib/x86_64-linux-gnu/libc-2.23.so
7fc902b42000-7fc902b44000 rw-p 001c4000 08:01 38797811 /lib/x86_64-linux-gnu/libc-2.23.so
7fc902b44000-7fc902b48000 rw-p 00000000 00:00 0
7fc902b48000-7fc902b60000 r-xp 00000000 08:01 38797898 /lib/x86_64-linux-gnu/libpthread-2.23.so
7fc902b60000-7fc902d5f000 ---p 00018000 08:01 38797898 /lib/x86_64-linux-gnu/libpthread-2.23.so
7fc902d5f000-7fc902d60000 r--p 00017000 08:01 38797898 /lib/x86_64-linux-gnu/libpthread-2.23.so
7fc902d60000-7fc902d61000 rw-p 00018000 08:01 38797898 /lib/x86_64-linux-gnu/libpthread-2.23.so
7fc902d61000-7fc902d65000 rw-p 00000000 00:00 0
7fc902d65000-7fc902d8b000 r-xp 00000000 08:01 38797787 /lib/x86_64-linux-gnu/ld-2.23.so
7fc902dc5000-7fc902f7b000 rw-p 00000000 00:00 0
7fc902f86000-7fc902f87000 rw-p 00000000 00:00 0
7fc902f87000-7fc902f88000 rwxp 00000000 00:00 0
7fc902f88000-7fc902f8a000 rw-p 00000000 00:00 0
7fc902f8a000-7fc902f8b000 r--p 00025000 08:01 38797787 /lib/x86_64-linux-gnu/ld-2.23.so
7fc902f8b000-7fc902f8c000 rw-p 00026000 08:01 38797787 /lib/x86_64-linux-gnu/ld-2.23.so
7fc902f8c000-7fc902f8d000 rw-p 00000000 00:00 0
7ffc38bde000-7ffc38bff000 rw-p 00000000 00:00 0 [stack]
7ffc38cd8000-7ffc38cda000 r--p 00000000 00:00 0 [vvar]
7ffc38cda000-7ffc38cdc000 r-xp 00000000 00:00 0 [vdso]
ffffffffff600000-ffffffffff601000 r-xp 00000000 00:00 0 [vsyscall]
Aborted (core dumped)
答案 0 :(得分：0)
可分配组件的所谓描述符的内存布局是特定于Fortran处理器的。对于可分配的数组组件，它总是不仅仅是一个内存地址。您需要查阅Fortran处理器的文档以获取描述符的详细信息。依赖于描述符布局的代码本身就是特定于处理器的。
英特尔编译器当前版本的相关文档可在标题为Handling Fortran Array Descriptors的部分中找到。
Fortran 2018的当前草案提供了与可分配伪参数互操作的附加功能，但仍然存在特定于平台的特性。
（在显示的代码中，您使用了内部模块ISO_C_BINDING，但代码似乎没有从中引用任何内容......）
答案 1 :(得分：0)
全部谢谢，
下面是Python将多维数组传递给Fortran的工作示例
python代码：
from ctypes import *
import ctypes
import sys
import os
import numpy as np
sim = cdll.LoadLibrary(os.path.dirname(os.path.abspath(__file__)) + "/lib/struct.so")
class Param( Structure ):
pass
class Result( Structure ):
pass
def main():
x = 2
y = 3
z = 4
Param._fields_ = [( "len_x", c_int ),
( "len_y", c_int ),
( "len_z", c_int ),
( "c", POINTER(c_double)),
( "d", POINTER(c_double * x)),
( "e", POINTER(c_double * x * y))]
Result._fields_ = [( "len_x", c_int ),
( "len_y", c_int ),
( "len_z", c_int ),
( "f", POINTER(c_double)),
( "g", POINTER(c_double * x)),
( "h", POINTER(c_double * x * y))]
param = Param()
result = Result()
cc = (c_double * x)()
dd = ( (c_double * x) * y )()
ee = ( ( ( (c_double * x) * y ) * z ) )()
#[x]
cc[0] = 10.0
cc[1] = 20.0
#[y][x]
dd[0][0] = 10.0
dd[1][0] = 20.0
dd[2][0] = 30.0
dd[0][1] = 40.0
dd[1][1] = 50.0
dd[2][1] = 60.0
#[z][y][x]
ee[0][0][0] = 1.0
ee[1][0][0] = 2.0
ee[2][0][0] = 3.0
ee[0][1][0] = 4.0
ee[1][1][0] = 5.0
ee[2][1][0] = 6.0
param.len_x = x
param.len_y = y
param.len_z = z
param.c = cc
param.d = dd
param.e = ee
sim.structtest(byref(param), byref(result))
#[x]
print "1D"
print result.f[0]
print result.f[1]
#[y][x]
print "2D"
print result.g[0][0]
print result.g[1][0]
print result.g[2][0]
print result.g[0][1]
print result.g[1][1]
print result.g[2][1]
#[z][y][x]
print "3D"
print result.h[0][0][0]
print result.h[1][0][0]
print result.h[2][0][0]
print result.h[0][1][0]
print result.h[1][1][0]
print result.h[2][1][0]
if __name__ == "__main__":
result = main()
fortran代码：
subroutine structtest(param, result) bind(c, name="structtest")
use, intrinsic :: ISO_C_BINDING
implicit none
type, BIND(C) :: args
integer (C_INT) :: len_x
integer (C_INT) :: len_y
integer (C_INT) :: len_z
type (C_PTR) :: c
type (C_PTR) :: d
type (C_PTR) :: e
end type args
type, BIND(C) :: output
integer (C_INT) :: len_x
integer (C_INT) :: len_y
integer (C_INT) :: len_z
type (C_PTR) :: f
type (C_PTR) :: g
type (C_PTR) :: h
end type output
type (args), intent(in):: param
type (output), intent(out):: result
real (C_DOUBLE), pointer :: arg_array_c(:)
real (C_DOUBLE), pointer :: arg_array_d(:,:)
real (C_DOUBLE), pointer :: arg_array_e(:,:,:)
real (C_DOUBLE), ALLOCATABLE, target, save :: result_array_f(:)
real (C_DOUBLE), ALLOCATABLE, target, save :: result_array_g(:,:)
real (C_DOUBLE), ALLOCATABLE, target, save :: result_array_h(:,:,:)
! Associate c_array with an array allocated in C
call C_F_POINTER (param%c, arg_array_c, [param%len_x] )
call C_F_POINTER (param%d, arg_array_d, [param%len_x,param%len_y] )
call C_F_POINTER (param%e, arg_array_e, [param%len_x,param%len_y,param%len_z] )
![x]
print *,"1D"
print *,arg_array_c(1)
print *,arg_array_c(2)
![x][y]
print *,"2D"
print *,arg_array_d(1,1)
print *,arg_array_d(1,2)
print *,arg_array_d(1,3)
print *,arg_array_d(2,1)
print *,arg_array_d(2,2)
print *,arg_array_d(2,3)
![x][y][z]
print *,"3D"
print *,arg_array_e(1,1,1)
print *,arg_array_e(1,1,2)
print *,arg_array_e(1,1,3)
print *,arg_array_e(1,2,1)
print *,arg_array_e(1,2,2)
print *,arg_array_e(1,2,3)
! Allocate an array and make it available in C
result%len_x = param%len_x
result%len_y = param%len_y
result%len_z = param%len_z
ALLOCATE (result_array_f(result%len_x))
ALLOCATE (result_array_g(result%len_x, result%len_y))
ALLOCATE (result_array_h(result%len_x, result%len_y, result%len_z))
result%f = c_loc(result_array_f)
result%g = c_loc(result_array_g)
result%h = c_loc(result_array_h)
![x]
result_array_f(1) = arg_array_c(1)
result_array_f(2) = arg_array_c(2)
![x][y]
result_array_g(1,1) = arg_array_d(1,1)
result_array_g(1,2) = arg_array_d(1,2)
result_array_g(1,3) = arg_array_d(1,3)
result_array_g(2,1) = arg_array_d(2,1)
result_array_g(2,2) = arg_array_d(2,2)
result_array_g(2,3) = arg_array_d(2,3)
![x][y][z]
result_array_h(1,1,1) = arg_array_e(1,1,1)
result_array_h(1,1,2) = arg_array_e(1,1,2)
result_array_h(1,1,3) = arg_array_e(1,1,3)
result_array_h(1,2,1) = arg_array_e(1,2,1)
result_array_h(1,2,2) = arg_array_e(1,2,2)
result_array_h(1,2,3) = arg_array_e(1,2,3)
end
输出：
1D
10.0000000000000
20.0000000000000
2D
10.0000000000000
20.0000000000000
30.0000000000000
40.0000000000000
50.0000000000000
60.0000000000000
3D
1.00000000000000
2.00000000000000
3.00000000000000
4.00000000000000
5.00000000000000
6.00000000000000
1D
10.0
20.0
2D
10.0
20.0
30.0
40.0
50.0
60.0
3D
1.0
2.0
3.0
4.0
5.0
6.0