Fortran-Cython工作流程
我想建立一个工作流以在Windows机器上使用Cython从Python到达fortran例程
经过一番搜索后,我发现:http : //www.fortran90.org/src/best-
practices.html#interface-with-c和https://stackoverflow.com/tags/fortran-
iso-c-binding/info
和一些代码图片:
Fortran方面:
pygfunc.h:
void c_gfunc(double x, int n, int m, double *a, double *b, double *c);
pygfunc.f90
module gfunc1_interface
use iso_c_binding
use gfunc_module
implicit none
contains
subroutine c_gfunc(x, n, m, a, b, c) bind(c)
real(C_FLOAT), intent(in), value :: x
integer(C_INT), intent(in), value :: n, m
type(C_PTR), intent(in), value :: a, b
type(C_PTR), value :: c
real(C_FLOAT), dimension(:), pointer :: fa, fb
real(C_FLOAT), dimension(:,:), pointer :: fc
call c_f_pointer(a, fa, (/ n /))
call c_f_pointer(b, fb, (/ m /))
call c_f_pointer(c, fc, (/ n, m /))
call gfunc(x, fa, fb, fc)
end subroutine
end module
gfunc.f90
module gfunc_module
use iso_c_binding
implicit none
contains
subroutine gfunc(x, a, b, c)
real, intent(in) :: x
real, dimension(:), intent(in) :: a, b
real, dimension(:,:), intent(out) :: c
integer :: i, j, n, m
n = size(a)
m = size(b)
do j=1,m
do i=1,n
c(i,j) = exp(-x * (a(i)**2 + b(j)**2))
end do
end do
end subroutine
end module
Cython端:
pygfunc.pyx
cimport numpy as cnp
import numpy as np
cdef extern from "./pygfunc.h":
void c_gfunc(double, int, int, double *, double *, double *)
cdef extern from "./pygfunc.h":
pass
def f(float x, a=-10.0, b=10.0, n=100):
cdef cnp.ndarray ax, c
ax = np.arange(a, b, (b-a)/float(n))
n = ax.shape[0]
c = np.ndarray((n,n), dtype=np.float64, order='F')
c_gfunc(x, n, n, <double *> ax.data, <double *> ax.data, <double *> c.data)
return c
和安装文件:
from distutils.core import setup
from distutils.extension import Extension
from Cython.Distutils import build_ext
import numpy as np
ext_modules = [Extension('pygfunc', ['pygfunc.pyx'])]
setup(
name = 'pygfunc',
include_dirs = [np.get_include()],
cmdclass = {'build_ext': build_ext},
ext_modules = ext_modules )
所有文件放在一个目录中
fortran文件编译(使用NAG Fortran Builder)pygfunc编译
但链接它们会引发:
错误LNK2019:函数___pyx_pf_7pygfunc_f中引用的未解析的外部符号_c_gfunc
而且当然:
致命错误LNK1120:1个未解决的外部零件
我想念什么?还是从一开始就在Python和Fortran之间建立这种工作流的这种方式被指责?
THX马丁
-
这是一个最小的工作示例。我使用gfortran并将编译命令直接写入安装文件。
gfunc.f90
module gfunc_module implicit none contains subroutine gfunc(x, n, m, a, b, c) double precision, intent(in) :: x integer, intent(in) :: n, m double precision, dimension(n), intent(in) :: a double precision, dimension(m), intent(in) :: b double precision, dimension(n, m), intent(out) :: c integer :: i, j do j=1,m do i=1,n c(i,j) = exp(-x * (a(i)**2 + b(j)**2)) end do end do end subroutine end module
pygfunc.f90
module gfunc1_interface use iso_c_binding, only: c_double, c_int use gfunc_module, only: gfunc implicit none contains subroutine c_gfunc(x, n, m, a, b, c) bind(c) real(c_double), intent(in) :: x integer(c_int), intent(in) :: n, m real(c_double), dimension(n), intent(in) :: a real(c_double), dimension(m), intent(in) :: b real(c_double), dimension(n, m), intent(out) :: c call gfunc(x, n, m, a, b, c) end subroutine end module
pygfunc.h
extern void c_gfunc(double* x, int* n, int* m, double* a, double* b, double* c);
pygfunc.pyx
from numpy import linspace, empty from numpy cimport ndarray as ar cdef extern from "pygfunc.h": void c_gfunc(double* a, int* n, int* m, double* a, double* b, double* c) def f(double x, double a=-10.0, double b=10.0, int n=100): cdef: ar[double] ax = linspace(a, b, n) ar[double,ndim=2] c = empty((n, n), order='F') c_gfunc(&x, &n, &n, <double*> ax.data, <double*> ax.data, <double*> c.data) return c
setup.py
from distutils.core import setup from distutils.extension import Extension from Cython.Distutils import build_ext # This line only needed if building with NumPy in Cython file. from numpy import get_include from os import system # compile the fortran modules without linking fortran_mod_comp = 'gfortran gfunc.f90 -c -o gfunc.o -O3 -fPIC' print fortran_mod_comp system(fortran_mod_comp) shared_obj_comp = 'gfortran pygfunc.f90 -c -o pygfunc.o -O3 -fPIC' print shared_obj_comp system(shared_obj_comp) ext_modules = [Extension(# module name: 'pygfunc', # source file: ['pygfunc.pyx'], # other compile args for gcc extra_compile_args=['-fPIC', '-O3'], # other files to link to extra_link_args=['gfunc.o', 'pygfunc.o'])] setup(name = 'pygfunc', cmdclass = {'build_ext': build_ext}, # Needed if building with NumPy. # This includes the NumPy headers when compiling. include_dirs = [get_include()], ext_modules = ext_modules)
test.py
# A script to verify correctness from pygfunc import f print f(1., a=-1., b=1., n=4) import numpy as np a = np.linspace(-1, 1, 4)**2 A, B = np.meshgrid(a, a, copy=False) print np.exp(-(A + B))
我所做的大多数更改都不是根本性的。这是重要的。
-
您正在混合双精度和单精度浮点数。 不要那样做 一起使用real(Fortran),float(Cython)和float32(NumPy),并一起使用double precision(Fortran),double(Cyton)和float64(NumPy)。尽量不要无意间将它们混合在一起。我以为您想在我的例子中加倍。
-
您应该将所有变量作为指针传递给Fortran。在这方面,它与C调用约定不匹配。Fortran中的iso_c_binding模块仅匹配C命名约定。将数组作为指针传递,其大小作为单独的值。可能还有其他方法可以执行此操作,但我不知道。
我还在安装文件中添加了一些东西,以显示在构建时可以在其中添加一些更有用的额外参数的地方。
要编译,请运行
python setup.py build_ext --inplace
。要验证它是否有效,请运行测试脚本。这是在fortran90.org上显示的示例:mesh_exp
这里还有两个,我放在一起前段时间:ftridiag,fssor
我当然不会在这方面的专家,但这些例子可能是一个良好的开端。 -