mar*_*urg 20 python fortran cython fortran-iso-c-binding
我想建立一个工作流程,在Windows机器上使用Cython从Python到达fortran例程
经过一番搜索,我找到了:http: //www.fortran90.org/src/best-practices.html#interfacing-with-c和https://stackoverflow.com/tags/fortran-iso-c-binding/info
和一些代码pices:
Fortran方面:
pygfunc.h:
void c_gfunc(double x, int n, int m, double *a, double *b, double *c);
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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
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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
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Cython方面:
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
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和设置文件:
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 )
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所有文件都在一个目录中
fortran文件编译(使用NAG Fortran Builder)pygfunc编译
但链接他们会抛出:
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个未解析的外部因素
我错过了什么?或者这是在Python和Fortran之间建立一个从一开始就被诅咒的工作流程?
THX马丁
Ian*_*anH 25
这是一个最低限度的工作示例.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
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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
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pygfunc.h
extern void c_gfunc(double* x, int* n, int* m, double* a, double* b, double* c);
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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
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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)
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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))
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我所做的大多数改变都不是非常根本的.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.使用real(Fortran),float(Cython)和float32(NumPy),并使用双精度(Fortran),double(Cyton)和float64(NumPy).尽量不要无意中混合它们.我以为你想在我的例子中想要双打.
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.可能有其他方法可以做到这一点,但我不知道.
我还在设置文件中添加了一些内容,以显示在构建时可以添加一些更有用的额外参数的位置.
要编译,运行python setup.py build_ext --inplace.要验证它是否有效,请运行测试脚本.
以下是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 我肯定不是专家在此,但这些例子可能是一个良好的开端.
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