f2py数组值函数 [英] f2py array valued functions
问题描述
最近版本的f2py支持包装数组值的fortran函数吗?
在一些古代文献中,这不被支持。那么现在呢?
举个例子,将下面的函数保存为func.f95。
函数func(x)
隐式无
双精度:: x(:),func(size(x))
integer :: i
i = 1,size(x)
func(i)= i * x(i)
end do
end function
我用 f2py --fcompiler = gnu95 -c -m func func.f95
$ b
然后让下面的python代码为test_func.py
import func
从numpy导入数组
x = array(xrange(1,10),dtype ='float64')
print'x =',x
y = func。 func(x)
print'func(x)=',y
python test_func.py
是
x = [1. 2. 3. 4. 5. 6. 7. 8. 9.]
分段错误
f2py的机制使Fortran 子程序插入到python函数中。它不知道如何将Fortran 函数转换为python函数。我发现我需要用子程序包装所有Fortran函数,或者甚至更好地将它们重写为子程序。
Do recent versions of f2py support wrapping array-valued fortran functions? In some ancient documentation this wasn't supported. How about it now?
Let's for example save the following function as func.f95.
function func(x)
implicit none
double precision :: x(:),func(size(x))
integer :: i
do i=1,size(x)
func(i) = i*x(i)
end do
end function
I compile this with f2py --fcompiler=gnu95 -c -m func func.f95
Then let the following python code be test_func.py
import func
from numpy import array
x = array(xrange(1,10),dtype='float64')
print 'x=',x
y = func.func(x)
print 'func(x)=',y
The output from
python test_func.py
is
x= [ 1. 2. 3. 4. 5. 6. 7. 8. 9.]
Segmentation fault
The mechanism of f2py turns Fortran subroutines into python functions. It doesn't understand how to turn a Fortran function into a python function. I have found that I need to wrap all Fortran functions with a subroutine, or even better, rewrite them as subroutines.
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