I am playing around with f2py. I’m a bit confused about numpy intrinsic types vs. fortran 90 types. It seems like I can only use single precision reals in fortran 90, when interacting with python. Let me illustrate with an example:
Say I have this fortran 90 module, test.f90, to be compiled with f2py and imported in python:
module test
implicit none
integer, parameter :: sp = selected_real_kind(6,37) ! single precision
integer, parameter :: dp = selected_real_kind(15,307) ! double precision
real(sp) :: r_sp = 1.0
real(dp) :: r_dp = 1.0_dp
end module
and I compile like this:
f2py -c -m test test.f90
Then, in python:
>>> import test
>>> test.test.r_sp
array(1.0, dtype=float32)
>>> test.test.r_dp
array(1.0)
IOW, it seems like f2py doesn’t accept double precision. This becomes even more problematic when passing input to a fortran 90 subroutine from python. Say I extend my module to:
module test
implicit none
integer, parameter :: sp = selected_real_kind(6,37) ! single precision
integer, parameter :: dp = selected_real_kind(15,307) ! double precision
real(sp) :: r_sp = 1.0
real(dp) :: r_dp = 1.0_dp
contains
subroutine input_sp(val)
real(sp), intent(in) :: val
real(sp) :: x
x = val
write(*,*) x
end subroutine
subroutine input_dp(val)
real(dp), intent(in) :: val
real(dp) :: x
x = val
write(*,*) x
end subroutine
end module
f2py -c -m test test.f90
python
>>> import test
>>> test.test.input_sp(array(1.0,dtype=float32))
1.0000000
>>> test.test.input_sp(array(1.0,dtype=float64))
1.0000000
>>> test.test.input_dp(array(1.0,dtype=float32))
-1.15948430791165406E+155
>>> test.test.input_dp(array(1.0,dtype=float64))
-1.15948430791165406E+155
So, it seems like any input variable to be sent from python must be declared single precision. Is this a known issue with f2py?
Also, as a follow up question: Converting from sp to dp works, in the following sense:
subroutine input_sp_to_dp(val)
real(sp), intent(in) :: val(2)
real(dp) :: x(2)
x = val
write(*,*) x
end subroutine
But I wonder if this is compiler specific at all? Can I expect the above subroutine to do the right thing with any compiler on any architecture? When testing, I used gfortran fro all the above examples.
In your first example, I don’t know why you say it seems like f2py doesn’t accept double precision, when
test.test.r_dpis double precision. A numpy array that shows a value with a decimal point and no explicit dtype is a double precision array.The second example shows a limitation in F2PY’s handling of type definitions with
kind=<kind>. See the FAQ:https://numpy.org/doc/stable/f2py/advanced.html#dealing-with-kind-specifiers
To see what is happening, run
f2py test.f90 -m test. I get this:Note that it is mapping both "real(kind=sp)" and "real(kind=dp)" to C "float", which is single precision.
There are several ways to fix this.
Method 1
Change the type declarations to "real(kind=4)" and "real(kind=8)" (or "real4" and "real8"),
respectively.
Of course, this defeats the purpose of using
selected_real_kind, and for some compilers,4 and 8 are not the correct KIND values for single and double precision.
In this case, with gfortran,
spis 4 anddpis 8, so it works.Method 2
Tell f2py how to handle those declarations. This is explained in the f2py FAQ, and it is the approach suggested in the "getctype: …" messages in the output of f2py shown above.
In this case, you would create a file called
.f2py_f2cmap(in the directory where you are running f2py) that contains the lineThen f2py will do the right thing with those
real(sp)andreal(dp)declarations.Method 3
It also works to rearrange your code a bit:
See Subroutine argument not passed correctly from Python to Fortran for a similar suggestion.