[Numpy-discussion] Getting Callbacks with arrays to work

[Jon Moore]

Hi,

Thanks all works now!  The implicit none only didn't work when defining 
dv as a function now its a subroutine it seems to work.

Regards

Jon

On 12/01/2010 13:44, Pearu Peterson wrote:
> Hi,
>
> The problem is that f2py does not support callbacks that
> return arrays. There is easy workaround to that: provide
> returnable arrays as arguments to callback functions.
> Using your example:
>
> SUBROUTINE CallbackTest(dv,v0,Vout,N)
>    IMPLICIT NONE
>
>    !F2PY     intent( hide ):: N
>    INTEGER:: N, ic
>    EXTERNAL:: dv
>
>    DOUBLE PRECISION, DIMENSION( N ), INTENT(IN):: v0
>    DOUBLE PRECISION, DIMENSION( N ), INTENT(OUT):: Vout
>
>    DOUBLE PRECISION, DIMENSION( N ):: Vnow
>    DOUBLE PRECISION, DIMENSION( N )::  temp
>
>    Vnow = v0
>    !f2py intent (out) temp
>    call dv(temp, Vnow, N)
>
>    DO ic = 1, N
>       Vout( ic ) = temp(ic)
>    END DO
>
> END SUBROUTINE CallbackTest
>
> $ f2py -c test.f90 -m t --fcompiler=gnu95
>
>>>> from numpy import *
>>>> from t import *
>>>> arr = array([2.0, 4.0, 6.0, 8.0])
>>>> def dV(v):
>      print 'in Python dV: V is: ',v
>      ret = v.copy()
>      ret[1] = 100.0
>      return ret
> ...
>>>> output = callbacktest(dV, arr)
> in Python dV: V is:  [ 2.  4.  6.  8.]
>>>> output
> array([   2.,  100.,    6.,    8.])
>
> What problems do you have with implicit none? It works
> fine here. Check the format of your source code,
> if it is free then use `.f90` extension, not `.f`.
>
> HTH,
> Pearu
>
> Jon Moore wrote:
>>   Hi,
>>
>> I'm trying to build a differential equation integrator and later a
>> stochastic differential equation integrator.
>>
>> I'm having trouble getting f2py to work where the callback itself
>> receives an array from the Fortran routine does some work on it and then
>> passes an array back.
>>
>> For the stoachastic integrator I'll need 2 callbacks both dealing with
>> arrays.
>>
>> The idea is the code that never changes (ie the integrator) will be in
>> Fortran and the code that changes (ie the callbacks defining
>> differential equations) will be different for each problem.
>>
>> To test the idea I've written basic code which should pass an array back
>> and forth between Python and Fortran if it works right.
>>
>> Here is some code which doesn't work properly:-
>>
>> SUBROUTINE CallbackTest(dv,v0,Vout,N)
>>      !IMPLICIT NONE
>>
>> cF2PY     intent( hide ):: N
>>      INTEGER:: N, ic
>>
>>      EXTERNAL:: dv
>>
>>      DOUBLE PRECISION, DIMENSION( N ), INTENT(IN):: v0
>>      DOUBLE PRECISION, DIMENSION( N ), INTENT(OUT):: Vout
>>
>>      DOUBLE PRECISION, DIMENSION( N ):: Vnow
>>      DOUBLE PRECISION, DIMENSION( N )::  temp
>>
>>      Vnow = v0
>>
>>
>>      temp = dv(Vnow, N)
>>
>>      DO ic = 1, N
>>          Vout( ic ) = temp(ic)
>>      END DO
>>
>> END SUBROUTINE CallbackTest
>>
>>
>>
>> When I test it with this python code I find the code just replicates the
>> first term of the array!
>>
>>
>>
>>
>> from numpy import *
>> import callback as c
>>
>> def dV(v):
>>      print 'in Python dV: V is: ',v
>>      return v.copy()
>>
>> arr = array([2.0, 4.0, 6.0, 8.0])
>>
>> print 'Arr is: ', arr
>>
>> output = c.CallbackTest(dV, arr)
>>
>> print 'Out is: ', output
>>
>>
>>
>>
>> Arr is:  [ 2.  4.  6.  8.]
>>
>> in Python dV: V is:  [ 2.  4.  6.  8.]
>>
>> Out is:  [ 2.  2.  2.  2.]
>>
>>
>>
>> Any ideas how I should do this, and also how do I get the code to work
>> with implicit none not commented out?
>>
>> Thanks
>>
>> Jon
>>
>>
>>
>> ------------------------------------------------------------------------
>>
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