Le mercredi 17 février 2010 à 15:43 -0600, Robert Kern a écrit : > On Wed, Feb 17, 2010 at 15:29, Fabrice Silva <si...@lma.cnrs-mrs.fr> wrote: > > I previously coded a fortran function that needs a variable number of > > scalar arguments. This number is not known at compile time, but at call > > time. So I used to pass them within a vector, passing also the length of > > this vector > > > > subroutine systeme(inc,t,nm,Dinc,sn) > > C > > C evaluate the derivative of vector x at time t > > C with complex modes (sn). Used for the calculation > > C of auto-oscillations in resonator-valve coupled system. > > C > > integer nm,np,ny,ind > > double precision inc(1:2*nm+2), Dinc(1:2*nm+2) > > complex*16 sn(1:nm) > > > > Cf2py double precision, intent(in) :: t > > Cf2py integer, intent(in), optional :: nm > > Cf2py double precision, intent(in), dimension(2*nm+2) :: inc > > Cf2py double precision, intent(out), dimension(2*nm+2) :: Dinc > > Cf2py complex, intent(in), dimension(nm) :: sn > > > > > > I do now want to pass, not nm float values, but nm arrays of variables > > lengths. I expect to pass the following objects : > > - nm: number of arrays > > - L : a 1d-array (dimension nm) containing the lengths of each array > > - np: the sum of lengths > > - X : a 1d-array (dimension np) containing the concatenated arrays. > > Yeah, that's pretty much what you would have to do.
What about the next step: a variable number of arguments that are 2d-arrays with different shapes ? -- Fabrice Silva LMA UPR CNRS 7051 _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
