Re: [Numpy-discussion] isfortran compatibility in numpy 1.10.

I bet it has all been said already, but to note just in case. In numpy itself we use it mostly to determine the memory order of the *output* and not for safty purpose. That is the macro of course and I think yelling people to use flags.fnc in python is better. - Sebastian On Mon Nov 2

Re: [Numpy-discussion] isfortran compatibility in numpy 1.10.

On Mon, Nov 2, 2015 at 11:28 AM, Sebastian Berg wrote: > I bet it has all been said already, but to note just in case. In numpy > itself we use it mostly to determine the memory order of the *output* and > not for safty purpose. That is the macro of course and I think

Re: [Numpy-discussion] isfortran compatibility in numpy 1.10.

Charles R Harris wrote: >1. Return `a.flags.f_contiguous`. This differs for 1-D arrays, but is >most consistent with the name isfortran. If the idea is to determine if an array can safely be passed to Fortran, this is the correct one. >2. Return

[Numpy-discussion] isfortran compatibility in numpy 1.10.

Hi All, The isfortran function calls a.fnc (Fortran-Not-C), which is implemented as F_CONTIGUOUS && !C_CONTIGUOUS. Before relaxed stride checking contiguous multidimensional arrays could not be both and continguous 1-D arrays were always CONTIGUOUS, but this is not longer the case. Consequently

Re: [Numpy-discussion] isfortran compatibility in numpy 1.10.

As I posted to the github issue, I support #2 as it is the original meaning. The most common case of isfortran that I recall was to support transpositions that needed to occur before calling Fortran-compiled linear algebra routines. However, with that said, you could also reasonably do #1 and