On 25 Feb 2007 01:44:01 +0000, Alexander Schmolck <[EMAIL PROTECTED]> wrote:
"Charles R Harris" <[EMAIL PROTECTED]> writes: > > Unfortunately I don't see an easy way to use the same approach the other > > way > > (matlab doesn't seem to offer much on the C level to manipulate arrays), > > so > > I'd presumably need something like: > > > > stuff_into_matlab_array(a.T.reshape(a.shape).copy()) > > > > the question is how to avoid doing two copies. > > > > Any comments appreciated, > > > The easiest way to deal with the ordering is to use the order keyword in > numpy: > > In [4]: a = array([0,1,2,3]).reshape((2,2), order='F') > > In [5]: a > Out[5]: > array([[0, 2], > [1, 3]]) > > You would still need to get access to something to reshape, shared memory or > something, but the key is that you don't have to reorder the elements, you > just need the correct strides and offsets to address the elements in Fortran > order. I have no idea if this works in numeric. It doesn't work in Numeric, but that isn't much of any issue because I think it ought to be pretty much equivalent by transposing and reshaping. However the problem is that I *do* need to reorder the elements for numpy->matlab and I'm not sure how to best do this (without unnecessary copying and temporary numpy array creation but using numpy functionality if possible).
I don't see any way to get around a copy, but you can make numpy do the work. For example: In [12]: a = array([[0,1],[2,3]]) In [13]: b = array(a, order='f') In [14]: a.flags Out[14]: C_CONTIGUOUS : True F_CONTIGUOUS : False OWNDATA : True WRITEABLE : True ALIGNED : True UPDATEIFCOPY : False In [15]: b.flags Out[15]: C_CONTIGUOUS : False F_CONTIGUOUS : True OWNDATA : True WRITEABLE : True ALIGNED : True UPDATEIFCOPY : False F_CONTIGUOUS is what you want. The trick is to somehow use memory in the construction of the reordered array that is already designated for matlab. I don't know how to do this, but I think it might be doable. Travis is your best bet to answer that question. Chuck
_______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
