On 5/23/07, Anne Archibald <[EMAIL PROTECTED]> wrote:
On 23/05/07, Albert Strasheim <[EMAIL PROTECTED]> wrote: > If you are correct that this is in fact a fresh new array, I really > don't understand where the values of these flags. To recap: > > In [19]: x = N.zeros((3,2)) > > In [20]: x.flags > Out[20]: > C_CONTIGUOUS : True > F_CONTIGUOUS : False > OWNDATA : True > WRITEABLE : True > ALIGNED : True > UPDATEIFCOPY : False > > In [21]: x[:,[1,0]].flags > Out[21]: > C_CONTIGUOUS : False > F_CONTIGUOUS : True > OWNDATA : False > WRITEABLE : True > ALIGNED : True > UPDATEIFCOPY : False > > So since x and x[:,[1,0]] are both new arrays, shouldn't their flags be > identical? I'd expect at least C_CONTIGUOUS and OWNDATA to be True. It looks like x[:,[1,0]] is done by fancy indexing on the first index and then transposing. I haven't looked at the implementation, though. If you need the result to be C-contiguous without further copying, you can do: x.transpose()[[1,0],:].transpose().flags which is horrible. I wouldn't rely on it, though, I'd use asconguousarray afterward.
Both copy and ascontiguousarray do the job: In [39]: ascontiguousarray(x[:,[1,0]]).flags Out[39]: C_CONTIGUOUS : True F_CONTIGUOUS : False OWNDATA : True WRITEABLE : True ALIGNED : True UPDATEIFCOPY : False In [40]: x[:,[1,0]].copy().flags Out[40]: C_CONTIGUOUS : True F_CONTIGUOUS : False OWNDATA : True WRITEABLE : True ALIGNED : True UPDATEIFCOPY : False The extra copy is unfortunate but I don't see how it is to be avoided. Maintaining order and contiguity in memory is not the goal of numpy, convenience and flexibility is. So interfacing with external C and FORTRAN is always going to need some care. Chuck
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