Example. In [18]:a = array([1,2,3])
In [19]:a.flags Out[19]: C_CONTIGUOUS : True F_CONTIGUOUS : True OWNDATA : True WRITEABLE : True ALIGNED : True UPDATEIFCOPY : False In [20]:a.shape = (1,3) In [21]:a.flags Out[21]: C_CONTIGUOUS : True F_CONTIGUOUS : False OWNDATA : True WRITEABLE : True ALIGNED : True UPDATEIFCOPY : False In [22]:a.shape = (3,1) In [23]:a.flags Out[23]: C_CONTIGUOUS : True F_CONTIGUOUS : False OWNDATA : True WRITEABLE : True ALIGNED : True UPDATEIFCOPY : False All three shapes are both C_CONTIGUOUS and F_CONTIGUOUS. I think ignoring all 1's in the shape would give the right results for otherwise contiguous arrays because in those positions the index can only take the value 0. Chuck
_______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
