Hello, I imagine that perhaps this issue I'm seeing is only an issue because I don't thoroughly understand the buffer issues associated with numpy arrays, but here it is anyway: In [16]:a1 = numpy.zero numpy.zeros numpy.zeros_like In [16]:a1 = numpy.zeros( (2,2) ) In [17]:a1[0,:] = 1 In [18]:a1 Out[18]: array([[ 1., 1.], [ 0., 0.]]) In [19]:str(a1.data) Out[19]:'\x00\x00\x00\x00\x00\x00\xf0?\x00\x00\x00\x00\x00\x00\xf0?\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00' In [20]:a2 = a1.transpose() In [21]:str(a2.data) Out[21]:'\x00\x00\x00\x00\x00\x00\xf0?\x00\x00\x00\x00\x00\x00\xf0?\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00' That is, when getting the .data from an array, if it was C_CONTIGUOUS but was .transposed(), the .data does not reflect this operation, right? So, would that imply that a .copy() should be done first on any array that you want to access .data on? Thanks, Glen