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
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