On Thu, Jan 19, 2012 at 1:37 AM, Mark Bakker mark...@gmail.com wrote:
I noticed that swapaxes(0,1) is consistently (on my system) 10% faster than
transpose on a 2D matrix.
Transpose is faster for me. And a.T is faster than a.transpose()
perhaps because a.transpose() checks that the inputs make sense? My
guess is that they all do the same thing. It's just a matter of which
function has the least overhead.
I[10] a = np.random.rand(1000,1000)
I[11] timeit a.T
1000 loops, best of 3: 153 ns per loop
I[12] timeit a.transpose()
1000 loops, best of 3: 171 ns per loop
I[13] timeit a.swapaxes(0,1)
100 loops, best of 3: 227 ns per loop
I[14] timeit np.transpose(a)
100 loops, best of 3: 308 ns per loop
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