John Hunter wrote:
John> I have two equal length 1D arrays of 256-4096 complex or John> floating point numbers which I need to put into a John> shape=(len(x),2) array.
I tested all the suggested methods and the transpose with [x] and [y] was the clear winner, with an 8 fold speed up over my original code. The concatenate method was between 2-3 times faster.
I was a little surprised by this, as I figured that the transpose method made an extra copy of the data (array() makes one copy, transpose() another. So I looked at the source for concatenate: def concatenate(a, axis=0): """concatenate(a, axis=0) joins the tuple of sequences in a into a single NumPy array. """ if axis == 0: return multiarray.concatenate(a) else: new_list = [] for m in a: new_list.append(swapaxes(m, axis, 0)) return swapaxes(multiarray.concatenate(new_list), axis, 0) So, if you are concantenating along anything other than the zero-th axis, you end up doing something similar to the transpose method. Seeign this, I trioed something else: def test_concat2(x,y): x.shape = (1,-1) y.shape = (1,-1) X = transpose( concatenate( (x, y) ) ) x.shape = (-1,) y.shape = (-1,) This then uses the native concatenate, but requires an extra copy in teh transpose. Here's a somewhat cleaner version, though you get more copies: def test_concat3(x,y): "Thanks to Chris Barker and Bryan Cole" X = transpose( concatenate( ( reshape(x,(1,-1)), reshape(y,(1,-1)) ) ) ) Here are the test results: testing on vectors of length: 4096 test_concat 0.286280035973 test_transpose 0.100033998489 test_naive 0.805399060249 test_concat3 0.109319090843 test_concat2 0.136469960213 All the transpose methods are essentially a tie. Would it be that hard for concatenate to do it's thing for any axis in C? It does seem like this is a fairly basic operation, and shouldn't require more than one copy. By the way, I realised that the transpose method had an extra call. transpose() can take an approprriate python sequence, so this works just fine: def test_transpose2(x,y): X = transpose([x]+[y]) However, it doesn't really save you the copy, as I'm retty sure transpose makes a copy internally anyway. Test results: testing on vectors of length: 4096 test_transpose 0.104995965958 test_transpose2 0.103582024574 I think the winner is: X = transpose([x]+[y]) well, I learned a little bit more about Numeric today. -Chris -- Christopher Barker, Ph.D. Oceanographer NOAA/OR&R/HAZMAT (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception Chris.Barker@noaa.gov