"John" == John Hunter <jdhunter@ace.bsd.uchicago.edu> writes:
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. John> I need to do this a lot, so I would like to use the most John> efficient means. Currently I am doing: 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. Thanks to all who responded, John Hunter cruncher2:~/python/test> python test.py test_naive test_naive 0.480427026749 cruncher2:~/python/test> python test.py test_concat test_concat 0.189149975777 cruncher2:~/python/test> python test.py test_transpose test_transpose 0.0698409080505 from Numeric import transpose, concatenate, reshape, array, zeros from RandomArray import normal import time, sys def test_naive(x,y): "Naive approach" X = zeros( (len(x),2), typecode=x.typecode()) X[:,0] = x X[:,1] = y def test_concat(x,y): "Thanks to Chris Barker and Bryan Cole" X = concatenate( ( reshape(x,(-1,1)), reshape(y,(-1,1)) ), 1) def test_transpose(x,y): "Thanks to Joachim Saul" X = transpose(array([x]+[y])) m = {'test_naive' : test_naive, 'test_concat' : test_concat, 'test_transpose' : test_transpose} nse1 = normal(0.0, 1.0, (4096,)) nse2 = normal(0.0, 1.0, nse1.shape) N = 1000 trials = range(N) func = m[sys.argv[1]] t1 = time.time() for i in trials: func(nse1,nse2) t2 = time.time() print sys.argv[1], t2-t1