Wed, 09 Sep 2009 13:08:22 +0200, Ruben Salvador wrote: > Perfect! Thank you very much :D > > It's not obvious, though...I think I should read more deeply into > Python/NumPy...but for the use I'm giving to it... > > Anyway, I thought the pythonic way would be faster, but after trying > with a size 80000 instead of 8...the for loop is faster! > > Pythonic time ==> 0.36776400 seconds > For loop time ==> 0.31708717 seconds
Doubtful: In [1]: import numpy as np In [2]: a = np.zeros((80000, 26)) In [3]: b = np.zeros((80000,)) In [4]: def foo(): ...: d = np.empty(a.shape, a.dtype) ...: for i in xrange(a.shape[0]): ...: d[i] = a[i] + b[i] ...: In [5]: %timeit d=a+b[:,None] 100 loops, best of 3: 18.3 ms per loop In [6]: %timeit foo() 10 loops, best of 3: 334 ms per loop _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
