My guess; First of all, you are actually manipulating twice as much data as opposed to an inplace sort.
Moreover, an inplace sort gains locality as it is being sorted, whereas the argsort is continuously making completely random memory accesses. -----Original Message----- From: josef.p...@gmail.com Sent: Sunday, February 16, 2014 11:43 PM To: Discussion of Numerical Python Subject: [Numpy-discussion] argsort speed currently using numpy 1.6.1 What's the fastest argsort for a 1d array with around 28 Million elements, roughly uniformly distributed, random order? Is there a reason that np.argsort is almost 3 times slower than np.sort? I'm doing semi-systematic timing for a stats(models) algorithm. Josef _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
