On 3/1/07, Francesc Altet <[EMAIL PROTECTED]> wrote:
Hi, I don't think there is a solution for this, but perhaps anybody may offer some idea. Given: In [79]:a=numpy.arange(9,-1,-1) In [80]:b=numpy.arange(10) In [81]:numpy.random.shuffle(b) In [82]:b Out[82]:array([2, 6, 3, 5, 4, 9, 0, 8, 7, 1]) In [83]:a=a[b] In [84]:a Out[84]:array([7, 3, 6, 4, 5, 0, 9, 1, 2, 8]) is there a way to make the step 83 without having to keep 3 arrays in-memory at the same time? This is, some way of doing fancy indexing, but changing the elements *inplace*. The idea is to keep memory requeriments as low as possible when a and b are large arrays. Thanks!
You can also put the arrays together and implement it as an inplace sort, which will save space at the price of n*log(n) operations. The idea is to sort on the shuffled array while carrying the corresponding elements of the other array along in the exchanges, which I think you can now do using fields and the order keyword in the sort. Chuck
_______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
