On 03/16/2011 02:35 PM, Paul Anton Letnes wrote: > Heisann! Hei der,
> On 16. mars 2011, at 14.30, Dag Sverre Seljebotn wrote: > >> On 03/16/2011 02:24 PM, Paul Anton Letnes wrote: >>> Hi! >>> >>> This little snippet of code tricked me (in a more convoluted form). The *= >>> operator does not change the datatype of the left hand side array. Is this >>> intentional? It did fool me and throw my results quite a bit off. I always >>> assumed that 'a *= b' means exactly the same as 'a = a * b' but this is >>> clearly not the case! >> >> In [1]: a = np.ones(5) > Here, a is numpy.float64: >>>> numpy.ones(5).dtype > dtype('float64') > >> In [2]: b = a >> >> In [3]: c = a * 2 >> >> In [4]: b >> Out[4]: array([ 1., 1., 1., 1., 1.]) >> >> In [5]: a *= 2 > So since a is already float, and b is the same object as a, the resulting a > and b are of course floats. >> In [6]: b >> Out[6]: array([ 2., 2., 2., 2., 2.]) >> > This is not the case I am describing, as in my case, a was of dtype integer. > Or did I miss something? I was just trying to demonstrate that it is NOT the case that "a = a * 2 is exactly the same as a *= 2". If you assume that the two statements are the same, then it does not make sense that b = [1, 1, ...] the first time around, but b = [2, 2, 2...] the second time around. And in trying to figure out why that happened, perhaps you'd see how it all fits together... OK, it perhaps wasn't a very good explanation... Dag Sverre _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion