On Thu, Jul 22, 2010 at 10:35 AM, Warren Weckesser <warren.weckes...@enthought.com> wrote: > Keith Goodman wrote: >> On Thu, Jul 22, 2010 at 7:48 AM, Warren Weckesser >> <warren.weckes...@enthought.com> wrote: >> >> >>> Actually, because of the use of reshape(3,3,4), your second >>> example does make a copy. >>> >> >> When does reshape return a view and when does it return a copy? >> >> > > According to the numpy.reshape docstring, it returns > a view when it can. In the previous example, it is > not possible to configure the strides so that the > four elements in each 2x2 block can be represented > in a single axis using the original memory layout, > so the data must be copied to achieve the shape > (3,3,4). > >> Here's a simple example that returns a view: >> >> >>>> x = np.array([1,2,3,4]) >>>> y = x.reshape(2,2) >>>> y[0,0] = 9 >>>> x >>>> >> array([9, 2, 3, 4]) >> >> What's a simple example that returns a copy? >> > > In [85]: x = np.array([[1,2],[3,4],[5,6]]).T # Note the transpose. > > In [86]: x > Out[86]: > array([[1, 3, 5], > [2, 4, 6]]) > > In [87]: y = x.reshape(6) > > In [88]: x[0,1] = 99 > > In [89]: y > Out[89]: array([1, 3, 5, 2, 4, 6])
Thanks, Warren. It's very useful to me to know that reshape can return a copy. Now I know how to slow down the other guy's function in a horse race. _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
