On Wed, Jun 29, 2011 at 11:05 AM, Robert Elsner <ml...@re-factory.de> wrote: > > Yeah great that was spot-on. And I thought I knew most of the slicing > tricks. I combined it with a slice object so that > > idx_obj = [ None for i in xrange(a.ndim) ]
or idx_obj = [None] * a.ndim otherwise this is also what I do quite often Josef > idx_obj[axis] = slice(None) > > a * x[idx_object] > > works the way I want it. Suggestions are welcome but I am happy with the > quick solution you pointed out. Thanks > > > On 29.06.2011 16:38, Skipper Seabold wrote: >> On Wed, Jun 29, 2011 at 10:32 AM, Robert Elsner <ml...@re-factory.de> wrote: >>> Hello everyone, >>> >>> I would like to solve the following problem (preferably without >>> reshaping / flipping the array a). >>> >>> Assume I have a vector v of length x and an n-dimensional array a where >>> one dimension has length x as well. Now I would like to multiply the >>> vector v along a given axis of a. >>> >>> Some example code >>> >>> a = np.random.random((2,3)) >>> x = np.zeros(2) >>> >>> a * x # Fails because not broadcastable >>> >>> >>> So how do I multiply x with the columns of a so that for each column j >>> a[:,j] = a[:,j] * x >>> >>> without using a loop. Is there some (fast) fast way to accomplish that >>> with numpy/scipy? >>> >> Is this what you want? >> >> a * x[:,None] >> >> or >> >> a * x[:,np.newaxis] >> >> or more generally >> >> a * np.expand_dims(x,1) >> >> Skipper >> _______________________________________________ >> 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 > _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
