Hello John! On Friday 26.11.2010 23:23:51 Peter Otten wrote: > John wrote: > > I know this is a simple problem, but I want to do it the most > > efficient way (that is vectorized...) > > > > import numpy as np > > > > a = np.array(([1,2,3,4],[1,.2,3,4],[1,22,3,4])) > > b = np.sum(a,axis=1) > > > > for i,elem in enumerate(a): > > a[i,:] = elem/b[i] > > > > suggestions? > > I'm not a numpy expert, but: > > (a.transpose()/np.sum(a, axis=1)).transpose()
The underlying feature of Peter's solution is called broadcasting. For a detailed explanation look at: http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html Eike. _______________________________________________ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: http://mail.python.org/mailman/listinfo/tutor
