On 3/22/07, Bill Baxter <[EMAIL PROTECTED]> wrote: > On 3/23/07, Eric Firing <[EMAIL PROTECTED]> wrote: > > Sebastian Haase wrote: > > > On 3/22/07, Stefan van der Walt <[EMAIL PROTECTED]> wrote: > > >> On Thu, Mar 22, 2007 at 08:13:22PM -0400, Brian Blais wrote: > > >>> Hello, > > >>> > > >>> I'd like to concatenate a couple of 1D arrays to make it a 2D array, > > >>> with two columns > > >>> (one for each of the original 1D arrays). I thought this would work: > > >>> > > >>> > > >>> In [47]:a=arange(0,10,1) > > >>> > > >>> In [48]:a > > >>> Out[48]:array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]) > > >>> > > >>> In [49]:b=arange(-10,0,1) > > >>> > > >>> In [51]:b > > >>> Out[51]:array([-10, -9, -8, -7, -6, -5, -4, -3, -2, -1]) > > >>> > > >>> In [54]:concatenate((a,b)) > > >>> Out[54]: > > >>> array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, -10, -9, -8, > > >>> -7, -6, -5, -4, -3, -2, -1]) > > >>> > > >>> In [55]:concatenate((a,b),axis=1) > > >>> Out[55]: > > >>> array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, -10, -9, -8, > > >>> -7, -6, -5, -4, -3, -2, -1]) > > >>> > > >>> > > >>> but it never expands the dimensions. Do I have to do this... > > >>> > > >>> In [65]:concatenate((a.reshape(10,1),b.reshape(10,1)),axis=1) > > >>> Out[65]: > > >>> array([[ 0, -10], > > >>> [ 1, -9], > > >>> [ 2, -8], > > >>> [ 3, -7], > > >>> [ 4, -6], > > >>> [ 5, -5], > > >>> [ 6, -4], > > >>> [ 7, -3], > > >>> [ 8, -2], > > >>> [ 9, -1]]) > > >>> > > >>> > > >>> ? > > >>> > > >>> I thought there would be an easier way. Did I overlook something? > > >> How about > > >> > > >> N.vstack((a,b)).T > > >> > > > Also mentioned here should be the use of > > > newaxis. > > > As in > > > a[:,newaxis] > > > > > > However I never got a "good feel" for how to use it, so I can't > > > complete the code you would need. > > > > n [9]:c = N.concatenate((a[:,N.newaxis], b[:,N.newaxis]), axis=1) > > > > In [10]:c > > Out[10]: > > array([[ 0, -10], > > [ 1, -9], > > [ 2, -8], > > [ 3, -7], > > [ 4, -6], > > [ 5, -5], > > [ 6, -4], > > [ 7, -3], > > [ 8, -2], > > [ 9, -1]]) > > > > Then of course, there's r_ and c_: > > c = numpy.c_[a,b] > > c = numpy.r_[a[None],b[None]].T > > --bb So, None is the same as newaxis - right?
But what is a[None] vs. a[:,N.newaxis] ? -Sebastian _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion