On Sat, Mar 15, 2014 at 2:12 PM, Alexander Belopolsky <ndar...@mac.com>wrote:
> > On Sat, Mar 15, 2014 at 4:00 PM, Charles R Harris < > charlesr.har...@gmail.com> wrote: > >> These days they are usually written as v*w.T, i.e., the outer product of >> two vectors and are a fairly common occurrence in matrix expressions. For >> instance, covariance matrices are defined as E(v * v.T) > > > With the current numpy, we can do > > >>> x = arange(1, 5) > >>> x[:,None].dot(x[None,:]) > array([[ 1, 2, 3, 4], > [ 2, 4, 6, 8], > [ 3, 6, 9, 12], > [ 4, 8, 12, 16]]) > > I assume once @ becomes available, we will have > > >>> x[:,None] @ x[None,:] > array([[ 1, 2, 3, 4], > [ 2, 4, 6, 8], > [ 3, 6, 9, 12], > [ 4, 8, 12, 16]]) > Yes, that works. I was thinking more of easy translation of the forms found in textbooks. Householder reflection, for instance, is usually written as I - 2 * v * v.T Where the `v` are unit vectors. Chuck
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