On Thu, Feb 28, 2008 at 3:41 PM, [EMAIL PROTECTED] <[EMAIL PROTECTED]> wrote: > > Arnar wrote > > > from scipy import linalg > > facearray-=facearray.mean(0) #mean centering > > u, s, vt = linalg.svd(facearray, 0) > > scores = u*s > > facespace = vt.T > > hi Arnar > when i do this i get these > u =< 'numpy.core.defmatrix.matrix'> (4, 4) > that matches the eigenvectors matrix in my previous data > s=< 'numpy.ndarray'> (4,) > and > vt=<'numpy.core.defmatrix.matrix'> (4, 12) > > here > scores=u*s causes a matrix not aligned error.. > > is there something wrong in the calculation? > > > D > _______________________________________________ > Numpy-discussion mailing list > Numpy-discussion@scipy.org > http://projects.scipy.org/mailman/listinfo/numpy-discussion
This example assumes that facearray is an ndarray.(like you described in original post ;-) ) It looks like you are using a matrix. (u =< 'numpy.core.defmatrix.matrix'> (4, 4)) . This causes the u*s-broadcasting to fail. Try again, with: facearray = numpy.asarray(facearray), before calculation. Arnar _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
