Hi,
I just confirmed Stefan's answer on one of the examples in
http://www.mathworks.co.jp/matlabcentral/newsreader/view_thread/262996
matlab:
A = randn(100,2)*[2 0;3 0;-1 2]';
A = A + randn(size(A))/3;
[U,S,V] = svd(A);
X = V(:,end)
python:
from numpy import *
A = random.randn(100
Hi Peter
On 5 May 2010 10:02, Peter Schmidtke wrote:
> u,s,vh=numpy.linalg.linalg.svd(M)
>
> Then in the matlab analog they use the last column of vh to get the a,b,c
> coefficients for the equation
> a,b,c=vh[:, -1] in numpy
Note that vh is the conjugate transpose of v. You are probably
intere
Dear Numpy Users,
I want to fit a 3d plane into a 3d point cloud and I saw that one could use
svd for this purpose. So as I am very fond of numpy I saw that svd was
implementented in the linalg module.
Currently I have a numpy array called xyz with n lines (number of points)
and 3 columns (x,y,z
