simEigen.svd
Description
|
SVD decomposition. See https://eigen.tuxfamily.org/dox/classEigen_1_1JacobiSVD.html for details. |
Lua synopsis |
grid s, grid u, grid v, grid x=simEigen.svd(grid m, bool computeThinU=true, bool computeThinV=true, grid b=nil)
|
Lua parameters |
m (grid): input matrix
computeThinU (bool, default: true):
computeThinV (bool, default: true):
b (grid, default: nil): an optional vector to solve for x the system m*x=b
|
Lua return values |
s (grid): singular values as a m-by-1 matrix
u (grid): U matrix (left singular vectors)
v (grid): V matrix (right singular vectors)
x (grid): the x solution if b has been specified
|
Python synopsis |
grid s, grid u, grid v, grid x=simEigen.svd(grid m, bool computeThinU=true, bool computeThinV=true, grid b=nil)
|
See also
|
|
|