[MATH-320] NaN singular value from SVD

• Type: Bug
• Status: Closed
• Priority: Major
• Resolution: Fixed
• Affects Version/s: 2.0
• Fix Version/s: 2.1

Environment

Linux (Ubuntu 9.10) java version "1.6.0_16"

• Assignee: Unassigned
• Reporter: Dieter Vandenbussche
• Created: 10/Nov/09 15:42
• Updated: 23/Jun/11 20:02
• Resolved: 31/Dec/09 17:55

Description

The following jython code
Start code

from org.apache.commons.math.linear import *

Alist = [[1.0, 2.0, 3.0],[2.0,3.0,4.0],[3.0,5.0,7.0]]

A = Array2DRowRealMatrix(Alist)

decomp = SingularValueDecompositionImpl(A)

print decomp.getSingularValues()

End code

prints
array('d', [11.218599757513008, 0.3781791648535976, nan])
The last singular value should be something very close to 0 since the matrix
is rank deficient. When i use the result from getSolver() to solve a system, i end
up with a bunch of NaNs in the solution. I assumed i would get back a least squares solution.

Does this SVD implementation require that the matrix be full rank? If so, then i would expect
an exception to be thrown from the constructor or one of the methods.