def test_approximate_symmetric_svd(self):
"""Compute the SVD of symmetric **A** such that **SVD(A) = V S V^T**"""
n = 100
A = El.DistMatrix()
El.Uniform(A, n, n)
A = A.Matrix()
# Make A symmetric
for i in xrange(0, A.Height()):
for j in xrange(0, i + 1):
A.Set(j, i, A.Get(i, j))
# Usign symmetric SVD
SA = El.Matrix()
VA = El.Matrix()
sl_nla.approximate_symmetric_svd(A, SA, VA, k=n)
# Check result
VAT = El.Matrix()
El.Copy(VA, VAT)
RESULT = El.Matrix()
El.Zeros(RESULT, n, n)
El.DiagonalScale(El.RIGHT, El.NORMAL, SA, VAT)
El.Gemm(El.NORMAL, El.ADJOINT, 1, VAT, VA, 1, RESULT)
self.assertTrue(utils.equal(A, RESULT))
def test_approximate_svd(self):
"""Compute the SVD of **A** such that **SVD(A) = U S V^T**."""
n = 100
# Generate random matrix
A = El.DistMatrix()
El.Uniform(A, n, n)
A = A.Matrix()
# Dimension to apply along.
k = n
U = El.Matrix()
S = El.Matrix()
V = El.Matrix()
sl_nla.approximate_svd(A, U, S, V, k=k)
# Check result
RESULT = El.Matrix()
El.Zeros(RESULT, n, n)
El.DiagonalScale(El.RIGHT, El.NORMAL, S, U)
El.Gemm(El.NORMAL, El.ADJOINT, 1, U, V, 1, RESULT)
self.assertTrue(utils.equal(A, RESULT))
x = El.SVM( A, d, lambd, ctrl )
endSVM = time.clock()
if worldRank == 0:
print "SVM time: ", endSVM-startSVM
w = x[0:n,0]
beta = x.Get(n,0)
z = x[n+1:n+m+1,0]
if display:
El.Display( w, "w" )
if worldRank==0:
print "beta=", beta
El.Display( z, "z" )
e = El.DistMatrix()
El.Zeros( e, m, 1 )
El.Gemv( El.NORMAL, 1., A, w, 1., e )
El.Shift( e, beta )
El.DiagonalScale( El.LEFT, El.NORMAL, d, e )
if display:
El.Display( e, "diag(d)*(A w + beta)" )
eTwoNorm = El.Nrm2( e )
if worldRank == 0:
print "|| A w + beta - d ||_2 =", eTwoNorm
# Require the user to press a button before the figures are closed
commSize = El.mpi.Size( El.mpi.COMM_WORLD() )
El.Finalize()
if commSize == 1:
raw_input('Press Enter to exit')
