def testRandomMat(self):
eps = 2.2204460492503131E-16
n = 30; m = 60; k = 30
for i in range(100):
A = spmatrix_util.ll_mat_rand(n, k, 0.9)
B = spmatrix_util.ll_mat_rand(k, m, 0.4)
C = spmatrix.matrixmultiply(A, B)
t = numpy.zeros(k, 'd')
y1 = numpy.zeros(n, 'd')
y2 = numpy.zeros(n, 'd')
for s in range(10):
x = RandomArray.random((m, ))
C.matvec(x, y1)
B.matvec(x, t)
A.matvec(t, y2)
self.failUnless(math.sqrt(numpy.dot(y1 - y2, y1 - y2)) < eps * n*m*k)
def testSubmatrix(self):
n = self.n
Psym = poisson.poisson1d_sym(n)
P = poisson.poisson1d(n)
for i in range(n):
P[i,i] = 4.0
Psym[i,i] = 4.0
# read and test diagonal blocks
for i in range(n):
self.failUnless(llmat_isEqual(self.A[n*i:n*(i+1),n*i:n*(i+1)], P))
self.failUnless(llmat_isEqual(self.S[n*i:n*(i+1),n*i:n*(i+1)], P))
self.failUnless(llmat_isEqual(self.A[n*i:n*(i+1),n*i:n*(i+1)], Psym))
self.failUnless(llmat_isEqual(self.S[n*i:n*(i+1),n*i:n*(i+1)], Psym))
# store and get diagonal blocks
R = spmatrix_util.ll_mat_rand(n*n, n*n, 0.01) # random matrix
for i in range(n):
R[n*i:n*(i+1),n*i:n*(i+1)] = P
self.failUnless(llmat_isEqual(R[n*i:n*(i+1),n*i:n*(i+1)], P))
R[n*i:n*(i+1),n*i:n*(i+1)] = Psym
self.failUnless(llmat_isEqual(R[n*i:n*(i+1),n*i:n*(i+1)], Psym))
# store and get off-diagonal blocks
for i in range(n-1):
R[n*i:n*(i+1),n*(i+1):n*(i+2)] = P
self.failUnless(llmat_isEqual(R[n*i:n*(i+1),n*(i+1):n*(i+2)], P))
R[n*i:n*(i+1),n*(i+1):n*(i+2)] = Psym
self.failUnless(llmat_isEqual(R[n*i:n*(i+1),n*(i+1):n*(i+2)], Psym))
# store and get diagonal blocks in symmetric matrix
R = spmatrix.ll_mat_sym(n*n)
for i in range(n):
R[n*i:n*(i+1),n*i:n*(i+1)] = Psym
self.failUnless(llmat_isEqual(R[n*i:n*(i+1),n*i:n*(i+1)], Psym))
# store and get off-diagonal blocks in symmetric matrix
for i in range(n-1):
R[n*(i+1):n*(i+2),n*i:n*(i+1)] = P
self.failUnless(llmat_isEqual(R[n*(i+1):n*(i+2),n*i:n*(i+1)], P))
R[n*(i+1):n*(i+2),n*i:n*(i+1)] = Psym
self.failUnless(llmat_isEqual(R[n*(i+1):n*(i+2),n*i:n*(i+1)], Psym))
printMatrix(Atemp)
print 'Matrix with rows 7 and 8 and deleted:'
mask = Numeric.ones(n, 'l')
mask[7:9] = 0
Atemp.delete_rows(mask)
printMatrix(Atemp)
print Atemp.delete_rows.__doc__
print 'deleting rows and column'
Atemp = As.copy()
print 'original matrix:'
printMatrix(Atemp)
print 'Matrix with rows/cols 7 and 8 and deleted:'
mask = Numeric.ones(n, 'l')
mask[7:9] = 0
Atemp.delete_rowcols(mask)
printMatrix(Atemp)
nn = 100
R = spmatrix_util.ll_mat_rand(nn, nn, 0.3)
##print R.nnz
for i in range(nn - 5):
mask = Numeric.ones(nn, 'l')
mask[0] = 0
R.delete_rowcols(mask)
nn -= 1
##print R
printMatrix(Atemp)
print 'Matrix with rows 7 and 8 and deleted:'
mask = Numeric.ones(n, 'l')
mask[7:9] = 0
Atemp.delete_rows(mask)
printMatrix(Atemp)
print Atemp.delete_rows.__doc__
print 'deleting rows and column'
Atemp = As.copy()
print 'original matrix:'
printMatrix(Atemp)
print 'Matrix with rows/cols 7 and 8 and deleted:'
mask = Numeric.ones(n, 'l')
mask[7:9] = 0
Atemp.delete_rowcols(mask)
printMatrix(Atemp)
nn = 100
R = spmatrix_util.ll_mat_rand(nn, nn, 0.3)
##print R.nnz
for i in range(nn-5):
mask = Numeric.ones(nn, 'l')
mask[0] = 0
R.delete_rowcols(mask)
nn -= 1
##print R
