def bidiag_unpack_diag(diag, superdiag):
"""
returns B
This functions unpacks the bidiagonal matrix T of the diagonal
and superdiagonal obtained from gsl_linalg_bidiag_unpack[_B]
"""
n = diag.shape[0]
B = numx.identity(n) * diag
sub = numx.identity(n - 1) * superdiag
sub2 = numx.concatenate((numx.concatenate((zeros([n - 1, 1]), sub),
1), zeros([1, n])))
B = sub2 + B
return B
def bidiag_unpack_diag(diag, superdiag):
"""
returns B
This functions unpacks the bidiagonal matrix T of the diagonal
and superdiagonal obtained from gsl_linalg_bidiag_unpack[_B]
"""
n = diag.shape[0]
B = numx.identity(n)*diag
sub = numx.identity(n-1)*superdiag
sub2 = numx.concatenate(
(numx.concatenate((zeros([n-1,1]),sub), 1), zeros([1,n])))
B = sub2 + B
return B
def symmtd_unpack_diag(diag, subdiag):
"""
returns T
This functions unpacks the tridiagonal matrix T of the diagonal
and subdiagonal obtained from gsl_linalg_symmtd_unpack[_T]
"""
n = diag.shape[0]
T = numx.identity(n) * diag
sub = numx.identity(n - 1) * subdiag
sub1 = numx.concatenate((zeros(
(1, n)), numx.concatenate((sub, zeros((n - 1, 1))), 1)))
sub2 = numx.concatenate((numx.concatenate((zeros([n - 1, 1]), sub),
1), zeros([1, n])))
T = sub1 + sub2 + T
return T
def symmtd_unpack_diag(diag, subdiag):
"""
returns T
This functions unpacks the tridiagonal matrix T of the diagonal
and subdiagonal obtained from gsl_linalg_symmtd_unpack[_T]
"""
n = diag.shape[0]
T = numx.identity(n)*diag
sub = numx.identity(n-1)*subdiag
sub1 = numx.concatenate(
(zeros((1,n)), numx.concatenate((sub, zeros((n-1,1))), 1)))
sub2 = numx.concatenate(
(numx.concatenate((zeros([n-1,1]),sub), 1), zeros([1,n])))
T = sub1 + sub2 + T
return T
def LU_unpack(LU):
"""
returns (L,U)
This function splits the matrix LU into the the upper matrix U and
the lower matrix L. The diagonal of L is the identity.
"""
code = get_typecode(LU)
u = zeros(LU.shape, code)
l = numx.identity(LU.shape[0], code)
for i in range(LU.shape[0]):
u[i, i:] = LU[i, i:]
l[i, 0:i] = LU[i, :i]
return (l, u)
def LU_unpack(LU):
"""
returns (L,U)
This function splits the matrix LU into the the upper matrix U and
the lower matrix L. The diagonal of L is the identity.
"""
code = get_typecode(LU)
u = zeros(LU.shape, code)
l = numx.identity(LU.shape[0], code)
for i in range(LU.shape[0]):
u[i, i: ] = LU[i, i:]
l[i, 0:i] = LU[i, :i]
return (l, u)
