def invtr(A, overwrite=False, lower=False):
"""Compute the inverse of a triangular matrix
Uses the corresponding LAPACK routine.
Parameters
----------
A : ndarray
An upper or lower triangular matrix.
overwrite : bool
Whether to overwrite the input array (may increase performance).
lower : bool
Whether the input array is lower-triangular, rather than upper-triangular.
Returns
-------
inv_A : ndarray
The inverse of A, which is also triangular.
"""
trtri, = la.lapack.get_lapack_funcs(('trtri', ), (A, ))
inv_A, info = trtri(A, lower=lower, overwrite_c=overwrite)
if info > 0:
raise sp.LinAlgError("%d-th diagonal element of the matrix is zero" %
info)
if info < 0:
raise ValueError('illegal value in %d-th argument of internal potri' %
-info)
return inv_A
def invpo(A, out=None, lower=False):
"""Efficient inversion of positive definite matrices using Cholesky decomposition.
NOT YET WORKING
"""
t = la.cholesky(A, lower=lower)
print sp.allclose(sp.dot(H(t), t), A)
#a, lower = la.cho_factor(A, lower=lower) #no.. we need a clean answer, it seems
potri, = la.lapack.get_lapack_funcs(('potri',), (A,))
inv_A, info = potri(t, lower=lower, overwrite_c=1, rowmajor=1) #rowmajor (C-order) is the default...
if info > 0:
raise sp.LinAlgError("%d-th diagonal element of the Cholesky factor is zero" % info)
if info < 0:
raise ValueError('illegal value in %d-th argument of internal potri'
% -info)
return inv_A