def _cholesky_block_diag(block_diag_operator):
# We take the cholesky of each block on the diagonal.
return linear_operator_block_diag.LinearOperatorBlockDiag(
operators=[
operator.cholesky() for operator in block_diag_operator.operators],
is_non_singular=True,
is_self_adjoint=False,
is_square=True)
def _inverse_block_diag(block_diag_operator):
# We take the inverse of each block on the diagonal.
return linear_operator_block_diag.LinearOperatorBlockDiag(
operators=[
operator.inverse() for operator in block_diag_operator.operators],
is_non_singular=block_diag_operator.is_non_singular,
is_self_adjoint=block_diag_operator.is_self_adjoint,
is_positive_definite=block_diag_operator.is_positive_definite,
is_square=True)
def _matmul_linear_operator_block_diag_block_diag(linop_a, linop_b):
return linear_operator_block_diag.LinearOperatorBlockDiag(
operators=[
o1.matmul(o2) for o1, o2 in zip(
linop_a.operators, linop_b.operators)],
is_non_singular=registrations_util.combined_non_singular_hint(
linop_a, linop_b),
# In general, a product of self-adjoint positive-definite block diagonal
# matrices is not self = self - adjoint.
is_self_adjoint=None,
# In general, a product of positive-definite block diagonal matrices is
# not positive-definite.
is_positive_definite=None,
is_square=True)
