Exemple #1
0
def _solve_linear_operator(linop_a, linop_b):
  """Generic solve of two `LinearOperator`s."""
  is_square = registrations_util.is_square(linop_a, linop_b)
  is_non_singular = None
  is_self_adjoint = None
  is_positive_definite = None

  if is_square:
    is_non_singular = registrations_util.combined_non_singular_hint(
        linop_a, linop_b)
  elif is_square is False:  # pylint:disable=g-bool-id-comparison
    is_non_singular = False
    is_self_adjoint = False
    is_positive_definite = False

  return linear_operator_composition.LinearOperatorComposition(
      operators=[
          linear_operator_inversion.LinearOperatorInversion(linop_a),
          linop_b
      ],
      is_non_singular=is_non_singular,
      is_self_adjoint=is_self_adjoint,
      is_positive_definite=is_positive_definite,
      is_square=is_square,
  )
def _matmul_linear_operator_circulant_circulant(linop_a, linop_b):
  return linear_operator_circulant.LinearOperatorCirculant(
      spectrum=linop_a.spectrum * linop_b.spectrum,
      is_non_singular=registrations_util.combined_non_singular_hint(
          linop_a, linop_b),
      is_self_adjoint=registrations_util.combined_commuting_self_adjoint_hint(
          linop_a, linop_b),
      is_positive_definite=(
          registrations_util.combined_commuting_positive_definite_hint(
              linop_a, linop_b)),
      is_square=True)
def _matmul_linear_operator_tril_diag(linop_triangular, linop_diag):
  return linear_operator_lower_triangular.LinearOperatorLowerTriangular(
      tril=linop_triangular.to_dense() * linop_diag.diag,
      is_non_singular=registrations_util.combined_non_singular_hint(
          linop_diag, linop_triangular),
      # This is safe to do since the Triangular matrix is only self-adjoint
      # when it is a diagonal matrix, and hence commutes.
      is_self_adjoint=registrations_util.combined_commuting_self_adjoint_hint(
          linop_diag, linop_triangular),
      is_positive_definite=None,
      is_square=True)
def _matmul_linear_operator_diag(linop_a, linop_b):
  return linear_operator_diag.LinearOperatorDiag(
      diag=linop_a.diag * linop_b.diag,
      is_non_singular=registrations_util.combined_non_singular_hint(
          linop_a, linop_b),
      is_self_adjoint=registrations_util.combined_commuting_self_adjoint_hint(
          linop_a, linop_b),
      is_positive_definite=(
          registrations_util.combined_commuting_positive_definite_hint(
              linop_a, linop_b)),
      is_square=True)
def _matmul_linear_operator_diag_scaled_identity_left(
    linop_scaled_identity, linop_diag):
  return linear_operator_diag.LinearOperatorDiag(
      diag=linop_diag.diag * linop_scaled_identity.multiplier,
      is_non_singular=registrations_util.combined_non_singular_hint(
          linop_diag, linop_scaled_identity),
      is_self_adjoint=registrations_util.combined_commuting_self_adjoint_hint(
          linop_diag, linop_scaled_identity),
      is_positive_definite=(
          registrations_util.combined_commuting_positive_definite_hint(
              linop_diag, linop_scaled_identity)),
      is_square=True)
def _matmul_linear_operator_scaled_identity(linop_a, linop_b):
  """Matmul of two ScaledIdentity `LinearOperators`."""
  return linear_operator_identity.LinearOperatorScaledIdentity(
      num_rows=linop_a.domain_dimension_tensor(),
      multiplier=linop_a.multiplier * linop_b.multiplier,
      is_non_singular=registrations_util.combined_non_singular_hint(
          linop_a, linop_b),
      is_self_adjoint=registrations_util.combined_commuting_self_adjoint_hint(
          linop_a, linop_b),
      is_positive_definite=(
          registrations_util.combined_commuting_positive_definite_hint(
              linop_a, linop_b)),
      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)
Exemple #8
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def _matmul_linear_operator_circulant_circulant(linop_a, linop_b):
  if not isinstance(linop_a, linop_b.__class__):
    return _matmul_linear_operator(linop_a, linop_b)

  return linop_a.__class__(
      spectrum=linop_a.spectrum * linop_b.spectrum,
      is_non_singular=registrations_util.combined_non_singular_hint(
          linop_a, linop_b),
      is_self_adjoint=registrations_util.combined_commuting_self_adjoint_hint(
          linop_a, linop_b),
      is_positive_definite=(
          registrations_util.combined_commuting_positive_definite_hint(
              linop_a, linop_b)),
      is_square=True)