LinearOperator representing the adjoint of another operator.

Inherits From: LinearOperator, Module

This operator represents the adjoint of another operator.

# Create a 2 x 2 linear operator.
operator = LinearOperatorFullMatrix([[1 - i., 3.], [0., 1. + i]])
operator_adjoint = LinearOperatorAdjoint(operator)

==> [[1. + i, 0.]
     [3., 1 - i]]

==> [2, 2]

==> - log(2)

x = ... Shape [2, 4] Tensor
==> Shape [2, 4] Tensor, equal to operator.matmul(x, adjoint=True)


The performance of LinearOperatorAdjoint depends on the underlying operators performance.

Matrix property hints

This LinearOperator is initialized with boolean flags of the form is_X, for X = non_singular, self_adjoint, positive_definite, square. These have the following meaning:

  • If is_X == True, callers should expect the operator to have the property X. This is a promise that should be fulfilled, but is not a runtime assert. For example, finite floating point precision may result in these promises being violated.
  • If is_X == False, callers should expect the operator to not have X.
  • If is_X == None (the default), callers should have no expectation either way.

operator LinearOperator object.
is_non_singular Expect that this operator is non-singular.
is_self_adjoint Expect that this operator is equal to its hermitian transpose.
is_positive_definite Expect that this operator is positive definite, meaning the quadratic form x^H A x has positive real part for all nonzero x. Note that we do not require the operator to be self-adjoint to be positive-definite. See:
is_square Expect that this operator acts like square [batch] matrices.
name A name for this LinearOperator. Default is + "_adjoint".

ValueError If operator.is_non_singular is False.

H Returns the adjoint of the current LinearOperator.

Given A representing this LinearOperator, return A*. Note that calling self.adjoint() and self.H are equivalent.

batch_shape TensorShape of batch dimensions of this LinearOperator.

If this operator acts like the batch matrix A with A.shape = [B1,...,Bb, M, N], then this returns TensorShape([B1,...,Bb]), equivalent to A.shape[:-2]

domain_dimension Dimension (in the sense of vector spaces) of the domain of this operator.

If this operator acts like the batch matrix A with A.shape = [B1,...,Bb, M, N], then this returns N.

dtype The DType of Tensors handled by this LinearOperator.
graph_parents List of graph dependencies of this LinearOperator. (deprecated)




is_square Return True/False depending on if this operator is square.
operator The operator before taking the adj