pylops_gpu.Diagonal

class pylops_gpu.Diagonal(diag, dims=None, dir=0, device='cpu', togpu=(False, False), tocpu=(False, False), dtype=torch.float32)

Diagonal operator.

Applies element-wise multiplication of the input vector with the vector diag in forward and with its complex conjugate in adjoint mode.

This operator can also broadcast; in this case the input vector is reshaped into its dimensions dims and the element-wise multiplication with diag is perfomed on the direction dir. Note that the vector diag will need to have size equal to dims[dir].

Parameters:

diag : numpy.ndarray or torch.Tensor or pytorch_complex_tensor.ComplexTensor

Vector to be used for element-wise multiplication.

dims : list, optional

Number of samples for each dimension (None if only one dimension is available)

dir : int, optional

Direction along which multiplication is applied.

device : str, optional

Device to be used

togpu : tuple, optional

Move model and data from cpu to gpu prior to applying matvec and rmatvec, respectively (only when device='gpu')

tocpu : tuple, optional

Move data and model from gpu to cpu after applying matvec and rmatvec, respectively (only when device='gpu')

dtype : torch.dtype, optional

Type of elements in input array.

Notes

Refer to pylops.basicoperators.Diagonal for implementation details.

Attributes:

shape : tuple

Operator shape

explicit : bool

Operator contains a matrix that can be solved explicitly (True) or not (False)

Methods

__init__(diag[, dims, dir, device, togpu, …])	Initialize this LinearOperator.
adjoint()	Hermitian adjoint.
apply_columns(cols)	Apply subset of columns of operator
cond([uselobpcg])	Condition number of linear operator.
conj()	Complex conjugate operator
div(y[, niter, tol])	Solve the linear problem \(\mathbf{y}=\mathbf{A}\mathbf{x}\).
dot(x)	Matrix-vector multiplication.
eigs([neigs, symmetric, niter, uselobpcg])	Most significant eigenvalues of linear operator.
matmat(X[, kfirst])	Matrix-matrix multiplication.
matrix()	Return diagonal matrix as dense torch.Tensor
matvec(x)	Matrix-vector multiplication.
rmatmat(X[, kfirst])	Adjoint matrix-matrix multiplication.
rmatvec(x)	Adjoint matrix-vector multiplication.
todense([backend])	Return dense matrix.
toimag([forw, adj])	Imag operator
toreal([forw, adj])	Real operator
tosparse()	Return sparse matrix.
transpose()	Transpose this linear operator.

matrix()

Return diagonal matrix as dense torch.Tensor

Returns:

densemat : torch.Tensor

Dense matrix.

Examples using pylops_gpu.Diagonal

Diagonal