pylops_gpu.signalprocessing.Convolve1D

class pylops_gpu.signalprocessing.Convolve1D(N, h, offset=0, dims=None, dir=0, zero_edges=False, device='cpu', togpu=(False, False), tocpu=(False, False), dtype=torch.float32)

1D convolution operator.

Apply one-dimensional convolution with a compact filter to model (and data) along a specific direction of a multi-dimensional array depending on the choice of dir.

Parameters:

N : int

Number of samples in model.

h : torch.Tensor or numpy.ndarray

1d compact filter to be convolved to input signal

offset : int

Index of the center of the compact filter

dims : tuple

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

dir : int, optional

Direction along which convolution is applied

zero_edges : bool, optional

Zero output at edges (True) or not (False)

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.signalprocessing.Convolve1D 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__(N, h[, offset, dims, dir, …])	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.
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.

Examples using pylops_gpu.signalprocessing.Convolve1D

Convolution

FISTA