pylops.Roll

class pylops.Roll(N, dims=None, dir=0, shift=1, dtype='float64')[source]

Roll along an axis.

Roll a multi-dimensional array along a specified direction dir for a chosen number of samples (shift).

Parameters:
N : int

Number of samples in model.

dims : list, optional

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

dir : int, optional

Direction along which rolling is applied.

shift : int, optional

Number of samples by which elements are shifted

dtype : str, optional

Type of elements in input array.

Notes

The Roll operator is a thin wrapper around numpy.roll and shifts elements in a multi-dimensional array along a specified direction for a chosen number of samples.

Attributes:
shape : tuple

Operator shape

explicit : bool

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

Methods

__init__(N[, dims, dir, shift, dtype]) 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, densesolver]) Solve the linear problem \(\mathbf{y}=\mathbf{A}\mathbf{x}\).
dot(x) Matrix-matrix or matrix-vector multiplication.
eigs([neigs, symmetric, niter, uselobpcg]) Most significant eigenvalues of linear operator.
matmat(X) Matrix-matrix multiplication.
matvec(x) Matrix-vector multiplication.
rmatmat(X) 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.
trace([neval, method, backend]) Trace of linear operator.
transpose() Transpose this linear operator.

Examples using pylops.Roll