pylops.Zero

class pylops.Zero(N, M=None, forceflat=None, dtype='float64', name='Z')

Zero operator.

Transform model into array of zeros of size \(N\) in forward and transform data into array of zeros of size \(N\) in adjoint.

Parameters

Nint or tuple

Number of samples in data (and model, if M is not provided). If a tuple is provided, this is interpreted as the data (and model) are nd-arrays.

Mint or tuple, optional

Number of samples in model. If a tuple is provided, this is interpreted as the model is an nd-array. Note that when M is a tuple, N must be also a tuple with the same number of elements.

forceflatbool, optional

New in version 2.2.0.

Force an array to be flattened after matvec and rmatvec. Note that this is only required when N and M are tuples (input and output arrays are nd-arrays).

dtypestr, optional

Type of elements in input array.

namestr, optional

New in version 2.0.0.

Name of operator (to be used by pylops.utils.describe.describe)

Notes

An Zero operator simply creates a null data vector \(\mathbf{y}\) in forward mode:

\[\mathbf{0} \mathbf{x} = \mathbf{0}_N\]

and a null model vector \(\mathbf{x}\) in forward mode:

\[\mathbf{0} \mathbf{y} = \mathbf{0}_M\]

Attributes

shapetuple

Operator shape

explicitbool

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

Methods

__init__(N[, M, forceflat, dtype, name])
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.
reset_count()	Reset counters
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()

Examples using pylops.Zero

Zero

Zero