# pylops.MatrixMult#

class pylops.MatrixMult(A, otherdims=None, forceflat=None, dtype='float64', name='M')[source]#

Matrix multiplication.

Simple wrapper to numpy.dot and numpy.vdot for an input matrix $$\mathbf{A}$$.

Parameters
A

Matrix.

otherdimstuple, optional

Number of samples for each other dimension of model (model/data will be reshaped and A applied multiple times to each column of the model/data).

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 otherdims=None, otherwise pylops will detect whether to return a 1d or nd array.

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)

Attributes
dimsdtuple

Shape of the array after the forward, but before linearization.

For example, y_reshaped = (Op * x.ravel()).reshape(Op.dimsd).

shapetuple

Operator shape

explicitbool

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

complexbool

Matrix has complex numbers (True) or not (False)

Methods

 __init__(A[, otherdims, 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. inv() Return the inverse of $$\mathbf{A}$$. 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.MatrixMult#

CGLS and LSQR Solvers

CGLS and LSQR Solvers

Describe

Describe

MP, OMP, ISTA and FISTA

MP, OMP, ISTA and FISTA

Matrix Multiplication

Matrix Multiplication

Operators concatenation

Operators concatenation

Operators with Multiprocessing

Operators with Multiprocessing

Restriction and Interpolation

Restriction and Interpolation

02. The Dot-Test

02. The Dot-Test

03. Solvers

03. Solvers

07. Post-stack inversion

07. Post-stack inversion

08. Pre-stack (AVO) inversion

08. Pre-stack (AVO) inversion

17. Real/Complex Inversion

17. Real/Complex Inversion

19. Automatic Differentiation

19. Automatic Differentiation