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:

Anumpy.ndarray or scipy.sparse matrix: 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: Added 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: Added in version 2.0.0.

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

Attributes:

dimsflattentuple

Same as dims but with first dimension flattened (i.e., defined as the product of otherdims).

dimsdflattentuple

Same as dimsd but with first dimension flattened (i.e., defined as the product of otherdims).

reshapebool

Whether to reshape the input prior to applying the matrix A (when otherdims is provided) or not (when otherdims=None).

complexbool

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

dimstuple

Shape of the array after the adjoint, but before flattening.

For example, x_reshaped = (Op.H * y.ravel()).reshape(Op.dims).

dimsdtuple

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

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).

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`()