class pylops.VStack(ops, nproc=1, dtype=None)[source]

Vertical stacking.

Stack a set of N linear operators vertically.

ops : list

Linear operators to be stacked. Alternatively, numpy.ndarray or scipy.sparse matrices can be passed in place of one or more operators.

nproc : int, optional

Number of processes used to evaluate the N operators in parallel using multiprocessing. If nproc=1, work in serial mode.

dtype : str, optional

Type of elements in input array.


If ops have different number of rows


A vertical stack of N linear operators is created such as its application in forward mode leads to

\[\begin{split}\begin{bmatrix} \mathbf{L}_{1} \\ \mathbf{L}_{2} \\ \vdots \\ \mathbf{L}_{N} \end{bmatrix} \mathbf{x} = \begin{bmatrix} \mathbf{L}_{1} \mathbf{x} \\ \mathbf{L}_{2} \mathbf{x} \\ \vdots \\ \mathbf{L}_{N} \mathbf{x} \end{bmatrix} = \begin{bmatrix} \mathbf{y}_{1} \\ \mathbf{y}_{2} \\ \vdots \\ \mathbf{y}_{N} \end{bmatrix}\end{split}\]

while its application in adjoint mode leads to

\[\begin{split}\begin{bmatrix} \mathbf{L}_{1}^H & \mathbf{L}_{2}^H & \ldots & \mathbf{L}_{N}^H \end{bmatrix} \begin{bmatrix} \mathbf{y}_{1} \\ \mathbf{y}_{2} \\ \vdots \\ \mathbf{y}_{N} \end{bmatrix} = \mathbf{L}_{1}^H \mathbf{y}_1 + \mathbf{L}_{2}^H \mathbf{y}_2 + \ldots + \mathbf{L}_{N}^H \mathbf{y}_N\end{split}\]
shape : tuple

Operator shape

explicit : bool

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


__init__(ops[, nproc, 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.