pylops.signalprocessing.Bilinear¶
-
class
pylops.signalprocessing.
Bilinear
(iava, dims, dtype='float64')[source]¶ Bilinear interpolation operator.
Apply bilinear interpolation onto fractionary positions
iava
along the first two axes of a n-dimensional array.Note
The vector
iava
should contain unique pais. If the same pair is repeated twice an error will be raised.Parameters: - iava :
list
ornumpy.ndarray
Array of size \([2 \times n_\text{ava}]\) containing pairs of floating indices of locations of available samples for interpolation.
- dims :
list
Number of samples for each dimension
- dtype :
str
, optional Type of elements in input array.
Raises: - ValueError
If the vector
iava
contains repeated values.
Notes
Bilinear interpolation of a subset of \(N\) values at locations
iava
from an input n-dimensional vector \(\mathbf{x}\) of size \([m_1 \times m_2 \times ... \times m_{ndim}]\) can be expressed as:\[y_{\mathbf{i}} = (1-w^0_{i}) (1-w^1_{i}) x_{l^{l,0}_i, l^{l,1}_i} + w^0_{i} (1-w^1_{i}) x_{l^{r,0}_i, l^{l,1}_i} + (1-w^0_{i}) w^1_{i} x_{l^{l,0}_i, l^{r,1}_i} + w^0_{i} w^1_{i} x_{l^{r,0}_i, l^{r,1}_i} \quad \forall i=1,2,\ldots,M\]where \(\mathbf{l^{l,0}}=[\lfloor l_1^0 \rfloor, \lfloor l_2^0 \rfloor, ..., \lfloor l_N^0 \rfloor]\), \(\mathbf{l^{l,1}}=[\lfloor l_1^1 \rfloor, \lfloor l_2^1 \rfloor, ..., \lfloor l_N^1 \rfloor]\), \(\mathbf{l^{r,0}}=[\lfloor l_1^0 \rfloor + 1, \lfloor l_2^0 \rfloor + 1, ..., \lfloor l_N^0 \rfloor + 1]\), \(\mathbf{l^{r,1}}=[\lfloor l_1^1 \rfloor + 1, \lfloor l_2^1 \rfloor + 1, ..., \lfloor l_N^1 \rfloor + 1]\), are vectors containing the indices of the original array at which samples are taken, and \(\mathbf{w^j}=[l_1^i - \lfloor l_1^i \rfloor, l_2^i - \lfloor l_2^i \rfloor, ..., l_N^i - \lfloor l_N^i \rfloor]\) (\(\forall j=0,1\)) are the bilinear interpolation weights.
Attributes: Methods
__init__
(iava, dims[, 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. - iava :