pylops.signalprocessing.ChirpRadon2D#
- class pylops.signalprocessing.ChirpRadon2D(taxis, haxis, pmax, dtype='float64', name='C')[source]#
2D Chirp Radon transform
Apply Radon forward (and adjoint) transform using Fast Fourier Transform and Chirp functions to a 2-dimensional array of size \([n_x \times n_t]\) (both in forward and adjoint mode).
Note that forward and adjoint are swapped compared to the time-space implementation in
pylops.signalprocessing.Radon2D
and a direct inverse method is also available for this implementation.- Parameters
- taxis
np.ndarray
Time axis
- haxis
np.ndarray
Spatial axis
- pmax
np.ndarray
Maximum slope defined as \(\tan\) of maximum stacking angle in \(x\) direction \(p_\text{max} = \tan(\alpha_{x, \text{max}})\). If one operates in terms of minimum velocity \(c_0\), set \(p_{x, \text{max}}=c_0 \,\mathrm{d}y/\mathrm{d}t\).
- dtype
str
, optional Type of elements in input array.
- name
str
, optional New in version 2.0.0.
Name of operator (to be used by
pylops.utils.describe.describe
)
- taxis
Notes
Refer to [1] for the theoretical and implementation details.
- 1
Andersson, F and Robertsson J. “Fast \(\tau-p\) transforms by chirp modulation”, Geophysics, vol 84, NO.1, pp. A13-A17, 2019.
- Attributes
Methods
__init__
(taxis, haxis, pmax[, 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.
inverse
(x)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
()