pylops.signalprocessing.ChirpRadon2Dยถ
- class pylops.signalprocessing.ChirpRadon2D(taxis, haxis, pmax, dtype='float64', name='C')[source]ยถ
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.Radon2Dand a direct inverse method is also available for this implementation.- Parameters:
- taxis
numpy.ndarray Time axis
- haxis
numpy.ndarray Spatial axis
- pmax
numpy.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 Added in version 2.0.0.
Name of operator (to be used by
pylops.utils.describe.describe)
- taxis
- Attributes:
- nh
int Number of samples in spatial axis.
- nt
int Number of samples in time axis.
- dh
float Sampling step in spatial axis.
- dt
float Sampling step in time axis.
- dims
tuple Shape of the array after the adjoint, but before flattening.
For example,
x_reshaped = (Op.H * y.ravel()).reshape(Op.dims).- dimsd
tuple Shape of the array after the forward, but before flattening. In this case, same as
dims.- shape
tuple Operator shape.
- nh
Notes
Refer to [1] for the theoretical and implementation details.
[1]Andersson, F and Robertsson J. โFast \(\tau-p\) transforms by chirp modulationโ, Geophysics, vol 84, NO.1, pp. A13-A17, 2019.
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()