class pylops.signalprocessing.ChirpRadon3D(taxis, hyaxis, hxaxis, pmax, engine='numpy', dtype='float64', **kwargs_fftw)[source]

Apply Radon forward (and adjoint) transform using Fast Fourier Transform and Chirp functions to a 3-dimensional array of size $$[n_y \times n_x \times n_t]$$ (both in forward and adjoint mode).

Note that forward and adjoint are swapped compared to the time-space implementation in pylops.signalprocessing.Radon3D and a direct inverse method is also available for this implementation.

Parameters: taxis : np.ndarray Time axis hxaxis : np.ndarray Fast patial axis hyaxis : np.ndarray Slow spatial axis pmax : np.ndarray Two element array $$(p_{y,max}, p_{x,max})$$ of $$\tan$$ of maximum stacking angles in $$y$$ and $$x$$ directions $$(\tan(\alpha_{y,max}), \tan(\alpha_{x,max}))$$. If one operates in terms of minimum velocity $$c_0$$, then $$p_{y.max}=c_0dy/dt$$ and $$p_{x,max}=c_0dx/dt$$ engine : str, optional Engine used for fft computation (numpy or fftw) dtype : str, optional Type of elements in input array. **kwargs_fftw Arbitrary keyword arguments for pyfftw.FTTW (reccomended: flags=('FFTW_ESTIMATE', ), threads=NTHREADS)

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: shape : tuple Operator shape explicit : bool Operator contains a matrix that can be solved explicitly (True) or not (False)

Methods

 __init__(taxis, hyaxis, hxaxis, pmax[, …]) 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]) 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. 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.