Compressed sensing reconstruction of sparse geophysical data: An example from regional magnetics

This folder contain archived data to accompany the paper "Compressed sensing reconstruction of sparse geophysical data: An example from regional magnetics" published in Exploration Geophysics, 2023, by C O'Neill.

The archive contains

1) Two files (CS_OWLQN_oneill_modded_code4aeromag.py and CS_wavelets_code4aeromag.py) that reconstruct aeromagnetic data using compressed sensing techniques described in the paper (an OWLQN minimization using DCT, and a wavelet transform approach with soft-thresholding). Full references for these codes are in the paper, and follow Taylor (2016) and Lustig (2007).

2) Three Jupyter notedbooks are included, which can reproduce Figure 1 (Figure1_1D_CompSens.ipynb), Figure 6/8 results (plot_spectrum_aeromag.ipynb), Figure 9 (pyGMT_minCurv_plots.ipynb).

3) Supplementary data files including the cropped ascii aeromagnetic data used in the CS reconstructions (DATA_mag_cropped.dat, and DATA_line_data.npy in npy format), as well as gridded output examples that may be used in the plotting/spectral analysis scripts, including DATA_Min_Curv2.npy (minimum curvature results), DATA_NN2.npy (nearest neighbour results), DATA_processed_CS_output_2.npy (OWLQN CS reconstruction), and DATA_waveltCS_2_4000.npy (Wavelet CS reconstruction). These data form the basis of Figure 9 in the paper.