array_processing.tools.detection module

array_processing.tools.detection.calculate_semblance(data_in)[source]

Calculates the semblance, a measure of multi-channel coherence, following the definition of Neidell & Taner (1971). Assumes data are already time-shifted to construct the beam.

Parameters:

data_in – Time-shifted ObsPy Stream or time-shifted NumPy array

Returns:

Multi-channel coherence defined on \([0, 1]\)

array_processing.tools.detection.fstatbland(dtmp, fs, tau)[source]

Calculates the F-statistic and SNR based on Blandford’s method (see Notes).

Parameters:

  • dtmp – (m, n) array; time series with m samples from n traces as columns

  • fs (int or float) – Sample rate [Hz]

  • tau – (n(n-1)//2) array; time delays of relative signal arrivals (TDOA) for all unique sensor pairings

Returns:

Tuple containing:

  • fstat – F-statistic

  • snr – SNR

Return type:

tuple

References

Blandford, R. R., 1974. An automatic event detector at the Tonto Forest Seismic Observatory. Geophysics, vol. 39, no. 5, p. 633–643. https://library.seg.org/doi/abs/10.1190/1.1440453