Python codes to compare the retrieval of impulse response functions with different methods (Viens et al., 2017, GJI)

Description:

This repository contains the functions used in Viens et al. (2017) along with an example.

This repository contains:

• Codes folder:
  • Functions_GJI_2017.py: Functions to compute cross-correlation, deconvolution, coherency of raw data, and cross-correlation of 1-bit data.
  • Interferometry.py: runs the different techniques on 1 day of data recorded at "station_1" and "station_2".
• Data folder:
  • station_1_1d.sac: 1 day of vertical data with a sampling rate of 4 Hz at station 1.
  • station_2_1d.sac: 1 day of vertical data with a sampling rate of 4 Hz at station 2.
• Figures folder:
  • Foo.png: Figure generated by Interferometry.py.

In this example, Station 1 and Station 2 are two MeSO-net stations located in the Kanto region, Japan. The distance between the two stations is 8.26 km. Therefore, the waves observed in the causal (positive) part between ~10 and 25 s in the figure below are likely Rayleigh waves. Note that the anti-causal (negative) and causal parts are strongly asymmetric due to the station locations, with Station 1 being closer to the Pacific Ocean than Station 2. Spurious arrivals near the zero time-lag can also be observed and disappear when the correlation functions are stacked over a longer time period.