AIMBAT

Automated and Interactive Measurement of Body wave Arrival Times

Documentation: https://aimbat.pysmo.org

Source Code: https://github.com/pysmo/aimbat

AIMBAT (Automated and Interactive Measurement of Body wave Arrival Times) is an open-source tool for measuring teleseismic body wave arrival times. Seismograms are automatically aligned using the ICCS [Iterative Cross-Correlation and Stack]¹ algorithm; picks are then reviewed and refined interactively before a final MCCC (Multi-Channel Cross-Correlation) ² pass computes the definitive arrival times.

Version 2

AIMBAT v2 is a complete rewrite. It shares the same goal as v1 but none of the code. The main improvements for users are:

• Flexible workflow. Snapshots save the complete processing state at any point, making it straightforward to roll back, compare parameter sets, or try a different approach without losing prior work. ICCS and MCCC can be run in any order and as many times as needed; results can be exported from any snapshot, not only after a final MCCC pass.
• Multi-event projects. A single project database holds any number of seismic events. Waveform files can live anywhere on disk — no prescribed directory layout and no need to manage separate directories per event.
• Structured output for downstream analysis. Each snapshot can be exported as a structured JSON document containing per-station arrival times, ICCS correlation coefficients, and — if MCCC has been run — formal timing standard errors. This makes AIMBAT useful as a data source beyond tomographic inversion: station quality assessment, delay patterns as a function of back-azimuth, or any workflow that requires picks and quality metrics in a machine-readable format.
• Multiple interfaces. AIMBAT can be used via a CLI, an interactive shell, a terminal UI, or directly as a Python library. All functionality is accessible through the Python API, making it straightforward to script any part of the workflow.

Quick Start

pip install aimbat

# Create a project in the current directory
aimbat project create

# Import SAC files — events and stations are detected automatically
aimbat data add *.sac

# List events to find their IDs, then set one as the default
aimbat event list
aimbat event default <ID>

# Open the terminal UI to run ICCS, review picks, and run MCCC
aimbat tui

# Or work interactively from the shell (tab-completion, command history)
aimbat shell

Authors' Contacts

• Xiaoting Lou — xlou at u.northwestern.edu
• Suzan van der Lee — suzan at northwestern.edu
• Simon Lloyd — simon at pysmo.org