A beginner friendly Python package for learning distributed acoustic sensing (DAS). It takes a student from an unfamiliar DAS array to a documented, reproducible first experiment, using synthetic data and a real ocean cable example from the Ocean Observatories Initiative.
Status: early release (v0.1.0). The tools and tutorials below work. Whale detection and localization are not part of this package yet.
- Installs as a modern
srclayout Python package. - Generates a deterministic, explicitly synthetic time and distance array.
- Summarizes array shape, duration, distance span, memory, data type, mean, standard deviation, frequency resolution, and invalid values.
- Downloads a small, real, checksum verified OOI example file, with size limits, caching, and a provenance manifest.
- Reads a bounded subset of channels from a real Silixa TDMS file into a NumPy array (
read_tdms_subset, with a 500 MiB safety limit). - Converts arrays into DASCore Patch objects, so DASCore tools like
pass_filterwork on this project's data. - Includes four tutorials, unit tests, and continuous integration.
01_inspect_synthetic_data.py: what DAS data is and how to read an array summary.02_from_array_to_visible_signal.py: waterfall plots and filtering on synthetic data.03_design_a_small_project.py: recording a reproducible project.04_real_data_first_look.py: a first look at real measured OOI data (an instrument noise check, not a