Metadata-Version: 2.5
Name: das-student-lab
Version: 0.1.0
Summary: Starter scaffold for beginner-facing Distributed Acoustic Sensing education
Project-URL: Dataset, https://doi.org/10.58046/5J60-FJ89
Project-URL: Documentation, https://github.com/dabidolee/DAS-Student-Lab
Project-URL: Repository, https://github.com/dabidolee/DAS-Student-Lab
Author-email: David Lee <davidtimberwolvesfan@gmail.com>
License-Expression: MIT
License-File: LICENSE
License-File: LICENSE_DECISION.md
Keywords: distributed acoustic sensing,education,scientific python
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Topic :: Education
Classifier: Topic :: Scientific/Engineering
Requires-Python: >=3.10
Requires-Dist: numpy>=1.26
Provides-Extra: dev
Requires-Dist: build>=1.2; extra == 'dev'
Requires-Dist: pytest>=8; extra == 'dev'
Requires-Dist: ruff>=0.9; extra == 'dev'
Provides-Extra: science
Requires-Dist: das4whales; extra == 'science'
Requires-Dist: dascore>=0.1.20; extra == 'science'
Requires-Dist: matplotlib>=3.8; extra == 'science'
Requires-Dist: nptdms>=1.9; extra == 'science'
Requires-Dist: scipy>=1.12; extra == 'science'
Description-Content-Type: text/markdown

# DAS Student Lab — Starter Repository

> Working scaffold for David Lee. This is not a finished scientific package.

DAS Student Lab is a proposed beginner-facing Python package for learning how to inspect DAS arrays, use safely sized examples, preserve data provenance, and begin reproducible experiments with established DAS tools.

## What this package already does

- Installs as a modern `src/`-layout Python package, published to TestPyPI.
- Generates a deterministic, explicitly synthetic time-distance array.
- Summarizes array shape, duration, distance span, memory, dtype, mean, standard deviation, frequency resolution, and invalid values.
- Downloads a small, real, checksum-verified OOI example file, with size limits, caching, and a full provenance manifest.
- Reads a bounded subset of a real Silixa TDMS file into a numpy array.
- Converts arrays into DASCore Patch objects, so DASCore's own processing tools (like `pass_filter`) work on this project's data.
- Includes four tutorials: what DAS data is, waterfall visualization and filtering on synthetic data, recording a reproducible project, and a first look at real measured data.
- Includes baseline unit tests, all currently passing, and continuous-integration configuration.
- Includes persistent AI-assistant instructions and research/decision logs.

## What is deliberately not implemented

- Whale detection, matched filtering, moveout fitting, or localization.
- Claims that the synthetic generator is a validated acoustic-propagation model.
- A final package name, license, institutional affiliation, or publication claim.

David should design and implement those pieces incrementally after reviewing existing tools and consulting Dr. Park.

## Setup

Windows PowerShell:

```powershell
py -m venv .venv
.venv\Scripts\Activate.ps1
python -m pip install --upgrade pip
python -m pip install -e ".[dev]"
python -m pytest
```

macOS/Linux:

```bash
python3 -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade pip
python -m pip install -e ".[dev]"
python -m pytest
```

Run the small command-line status report:

```bash
das-student-lab info
```

Run the first tutorial as a Python script:

```bash
python tutorials/01_inspect_synthetic_data.py
```

## Read before developing

1. `CLAUDE.md` or `AGENTS.md`
2. `docs/architecture.md`
3. `docs/related-work.md`
4. `docs/decision-log.md`
5. `docs/research-log.md`
6. `tests/TODO_TESTS.md`

## Required data citation

Wilcock, W., & Ocean Observatories Initiative. (2023). *Rapid: A Community Test of Distributed Acoustic Sensing on the Ocean Observatories Initiative Regional Cabled Array* [Data set]. Ocean Observatories Initiative. https://doi.org/10.58046/5J60-FJ89

This repository is not affiliated with or endorsed by OOI, the University of Washington, WHOI, DASCore, or DAS4Whales.

