Table of Contents

• Python NSNSD Acoustic Monitoring Toolbox (AMT)
• Prepare your machine
  • Prerequisites
  • One-time setup
  • Pulling updates
• Scripts
• Sound Level Meters
• Acknowledgments

Python NSNSD Acoustic Monitoring Toolbox (AMT)

This repository mirrors the NSNSD Acoustic Monitoring Toolbox (AMT) — originally a C# application used to process, visualize, and summarize acoustic data. These tools port core AMT workflows to Python for easier maintenance and updates.

This mostly replaces the Type1-821envtools repository. That toolbox was meant to transition 821 and HOBO data into AMT, which required reformatting raw data before AMT could use it. AMT2PY avoids that extra step by:

1. Creating NVSPL (NPS/Volpe Transportation Center Sound Pressure Level) files in Python instead of inside AMT
2. Supporting more flexible wind-data merge (timestep and formatting) during NVSPL conversion

Type 1 (821‑ENV) processing — start here: docs/821/pipeline.md

Downloading field data from the SLM, wind logger, and Song Meter → docs/821/data-download.md.

Legacy Model 831 workflow: docs/831/README.md.

All 821 scripts open a GUI — nothing to edit in the code before running.

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Prepare your machine

Prerequisites

1. Python 3.9++ (Company Portal) - IMPORTANT: On DOI hosts, you may need to launch "Miniforge Prompt" (install miniforge from the company portal if you do not already have it) and run Python commands from there to work smoothly with AppLocker. This approach works as of 2026-09-22.
2. Git (Company Portal)
3. Field data downloaded and organized per docs/821/data-download.md (then process with docs/821/pipeline.md)

One-time setup

1. Open Git Bash or Command Prompt and go where you want the repo:

cd [path to the place where you would like to save the project]

2. Clone the repo and change to its directory:

git clone https://github.com/emeyer34/AMT2PY.git
cd AMT2PY

3. Create and activate a virtual environment:

python -m venv .venv

# Command Prompt
.venv\Scripts\activate

# Git Bash
source .venv/Scripts/activate

4. Install required packages:

python -m pip install --upgrade pip
python -m pip install -r requirements.txt

5. Now you're ready to proceed with the steps in docs/821/pipeline.md! With the environment active, you can run the data processing scripts, for example:

python FeatherMC_combine.py

Pulling updates

cd [path where you have saved the project]
git pull

Re-run pip install -r requirements.txt with the virtual environment activated if dependencies (requirements.txt) changes.

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Scripts

Script	Workflow	Detail
ld821_combine.py	Merge G4 Time History CSVs	docs/821/pipeline.md · docs/821/ld821-combine.md
FeatherMC_combine.py	Combine Feather MC wind logger CSVs	docs/821/pipeline.md · docs/821/feathermc-combine.md
ld821_to_nvspl.py	Combined G4 CSV → hourly NVSPL (optional wind merge)	docs/821/pipeline.md · docs/821/ld821-to-nvspl.md
831Renamer.py	Merge LD831 folders → .831	docs/831/renamer.md
831_to_NVSPL_external_wind_log.py	.831 → NVSPL (+ optional wind CSV)	docs/831/to-nvspl.md

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Sound Level Meters

Both the 821‑ENV and Model 831 are Larson Davis instruments with different download formats and software paths in this repo.

821‑ENV (SoundExpert) — NSNSD’s current Type 1 system (G4 Utility, Feather MC wind, Song Meter audio). Follow docs/821/pipeline.md.

Model 831 — discontinued in 2022; successor is SoundAdvisor 831C. See docs/831/README.md when you still have .831 logger data.

Acknowledgments

• Original AMT C# implementation
• Larson Davis LD831/LD821 data specifications