das-nidf 1.0.2

Distributed Acoustic Sensing Processing and Data Visualization Library

DAS_NIDF - Distributed Acoustic Sensing Data Visualization

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Overview

DAS_NIDF is a comprehensive Python library for visualizing and analyzing Distributed Acoustic Sensing (DAS) data. It provides interactive, high-performance visualization tools using Holoviews + Datashader, capable of handling billions of data points.

Developed exclusively for internal use by the Núcleo Interdisciplinar de Dinâmica dos Fluidos (NIDF).

Restricted Use Notice: This package was created specifically for research and technical activities within NIDF and is not intended for public or commercial use.

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Features

• Interactive Waterfall Plots - Real-time zoom, pan, and hover
• Spectrogram Analysis - Integrated band power maps
• Frequency-Wavenumber (f-k) Analysis - 2D FFT for wavefield analysis
• ROI Analysis - Region of Interest extraction and visualization
• Customizable Colormaps - Viridis, Plasma, and more
• High Performance - Datashader rendering for large datasets
• Interactive Dashboard - All plots combined in a single HTML page
• Complete Processing Pipeline - From HDF5 to visualization

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Installation

From PyPI (authorized internal users only)

pip install das-nidf

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Dependencies

Automatically installed with the package:

• numpy >= 1.20.0
• scipy >= 1.7.0
• h5py >= 3.0.0
• holoviews >= 1.15.0
• datashader >= 0.14.0
• bokeh >= 2.4.0
• scikit-image >= 0.19.0

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🚀 Quick Start

from DAS_NIDF import run_server
run_server()

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📖 Detailed Usage

1. Complete Processing Pipeline

The process_full_pipeline() method handles:

• Reads HDF5 file
• Extracts metadata (fs, dx, num_locs)
• Applies temporal cutting
• Removes DC mean
• Applies bandpass filter

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🔒 License / Usage Policy

This software is intended solely for internal academic and technical use within NIDF. Redistribution, resale, external deployment, or unauthorized modification may be restricted.

For access requests or collaboration inquiries, please contact the maintainers.

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🌟 Acknowledgments

• HoloViz team for Holoviews and Datashader
• Bokeh team for interactive visualization
• NIDF and LPS - UFRJ for research support