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pydvma

A Python package for dynamics and vibration measurements and analysis.

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About

pydvma is a modular library for data measurement and analysis in the context of dynamics and vibration, developed at the University of Cambridge Department of Engineering. It's designed for use in student laboratory experiments and research projects.

Key features:

  • Data acquisition via soundcards or National Instruments DAQs
  • Pre-trigger recording and PC-generated output stimulus for impulse/transfer-function measurements
  • FFT, transfer functions, coherence, and spectrograms (STFT and CWT)
  • Modal analysis tools (mode-fitting, damping estimation)
  • A browser-based web logger with a live oscilloscope, analysis and modal-fitting views
  • Export to .dvma, MATLAB and CSV; theme-invariant figure export (PNG/PDF)

The interactive interface is now the web logger, which runs in three modes over one shared analysis engine:

Mode Open it Install
Pages app — analysis of saved files + soundcard capture torebutlin.github.io/pydvma/app/ none
Local bridge — the same app driving real hardware (soundcard or NI-DAQ) pydvma-serve --open pip install "pydvma[serve,soundcard]"
JupyterLite — import pydvma in a browser notebook torebutlin.github.io/pydvma/lite/ none

The earlier desktop Qt logger GUI has been removed now that the web logger has full parity (its last version is the qt-final git tag).

Quick Start

Analyse or measure in the browser with no install — open the Pages app and drag in a .dvma, .npy or .mat file, or capture from a soundcard.

To drive real hardware (soundcard or NI-DAQ) from the same app on your own machine:

pip install "pydvma[serve,soundcard]"   # add [ni] for National Instruments
pydvma-serve --open                     # serves the app + bridge, opens a browser

[serve] on its own installs only the bridge itself — name the backends you need alongside it (soundcard, ni), or use pydvma[full] for both.

To script analysis and acquisition in Python:

import pydvma as dvma

dataset = dvma.load_data('measurement.dvma')   # or record with log_data
freq = dvma.calculate_fft(dataset.time_data_list[0])

Plain pip install pydvma installs the analysis-only core (data structures, FFT/TF/modal analysis, file I/O) with no hardware dependencies — it runs anywhere, including in-browser under pyodide. Native data format is .dvma (safe, pickle-free); .npy files saved by older versions still load.

Documentation

Full documentation: torebutlin.github.io/pydvma

Contributing

Contributions are welcomed:

  • Report bugs via GitHub Issues
  • Submit pull requests for bug fixes and improvements
  • Contact us for significant changes or new features

See the Contributing Guide for details.

Support & citation

pydvma is free and open for everyone — no features are gated. If it supports your teaching or research, the most valuable thing you can do is cite it. This repository includes a CITATION.cff file, so GitHub's "Cite this repository" button and most reference managers can import the citation directly.

If your institution would like to support continued development, or you would simply like to tell us how you use pydvma, get in touch: tb267@cam.ac.uk. See the Support & citation page for details (a DOI will follow via Zenodo once a release is archived).

License

BSD 3-Clause License - see LICENSE for details.

Metadata

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