modalyzer 1.2.1

Modalyzer: Operational Modal Analysis (OMA) toolkit in Python (EFDD, SSI, PolyMAX, ITD).

Modalyzer

Open‑source Python library for Operational Modal Analysis (OMA) and system identification.
Modalyzer provides multiple algorithms — EFDD/FDD, SSI (cov/data), ITD, and PolyMAX — along with helpers for preprocessing, stabilization diagrams, and drawing mode shapes for common structures.

Status: research code under active revision, shared to accompany an open‑source paper. Interfaces may still evolve.

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Key Features

• Preprocessing: detrend, band‑pass filter, decimate, channel removal, and auto‑sync across channels.
• Frequency Domain Decomposition (EFDD/FDD): PSD SVD, manual peak picking, complex mode shapes, SDOF autocorrelation damping.
• SSI (cov & data variants): state‑space estimation and pole stabilization.
• ITD: fast coarse extraction of poles and damping.
• PolyMAX / p‑LSCF: accurate poles and mode shapes and a stabilization diagram.
• Plots: stabilization diagrams, MAC, and structure‑specific mode‑shape drawings (Farrar 4‑story frame, bridges, etc.).

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Installation

Modalyzer is currently distributed as source. You can install it in editable mode:

# Clone your (test) repository then install locally
git clone https://github.com/<your-username>/modalyzer-test.git
cd modalyzer-test
python -m venv .venv
# Windows PowerShell:
. .venv\\Scripts\\Activate.ps1
pip install -U pip
pip install -e .  # optional; or just run with PYTHONPATH

If you don't have a setup.py/pyproject.toml yet, you can still use it as a plain package by keeping this repo root on your PYTHONPATH or by running examples from the repo root.

Dependencies

The modules use: numpy, pandas, matplotlib, scipy, torch, and optionally plotly. Install them with:

pip install numpy pandas matplotlib scipy torch plotly

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Repository Layout

modalyzer/
├─ src/modalyzer/
│  ├─ Preprocess.py         # preprocess(), choose_modes(), results_table(), etc.
│  ├─ EFDD.py               # FDD_SVD_Diagram(), FDD_ModeShape(), FDD_Damping(), ...
│  ├─ SSI.py                # SSI_COV(), SSI_DATA(), modal_parameters(), Stable_Poles(), stabilization_diagram()
│  ├─ ITD.py                # ITD_alg(), helpers for correlation & poles
│  ├─ PolyMAX.py            # PolyMAX(), independent_mode_shape(), stabilization_diagram(), ...
│  └─ ModeShape.py          # draw_mode_shapes(), draw_MAC_diagram(), structure‑specific plotters
├─ tests/
│  └─ test_basic.py
├─ README.md
├─ LICENSE
└─ AUTHORS.md

Tip: Most core functions accept both numpy arrays and pandas DataFrames; when matrices are in sensor‑by‑time or time‑by‑sensor shape, some functions auto‑transpose to [channels, samples] internally.

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Citing

If this library helps your research, please cite the Modalyzer paper (details will be added once it is published). You can also star the repository to support the project.

A CITATION.cff will be added after publication.

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License

This project is licensed under the terms in LICENSE (e.g., BSD‑3‑Clause or MIT depending on your choice).

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Contributing

Pull requests and issues are welcome. If you plan significant changes, please open an issue to discuss the proposal first.

• Run tests with pytest (to be expanded).
• Follow PEP8/black where possible.
• Please include small reproducible examples when reporting bugs.