data-tools

Command-line tools for data processing, smoothing, onset detection, and visualization in scientific and engineering workflows.

This repository collects small, self-contained Python utilities developed for research data analysis, sensor calibration, and image- or signal-based measurement workflows.

Each tool lives in its own subdirectory with its own documentation, scripts, and examples.

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🔗 Quick links

• pchip-onsets/ PCHIP-based MGI/BW onset analysis workflow with a synthetic RGB-TR example dataset, generated output files, diagnostic plots, and a static offline HTML gallery.

• xy-pchip/ PCHIP-based smoothing/interpolation tools for x-y data.

• Unified Slope-Based Onset Detection/ Earlier slope-based onset detection tools.

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🧩 Key principles

• Reproducible: tools use clear command-line workflows and documented input/output files.
• Lightweight: dependencies are kept minimal where practical.
• Self-contained: tools are organized into separate directories.
• Modular: scripts can be used independently or combined in analysis workflows.
• KISS-oriented: workflows should remain as simple, explainable, and practical as possible.

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📈 PCHIP onset workflow

The newest workflow is available under:

pchip-onsets/

It provides a PCHIP-based onset analysis workflow for MGI/BW cooling datasets.

The workflow starts from:

rgb-tr.csv

and can generate:

rgb-tr-sg.csv
pchip/
bw-pchip-workflow-summary.csv
bw-pchip-workflow-report.txt

The directory includes:

pchip-onsets/
├── README.md
├── requirements.txt
├── docs/
│   └── figures/
├── examples/
│   └── synthetic-rgb-tr/
├── scripts/
└── tests/

The synthetic example is available here:

pchip-onsets/examples/synthetic-rgb-tr/

The example includes synthetic input data, SG-smoothed data, PCHIP workflow outputs, diagnostic plots, and a static offline HTML gallery.

The example data are synthetic demonstration data. They are not experimental results and must not be used for scientific conclusions.

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⚙️ Installation

Create or activate a suitable Python environment and install the required packages for the tool you want to use.

For the PCHIP onset workflow:

cd pchip-onsets
pip install -r requirements.txt

Typical dependencies include:

numpy
pandas
matplotlib
scipy
openpyxl

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📝 Notes

This repository is a practical research-tool collection. Some tools may be more polished than others, depending on their maturity and current use.

For details, see the README.md file inside each tool directory.