nanoshot-stamp 0.1.0a1

Stereological Tools for Analysis of Microstructural Parameters

STAMP

Stereological Tools for Analysis of Microstructural Parameters

STAMP is a scientific Python package for quantitative 2-D microstructural analysis. It provides tools to load grain or precipitate measurements, apply stereological corrections to recover 3-D size distributions, compute descriptive statistics with confidence intervals, and generate publication-ready figures.

Modules

Module	Purpose
stamp.io	Load CSV, Excel, or TXT/TSV files and MIPAR feature-measurement exports into a pd.DataFrame
stamp.stereo	Stereological corrections: ECD conversion, Fullman (1953) linear intercept, Saltykov/Wicksell (1925/1967) matrix unfolding, two-step lognormal fitting (Lopez-Sanchez & Llana-Funez 2016)
stamp.stats	Descriptive statistics with confidence intervals: arithmetic mean (ASTM E112, GCI, mCox), geometric mean (CLT, Bayesian), median (Hollander–Wolfe), KDE mode, MLE distribution fitting with KS goodness-of-fit
stamp.plot	Publication-ready figures: histogram + KDE, Saltykov dual-panel (frequency + volume CDF), two-step fit with ±3σ band, PDF/CDF profile, Q-Q plot
stamp.pipeline	Batch processing across multiple material states; produces a PipelineResult with per-state statistics, a summary DataFrame, and optional auto-saved box plot and CSV

Installation

pip install nanoshot-stamp

Or with uv:

uv add nanoshot-stamp

Documentation

Full documentation is available at stamp.readthedocs.io.

Citation

If you use STAMP in your research, please cite it:

@software{westraadt_stamp_2026,
  author  = {Westraadt, Johan},
  title   = {STAMP: Stereological Tools for Analysis of Microstructural Parameters},
  year    = {2026},
  url     = {https://github.com/jwestraadt/STAMP},
  license = {MIT}
}

Or use GitHub's Cite this repository button (powered by CITATION.cff).

Contributing

Contributions are welcome! See CONTRIBUTING.md for details.

License

MIT — see LICENSE for details.