pdfanalysis 0.1.0

Automated PDF structure analysis for nanoparticles

PDFanalysis

Automated PDF (Pair Distribution Function) structure analysis for small metallic nanoparticles.

Description

PDFanalysis is a comprehensive Python package for analyzing nanoparticle structures using pair distribution function (PDF) analysis. It provides tools for:

• PDF extraction from experimental data
• Structure generation (icosahedra, decahedra, octahedra, spheres)
• Structure customization (zoomscale, element substitution)
• PDF refinement using diffpy.srfit
• Structure screening against experimental PDFs
• Report generation with detailed analysis results

The recommended workflow for a single pdf is the following:

• Estimation of particle size from experimental pdf data. Determines the r value at which the pdf signal is dominated by noise
• Structure generation: icosahedra, octahedra, spheres and decahedra are generated with the size determined above (or specified by the user)
• Fast structure screening: each structure is roughly refined against experimental data. Best results within a given confidence interval are considered for the fine refinement
• Fine strucutre screening: structures who have passed the first refinement cycle are refined against experimental pdf.

Installation

Install from PyPI (recommended)

pip install pdfanalysis

Install with optional dependencies

# For Streamlit web app
pip install pdfanalysis[app]

# For Jupyter notebooks
pip install pdfanalysis[notebook]

# For development tools
pip install pdfanalysis[dev]

# Install everything
pip install pdfanalysis[all]

Install from source

git clone https://github.com/nicoratel/pdfanalysis.git
cd pdfanalysis
pip install .

Development installation (editable mode)

git clone https://github.com/nicoratel/pdfanalysis.git
cd pdfanalysis
pip install -e .

Dependencies

Core dependencies

• numpy - Numerical computations
• scipy - Scientific computing and optimization
• matplotlib - Plotting and visualization
• ase - Atomic Simulation Environment
• diffpy-cmi - DiffPy suite (structure manipulation + PDF refinement)
• tqdm - Progress bars
• psutil - CPU/memory management

Optional dependencies

• streamlit - Web application framework
• plotly - Interactive plots
• ipython - Enhanced Python shell
• jupyter - Notebook interface
• py3Dmol - 3D molecular visualization

Quick Start

Using the main analysis function

from pdfanalysis import perform_automatic_pdf_analysis

results = perform_automatic_pdf_analysis(
    pdf_file="path/to/data.gr",
    cif_file="path/to/structure.cif",
    r_coh=30.0,  # Coherence length in Angstroms
    tolerance_size_structure=3.0,
    n_spheres=2
)

Using individual classes

from pdfanalysis import (
    PDFExtractor,
    StructureGenerator,
    PDFRefinement,
    StructureScreener
)

# Generate structures
generator = StructureGenerator(
    pdfpath="output_dir",
    cif_file="structure.cif",
    auto_mode=True,
    pdf_file="data.gr"
)
strufile_dir = generator.run()

# Screen structures
screener = StructureScreener(
    strufile_dir=strufile_dir,
    pdffile_dir="pdf_directory",
    fast_screening=True
)
best_results, candidates = screener.run()

# Refine best structure
refinement = PDFRefinement(
    pdffile="data.gr",
    strufile=best_results["data.gr"]["strufile"],
    save_tag=True
)
rw = refinement.refine()

Running the Streamlit app

After installing with the app extras:

streamlit run app_pdf_analysis.py

Package Structure

app_pdf_analysis.py             # Streamlit web interface
pdfanalysis/
├── __init__.py                      # Package initialization
├── pdf_extractor.py                 # PDF extraction from experimental data
├── structure_generator.py           # Nanoparticle structure generation
├── structure_custom.py              # Structure transformation
├── structure_report_generator.py    # PDF report generation
├── pdf_refinement.py               # Full PDF refinement
├── pdf_refinement_fast.py          # Fast refinement for screening
├── structure_screener.py           # Structure screening
├── pdfanalysis.py                  # Main analysis workflow

Features

Automatic Structure Generation

• Auto-detection of coherence length from PDF
• Multiple structure types: icosahedra, decahedra, octahedra, spheres
• Parallel processing for fast generation
• Automatic filtering based on size range

Fast Screening

• Two-pass screening: fast initial screening + full refinement
• Automatic candidate selection (min(Rw) ± threshold%)
• Progress tracking with tqdm
• Multiprocessing support

Comprehensive Reports

• PDF reports with fit curves, structure thumbnails
• Top N results tables
• 3D structure visualizations
• Complete refinement statistics

Examples

See the examples/ directory for Jupyter notebooks demonstrating:

• Basic PDF analysis workflow
• Custom structure generation
• Advanced refinement options
• Batch processing

Citation

If you use this package in your research, please cite:

@software{pdfanalysis,
  author = {Ratel-Ramond, Nicolas},
  title = {PDFanalysis: Automated PDF structure analysis for nanoparticles},
  year = {2026},
  url = {https://github.com/nicoratel/pdfanalysis}
}

License

MIT License - see LICENSE file for details

Contributing

Contributions are welcome! Please:

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests if applicable
5. Submit a pull request

Support

For bugs and feature requests, please open an issue on GitHub: https://github.com/nicoratel/pdfanalysis/issues

Acknowledgments

This package uses:

• DiffPy-CMI for PDF refinement
• ASE for structure manipulation
• The Scientific Python ecosystem (NumPy, SciPy, Matplotlib)