sans-webapp 0.0.3

A webapp for SANS data fitting using SANS-fitter module.

SANS Model Fitter

SANS-webapp

A Streamlit-based web application is now available for interactive SANS data analysis with a user-friendly interface.

Features

• 📤 Data Upload: Upload your SANS datasets (CSV or .dat files)
• 🤖 AI-Assisted Model Selection: Get intelligent model suggestions based on your data
• 🎯 Manual Model Selection: Choose from all available SasModels
• ⚙️ Interactive Parameter Tuning: Adjust parameters with real-time UI controls
• 📊 Interactive Plots: Visualize data and fits with Plotly's zoom, pan, and export features
• 💾 Export Results: Save fitted parameters and curves to CSV

Quick Start (Web App)

# Install the application
pip install -e .

# Run the Streamlit app (choose one)
sans-webapp              # CLI command
python -m sans_webapp    # Module execution

The app will open in your browser at http://localhost:8501.

Install from PyPI

pip install sans-webapp
sans-webapp

Using the Web Application

1. Upload Data: Use the sidebar to upload your SANS data file (CSV or .dat format with Q, I, dI columns) or load the example dataset
2. Select Model:
   • Manual: Choose from dropdown of all SasModels models
   • AI-Assisted: Optionally provide an Anthropic (Claude) API key for AI-powered suggestions and MCP tool access, or use built-in heuristics
3. Configure Parameters: Set initial values, bounds, and which parameters to fit
4. Run Fit: Choose optimization engine (BUMPS or LMFit) and method, then click "Run Fit"
5. View Results: Interactive plots show data with error bars and fitted curve
6. Export: Download fitted parameters as CSV

Web App Deployment

Streamlit Cloud

1. Push this repository to GitHub
2. Go to share.streamlit.io
3. Connect your GitHub account and deploy from the repository
4. Set src/sans_webapp/app.py as the main file

Heroku

# The Procfile is already configured
# Deploy directly
heroku create your-app-name
git push heroku main

Docker

# Build image
docker build -t SANS-webapp-app .

# Run container
docker run -p 8501:8501 SANS-webapp-app

API Integration

The web app supports optional AI-powered model suggestions and MCP tool usage via Anthropic (Claude):

1. Get an API key from Anthropic (https://console.anthropic.com/)
2. Enter the key in the sidebar when using AI-Assisted mode
3. Or set as environment variable: export ANTHROPIC_API_KEY=your-key-here

Note: The app also works without an API key using built-in heuristic suggestions.

License

BSD 3-Clause License. See LICENSE for the full text.

References

• SasModels: https://github.com/SasView/sasmodels
• BUMPS: https://github.com/bumps/bumps
• LMFit: https://lmfit.github.io/lmfit-py/
• Streamlit: https://streamlit.io
• Plotly: https://plotly.com/python/