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---
license: other
license_name: license
license_link: LICENSE
tags:
- medical
- chemistry
- saxs
- small-angle-x-ray-scattering
- nanoparticles
- synthetic-data
- physics-simulation
- materials-science
- scattering
- machine-learning
- deep-learning
pretty_name: SAXS Scattering Curves Dataset
size_categories:
- 100K<n<1M
task_categories:
- tabular-regression
- tabular-classification
---


# πŸ“‘ SAXS Synthetic Scattering Curves Dataset

> **Thousands of physically accurate Small Angle X-ray Scattering (SAXS) curves, generated from rigorous physical models.**

---

## πŸ”¬ What is this dataset?

This dataset provides synthetic **SAXS intensity curves I(q)** generated using validated physical scattering models (via [SASmodels](https://github.com/SasView/sasmodels)), covering a wide range of nanoparticle shapes, materials, sizes, and concentrations.

Each curve is **fully labelled** with its physical parameters, making it immediately usable for:
- Training ML models to **predict nanoparticle parameters from experimental curves**
- **Benchmarking** fitting algorithms
- **Data augmentation** for experimental datasets
- Developing **automated analysis pipelines**

---

## πŸ“Š Sample Visualization
*(See attached figures in the dataset repository)*
---

## πŸ’Ό Versions & Pricing

This page hosts a **free sample** (~100 curves).  
Full commercial versions are available on [Gumroad β†’](https://venon28.gumroad.com/)

| Tier | Curves | Shape | Material | Price |
|---|---|---|---|---|
| **Sample** (this page) | 100 | sphere | ag | Free |
| [ag_sphere](https://venon28.gumroad.com/l/ipyyeu) | 100k | Sphere | Ag | 49€ |
| [au_sphere](https://venon28.gumroad.com/l/bmoiw) | 100k | Sphere | Au | 49€ |
| [sio2_sphere](https://venon28.gumroad.com/l/noathn) | 100k | Sphere | SiO2 | 49€ |
| [latex_sphere](https://venon28.gumroad.com/l/silrpc) | 100k | Sphere | Latex | 49€ |
| [ag_cylinder](https://venon28.gumroad.com/l/veduiq) | 100k | Cylinder | Ag | 49€ |
| [au_cylinder](https://venon28.gumroad.com/l/qikxjv) | 100k | Cylinder | Au | 49€ |
| [sio2_cylinder](https://venon28.gumroad.com/l/imkld) | 100k | Cylinder | SiO2 | 49€ |
| [latex_cylinder](https://venon28.gumroad.com/l/dkepz) | 100k | Cylinder | Latex | 49€ |
| [ag_parallelepiped](https://venon28.gumroad.com/l/vbxbtjm) | 100k | Parallelepiped | Ag | 49€ |
| [au_parallelepiped](https://venon28.gumroad.com/l/mlddye) | 100k | Parallelepiped | Au | 49€ |
| [sio2_parallelepiped](https://venon28.gumroad.com/l/iveenk) | 100k | Parallelepiped | SiO2 | 49€ |
| [latex_parallelepiped](https://venon28.gumroad.com/l/ljdcd) | 100k | Parallelepiped | Latex | 49€ |
| **Custom** | Unlimited | Custom | Custom | On request |


---

## πŸš€ Ploting function exemple

```python
import h5py
import numpy as np
import matplotlib.pyplot as plt

def plotSaxs(h5_path, index_to_plot=0):
    with h5py.File(h5_path, 'r') as f:
        # Extract Data
        q = f.attrs['q']
        intensities = f['intensities'][index_to_plot]
        material = f.attrs.get('material', 'Unknown').upper()
        shape = f.attrs.get('shape', 'Unknown').capitalize()

        # Extract specific metadata for the legend
        params_str = ""
        for k in f.keys():
            if k == 'intensities':
                continue
            val = f[k][index_to_plot]
            params_str += f"{k}: {val:.2f} | "

    # Plotting Setup
    plt.rcParams.update({
        'font.size': 12,
        'axes.labelsize': 14,
        'xtick.labelsize': 12,
        'ytick.labelsize': 12,
        'legend.fontsize': 10,
        'lines.linewidth': 2,
        'figure.dpi': 200
    })

    fig, ax = plt.subplots(figsize=(9, 5))

    # main curve
    ax.loglog(q, intensities, color='#1f77b4', label=f"{material} {shape}")

    ax.set_xlabel(r'Scattering Vector $q$ ($\mathring{A}^{-1}$)')
    ax.set_ylabel(r'Intensity $I(q)$ ($cm^{-1}$)')
    ax.set_title(f'Simulated SAXS Profile: {material} {shape}', pad=15)

    # Styling the Grid and Spines
    ax.grid(True, which="both", ls="-", alpha=0.2)
    ax.spines['top'].set_visible(False)
    ax.spines['right'].set_visible(False)

    # Adding metadata info as a text box or legend
    props = dict(boxstyle='round', facecolor='white', alpha=0.5)
    ax.text(0.05, 0.05, params_str.rstrip(' | '), transform=ax.transAxes,
            fontsize=9, verticalalignment='bottom', bbox=props)

    ax.legend(frameon=False)

    plt.tight_layout()

    # Save as PDF or TIFF
    save_path = h5_path.replace('.h5', '.tiff')
    plt.savefig(save_path)
    print(f"Plot saved to: {save_path}")
    plt.show()
```



---

## πŸ“„ License

This dataset is released under a **Commercial Restricted License**.  
- βœ… Academic and research use: **free**
- βœ… Internal ML training: **free for non-commercial entities**
- ❌ Commercial use (products, services, APIs): **requires a paid license**

See [LICENSE](./LICENSE) for full terms.

---

## πŸ“¬ Contact & Custom Orders

Need a specific material, shape, q-range, or instrument noise model?  
β†’ **[Contact via Gumroad](https://venon28.gumroad.com/)** or open a Discussion on this page.

---

## πŸ“– Citation

If you use this dataset in academic work, please cite:

```bibtex
@dataset{saxs_2026,
  author    = {Thevenon, Esteban},
  title     = {SAXS Synthetic Scattering Curves Dataset},
  year      = {2026},
  publisher = {Hugging Face},
  url       = {https://huggingface.co/datasets/Venon28/SAXS}
}
```