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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
---
# π‘ SAXS Synthetic Scattering Curves Dataset
> **Thousands of physically accurate Small Angle X-ray Scattering (SAXS) curves, generated from rigorous physical models.**
---
## π¬ 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**
---
## π Sample Visualization
*(See attached figures in the dataset repository)*
---
## πΌ 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 | 49β¬ |
| [au_sphere](https://venon28.gumroad.com/l/bmoiw) | 100k | Sphere | Au | 49β¬ |
| [sio2_sphere](https://venon28.gumroad.com/l/noathn) | 100k | Sphere | SiO2 | 49β¬ |
| [latex_sphere](https://venon28.gumroad.com/l/silrpc) | 100k | Sphere | Latex | 49β¬ |
| [ag_cylinder](https://venon28.gumroad.com/l/veduiq) | 100k | Cylinder | Ag | 49β¬ |
| [au_cylinder](https://venon28.gumroad.com/l/qikxjv) | 100k | Cylinder | Au | 49β¬ |
| [sio2_cylinder](https://venon28.gumroad.com/l/imkld) | 100k | Cylinder | SiO2 | 49β¬ |
| [latex_cylinder](https://venon28.gumroad.com/l/dkepz) | 100k | Cylinder | Latex | 49β¬ |
| [ag_parallelepiped](https://venon28.gumroad.com/l/vbxbtjm) | 100k | Parallelepiped | Ag | 49β¬ |
| [au_parallelepiped](https://venon28.gumroad.com/l/mlddye) | 100k | Parallelepiped | Au | 49β¬ |
| [sio2_parallelepiped](https://venon28.gumroad.com/l/iveenk) | 100k | Parallelepiped | SiO2 | 49β¬ |
| [latex_parallelepiped](https://venon28.gumroad.com/l/ljdcd) | 100k | Parallelepiped | Latex | 49β¬ |
| **Custom** | Unlimited | Custom | Custom | On request |
---
## π 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()
```
---
## π License
This dataset is released under a **Commercial Restricted License**.
- β
Academic and research use: **free**
- β
Internal ML training: **free for non-commercial entities**
- β Commercial use (products, services, APIs): **requires a paid license**
See [LICENSE](./LICENSE) for full terms.
---
## π¬ 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.
---
## π 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}
}
```
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