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license: cc-by-4.0
tags:
- physics-informed
- spectroscopy
- infrared
- synthetic
pretty_name: PIDU simulated datasets
---
# PIDU simulated datasets
Simulated infrared spectra (Transfer Matrix Method, random Drude-Lorentz layer and oscillator
parameters) with their ground-truth parameters, used to train and test the models of
**Physics-infused Deep Unfolding for Automated Material Parameter Extraction of Optical Data**
(Koumans, Stevens, van Sloun, van Mechelen).
Code: https://github.com/MKoumans/PIDU · Checkpoints: [`MKoumans/pidu-optical-parameter-extraction`](https://huggingface.co/MKoumans/pidu-optical-parameter-extraction)
## Contents
| Path | Content |
| --- | --- |
| `data/datasets/usecase1/*.npz` | Use case 1: train / val / test sets |
| `data/datasets/usecase2/*.npz` | Use case 2: train / val / test sets, with (`wsn`) and without (`nwsn`) the second system |
| `data/labels/*.xlsx` | Label mappings used during dataset generation |
| `outputs/case<N>/outputs/loss_{CNN,DU,PIDU}_<i>_001/` | Test exports of the trained runs (8 seeds per model; use case 2 includes `test_exp`, the predictions on the measured spectra) |
| `outputs/case<N>/loss/loss_{CNN,DU,PIDU}_<i>_001/` | Per-epoch train / val / test loss of those runs |
| `outputs/case<N>/logs/train_<TYPE>_<i>.log` | Training logs of those runs |
| `models/usecase<N>/<TYPE>-t01-<i>.pt` | Checkpoints of those runs (the Fig. 2 timings average over seeds) |
| `outputs/case<N>/outputs/loss_lma_{baseline,noisy,random}/` | TRF (LMA) baseline: use case 1 on the 1024 simulated test spectra, use case 2 on the 75 measured spectra |
Each `.npz` holds the clean spectra (`data_y_*`), noised spectra (`data_y_noised_*`), initial and
target parameters (`data_x_*`), and the wavenumber axis (`wn_*`).
**Not included:** the experimental SrTiO₃ measurements themselves (the predictions and fits on them are).
## Usage
```bash
pidu-hub download --usecase 1 2 # everything
pidu-hub download --what data logs --usecase 1 # datasets and training logs only
```
## Citation
To be added.
|