hduvallh's picture
OC-FEM metadata-fix: corrected geometries, Helmholtz, JCM blobs (#2)
0c3265e
|
Raw
History Blame Contribute Delete
1.52 kB
---
license: mit
tags:
- electromagnetics
- nanophotonics
- jcmwave
- optical-constants
- parquet
configs:
- config_name: metadata
default: true
data_files:
- split: train
path: metadata/train-*
- config_name: validation
data_files:
- split: train
path: validation/train-*
---
# squiggles (metadata-fix)
OC-map FEM rebuild at **35 pixels per wavelength**, with corrected geometries,
Helmholtz residuals, and the **resolved JCMsuite `.jcm` / `.jcmp` files** used
for each solve.
## Configs
### `metadata` (default)
One row per structure folder (`sample_XXXX`). Geometry comes from published
optical-constant maps (not the old nested-interface metadata).
### `validation`
One row per FEM incidence (`theta` in `{0, 45}`). Self-contained pixel map:
```text
pitch_nm = wavelength_nm / pixels_per_wavelength
x_nm = x0_nm + ix * pitch_nm
y_nm = y0_nm + iy * pitch_nm
```
Also includes nested OC/E arrays, Helmholtz scalar metrics (s-pol staggered FD),
and binary blobs of the generated project files:
- `layout` <- `layout.jcm`
- `materials` <- `materials.jcm`
- `sources` <- `sources.jcm`
- `project` <- `project.jcmp` (JCMsuite expanded project)
- `grid` <- `grid.jcm`
## Load
```python
from datasets import load_dataset
meta = load_dataset("als-rixs/latent-image-training", "metadata", split="train", revision="metadata-fix")
val = load_dataset("als-rixs/latent-image-training", "validation", split="train", revision="metadata-fix")
row = val[0]
layout_jcm = row["layout"] # bytes
```