README.md

---
license: apache-2.0
language:
- en
task_categories:
- text-generation
tags:
- physics
- rigid-body
- pymunk
- next-frame-prediction
- simulation
- icml-2026
size_categories:
- 100K<n<1M
---

# physics-scenarios-raw

Raw (un-tarred) JSONL version of the 2D rigid body physics dataset. Each scene is a separate file under `<split>/<scenario_type>/scene_<id>.jsonl`. Streaming-friendly for HF `datasets` and curriculum sampling.

For the bandwidth-efficient packaged version, see [physics-scenarios-packed](https://huggingface.co/datasets/AlexWortega/physics-scenarios-packed).

## Scale (this snapshot)

- **Train**: 80,000 scenes
- **Val**: 10,000 scenes
- **Test**: 10,000 scenes
- **Frames per scene**: 200
- **Format**: one `.jsonl` per scene (1 header + 200 frame lines)

This is a subset of the full 1M-scene dataset; the full dataset is in [physics-scenarios-packed](https://huggingface.co/datasets/AlexWortega/physics-scenarios-packed).

## Layout

```
train/
  000000/scene_000000.jsonl
  000000/scene_000001.jsonl
  ...
  000079/...
val/
  ...
test/
  ...
```

Files are sharded into directories of ~1000 scenes (zero-padded shard ids) to keep listings tractable.

## Schema (per scene file)

Line 1 — scene header:
```json
{
  "scenario": "billiards",
  "difficulty": 3,
  "static_geometry": [...],
  "constraints": [...],
  "objects": [{"id": 0, "type": "circle", "radius": 0.5, "mass": 1.0, ...}, ...]
}
```

Lines 2–201 — per-frame state:
```json
{"frame": 0, "objects": [{"id": 0, "x": 1.234, "y": 5.678, "vx": ..., "vy": ..., "angle": ..., "omega": ...}, ...]}
```

## Loading

```python
from datasets import load_dataset
ds = load_dataset("AlexWortega/physics-scenarios-raw", split="train", streaming=True)
```

Or stream directly from the hub with `huggingface_hub.HfFileSystem`.

## Citation

ICML-2026 submission (in progress).