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---
language:
- en
- ru
license: apache-2.0
task_categories:
- text-generation
tags:
- physics
- simulation
- 2d-physics
- rigid-body
- pymunk
- synthetic
- scene-generation
size_categories:
- 1M<n<10M
---
# Physics Generalization Dataset
**1,000,020 diverse 2D rigid body physics simulation scenes** for training and evaluating LLMs on physics prediction tasks.
## Overview
This dataset contains procedurally generated physics simulations across **30 distinct scenario types** organized in 6 categories. Unlike typical physics datasets that only feature random objects falling in a box, this dataset covers a wide range of physical phenomena: collisions, stacking, ramps, pendulums, constraints, and mini-game-inspired physics.
Each scene is a 200-frame simulation at 1/60s timestep using the Pymunk (Chipmunk2D) physics engine, exported in JSONL format with rich metadata.
## Dataset Structure
### Splits
| Split | Scenes | Scenario Types | Purpose |
|-------|--------|----------------|---------|
| **train** | 900,000 | 24 (seen only) | Training |
| **val** | 100,020 | 30 (seen + unseen) | Evaluation |
### Unseen Scenarios (held out from training)
6 scenario types appear **only in val**, enabling out-of-distribution generalization evaluation:
| Difficulty | Scenario | Description |
|-----------|----------|-------------|
| Simple | `pong` | Ball bouncing between two paddles (zero gravity) |
| Simple | `bowling` | Heavy ball rolling toward arranged pins |
| Simple | `ramp_roll` | Objects rolling down an inclined plane |
| Complex | `angry_birds` | Projectile launched at multi-layer block structure |
| Complex | `hourglass` | Objects falling through narrow gap between chambers |
| Complex | `newtons_cradle` | Balls suspended by pin joints, momentum transfer |
### Seen Scenarios (in both train and val)
24 scenario types with 37,500 samples each in train:
**Collision & Ballistics:** `billiards`, `breakout`, `explosion`, `head_on`, `projectile`
**Stacking & Structural:** `bridge`, `dominos`, `jenga`, `pyramid`, `tower`
**Ramps & Terrain:** `funnel`, `marble_run`, `plinko`, `ski_jump` (+ unseen `ramp_roll`)
**Pendulums & Constraints:** `chain`, `pendulum`, `seesaw`, `wrecking_ball` (+ unseen `newtons_cradle`)
**Mini-game Physics:** `basketball`, `pinball` (+ unseen `angry_birds`, `bowling`, `pong`)
**Complex & Chaotic:** `avalanche`, `conveyor`, `orbit`, `wind` (+ unseen `hourglass`)
## Data Format
Each scene is a JSONL file (1 header line + 200 frame lines).
### Header (line 1)
```json
{
"type": "scene_header",
"seed": 1315353,
"scenario_type": "explosion",
"scenario_category": "collision",
"difficulty": 4,
"description": "Explosion: 25 objects flying outward from center.",
"object_count": 25,
"gravity": {"x": 0.0, "y": -981.0},
"timestep": 0.016666666666666666,
"static_geometry": [...],
"constraints": [...],
"objects": [
{
"id": 0, "type": "circle",
"position": {"x": 401.23, "y": 302.45},
"material": {"mass": 2.5, "friction": 0.6, "elasticity": 0.7},
"radius": 15.3
}
]
}
```
### Frame (lines 2-201)
```json
{
"frame": 1,
"description": "Frame 1: All objects are in motion.",
"objects": [
{
"id": 0, "type": "circle",
"position": {"x": 415.67, "y": 318.90},
"velocity": {"x": 280.5, "y": 320.1},
"angle": 0.052,
"angular_velocity": 0.003,
"material": {"mass": 2.5, "friction": 0.6, "elasticity": 0.7}
}
]
}
```
## Key Features
- **30 scenario types** with qualitatively different physics (not just parameter variation)
- **Difficulty scaling** (1-5) per scenario: controls object count, velocity, structural complexity
- **Deterministic** generation via seed-based RNG
- **Constraints/Joints**: PinJoint, PivotJoint for pendulums, seesaws, chains, Newton's cradle
- **Custom static geometry**: ramps, funnels, peg grids, bumpers, hourglass chambers, basketball hoops
- **Rich text descriptions** for each scene (useful as LLM context)
- **Zero gravity** scenarios: billiards, pong, orbit
- **Initial velocities**: projectiles, explosions, head-on collisions (not just "objects at rest")
- **Clean train/unseen split** for generalization evaluation
## Physics Engine
- **Pymunk** (Python wrapper for Chipmunk2D)
- Scene: 800×600 pixels
- Fixed timestep: 1/60s
- Elasticity always < 1.0 (energy conservation, no Pymunk instability)
- Threading disabled (determinism)
## Generation
Generated using 22 CPU cores in ~29 minutes at ~578 scenes/sec.
```bash
python scripts/generate_scenarios_dataset.py --split all --workers 22
```
## File Organization
```
data_scenarios/
├── manifest.json # Split config, seen/unseen lists
├── train/
│ ├── avalanche/ # 37,500 scenes
│ ├── basketball/
│ ├── ... # 24 scenario type directories
│ └── wrecking_ball/
└── val/
├── angry_birds/ # 3,334 scenes (UNSEEN)
├── avalanche/
├── bowling/ # 3,334 scenes (UNSEEN)
├── ... # 30 scenario type directories
└── wind/
```
## Citation
Part of a research project on training LLMs to predict 2D rigid body physics.
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