Publish ArchEGraph-demo snapshot via Xet

.gitattributes

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+*.npz filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+pretty_name: PACK
+license: other
+task_categories:
+- regression
+language:
+- en
+tags:
+- building-energy
+- simulation
+- graph
+- weather
+size_categories:
+- 10K<n<100K
+---
+
+# PACK
+
+PACK is a building-energy dataset organized for graph-based and weather-conditioned learning.
+
+## Dataset Summary
+
+- Total cases in `manifest.csv`: 49,326
+- Unique buildings: 5,481
+- Unique weather IDs: 64
+- `n_steps` range: 968 to 8,760
+- `n_spaces` range: 1 to 231
+
+This repository currently stores:
+
+- `manifest.csv` (index of all cases)
+- `building/` (5,481 files)
+- `geometry/` (5,482 files)
+- `weather/` (64 files)
+- `energy/` (49,326 files; nested under subfolders like `00/`)
+- `split/` (predefined split CSV files)
+
+## Data Layout
+
+Each row in `manifest.csv` contains:
+
+- `sample_id`: case ID (`building__weather` style)
+- `source_job_tag`: source identifier
+- `weather_id`: weather/location key
+- `building_id`: building key
+- `energy_file`: relative path to energy npz file under `energy/`
+- `n_steps`: number of time steps
+- `n_spaces`: number of spaces/zones
+
+## Included Split Files
+
+- `split/split_p.csv` (30,658 rows)
+- `split/split_m.csv` (18,668 rows)
+- `split/split_demo.csv` (300 rows)
+- `split/split_building_bias.csv` (3,000 rows)
+- `split/split_weather_bias.csv` (3,000 rows)
+
+Each split CSV uses the same columns:
+
+- `case_id`, `sample_id`, `building_id`, `weather_id`, `subset`, `split`, `scenario`
+
+## Quick Start
+
+```python
+import pandas as pd
+from pathlib import Path
+
+root = Path(".")  # dataset root
+manifest = pd.read_csv(root / "manifest.csv")
+
+row = manifest.iloc[0]
+energy_path = root / "energy" / row["energy_file"]
+building_path = root / "building" / f"{row['building_id']}.npz"
+weather_path = root / "weather" / f"{row['weather_id']}.npz"
+
+print(row["sample_id"])
+print(energy_path, building_path, weather_path)
+```
+
+## Notes
+
+- Energy files are stored in nested folders referenced by `energy_file`; do not assume all files are directly under `energy/`.
+- If you need a smaller download, use a demo subset generated from `split/split_demo.csv`.
+
+## Citation
+
+If you use this dataset, please cite your project/paper and this Hugging Face dataset page.

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