Datasets:

ArchEGraph
/

ArchEGraph-demo

pretty_name: ArchEGraph-demo
license: apache-2.0
task_categories:
  - graph-ml
  - time-series-forecasting
language:
  - en
tags:
  - building-energy
  - simulation
  - graph
  - weather
  - demo
size_categories:
  - n<1K
configs:
  - config_name: manifest
    default: true
    data_files:
      - split: train
        path: manifest.csv
  - config_name: split_demo
    data_files:
      - split: train
        path: split/split_demo.csv
  - config_name: split_demo_mesh
    data_files:
      - split: train
        path: split/split_demo_mesh.csv

ArchEGraph-demo

ArchEGraph-demo is a compact demo package of the ArchEGraph building-energy dataset for graph-based and weather-conditioned learning.

Dataset Summary

Total cases in manifest.csv: 300
Unique buildings: 75
Unique weather IDs: 48
n_steps: always 8,760
n_spaces range: 2 to 132

This package currently stores:

manifest.csv (index of all demo cases)
building/ (75 files)
geometry/ (75 files)
weather/ (48 files)
energy/ (300 files)
split/ (demo 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_demo.csv (300 rows)
split/split_demo_mesh.csv (300 rows)

split/split_demo.csv uses these columns:

case_id, sample_id, building_id, weather_id, subset, split, scenario

split/split_demo_mesh.csv uses these columns:

building_id, split

Quick Start

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

This repository is the demo package, not the full PACK release.
Energy files in this demo package are referenced by energy_file from manifest.csv.
split/split_demo.csv and split/split_demo_mesh.csv provide ready-to-use predefined splits for the packaged demo samples.

Citation

If you use this dataset, please cite your project/paper and this Hugging Face dataset page.