| --- |
| license: cc-by-4.0 |
| language: |
| - en |
| tags: |
| - chemistry |
| configs: |
| - config_name: k3 |
| default: true |
| data_files: |
| - "k3/k3_split.parquet" |
|
|
| - config_name: k4 |
| data_files: |
| - "k4/k4_split.parquet" |
|
|
| - config_name: k4_2ar |
| data_files: |
| - "k4_2ar/k4_2ar_split.parquet" |
|
|
| - config_name: k5 |
| data_files: |
| - "k5/k5_split.parquet" |
|
|
| - config_name: k3_labels |
| data_files: |
| - "k3/k3_labels.parquet" |
|
|
| - config_name: k4_labels |
| data_files: |
| - "k4/k4_labels.parquet" |
|
|
| - config_name: k4_2ar_labels |
| data_files: |
| - "k4_2ar/k4_2ar_labels.parquet" |
|
|
| - config_name: k5_labels |
| data_files: |
| - "k5/k5_labels.parquet" |
| --- |
| # Pharmaco-Explainer Datasets |
|
|
| This repository contains **datasets used in the Pharmaco-Explainer project**. |
| They are shared separately on Hugging Face and are used by the training and |
| experimentation code hosted on GitHub: |
|
|
| 👉 **Training code and scripts:** |
| https://github.com/AdamSulek/pharmaco-explainer/ |
|
|
| --- |
|
|
| ## Available Datasets |
|
|
| The following datasets are available: |
| - **k3:** 3-element pharmacophore |
| - **k4_2ar:** 4-element pharmacophore with two aromatic features |
| - **k4:** 4-element pharmacophore |
| - **k5** 5-element pharmacophore |
| |
| Each dataset consists of three files: |
| |
| - `<dataset>.parquet` – main feature data |
| - `<dataset>_split.parquet` – predefined train/val/test split |
| - `<dataset>_labels.parquet` – labels |
| |
| Repository structure: |
| ``` |
| k3/ |
| ├── k3.parquet |
| ├── k3_split.parquet |
| └── k3_labels.parquet |
| k4_2ar/ |
| ├── k4_2ar.parquet |
| ├── k4_2ar_split.parquet |
| └── k4_2ar_labels.parquet |
| k4/ |
| ├── k4.parquet |
| ├── k4_split.parquet |
| └── k4_labels.parquet |
| k5/ |
| ├── k5.parquet |
| ├── k5_split.parquet |
| └── k5_labels.parquet |
| ``` |
| |
| |
| ## Downloading the Data |
| |
| Datasets can be downloaded **directly from Hugging Face** using the Python |
| script below. |
| |
| ### Requirements |
| |
| - Python ≥ 3.8 |
| - `requests` |
| - Environment variable `PHARM_PROJECT_ROOT` pointing to the project root |
| |
| ```bash |
| import argparse |
| from pathlib import Path |
| import requests |
| import os |
| |
| def project_path(*parts): |
| root = os.environ.get("PHARM_PROJECT_ROOT") |
| if root is None: |
| raise RuntimeError( |
| "Environment variable PHARM_PROJECT_ROOT is not set.\n" |
| "Run:\n" |
| " export PHARM_PROJECT_ROOT=/path/to/project" |
| ) |
| return os.path.join(root, *parts) |
| |
| def download_file(url, dest_path: Path): |
| dest_path.parent.mkdir(parents=True, exist_ok=True) |
| if dest_path.exists(): |
| print(f"File already exists, skipping: {dest_path}") |
| return |
| print(f"Downloading {url} -> {dest_path}") |
| r = requests.get(url, stream=True) |
| r.raise_for_status() |
| with open(dest_path, "wb") as f: |
| for chunk in r.iter_content(chunk_size=1024 * 1024): |
| if chunk: |
| f.write(chunk) |
| |
| def download_dataset(dataset_name): |
| base_url = ( |
| f"https://huggingface.co/datasets/" |
| f"klimczakjakubdev/pharmaco-explainer/resolve/main/{dataset_name}/" |
| ) |
| files = [ |
| f"{dataset_name}.parquet", |
| f"{dataset_name}_split.parquet", |
| f"{dataset_name}_labels.parquet", |
| ] |
| |
| dest_dir = Path(project_path("data", dataset_name)) |
| for file_name in files: |
| url = base_url + file_name |
| dest_path = dest_dir / file_name |
| download_file(url, dest_path) |
| |
| if __name__ == "__main__": |
| parser = argparse.ArgumentParser() |
| parser.add_argument( |
| "--dataset", |
| type=str, |
| default="k3", |
| choices=["k3", "k4", "k4_2ar", "k5"], |
| help="Which dataset to download" |
| ) |
| args = parser.parse_args() |
| |
| download_dataset(args.dataset) |
| ``` |
| |
| Example Usage |
| ``` |
| python download_dataset.py --dataset k4 |
| ``` |
| |
| Files will be downloaded to: |
| ``` |
| $PHARM_PROJECT_ROOT/data/k4/ |
| ``` |
| |
| ## Related Repository |
| These datasets are used by the main Pharmaco-Explainer codebase: |
| |
| 🔗 https://github.com/AdamSulek/pharmaco-explainer/ |
| |
| That repository contains: |
| |
| * model training code |
| * experiment configurations |
| * preprocessing scripts |
| * evaluation and explainability pipelines |
