---
license: mit
language: en
pretty_name: "Koopman DA Benchmark Dataset"
size_categories:
- n<1K
tags:
- numpy
- hdf5
---

# Koopman Data Assimilation Dataset

Dataset accompanying the benchmark for Data Assimilation (DA) tasks with Koopman-inspired models.

Code repository: [github.com/Wenxuan52/KoopmanDABench](https://github.com/Wenxuan52/KoopmanDABench) (Currently private, will release codebase when paper finished)

## What Is Hosted Where

The project is split across two locations:

- **GitHub repo** — source code, plus a few small files under `data/` (e.g. data-generation scripts, small reference files, configs).
- **This Hugging Face dataset** — the large pre-computed `.npy` / `.h5` files that are too big to track in Git.

On a new machine, cloning the GitHub repo and then downloading this dataset into the same `data/` folder gives you the complete setup. The two sets of files do not overlap.

## Final `data/` Layout

After both `git clone` and `hf download`, the `data/` folder should look like:

```
data/
├── kol_generate_data/            # from GitHub
├── ERA5_High/
│   ├── process_weatherbench.py   # from GitHub
│   ├── test.py                   # from GitHub
│   └── raw_data/                 # from Hugging Face
├── ERA5/                         # from Hugging Face
├── dam/                          # from Hugging Face
├── cylinder/                     # from Hugging Face
└── kol/                          # from Hugging Face
```

---

## Quick Start on a New Machine

### 1. Clone the code from GitHub

```bash
git clone https://github.com/Wenxuan52/KoopmanDA.git
cd KoopmanDA
```

This already populates `data/` with the small files tracked in Git (e.g. generation scripts).

### 2. Set up the Python environment

```bash
conda create -n koopmanda python=3.10 -y
conda activate koopmanda
pip install -r requirements.txt        # or: pip install -e .
pip install -U huggingface_hub
```

### 3. Pull the large data files from Hugging Face into `data/`

Download into the existing `data/` folder — files from GitHub are not affected:

```bash
hf download BruceYuan/KoopmanDA \
    --repo-type dataset \
    --local-dir ./data
```

Equivalent Python call:

```python
from huggingface_hub import snapshot_download
snapshot_download(
    repo_id="BruceYuan/KoopmanDA",
    repo_type="dataset",
    local_dir="./data",
)
```

The project should now run exactly as it did on the original machine.

## License

Released under the MIT License.