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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. |