---
license: mit
size_categories:
- 10K<n<100K
tags:
- astronomy
- multimodal
- classification
arxiv:
- arXiv:2411.08842
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---
# AstroM3Processed

## Description

AstroM3Processed is a time-series astronomy dataset containing photometry, spectra, and metadata features for variable stars. 
The dataset includes multiple subsets (`full`, `sub10`, `sub25`, `sub50`) and supports different random seeds (`42`, `66`, `0`, `12`, `123`). 
Each sample consists of:

- **Photometry**: Light curve data of shape `(N, 9)` (time, flux, flux\_error, amplitude, period, lksl_statistic, rfr_score, mad, delta_t).
- **Spectra**: Spectra observations of shape `(3, 2575)` (wavelength, flux, flux\_error).
- **Metadata**: List of metadata values of shape `(34,)`
- **Label**: The class name as int.

## Corresponding paper and code

- Paper: [AstroM<sup>3</sup>: A self-supervised multimodal model for astronomy](https://arxiv.org/abs/2411.08842)
- Code Repository: [GitHub: AstroM<sup>3</sup>](https://github.com/MeriDK/AstroM3/)
- Original Data: [MeriDK/AstroM3Dataset](https://huggingface.co/datasets/MeriDK/AstroM3Dataset/)

**Note:** The processed dataset `AstroM3Processed` is created from the original dataset `AstroM3Dataset` 
by using [preprocess.py](https://huggingface.co/datasets/MeriDK/AstroM3Dataset/blob/main/preprocess.py)

## Subsets and Seeds
AstroM3Dataset is available in different subset sizes:  

- `full`: Entire dataset  
- `sub50`: 50% subset  
- `sub25`: 25% subset  
- `sub10`: 10% subset  

Each subset is sampled from the respective train, validation, and test splits of the full dataset.  
For reproducibility, each subset is provided with different random seeds:  

- `42`, `66`, `0`, `12`, `123`  

## Usage
To load the dataset using the Hugging Face `datasets` library, specify the name in the format "{subset}_{seed}". For example:

```python
from datasets import load_dataset

# Load the full dataset with seed 42
dataset = load_dataset("MeriDK/AstroM3Processed", name="full_42")

# Load the 25% subset sampled using seed 123
dataset = load_dataset("MeriDK/AstroM3Processed", name="sub25_123")
```

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## Citation
🤗 If you find this dataset usefull, please cite our paper 🤗
```bibtex
@article{rizhko2024astrom,
  title={AstroM $\^{} 3$: A self-supervised multimodal model for astronomy},
  author={Rizhko, Mariia and Bloom, Joshua S},
  journal={arXiv preprint arXiv:2411.08842},
  year={2024}
}
```