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---
license: mit
pretty_name: AstroM3Dataset
size_categories:
- 10K<n<100K
tags:
- astronomy
- multimodal
- classification
arxiv:
- arXiv:2411.08842
---
# AstroM3Dataset
## Description
AstroM3Dataset 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, 3)` (time, flux, flux\_error).
- **Spectra**: Spectra observations of shape `(M, 3)` (wavelength, flux, flux\_error).
- **Metadata**: Auxiliary features of shape `(38,)`.
- **Label**: The class name as a string.
## 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/)
---
## 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`
## Data Organization
The dataset is organized as follows:
```
AstroM3Dataset/
├── photometry.zip # Contains all photometry light curves
├── utils/
│ ├── parallelzipfile.py # Zip file reader to open photometry.zip
├── spectra/ # Spectra files organized by class
│ ├── EA/
│ │ ├── file1.dat
│ │ ├── file2.dat
│ │ ├── ...
│ ├── EW/
│ ├── SR/
│ ├── ...
├── splits/ # Train/val/test splits for each subset and seed
│ ├── full/
│ │ ├── 42/
│ │ │ ├── train.csv
│ │ │ ├── val.csv
│ │ │ ├── test.csv
│ │ │ ├── info.json # Contains feature descriptions and preprocessing info
│ │ ├── 66/
│ │ ├── 0/
│ │ ├── 12/
│ │ ├── 123/
│ ├── sub10/
│ ├── sub25/
│ ├── sub50/
│── AstroM3Dataset.py # Hugging Face dataset script
```
## Usage
To load the dataset using the Hugging Face `datasets` library:
```python
from datasets import load_dataset
# Load the default full dataset with seed 42
dataset = load_dataset("MeriDK/AstroM3Dataset", trust_remote_code=True)
```
The default configuration is **full_42** (entire dataset with seed 42).
To load a specific subset and seed, use {subset}_{seed} as the name:
```python
from datasets import load_dataset
# Load the 25% subset sampled using seed 123
dataset = load_dataset("MeriDK/AstroM3Dataset", name="sub25_123", trust_remote_code=True)
```
---
## Citation
If you find this dataset usefull, please cite:
```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}
}
``` |