The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 83, in _split_generators
raise ValueError(
...<2 lines>...
)
ValueError: The TAR archives of the dataset should be in WebDataset format, but the files in the archive don't share the same prefix or the same types.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 66, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
SBI_INAF
SBI_INAF is a dataset designed for Simulation-Based Inference (SBI) on atmospheric retrieval of exoplanets at a spectral resolution of approximately R = 40000, tailored for the GIANO-B echelle spectrograph. It contains transmission spectra (stellar and telluric free) together with their associated physical parameters, auxiliary metadata, normalization statistics, and predefined train/validation/test splits.
The dataset is built upon the Atmospheric Big Challenge (ABC) database, with major modifications to address the research goals of the research paper "Towards Scalable High-Resolution Atmospheric Retrieval of Exoplanets with Flow Matching" - M. Giordano Orsini et al., 2026.
The dataset is intended for supervised learning tasks involving parameter estimation from synthetic or simulated transmission spectra.
Dataset Structure
SBI_INAF_R1500/
├── AuxillaryTable.csv
├── FM_Parameter_Table.csv
├── h5s/
├── norm_params.pkl
├── QuartilesTable.csv
├── test_indices.npy
├── train_indices.npy
├── val_indices.npy
├── wavelengths.npy
├── widths.npy
File Descriptions
| File | Description |
|---|---|
h5s/ |
Collection of HDF5 files containing the spectra and associated sample information. |
FM_Parameter_Table.csv |
Physical parameters (forward-model parameters) associated with each simulated spectrum. These serve as prediction targets. |
AuxillaryTable.csv |
Additional metadata describing each sample (planetary system-related parameters). |
QuartilesTable.csv |
Summary statistics (quartiles) of selected parameters or features. Useful for exploratory data analysis. |
norm_params.pkl |
Stored normalization parameters used during preprocessing. |
wavelengths.npy |
Common wavelength grid for all spectra. |
widths.npy |
Spectral bin widths corresponding to the wavelength grid. |
train_indices.npy |
Indices defining the training split. |
val_indices.npy |
Indices defining the validation split. |
test_indices.npy |
Indices defining the held-out test split. |
Citation
If this dataset contributes to published work, please cite:
@article{GiordanoOrsini_2026,
author = {Giordano Orsini, Massimiliano and Ferone, Alessio and Inno, Laura and Maratea, Antonio and Casolaro, Angelo and Giacobbe, Paolo and Pino, Lorenzo and Bonomo, Aldo S.},
title = {Towards Scalable High-Resolution Atmospheric Retrieval of Exoplanets with Flow Matching},
year = 2026,
journal = {Journal of Computational Physics},
addendum = {(Submitted)},
}
License
Please refer to the accompanying repository or publication for licensing information.
Contact
For questions regarding the dataset, please contact the dataset maintainers or the authors of the accompanying publication.
- Downloads last month
- 30