The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: ValueError
Message: Dataset 'batch' has length 501334 but expected 27380
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 129, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 544, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 3052, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 558, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 76, in _generate_tables
num_rows = _check_dataset_lengths(h5, self.info.features)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 353, in _check_dataset_lengths
raise ValueError(f"Dataset '{path}' has length {dset.shape[0]} but expected {num_rows}")
ValueError: Dataset 'batch' has length 501334 but expected 27380Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
MPTS-52
MPTS-52 contains 40,476 experimental structures from the Materials Project with 1 to 52 atoms per unit cell, split by the year of their first publication (the time split of Baird et al.), as released with DiffCSP. Models are trained on older structures and tested on newer ones.
This repository holds the complete, unfiltered dataset (40,476 structures) preprocessed to HDF5 with torchms, one file per split of the original release.
Files
| File | Structures | Atoms per structure | Years |
|---|---|---|---|
train.hdf5 |
27,380 | 1–52 | 1913–1997 |
val.hdf5 |
5,000 | 1–52 | 1997–2004 |
test.hdf5 |
8,096 | 1–52 | 2004–2013 |
Labels
| Field | Source column | Meaning |
|---|---|---|
formation_energy_per_atom |
formation_energy_per_atom |
formation energy in eV/atom |
energy_above_hull |
energy_above_hull |
energy above the convex hull in eV/atom |
Fields with no source in this dataset are filled with NaN: total_energy, band_gap.
Source columns that are not stored: material_id, theoretical (false for every row),
year. Row i of a split file is row i of the corresponding source CSV.
Format
Each file stores flat concatenated arrays:
| Dataset | Shape | Type | Content |
|---|---|---|---|
lattice |
(n_struct, 3, 3) | float32 | lattice vectors as rows, in angstrom |
num_atoms |
(n_struct,) | int64 | number of atoms of each structure |
ptr |
(n_struct,) | int64 | index of the first atom of each structure in x and z |
x |
(n_atoms, 3) | float32 | fractional coordinates in [0, 1) |
z |
(n_atoms,) | int64 | atomic numbers |
total_energy, formation_energy_per_atom, energy_above_hull, band_gap |
(n_struct,) | float32 | labels, NaN when unknown |
The lattice is rebuilt from the cell lengths and angles of the source CIF, so it is in the standard orientation (first vector along x).
Usage
from torchms.data import load_dataset
dataset = load_dataset("mpts-52", "train")
structures = dataset[:32] # batched Structures
Source and processing
- Source files:
https://github.com/jiaor17/DiffCSP/tree/7121d159826efa2ba9500bf299250d96da37f146/data/mpts_52(train.csv,val.csv,test.csv). - Built with torchms,
scripts/build_cdvae.py --only mpts_52: CSV to CIF, then CIF to HDF5, with no filter. - Checked against the source: same number of rows, every stored label equal to its source column row by row, and a sample of 300 structures per split compared with pymatgen's parsing of the same CIF (elements, fractional coordinates, lattice).
The data is redistributed from the sources below; refer to them for licence and terms of use.
References
- S. G. Baird, H. M. Sayeed, J. Montoya, T. D. Sparks, matbench-genmetrics: A Python library for benchmarking crystal structure generative models using time-based splits of Materials Project structures, Journal of Open Source Software 9, 5618 (2024).
- R. Jiao et al., Crystal Structure Prediction by Joint Equivariant Diffusion, NeurIPS 2023.
- A. Jain et al., Commentary: The Materials Project: A materials genome approach to accelerating materials innovation, APL Materials 1, 011002 (2013).
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