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The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    ValueError
Message:      Illegal slicing argument for scalar dataspace
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                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 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2815, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2352, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2377, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 87, in _generate_tables
                  pa_table = _recursive_load_arrays(h5, self.info.features, start, end)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 273, in _recursive_load_arrays
                  arr = _recursive_load_arrays(dset, features[path], start, end)
                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 275, in _recursive_load_arrays
                  arr = _load_array(dset, path, start, end)
                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 242, in _load_array
                  arr = dset[start:end]
                        ~~~~^^^^^^^^^^^
                File "h5py/_objects.pyx", line 56, in h5py._objects.with_phil.wrapper
                File "h5py/_objects.pyx", line 57, in h5py._objects.with_phil.wrapper
                File "/usr/local/lib/python3.12/site-packages/h5py/_hl/dataset.py", line 879, in __getitem__
                  selection = sel2.select_read(fspace, args)
                              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/h5py/_hl/selections2.py", line 101, in select_read
                  return ScalarReadSelection(fspace, args)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/h5py/_hl/selections2.py", line 86, in __init__
                  raise ValueError("Illegal slicing argument for scalar dataspace")
              ValueError: Illegal slicing argument for scalar dataspace

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Hessian-OMol

This dataset contains recalculated Hessians for selected molecules from the THEMol Hessian data, using the hessian_0.h5 source shard. The files here are the Hessians calculated so far for the comparison study in THEMol; the full original THEMol source HDF5 shards are not included in this upload.

Contents

  • HDF5 Hessian files: 201
  • Unique source samples: 57
  • Atom count range: 3 to 50 atoms
  • Total uploaded HDF5 size: 21.02 MB
  • Manifest: metadata/manifest.csv
  • Method summary: metadata/method_summary.csv

File Layout

Files are organized by calculation engine and method:

hessians/
  ml/uma_s_1p2_omol/
  orca/wb97m_d4_def2_qzvppd/
  orca/wb97m_d4_def2_tzvpd/
  pyscf/ccsd_t_cbs/
  pyscf/wb97m_v_def2_tzvpd/
  pyscf/wb97m_v_def2_tzvpd_density_fit/
  semiempirical/g_xtb/
  semiempirical/gfn2_xtb/
metadata/
  manifest.csv
  method_summary.csv
  summary.json

Each Hessian file is named hessian_0_sample_<zero-padded sample id>.h5. The path and original_path columns in metadata/manifest.csv map uploaded names back to the local calculation outputs.

HDF5 Schema

Each .h5 file contains one molecule group keyed by the original THEMol sample key. Within that group, the common datasets are:

  • atomic_numbers: atomic numbers, shape (N, 1)
  • coords: coordinates, shape (N, 3)
  • energy: scalar energy from the method in that file
  • force: force array, shape (N, 3)
  • gradient: gradient array, shape (N, 3)
  • hessian: flattened Cartesian Hessian, shape (3N, 3N)
  • hessian_4d: Hessian as atom/axis blocks, shape (N, N, 3, 3) when present
  • reference_hessian: source THEMol Hessian copied from hessian_0.h5 when present
  • metadata_json: calculation metadata, including source sample id and method details

Methods

  • g_xtb: 40 files, g-xTB
  • gfn2_xtb: 10 files, GFN2-xTB
  • orca_wb97m_d4_def2_qzvppd: 37 files, ORCA wB97M-D4/def2-QZVPPD
  • orca_wb97m_d4_def2_tzvpd: 45 files, ORCA wB97M-D4/def2-TZVPD
  • pyscf_ccsd_t_cbs: 2 files, PySCF RCCSD(T)/CBS
  • pyscf_wb97m_v_def2_tzvpd: 28 files, PySCF wB97M-V/def2-TZVPD
  • pyscf_wb97m_v_def2_tzvpd_density_fit: 9 files, PySCF wB97M-V/def2-TZVPD with density fitting
  • uma_s_1p2_omol: 30 files, UMA-S-1.2 OMol autograd Hessian

Notes

The calculations were run on samples from data/hessians/hessian_0.h5 in the local THEMol workflow. The original source THEMol shard is referenced in metadata but is not uploaded here.

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