The dataset viewer is not available for this split.
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 2543, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2060, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2083, 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 544, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 383, 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 dataspaceNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Magnetohydrodynamics (MHD) compressible turbulence
NOTE: This dataset is available in two different resolutions $256^3$ for MHD_256 and $64^3$ for MHD_64. The data was first generated at $256^3$ and then downsampled to $64^3$ after anti-aliasing with an ideal low-pass filter. The data is available in both resolutions.
One line description of the data: This is an MHD fluid flows in the compressible limit (subsonic, supersonic, sub-Alfvenic, super-Alfvenic).
Longer description of the data: An essential component of the solar wind, galaxy formation, and of interstellar medium (ISM) dynamics is magnetohydrodynamic (MHD) turbulence. This dataset consists of isothermal MHD simulations without self-gravity (such as found in the diffuse ISM) initially generated with resolution $256^3$ and then downsampled to $64^3$ after anti-aliasing with an ideal low-pass filter. This dataset is the downsampled version.
Associated paper: Paper
Domain expert: Blakesley Burkhart, CCA, Flatiron Institute & Rutgers University.
Code or software used to generate the data: Fortran + MPI.
Equation:
where $\rho$ is the density, $\mathbf{v}$ is the velocity, $\mathbf{B}$ is the magnetic field, $\mathbf{I}$ the identity matrix and $p$ is the gas pressure.
| Dataset | FNO | TFNO | Unet | CNextU-net |
|---|---|---|---|---|
MHD_64 |
0.3605 | 3561 | 0.1798 | $\mathbf{0.1633}$ |
Table: VRMSE metrics on test sets (lower is better). Best results are shown in bold. VRMSE is scaled such that predicting the mean value of the target field results in a score of 1.
About the data
Dimension of discretized data: 100 timesteps of 64 $\times$ 64 $\times$ 64 cubes.
Fields available in the data: Density (scalar field), velocity (vector field), magnetic field (vector field).
Number of trajectories: 10 Initial conditions x 10 combination of parameters = 100 trajectories.
Estimated size of the ensemble of all simulations: 71.6 GB.
Grid type: uniform grid, cartesian coordinates.
Initial conditions: uniform IC.
Boundary conditions: periodic boundary conditions.
Data are stored separated by ($\Delta t$): 0.01 (arbitrary units).
Total time range ($t_{min}$ to $t_{max}$): $t_{min} = 0$, $t_{max} = 1$.
Spatial domain size ($L_x$, $L_y$, $L_z$): dimensionless so 64 pixels.
Set of coefficients or non-dimensional parameters evaluated: all combinations of $\mathcal{M}_s=${0.5, 0.7, 1.5, 2.0 7.0} and $\mathcal{M}_A =${0.7, 2.0}.
Approximate time and hardware used to generate the data: Downsampled from MHD_256 after applying ideal low-pass filter.
What is interesting and challenging about the data:
What phenomena of physical interest are catpured in the data: MHD fluid flows in the compressible limit (sub and super sonic, sub and super Alfvenic).
How to evaluate a new simulator operating in this space: Check metrics such as Power spectrum, two-points correlation function.
Please cite the associated paper if you use this data in your research:
@article{burkhart2020catalogue,
title={The catalogue for astrophysical turbulence simulations (cats)},
author={Burkhart, B and Appel, SM and Bialy, S and Cho, J and Christensen, AJ and Collins, D and Federrath, Christoph and Fielding, DB and Finkbeiner, D and Hill, AS and others},
journal={The Astrophysical Journal},
volume={905},
number={1},
pages={14},
year={2020},
publisher={IOP Publishing}
}
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