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The dataset generation failed because of a cast error
Error code: DatasetGenerationCastError
Exception: DatasetGenerationCastError
Message: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 12 new columns ({'right_sampler', 'domain', 'physics', 'frequency_samples', 'top_samples', 'top_sampler', 'right_samples', 'top_boundary', 'mesh', 'n_observations', 'right_boundary', 'frequency_sampler'}) and 12 missing columns ({'transport_0', 'rank', 'mkdir_mus', 'threads', 'meta_sort_merge_mus', 'minmax_mus', 'bytes', 'start', 'transport_1', 'buffering_mus', 'aggregation_mus', 'memcpy_mus'}).
This happened while the json dataset builder was generating data using
hf://datasets/JakobEWagner/helmholtz_pulsating_sphere_s4096_f400-500_Yre0-1_Yim-1-0/train/properties.json (at revision 87bd9acb3b41ac1cd447848a711de833ff02aa6a)
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2011, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, in write_table
pa_table = table_cast(pa_table, self._schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
domain: struct<box_lengths: list<item: double>, sphere_radius: double, ndim: int64>
child 0, box_lengths: list<item: double>
child 0, item: double
child 1, sphere_radius: double
child 2, ndim: int64
mesh: struct<elements_per_wavelengths: int64, elements_per_radians: double, excitation_boundary: int64, top_boundary: int64, right_boundary: int64>
child 0, elements_per_wavelengths: int64
child 1, elements_per_radians: double
child 2, excitation_boundary: int64
child 3, top_boundary: int64
child 4, right_boundary: int64
physics: struct<c: double, rho: double>
child 0, c: double
child 1, rho: double
n_observations: int64
frequency_sampler: struct<type: string, x_min: list<item: double>, x_max: list<item: double>>
child 0, type: string
child 1, x_min: list<item: double>
child 0, item: double
child 2, x_max: list<item: double>
child 0, item: double
top_boundary: string
top_sampler: struct<type: string, x_min: list<item: double>, x_max: list<item: double>>
child 0, type: string
child 1, x_min: list<item: double>
child 0, item: double
child 2, x_max: list<item: double>
child 0, item: double
right_boundary: string
right_sampler: struct<type: string, x_min: list<item: double>, x_max: list<item: double>>
child 0, type: string
child 1, x_min: list<item: double>
child 0, item: double
child 2, x_max: list<item: double>
child 0, item: double
frequency_samples: list<item: double>
child 0, item: double
top_samples: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
right_samples: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
to
{'transport_0': {'close_mus': Value(dtype='int64', id=None), 'open_mus': Value(dtype='int64', id=None), 'type': Value(dtype='string', id=None), 'write_mus': Value(dtype='int64', id=None)}, 'rank': Value(dtype='int64', id=None), 'mkdir_mus': Value(dtype='int64', id=None), 'threads': Value(dtype='int64', id=None), 'meta_sort_merge_mus': Value(dtype='int64', id=None), 'minmax_mus': Value(dtype='int64', id=None), 'bytes': Value(dtype='int64', id=None), 'start': Value(dtype='string', id=None), 'transport_1': {'close_mus': Value(dtype='int64', id=None), 'open_mus': Value(dtype='int64', id=None), 'type': Value(dtype='string', id=None), 'write_mus': Value(dtype='int64', id=None)}, 'buffering_mus': Value(dtype='int64', id=None), 'aggregation_mus': Value(dtype='int64', id=None), 'memcpy_mus': Value(dtype='int64', id=None)}
because column names don't match
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1577, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1191, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1882, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2013, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 12 new columns ({'right_sampler', 'domain', 'physics', 'frequency_samples', 'top_samples', 'top_sampler', 'right_samples', 'top_boundary', 'mesh', 'n_observations', 'right_boundary', 'frequency_sampler'}) and 12 missing columns ({'transport_0', 'rank', 'mkdir_mus', 'threads', 'meta_sort_merge_mus', 'minmax_mus', 'bytes', 'start', 'transport_1', 'buffering_mus', 'aggregation_mus', 'memcpy_mus'}).
This happened while the json dataset builder was generating data using
hf://datasets/JakobEWagner/helmholtz_pulsating_sphere_s4096_f400-500_Yre0-1_Yim-1-0/train/properties.json (at revision 87bd9acb3b41ac1cd447848a711de833ff02aa6a)
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)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.
transport_0
dict | rank
int64 | mkdir_mus
int64 | threads
int64 | meta_sort_merge_mus
int64 | minmax_mus
int64 | bytes
int64 | start
string | transport_1
dict | buffering_mus
int64 | aggregation_mus
int64 | memcpy_mus
int64 | domain
dict | mesh
dict | physics
dict | n_observations
int64 | frequency_sampler
dict | top_boundary
string | top_sampler
dict | right_boundary
string | right_sampler
dict | frequency_samples
sequence | top_samples
sequence | right_samples
sequence |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
{
"close_mus": 10,
"open_mus": 111,
"type": "File_POSIX",
"write_mus": 695151
} | 0 | 100 | 1 | 163,071 | 225,509 | 762,404,487 | Tue_Jul_09_12:07:07_2024 | {
"close_mus": 0,
"open_mus": 106,
"type": "File_POSIX",
"write_mus": 29679
} | 549,520 | 0 | 45,455 | null | null | null | null | null | null | null | null | null | null | null | null |
null | null | null | null | null | null | null | null | null | null | null | null | {
"box_lengths": [
1,
1
],
"sphere_radius": 0.2,
"ndim": 2
} | {"elements_per_wavelengths":15,"elements_per_radians":30.0,"excitation_boundary":101,"top_boundary":(...TRUNCATED) | {
"c": 343.2,
"rho": 1.2043
} | 4,096 | {
"type": "UniformSampler",
"x_min": [
400
],
"x_max": [
500
]
} | lambda a: lambda x: np.ones(x[0].shape) * a[0] + 1j * a[1] * np.ones(x[0].shape)
| {
"type": "UniformSampler",
"x_min": [
0,
-1
],
"x_max": [
1,
0
]
} | lambda a: lambda x: np.ones(x[1].shape) * a[0] + 1j * a[1] * np.ones(x[1].shape)
| {
"type": "UniformSampler",
"x_min": [
0,
-1
],
"x_max": [
1,
0
]
} | [434.6165019391972,420.4460772608176,405.8112930826629,405.62020055309284,448.8348308228759,466.2431(...TRUNCATED) | [[0.8601686212786032,-0.2786319944558162],[0.791580906537889,-0.7637266205339663],[0.780039091103954(...TRUNCATED) | [[0.7649005505092011,-0.5652698979192223],[0.37385365784649094,-0.5976737086596499],[0.3398699743841(...TRUNCATED) |
The Helmholtz pulsating sphere datasets provides numerical solutions of the time-harmonic Helmholtz equation. The dataset is generated using the DOLFINx framework.
Dataset Details
- Domain Description: The domain consists of a 2D domain with a pulsating sphere placed at the center. The pulsating sphere is encompassed by a bigger square.
- Physics Constants: The speed of sound is $c=343.20, ms^{-1}$, and the fluid density is $\rho=1.2043, kgm^{-3}.
- Frequency: The frequency is sampled uniformly from the interval $[400Hz,, 500Hz]$.
- Velocity Boundary Condition: The surface S of the sphere has a boundary velocity condition with $v_0=1e-3mms^{-1}$.
- Normalized Admittance Boundary Condition: Both boundaries $\Gamma_1$ and $\Gamma_2$ have a normalized admittance boundary condition. The values for each boundary is sampled uniformly and individually from the interval $[0,, 1]\times [0i,, 1i]$.
- Samples: The train dataset contains a total of 4096 samples and the test dataset 512 samples.
- Mesh: Gmsh is used to create the mesh and parameters were chosen to ensure at least 15 elements per wavelength for the highest frequency. The mesh is created once and used for every sample.
Generation Method
To define, assemble, and solve the problem, we use the DOLFINx FEM framework. DOLFINx serves as the computational environment of FEniCSx, representing the next generation of FEniCS. FEniCSx implements a substantial user interface that allows for defining the PDE and its boundary conditions in the Unified Form Language (UFL) format, assembling the problem, specifying a solver and its options, solve and writing the solution to files. It benefits from a large community and stands as one of the most popular open-source alternatives to commercial software like COMSOL. The solution process involves multiple steps:
- Mesh Loading: The mesh is created using the Gmsh API and is then imported into DOLFINx, along with the previously defined tags for cells and boundaries.
- Function Space Definition: The function space on which the trail and test functions are defined is a Lagrange space of degree 2. Additionally, a second Lagrange function space of degree 1 is defined, facilitating saving the solution to simpler file formats, as higher order elements are not supported by all output schemes.
- Defining the Linear Problem: The linear problem is defined using the weak fromulation of the Helmholtz equation in ufl.
- Solving the System: A “preonly” Krylov method with a Cholesky preconditioner, and the MUltifrontal Massively Parallel sparse direct Solver (MUMPS) algorithm, a parallel sparse direct solver, is employed ensuring efficient and precise solutions.
- Output Saving: Solutions are saved to the hierarchical ADIOS2 native binary-pack (bp version 4) format. Detailed implementations can be found on GitHub. Refer to the GitHub repository https://github.com/JakobEliasWagner/Helmholtz-Pulsating-Sphere.
Usage
The dataset is saved in the hierarchical ADIOS2 native binary-pack (bp version 4) format. The solution p is a complex valued function saved in p_real and p_imag. As the domain is symmectric (indicated by dash-dotted lines) only one quarter of the domain is simulated and saved to file. The saved data is the upper right (first) quadrant.
References
[DOLFINx] Igor A. Baratta, Joseph P. Dean, Jørgen S. Dokken, Michal Habera, Jack S. Hale, Chris N. Richardson, Marie E. Rognes, Matthew W. Scroggs, Nathan Sime, and Garth N. Wells. DOLFINx: the next generation FEniCS problem solving environment.
[Gmsh] Christophe Geuzaine and Jean-Fran¸cois Remacle. Gmsh: A 3-d finite element mesh generator with built-in pre-and post-processing facilities. 79(11):1309–1331. Publisher: Wiley Online Library.
[Acoustics] Steffen Marburg and Bodo Nolte. Computational acoustics of noise propagation in fluids: finite and boundary element methods, volume 578. Springer.
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