Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
Exception:    SplitsNotFoundError
Message:      The split names could not be parsed from the dataset config.
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 289, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                                         ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 64, in _split_generators
                  with h5py.File(first_file, "r") as h5:
                       ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/h5py/_hl/files.py", line 564, in __init__
                  fid = make_fid(name, mode, userblock_size, fapl, fcpl, swmr=swmr)
                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/h5py/_hl/files.py", line 238, in make_fid
                  fid = h5f.open(name, flags, fapl=fapl)
                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                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 "h5py/h5f.pyx", line 102, in h5py.h5f.open
              FileNotFoundError: [Errno 2] Unable to synchronously open file (unable to open file: name = 'hf://datasets/FluidVerse/LIDE@727a8f22a60a7b2d85cdd498db6a2f3be4877259/LIDE_train/train.h5.part0', errno = 2, error message = 'No such file or directory', flags = 0, o_flags = 0)
              
              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 65, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                               ^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 343, in get_dataset_split_names
                  info = get_dataset_config_info(
                         ^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 294, 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.

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Description:

This Dataset includes 128 trajectories of time-dependent Laser-Induced Droplet Explosion (LIDE). Using a Finite Volume solver, we solve the two-dimensional (2D) axisymmetric compressible Euler equations for this multiphase problem.

  • dataset_name: Laser-Induced Droplet Explosion,
  • PDE: 2D axisymmetric compressible Euler equations,
  • created: 08-2025,
  • time_dependent: true,
  • include_initial_state: true,

Spatiotemporal Information:

  • num_trajectories: 128,
  • num_time_steps: 201,
  • num_channels: 6,
  • channel_names: ["density", "pressure", "velocity_x", "velocity_y", "schlieren", "energy"],
  • spatial_dimensions: 2,
  • spatial_grid_size: [256, 256],
  • dx=dy: 1.250000000e-07

Boundary conditions:

  • west: Axisymmetric,
  • east: ZeroGradient,
  • south: Symmetry,
  • north: ZeroGradient

Two separet files, "train.h5" and "test.h5", are provided. The former includes 96 trajectories for training and validation; the latter covers the 32 remaining trajectories for inference only.

Refer to the "metadat_LIDE.json" file for more details on the dataset.

A sample Out-of-Distribution, "OOD.h5", is added as well, which covers higher pressure values across 32 trajectories. For more details, refer to "metadata_LIDE_OOD.json".

Download:

The dataset can be downloaded, e.g., via huggingface-cli download.

huggingface-cli download FluidVerse/LIDE --repo-type dataset --local-dir <LOCAL_DIR>

Assembly:

After download, data parts for each file, train.h5, test.h5, or OOD.h5, can be assembled into a single HDF5 file using the provided assemble.py script. Use it as follows:

python ./assemble.py --folder_path <FOLDER_PATH> --output_path <OUTPUT_PATH>

Extra Data Generation:

Use the instructions inside the generation script, "generator.py", for creating larger datasets. This script runs the solver specified in the "metadata_LIDE.json" file.

Strict Licensing Notice:

This dataset is released under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0) and is exclusively for non-commercial research and educational purposes. Any commercial use—including, but not limited to, training machine learning models, developing generative AI tools, creating software products, or other commercial R&D applications—is strictly prohibited.

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