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Datasets:
huxinchn
/
PIFNO-LAW

Languages:
English
Tags:
physics
pde
pino
fno
neural-operator
burgers-equation
License:
Dataset card Files
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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:      Dataset 't' has length 51 but expected 1024
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 2674, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2208, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2232, 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 483, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, 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 80, in _generate_tables
                  num_rows = _check_dataset_lengths(h5, self.info.features)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 359, in _check_dataset_lengths
                  raise ValueError(f"Dataset '{path}' has length {dset.shape[0]} but expected {num_rows}")
              ValueError: Dataset 't' has length 51 but expected 1024

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📊 Dataset Description

This dataset provides comprehensive one-dimensional inviscid Burgers' equation simulations, explicitly generated for training and evaluating advanced operator learning architectures.

1D Inviscid Burgers' Equation

  • Equation: ∂tu+u∂xu=0\partial_t u + u \partial_x u = 0
  • Initial Conditions: Drawn from a Gaussian Random Field (GRF) with a squared exponential kernel ( l=0.1l=0.1 ).
  • Solver: High-fidelity Fifth-order WENO (WENO5) with an HLL Riemann solver and RK3 time integration.
  • Goal: Evaluate accurate resolution of nonlinear wave steepening and shock formation.

📂 Data Structure

1D Benchmark (burgers.h5)

  • Resolution: 1,024 spatial points, 51 time steps.
  • Fields:
    • x: Spatial grid
    • t: Temporal grid
    • u: Scalar solution field
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