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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:    ArrowInvalid
Message:      Float value nan was truncated converting to int64
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 2690, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, 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 494, 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/json/json.py", line 299, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2255, in cast_table_to_schema
                  cast_array_to_feature(
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1804, in wrapper
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2011, in cast_array_to_feature
                  _c(array.field(name) if name in array_fields else null_array, subfeature)
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1806, in wrapper
                  return func(array, *args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2011, in cast_array_to_feature
                  _c(array.field(name) if name in array_fields else null_array, subfeature)
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1806, in wrapper
                  return func(array, *args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2095, in cast_array_to_feature
                  return array_cast(
                         ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1806, in wrapper
                  return func(array, *args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1958, in array_cast
                  return array.cast(pa_type)
                         ^^^^^^^^^^^^^^^^^^^
                File "pyarrow/array.pxi", line 1135, in pyarrow.lib.Array.cast
                File "/usr/local/lib/python3.12/site-packages/pyarrow/compute.py", line 412, in cast
                  return call_function("cast", [arr], options, memory_pool)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "pyarrow/_compute.pyx", line 604, in pyarrow._compute.call_function
                File "pyarrow/_compute.pyx", line 399, in pyarrow._compute.Function.call
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: Float value nan was truncated converting to int64

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smartFRACs - Dataset of flow simulations in single rough fractures

Hugging Face Dataset

A brief description of the dataset, its purpose, and what it contains.

Dataset of lattice Boltzmann and finite volume simulations for single phase laminar flow into single rough fractures.

Dataset Summary

  • Size: [e.g., 10,000 samples]
  • Languages: [e.g., English, Multilingual]
  • Data Type: [e.g., Text, Image, Audio, Tabular]
  • Use Case: [e.g., NLP, Vision, Speech Recognition]
  • Source: [e.g., Collected from ... / Synthesized / Scraped]

How to Use

You can load the dataset using 🤗 datasets:

import os
from huggingface_hub import HfFileSystem
from concurrent.futures import ThreadPoolExecutor

# User configuration:
hf_token = "your_token"

repo_type = "dataset"

# Base local directory to store downloaded data
local_base_dir = "./smartFRACs"

# Initialize Hugging Face Filesystem
fs = HfFileSystem(token=hf_token, repo_type=repo_type)


def download_files(remote_files, local_base):
    os.makedirs(local_base, exist_ok=True)

    def download(remote_file):
        relative_path = remote_file.split(f"datasets/{repo_id}/")[-1]
        local_file_path = os.path.join(local_base, relative_path)
        os.makedirs(os.path.dirname(local_file_path), exist_ok=True)
        fs.get_file(remote_file, local_file_path)
        print(f"Downloaded: {remote_file} to {local_file_path}")

    with ThreadPoolExecutor(max_workers=4) as executor:
        executor.map(download, remote_files)
        
repo_id = "smartFRACs/smartFRACs"
subset="**" # options: basic_LBM...
frac_id="*" # options: frac_001
path=f"datasets/{repo_id}/{subset}/{frac_id}.h5"
print(path)
remote_files = fs.glob(path)
download_files(remote_files, local_base_dir)
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