The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 153, in compute
compute_split_names_from_info_response(
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 125, in compute_split_names_from_info_response
config_info_response = get_previous_step_or_raise(kind="config-info", dataset=dataset, config=config)
File "/src/libs/libcommon/src/libcommon/simple_cache.py", line 591, in get_previous_step_or_raise
raise CachedArtifactError(
libcommon.simple_cache.CachedArtifactError: The previous step failed.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 499, in get_dataset_config_info
for split_generator in builder._split_generators(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 99, in _split_generators
inferred_arrow_schema = pa.concat_tables(pa_tables, promote_options="default").schema
File "pyarrow/table.pxi", line 5317, in pyarrow.lib.concat_tables
File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
pyarrow.lib.ArrowTypeError: Unable to merge: Field sign.pth has incompatible types: int32 vs list<item: float>
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 71, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 572, in get_dataset_split_names
info = get_dataset_config_info(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 504, 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.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.
astrophysics astroparticle simulation timeseries point-cloud
Dataset Card for FACT Open Crab Sample
Dataset Summary
This is a mirror of the Open Crab Sample released by the FACT collaboration, containing simulations of astroparticle events as seen by the FACT telescope from the CORSIKA simulation program, as well as a few nights of observations of the Crab Nebula over 2013 and 2014. The simulation data is in two formats, the photon stream format, as well as a preprocessed version containing extracted features, and cleaned point clouds, which were performed with various levels of DBSCAN. The observations are all the raw data, with no cleaning or extracted features.
Supported Tasks and Leaderboards
- 'classification': Classification of simulated events as either hadron or gamma events.
- 'regression': Predicting the energy of the initial energy of the simulated events, or where in the night sky the original particle originated
Languages
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Dataset Structure
Data Instances
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Data Fields
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Data Splits
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Dataset Creation
Curation Rationale
The goal of the Open Crab Sample is to open up astroparticle data for exploring different ways of doing analysis.
Source Data
Initial Data Collection and Normalization
The initial simulated data was generated by the CORSIKA simulation program. The observations were taken by the FACT telescope on La Palma between 2013 and 2014. The data is not normalized.
Who are the source language producers?
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Annotations
Annotation process
The simulations were annotated from the ground truth in the simulation, while the observations have no ground truths.
Who are the annotators?
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Personal and Sensitive Information
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Considerations for Using the Data
Social Impact of Dataset
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Discussion of Biases
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Other Known Limitations
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Additional Information
Dataset Curators
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Licensing Information
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Citation Information
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