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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 1 new columns ({'constraints'})
This happened while the csv dataset builder was generating data using
hf://datasets/ClarusC64/fusion-confinement-collapse-horizon-and-control-routing-v0.1/data/test.csv (at revision 605899345404ec7ee3f796f87332072ec13b9a17), [/tmp/hf-datasets-cache/medium/datasets/73447319861263-config-parquet-and-info-ClarusC64-fusion-confinem-33e5e975/hub/datasets--ClarusC64--fusion-confinement-collapse-horizon-and-control-routing-v0.1/snapshots/605899345404ec7ee3f796f87332072ec13b9a17/data/test.csv (origin=hf://datasets/ClarusC64/fusion-confinement-collapse-horizon-and-control-routing-v0.1@605899345404ec7ee3f796f87332072ec13b9a17/data/test.csv)]
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 "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1887, in _prepare_split_single
writer.write_table(table)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 675, in write_table
pa_table = table_cast(pa_table, self._schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
id: string
scenario: string
total_heating_mw: double
line_avg_density_1e19m3: double
core_temp_kev: double
tau_e_ms: int64
baseline_expected_tau_e_ms: int64
collapse_risk_score: double
precursor_pattern_type: string
primary_driver: string
collapse_horizon_ms: double
reversible_flag: double
recommended_control_route: double
expected_tau_e_recovery_ms: double
stability_margin: double
notes: string
constraints: string
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 2498
to
{'id': Value('string'), 'scenario': Value('string'), 'total_heating_mw': Value('float64'), 'line_avg_density_1e19m3': Value('float64'), 'core_temp_kev': Value('float64'), 'tau_e_ms': Value('int64'), 'baseline_expected_tau_e_ms': Value('int64'), 'collapse_risk_score': Value('float64'), 'precursor_pattern_type': Value('string'), 'primary_driver': Value('string'), 'collapse_horizon_ms': Value('int64'), 'reversible_flag': Value('int64'), 'recommended_control_route': Value('string'), 'expected_tau_e_recovery_ms': Value('int64'), 'stability_margin': Value('float64'), 'notes': Value('string')}
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 1347, 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 980, in convert_to_parquet
builder.download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 884, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 947, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1736, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1889, 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 1 new columns ({'constraints'})
This happened while the csv dataset builder was generating data using
hf://datasets/ClarusC64/fusion-confinement-collapse-horizon-and-control-routing-v0.1/data/test.csv (at revision 605899345404ec7ee3f796f87332072ec13b9a17), [/tmp/hf-datasets-cache/medium/datasets/73447319861263-config-parquet-and-info-ClarusC64-fusion-confinem-33e5e975/hub/datasets--ClarusC64--fusion-confinement-collapse-horizon-and-control-routing-v0.1/snapshots/605899345404ec7ee3f796f87332072ec13b9a17/data/test.csv (origin=hf://datasets/ClarusC64/fusion-confinement-collapse-horizon-and-control-routing-v0.1@605899345404ec7ee3f796f87332072ec13b9a17/data/test.csv)]
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.
id string | scenario string | total_heating_mw float64 | line_avg_density_1e19m3 float64 | core_temp_kev float64 | tau_e_ms int64 | baseline_expected_tau_e_ms int64 | collapse_risk_score float64 | precursor_pattern_type string | primary_driver string | collapse_horizon_ms int64 | reversible_flag int64 | recommended_control_route string | expected_tau_e_recovery_ms int64 | stability_margin float64 | notes string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
FCCH-001 | early_drift_low_risk | 10.5 | 3.7 | 6.7 | 192 | 200 | 0.35 | slope_collapse | transport | 720 | 1 | adjust_heating_mix | 10 | 0.62 | Small drift, recoverable |
FCCH-002 | drift_density_driven | 11 | 4.8 | 6.3 | 205 | 230 | 0.55 | density_transport_divergence | density | 540 | 1 | density_reduction | 18 | 0.55 | Back off density to restore response |
FCCH-003 | pedestal_erosion_mid | 13 | 3.9 | 7 | 230 | 250 | 0.58 | pedestal_erosion | edge | 480 | 1 | magnetic_shear_tweak | 22 | 0.5 | Edge support weakening |
FCCH-004 | radiation_lock_mid | 12.5 | 4.2 | 6.8 | 220 | 245 | 0.6 | radiation_lock | impurity | 420 | 1 | impurity_control | 20 | 0.46 | Reduce impurity load |
FCCH-005 | turbulence_onset_high | 14 | 3.8 | 7.2 | 240 | 270 | 0.72 | turbulence_onset | transport | 300 | 1 | power_ramp_down | 15 | 0.38 | Avoid pushing into collapse |
FCCH-006 | control_phase_lag_high | 14 | 3.5 | 7.1 | 245 | 268 | 0.7 | control_latency_phase_lag | control | 270 | 1 | control_gain_retune | 12 | 0.4 | Fix loop latency |
FCCH-007 | response_inversion_acute | 15 | 4.4 | 6.9 | 225 | 280 | 0.85 | response_inversion | transport | 180 | 0 | power_ramp_down | 5 | 0.22 | Inversion underway, limited recovery |
FCCH-008 | near_greenwald_break | 14 | 5.1 | 6.4 | 205 | 275 | 0.9 | response_inversion | density | 150 | 0 | density_reduction | 6 | 0.18 | Density cliff, rapid collapse |
FCCH-009 | impurity_spike_acute | 13.5 | 4.6 | 6.5 | 210 | 265 | 0.88 | radiation_lock | impurity | 165 | 0 | impurity_control | 7 | 0.2 | Impurity rise drives loss |
FCCH-010 | late_stage_unstable | 12 | 4.9 | 6.2 | 200 | 260 | 0.92 | response_inversion | transport | 120 | 0 | power_ramp_down | 4 | 0.14 | Collapse imminent |
What this dataset tests
Control routing.
Given a detected confinement decoupling pattern, forecast how soon performance collapse becomes inevitable, and choose the minimal control action that restores coherence.
This is the third layer of COH-FUSION-002.
Inputs
total_heating_mw line_avg_density_1e19m3 core_temp_kev tau_e_ms baseline_expected_tau_e_ms
collapse_risk_score precursor_pattern_type primary_driver
Required output
Return JSON
collapse_horizon_ms reversible_flag recommended_control_route expected_tau_e_recovery_ms stability_margin
Example { "collapse_horizon_ms": 180, "reversible_flag": 0, "recommended_control_route": "density_reduction", "expected_tau_e_recovery_ms": 6, "stability_margin": 0.18 }
Control routes
adjust_heating_mix density_reduction magnetic_shear_tweak impurity_control power_ramp_down control_gain_retune
Field meaning
collapse_horizon_ms Estimated time to confinement performance collapse.
reversible_flag 1 = coherent basin can be recovered with intervention 0 = collapse likely irreversible without major reset
expected_tau_e_recovery_ms Predicted improvement of tau_E after the recommended action.
stability_margin 0..1 margin to collapse after the recommended action.
Version
v0.1
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