Dataset Viewer
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: CastError
Message: Couldn't cast
meta: struct<variant: string, variant_display: string, stage: string, n_events: struct<dh_m12: int64, dh_0 (... 4733 chars omitted)
child 0, variant: string
child 1, variant_display: string
child 2, stage: string
child 3, n_events: struct<dh_m12: int64, dh_0: int64, dh_p12: int64>
child 0, dh_m12: int64
child 1, dh_0: int64
child 2, dh_p12: int64
child 4, levels: list<item: int64>
child 0, item: int64
child 5, field_labels: struct<z: string, pv_anom: string, pv: string, pv_bar: string, Q: string, w: string, w_adiabatic: st (... 2769 chars omitted)
child 0, z: string
child 1, pv_anom: string
child 2, pv: string
child 3, pv_bar: string
child 4, Q: string
child 5, w: string
child 6, w_adiabatic: string
child 7, w_diabatic: string
child 8, w_qg_diabatic: string
child 9, w_lhr_moist: string
child 10, pv_dt: string
child 11, pv_anom_dt: string
child 12, pv_bar_dt: string
child 13, pv_anom_dx: string
child 14, pv_anom_dy: string
child 15, pv_anom_dp: string
child 16, pv_bar_dx: string
child 17, pv_bar_dy: string
child 18, pv_bar_dp: string
child 19, pv_dx: string
child 20, pv_dy: string
child 21, pv_dp: string
child 22, u: string
child 23, v: string
child 24, u_anom: string
child 25, v_anom: string
child 26, u_bar: string
child 27, v_bar: string
child 28, u_rot_anom: string
...
: double>
child 0, item: double
child 5, phi_lap: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
child 6, weights: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
child 7, mask: list<item: list<item: int64>>
child 0, item: list<item: int64>
child 0, item: int64
child 8, norms: struct<beta: double, ax: double, ay: double, gamma1: double, gamma2: double, sigma: double>
child 0, beta: double
child 1, ax: double
child 2, ay: double
child 3, gamma1: double
child 4, gamma2: double
child 5, sigma: double
child 9, scale_factors: struct<beta: double, ax: double, ay: double, gamma1: double, gamma2: double, sigma: double>
child 0, beta: double
child 1, ax: double
child 2, ay: double
child 3, gamma1: double
child 4, gamma2: double
child 5, sigma: double
variants: list<item: struct<variant: string, display: string, stage: string>>
child 0, item: struct<variant: string, display: string, stage: string>
child 0, variant: string
child 1, display: string
child 2, stage: string
to
{'variants': List({'variant': Value('string'), 'display': Value('string'), 'stage': Value('string')})}
because column names don't match
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 2249, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
meta: struct<variant: string, variant_display: string, stage: string, n_events: struct<dh_m12: int64, dh_0 (... 4733 chars omitted)
child 0, variant: string
child 1, variant_display: string
child 2, stage: string
child 3, n_events: struct<dh_m12: int64, dh_0: int64, dh_p12: int64>
child 0, dh_m12: int64
child 1, dh_0: int64
child 2, dh_p12: int64
child 4, levels: list<item: int64>
child 0, item: int64
child 5, field_labels: struct<z: string, pv_anom: string, pv: string, pv_bar: string, Q: string, w: string, w_adiabatic: st (... 2769 chars omitted)
child 0, z: string
child 1, pv_anom: string
child 2, pv: string
child 3, pv_bar: string
child 4, Q: string
child 5, w: string
child 6, w_adiabatic: string
child 7, w_diabatic: string
child 8, w_qg_diabatic: string
child 9, w_lhr_moist: string
child 10, pv_dt: string
child 11, pv_anom_dt: string
child 12, pv_bar_dt: string
child 13, pv_anom_dx: string
child 14, pv_anom_dy: string
child 15, pv_anom_dp: string
child 16, pv_bar_dx: string
child 17, pv_bar_dy: string
child 18, pv_bar_dp: string
child 19, pv_dx: string
child 20, pv_dy: string
child 21, pv_dp: string
child 22, u: string
child 23, v: string
child 24, u_anom: string
child 25, v_anom: string
child 26, u_bar: string
child 27, v_bar: string
child 28, u_rot_anom: string
...
: double>
child 0, item: double
child 5, phi_lap: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
child 6, weights: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
child 7, mask: list<item: list<item: int64>>
child 0, item: list<item: int64>
child 0, item: int64
child 8, norms: struct<beta: double, ax: double, ay: double, gamma1: double, gamma2: double, sigma: double>
child 0, beta: double
child 1, ax: double
child 2, ay: double
child 3, gamma1: double
child 4, gamma2: double
child 5, sigma: double
child 9, scale_factors: struct<beta: double, ax: double, ay: double, gamma1: double, gamma2: double, sigma: double>
child 0, beta: double
child 1, ax: double
child 2, ay: double
child 3, gamma1: double
child 4, gamma2: double
child 5, sigma: double
variants: list<item: struct<variant: string, display: string, stage: string>>
child 0, item: struct<variant: string, display: string, stage: string>
child 0, variant: string
child 1, display: string
child 2, stage: string
to
{'variants': List({'variant': Value('string'), 'display': Value('string'), 'stage': Value('string')})}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Blocking Composite Viewer Data
This Hugging Face dataset stores compressed JSON payloads for the interactive Blocking Composite Viewer at https://yanxingjianken.github.io/blocking-plots/. The viewer reads these files directly from the dataset repository and renders ERA5 blocking and propagating-anticyclone composites with Plotly.
Contents
blocking/*.json.gz: blocking-anticyclone composites and RWB subcluster composites.prp/*.json.gz: propagating-anticyclone composites and RWB subcluster composites.blocking/_catalog.jsonandprp/_catalog.json: variant/stage catalogs used by the viewer dropdowns.README.md: this dataset card.
The old root-level JSON exports and the stale figures/ directory are cleaned
during the current upload workflow. Publication figures are maintained in the
pvtend source repository instead of this dataset repository.
Workflow
graph TD
A[ERA5 event NPZ patches] --> B[outputs/blowup_scan/exclude_tracks_blocking.csv]
A --> C[outputs/blowup_scan/exclude_tracks_prp.csv]
A --> D[pvtend-pipeline classify]
B --> D
C --> D
D --> E[rwb_variant_tracksets_wavg.pkl]
A --> F[website/build_and_export_clusters.py]
B --> F
C --> F
E --> F
F --> G[website/blocking_export/*.json.gz]
F --> H[website/prp_export/*.json.gz]
G --> I[website/upload_to_hf.py]
H --> I
I --> J[yanxingjianken/blocking-composites]
J --> K[GitHub Pages blocking-plots viewer]
Blowup Track Exclusion
The web export applies the latest blowup-screen CSVs by default:
outputs/blowup_scan/exclude_tracks_blocking.csvoutputs/blowup_scan/exclude_tracks_prp.csv
Those CSVs are generated from per-event NPZ diagnostics by scanning the
QG-omega-related vertical-motion fields and excluding tracks whose any-stage
maximum absolute value exceeds 25 Pa s^-1. Applying the same CSVs during web
export keeps the viewer's All Events count consistent with the screened
production composites and avoids displaying blowup-contaminated composites.
The cluster builder also prefers rwb_variant_tracksets_wavg.pkl by default,
matching the weighted-average RWB classifications used in the production viewer.
Regeneration Commands
Run from the pvtend repository on the HPC system with the blocking micromamba
environment:
cd /net/flood/data2/users/x_yan/pvtend
micromamba run -n blocking python website/build_and_export_clusters.py --event-type blocking
micromamba run -n blocking python website/build_and_export_clusters.py --event-type prp
micromamba run -n blocking python website/upload_to_hf.py --clean-figures
If clustering has already completed and rwb_cluster_variant_tracksets.pkl is
present, resume from the composite-building/export step with parallel workers:
micromamba run -n blocking python website/build_and_export_clusters.py --event-type blocking --resume-from-step5 --n-workers 16
micromamba run -n blocking python website/build_and_export_clusters.py --event-type prp --resume-from-step5 --n-workers 16
To override the automatic exclude CSV lookup, pass --exclude-file to
website/build_and_export_clusters.py.
Viewer Contract
Each {variant}_{stage}.json.gz file contains:
meta.n_events: event counts atdh=-12,dh=0, anddh=+12.coords: relative longitude/latitude grids.dh_m12,dh_0,dh_p12: level-wise composite fields and orthogonal basis payloads.meta.field_labelsandmeta.field_groups: dropdown labels used by the viewer.
The GitHub Pages frontend fetches files from:
https://huggingface.co/datasets/yanxingjianken/blocking-composites/resolve/main/{blocking,prp}/
- Downloads last month
- 53