Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
Exception:    SplitsNotFoundError
Message:      The split names could not be parsed from the dataset config.
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 290, in _generate_tables
                  pa_table = paj.read_json(
                      io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
                  )
                File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
                  raise convert_status(status)
              pyarrow.lib.ArrowInvalid: JSON parse error: Column(/fixtures/[]/time/[]) changed from array to string in row 0
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                                         ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 101, in _split_generators
                  pa_table = next(iter(self._generate_tables(**splits[0].gen_kwargs, allow_full_read=False)))[1]
                             ~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 304, in _generate_tables
                  batch = json_encode_fields_in_json_lines(original_batch, json_field_paths)
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 111, in json_encode_fields_in_json_lines
                  examples = [ujson_loads(line) for line in original_batch.splitlines()]
                              ~~~~~~~~~~~^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 20, in ujson_loads
                  return pd.io.json.ujson_loads(*args, **kwargs)
                         ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
              ValueError: Expected object or value
              
              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 68, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                               ~~~~~~~~~~~~~~~~~~~~~~~^
                      path=dataset,
                      ^^^^^^^^^^^^^
                      config_name=config,
                      ^^^^^^^^^^^^^^^^^^^
                      token=hf_token,
                      ^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
                  info = get_dataset_config_info(
                      path,
                  ...<6 lines>...
                      **config_kwargs,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, 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.

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Rumi API Fixtures

A small, deterministic collection of Earth-observation arrays encoded as Rumi files.

This repository exists to test the Rumi API and its stateless remote range reads through Karu. It is not a training dataset, a scientific benchmark, or a general-purpose imagery archive.

What this dataset tests

The fixtures cover:

  • complete and windowed reads;
  • band selection and ordering;
  • temporal selection;
  • batch reads with rumi.read_many;
  • different Rumi frame layouts;
  • signed and unsigned integer types;
  • single-band, multiband, and high-dimensional arrays;
  • geospatial and temporal metadata;
  • HTTP Range reads from Hugging Face.

Repository structure

data/             Rumi containers
headers/          external binary headers required for remote reads
verify/           local and Hugging Face verification programs
manifest.json     source identity, storage metadata, and expected results
checksums.sha256  SHA-256 checksums for every container and header
SOURCE_DATA.md    source attribution and licensing notes

Each .rumi file has a corresponding external header. The manifest records its original EarthCompress sample, logical shape, data type, frame layout, tile size, metadata, and checksums.

Reading a fixture

from pathlib import Path

import rumi
from huggingface_hub import hf_hub_download

repo = "asterisk-labs/rumi-api-fixtures"
name = "s2-00-tile"

header_path = hf_hub_download(
    repo_id=repo,
    repo_type="dataset",
    filename=f"headers/{name}.header",
)

header = Path(header_path).read_bytes()
image = rumi.read(
    f"hf://datasets/{repo}/data/{name}.rumi",
    header,
    bands=[0, 3],
    window=(0, 0, 256, 256),
)

print(image.shape)

For reproducible tests, replace the default repository revision with a pinned commit or release tag.

Fixtures

Fixture Source corpus Purpose
s2-00-tile Sentinel-2 L1C Window and band-selective reads
s2-01-tile Sentinel-2 L1C Batch reads
s2-02-tile Sentinel-2 L1C Batch reads
s2-00-planar Sentinel-2 L1C Planar frame layout
s2-00-chunky Sentinel-2 L1C Pixel-interleaved frame layout
era5-t2m-00-time ERA5 Temporal selections and ragged edges
alphaearth-00 AlphaEarth Signed int8 with 64 bands
emit-00 EMIT L2A Signed int16 with 285 bands
s1-00 Sentinel-1 GRD Signed radar values
worldcover-00 ESA WorldCover Single-band categorical data

The three encodings of s2-00 contain the same logical array. They are intentionally repeated to verify that frame layout changes storage and range behavior without changing decoded results.

Verification

Validate the generated files locally:

python verify/verify_local.py

After publication, validate actual remote range reads:

python verify/verify_huggingface.py --revision main

The remote verifier downloads only the manifest and the small external headers through huggingface_hub. Rumi reads the selected array windows directly from the remote .rumi objects.

Data provenance

The arrays are selected from the EarthCompress benchmark corpora. Their values are preserved; only their storage representation changes when encoded as Rumi files.

manifest.json identifies the exact source corpus and sample for every fixture and preserves the original array checksum. See SOURCE_DATA.md for the required source attributions.

Licensing

The underlying observations remain subject to the terms of their respective data providers. The applicable attribution and redistribution notes are recorded in SOURCE_DATA.md.

Scope

These fixtures are deliberately small and are not statistically representative of their source datasets. Passing these tests establishes API and format compatibility; it does not measure compression performance or scientific fitness.

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