HDF5 Dimension Scales Attached to a 3-D Array (.h5)
The CF NetCDF grid expressed with HDF5's own dimension-scale mechanism, so each axis of the 3-D array points at a real coordinate dataset through DIMENSION_LIST references. It lets a reader be tested on scale resolution instead of on filename conventions.
| Axis | Scale dataset | Label | units |
|---|---|---|---|
| 0 | /time | time | hours since 2026-01-01 00:00:00 |
| 1 | /lat | lat | degrees_north |
| 2 | /lon | lon | degrees_east |
Specifications
- Array
- tas float32 (4, 5, 6)
- Scales
- 3
- Labels
- time, lat, lon
- Mechanism
- H5DS dimension scales (DIMENSION_LIST / REFERENCE_LIST)
- Same Values As
- sci-nc-cf-grid
Testing contract
Expected to pass- Scenario
- Read the tas dataset and resolve the dimension scale attached to each of its three axes.
- Expected result
- Axis 0 resolves to /time with label 'time', axis 1 to /lat and axis 2 to /lon, and the coordinate values equal those of the paired CF NetCDF file.
What is a .h5 file?
HDF5 (.h5) is a binary container format for large, heterogeneous scientific data. It stores multidimensional arrays (datasets) in a hierarchical group structure with attributes and chunked, compressed storage, and is standard in ML, physics, and geoscience.
How to use this file
Use an example .h5 file to test HDF5 readers (h5py, PyTables), group and dataset traversal, and attribute extraction.
How to use this file for testing
“HDF5 Dimension Scales Attached to a 3-D Array (.h5)” is a deterministic Novus Examples fixture for Scientific data, Serialization testing. Citation catalogs (BibTeX, RIS), chemistry structures (MDL Molfile, PDB), and gridded binary data (NetCDF, FITS) — for testing reference managers, molecule viewers, and scientific-data loaders.
Documented properties for this file: H5 · 9,624 bytes. Compare results against paired or grouped companions on this page when present (clean↔damaged, searchable↔scanned, or format twins) so scores stay reproducible across runs.
Download the file once, keep the path stable in CI or local scripts, and treat the spec table as the contract: dimensions, seeds, field lists, and roles are intentional. Corrupt or invalid samples are labelled as such — expect parsers to fail loudly rather than silently accept them.
Scientific fixtures are small, valid, and fully synthetic — no real organism, patient, sample, or observation. Point your parser or loader at the file and check it reads the documented records, variables, or headers; binary formats ship a readable twin or metadata listing for comparison.
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