Json Decoded-Result Reference For The Hdf5 Hierarchy And Its Normalisation Invariant
JSON decoded-result reference for the HDF5 hierarchy and its normalisation invariant, kept beside the binary source for semantic rather than byte-level comparison. Stable P8 artifact p8-convert-hdf5-expected.
{
"datasets": [
{
"path": "/raw/detector_counts",
"shape": [
32,
8
],
"units": "counts"
},
{
"path": "/raw/timestamp_s",
"shape": [
32
],
"units": "s"
},
{
"path": "/processed/normalised",
"shape": [
32,
8
],
"units": "1"
},
{
"path": "/metadata/channel_index",
"shape": [
8
],
"units": "1"
}
],
"groups": [
"/raw",
"/processed",
"/metadata"
],
"normalisation": "processed/normalised = raw/detector_counts / 1000"
}
Specifications
- Source Format
- h5
- Delivery Mode
- download-only
- Provider
- converter-v2
- Provenance
- Synthetic deterministic P8 fixture generated by generation/p8_content.py; seed namespace 2026082300
- Fixture Reserve
- convert-v2
Testing contract
Reference control- Scenario
- Validate the decoded HDF5 result against this JSON artifact.
- Expected result
- Three named groups, four datasets, and the divide-by-1000 normalisation rule remain explicit and machine-checkable.
What is a .json file?
JSON (JavaScript Object Notation) is a lightweight, text-based data-interchange format representing objects, arrays, strings, numbers, booleans, and null. It is language-independent, human-readable, and the dominant format for web APIs and configuration. It requires a single well-formed root value.
How to use this file
Use an example JSON file to test parsers and serializers, schema validation, Unicode and number-precision handling, and API request or response processing.
How to use this file for testing
“Json Decoded-Result Reference For The Hdf5 Hierarchy And Its Normalisation Invariant” is a deterministic Novus Examples fixture for Conversion testing, Scientific data, Schema validation. The same content exported across many formats and linked as a group, so you can convert one and diff against the expected twin.
Documented properties for this file: JSON · 614 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.
Code examples
import json
with open("experiment-hierarchy-expected.json") as f:
data = json.load(f)
print(type(data), len(data))Related files
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Generated by generation/p8_content.py. Free for any use, no attribution required — license.