NaN Payloads and Signalling NaNs (.npy)
Six distinct NaN bit patterns — quiet, signalling, signed and payload-carrying — stored as float64. They are all NaN and none equals another, so any code that deduplicates, sorts or hashes them by value is doing something undefined and this array proves it.
| Index | Bits | Kind |
|---|---|---|
| 0 | 0x7ff8000000000000 | canonical quiet NaN |
| 1 | 0x7ff8000000beef01 | quiet NaN with a payload |
| 2 | 0xfff8000000000000 | negative quiet NaN |
| 3 | 0x7ff0000000000001 | signalling NaN |
| 4 | 0xfff0000000000001 | negative signalling NaN |
| 5 | 0x7ff7ffffffffffff | signalling NaN, maximal payload |
Specifications
- Dtype
- float64
- Elements
- 6
- Quiet Na Ns
- 3
- Signalling Na Ns
- 3
- All Compare Unequal To Themselves
- true
- Note
- every element is NaN, and no two are the same 64 bits
Testing contract
Expected to pass- Scenario
- Load the array, confirm every element is NaN, and compare the underlying 64-bit patterns for uniqueness.
- Expected result
- All six elements report as NaN and none compares equal to itself, yet the six bit patterns are pairwise distinct — a value-based deduplication collapses them to one.
What is a .npy file?
NPY is NumPy's native binary format for a single array. A short header records the dtype, shape, and memory order, followed by the raw array bytes, so an array round-trips exactly without any text parsing. It is the standard way to persist embeddings, tensors, and numeric matrices in the Python data stack.
How to use this file
Use an example .npy to test array loaders (numpy.load), tensor and embedding pipelines, and converters between .npy, JSON, and columnar formats like Parquet.
How to use this file for testing
“NaN Payloads and Signalling NaNs (.npy)” is a deterministic Novus Examples fixture for Scientific data, Error handling. 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: NPY · 176 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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