FITS Image — float32 with NaN and Inf Pixels (.fits)
Single-precision FITS pixels including two NaNs, which is the only way the standard marks undefined data for floating BITPIX, plus one +Inf. Statistics computed without NaN-aware reductions come back as NaN for the entire frame.
| Pixel | Value | Meaning |
|---|---|---|
| [0,0] | NaN | undefined — the only blank convention legal for float BITPIX |
| [15,23] | NaN | undefined |
| [8,12] | +Inf | saturated / overflowed, still a legal IEEE-754 value |
| all others | 120 to 1500 | flux density in Jy/beam |
Specifications
- Bitpix
- -32
- Nan Pixels
- 2
- Inf Pixels
- 1
- Bunit
- Jy/beam
- Byte Order
- big-endian IEEE-754
- Total Pixels
- 384
Testing contract
Expected to pass- Scenario
- Read the array and compute the minimum, maximum and mean using NaN-aware reductions.
- Expected result
- Exactly two pixels are NaN and one is +Inf; NaN-aware statistics return finite minimum and mean while a plain mean over the raw array returns NaN.
What is a .fits file?
FITS (.fits, Flexible Image Transport System) is the standard binary format in astronomy. It pairs human-readable 80-character header cards (in 2880-byte blocks) with binary image or table data, storing pixel arrays, coordinates, and instrument metadata. It has been the astronomical archive format for decades.
How to use this file
Use an example .fits file to test FITS readers (astropy, CFITSIO, DS9), header-card parsing, and image or table extraction, or to verify block-alignment handling.
How to use this file for testing
“FITS Image — float32 with NaN and Inf Pixels (.fits)” is a deterministic Novus Examples fixture for Scientific data, Serialization testing, 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: FITS · 5,760 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.
Related files
- fitsFITS Header-Only — Valid File With No Pixels (.fits)A completely valid FITS file consisting of one 2880-byte header block and no data unit, which the standard permits whenever NAXIS is 0. It separates readers that model the data array as optional from readers that treat 'no pixels' as corruption.
- binDICOM-Shaped Stream — No Preamble, No DICM Magic (.bin)The identical element stream with the 128-byte preamble and the DICM magic stripped, which is how DICOM often arrives out of a network transfer or a database blob column. It is not a conformant Part 10 file and its content is entirely recoverable, so a reader should fall back rather than reject.
- h5HDF5 Degenerate Shapes — Scalar, Zero-Length and Null (.h5)Five degenerate but entirely legal datasets — a rank-0 scalar, a zero-length vector, a (0, 5) array, a single-element vector and a NULL dataspace — plus an empty group. None of them is corrupt, and a reader that reports them as errors is the thing being tested.
- h5HDF5 Hard, Soft and Dangling Links (.h5)One array reachable under four names: itself, a hard link sharing its object address, a soft link resolved at access time, and a soft link pointing nowhere. A walker that counts names instead of object addresses reports four arrays and then crashes on the dangling one.
- h5HDF5 Numeric dtype Zoo — Every Width at Its Limits (.h5)Twelve datasets, one per numeric HDF5 type, each holding the extreme values of that type including the uint64 and int64 limits that do not survive a trip through a double. It is the fixture that exposes a reader which widens everything to float64 on the way in.
- ncNetCDF _FillValue, missing_value and NaN Together (.nc)One variable that hides absent data three different ways at once: two _FillValue cells, one legacy missing_value cell and one raw NaN, with valid_min and valid_max also declared. Averaging the raw array without honouring all three gives roughly -60 K instead of a real mean.
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