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Preview of FITS BINTABLE — Typed Columns with TUNIT (.fits)
fits
8.4 KB
Actual file preview for FITS BINTABLE — Typed Columns with TUNIT (.fits)

FITS BINTABLE — Typed Columns with TUNIT (.fits)

A FITS binary table with four typed columns, big-endian numerics packed with no inter-field padding and TUNIT declaring milli-jansky on the two flux columns. It is the fixture for a table reader that has to build a row struct from TFORM codes rather than guess widths.

File
FITS · Fits · 12 rows
Use case
Scientific dataSerialization testing+1· Conversion set
Preview of FITS BLANK — Undefined Integer Pixels (.fits)
fits
5.6 KB
Actual file preview for FITS BLANK — Undefined Integer Pixels (.fits)

FITS BLANK — Undefined Integer Pixels (.fits)

Integer FITS images mark undefined pixels with the BLANK keyword, and BLANK is compared against the stored value before BZERO and BSCALE are applied. Scale first and the four undefined pixels turn into a perfectly plausible zero, which is the ordering bug this file exists to expose.

File
FITS · Fits
Use case
Scientific dataSerialization testing+1· Conversion set
Preview of FITS Header-Only — Valid File With No Pixels (.fits)
fits
2.8 KB
Actual file preview for FITS Header-Only — Valid File With No Pixels (.fits)

FITS 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.

File
FITS · Fits
Use case
Scientific dataSerialization testing+1· Conversion set
Preview of FITS Image — BITPIX 16 with BZERO Unsigned Trick (.fits)
fits
5.6 KB
Actual file preview for FITS Image — BITPIX 16 with BZERO Unsigned Trick (.fits)

FITS Image — BITPIX 16 with BZERO Unsigned Trick (.fits)

FITS has no unsigned 16-bit type, so unsigned data is stored signed with BZERO = 32768 and recovered as BZERO + BSCALE * stored. Every stored value in this image is negative, so a reader that ignores the scaling returns an entirely negative frame while parsing the file perfectly.

File
FITS · Fits
Use case
Scientific dataSerialization testing· Conversion set
Preview of FITS Image — BITPIX 8 Unsigned Bytes (.fits)
fits
5.6 KB
Actual file preview for FITS Image — BITPIX 8 Unsigned Bytes (.fits)

FITS Image — BITPIX 8 Unsigned Bytes (.fits)

The baseline rung of the BITPIX ladder: a 24x16 synthetic star field stored as unsigned bytes, the one integer width FITS holds without a BZERO shift. Every image in this family carries the same scene so a decoder can be scored across data types.

File
FITS · Fits
Use case
Scientific dataSerialization testing· Conversion set
Preview of FITS Image — float32 with NaN and Inf Pixels (.fits)
fits
5.6 KB
Actual file preview for FITS Image — float32 with NaN and Inf Pixels (.fits)

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.

File
FITS · Fits
Use case
Scientific dataSerialization testing+1· Conversion set
Preview of FITS Image — float64 Double Precision (.fits)
fits
8.4 KB
Actual file preview for FITS Image — float64 Double Precision (.fits)

FITS Image — float64 Double Precision (.fits)

The top rung of the BITPIX ladder, carrying the identical synthetic scene as IEEE-754 doubles with DATAMIN and DATAMAX declared. It is the reference against which the 8-, 16- and 32-bit members of the family are scored for precision loss.

File
FITS · Fits
Use case
Scientific dataSerialization testing· Conversion set
Preview of FITS WCS Header Cards — CSV Reference (.csv)
csv
842 B
Actual file preview for FITS WCS Header Cards — CSV Reference (.csv)

FITS WCS Header Cards — CSV Reference (.csv)

Every header card of the tangent-plane WCS file transcribed to keyword, value and comment columns. Diff a header parser's output against it to prove the parser split each 80-column card at the right places instead of guessing on whitespace.

File
CSV · Fits
Use case
Scientific dataConversion testing+1· Conversion set
Preview of FITS with World Coordinate System — Tangent Plane (.fits)
fits
5.6 KB
Actual file preview for FITS with World Coordinate System — Tangent Plane (.fits)

FITS with World Coordinate System — Tangent Plane (.fits)

A 32-bit integer image carrying a complete tangent-plane WCS: 1-based CRPIX reference pixels, a deliberately negative CDELT1 so right ascension runs the other way, and an ICRS frame. It targets the two mistakes every WCS implementation makes first, the 1-based origin and the flipped axis.

File
FITS · Fits
Use case
Scientific dataSerialization testing+1· Conversion set
Preview of float64 2-D Grid — Exact-Repr CSV Twin (.csv)
csv
1.7 KB
Actual file preview for float64 2-D Grid — Exact-Repr CSV Twin (.csv)

float64 2-D Grid — Exact-Repr CSV Twin (.csv)

Every element of the float64 .npy array written as its shortest round-tripping decimal representation, one row per element in C order. Parsing this text back to float64 reproduces the binary array bit for bit, so it is a usable oracle rather than a lossy printout.

File
CSV · Arrays · 96 rows
Use case
Scientific dataConversion testing+1· Paired fixture
Preview of float64 Subnormal Ladder — Gradual Underflow (.npy)
npy
208 B
Actual file preview for float64 Subnormal Ladder — Gradual Underflow (.npy)

float64 Subnormal Ladder — Gradual Underflow (.npy)

A ten-step ladder from the smallest representable double up across the subnormal boundary into normal range, showing precision degrading to a single significant bit. Any pipeline running with flush-to-zero enabled turns the first eight entries into plain zeros without reporting anything.

File
NPY · Numeric Edges
Use case
Scientific dataError handling· Paired fixture
Preview of float64 Subnormal Ladder — Reference Table (.csv)
csv
865 B
Actual file preview for float64 Subnormal Ladder — Reference Table (.csv)

float64 Subnormal Ladder — Reference Table (.csv)

Each rung of the subnormal ladder with its bit pattern, decimal value, C99 hex float and remaining significant bits, plus the value a flush-to-zero pipeline would produce instead. It makes gradual underflow a table you can diff rather than a behaviour you have to infer.

File
CSV · Numeric Edges · 10 rows
Use case
Scientific dataEditor testing+1· Paired fixture
Preview of float64 to float32 Precision Loss — Paired Array (.npy)
npy
320 B
Actual file preview for float64 to float32 Precision Loss — Paired Array (.npy)

float64 to float32 Precision Loss — Paired Array (.npy)

The precision-loss cases as a two-column float64 array holding the original value beside its float32 round trip, both kept at double width so the difference itself is representable. Subtracting the columns gives the error directly without a second narrowing step.

File
NPY · Numeric Edges
Use case
Scientific dataError handling· Paired fixture
Preview of float64 to float32 Precision Loss — Per-Value Error (.csv)
csv
1.1 KB
Actual file preview for float64 to float32 Precision Loss — Per-Value Error (.csv)

float64 to float32 Precision Loss — Per-Value Error (.csv)

Twelve doubles narrowed to single precision with the absolute, relative and ULP error of each, plus whether the value survived unchanged. It covers the three distinct ways narrowing fails: rounding, overflow to infinity at 1e39, and demotion to a subnormal at 1e-40.

File
CSV · Numeric Edges · 12 rows
Use case
Scientific dataEditor testing+1· Paired fixture
Preview of Floating-Point Summation — Five Orders, Five Answers (.csv)
csv
422 B
Actual file preview for Floating-Point Summation — Five Orders, Five Answers (.csv)

Floating-Point Summation — Five Orders, Five Answers (.csv)

The same 1002 numbers added five different ways, giving results from 0 to 1000 for an exact answer of 1000. Floating-point addition is not associative, and this file is the smallest complete demonstration of what that costs a naive accumulator.

File
CSV · Numeric Edges
Use case
Scientific dataCSV parsing+1· Conversion set
Preview of Genomic Coordinate Conventions — BED versus GFF3 Side by Side (.csv)
csv
274 B
Actual file preview for Genomic Coordinate Conventions — BED versus GFF3 Side by Side (.csv)

Genomic Coordinate Conventions — BED versus GFF3 Side by Side (.csv)

Every interval written in both coordinate conventions with its length, which is identical either way. It is the lookup table for the most common bioinformatics off-by-one, and the length column is what proves a conversion did not quietly change an interval's size.

File
CSV · Bioinformatics · 6 rows
Use case
Scientific dataEditor testing+1· Conversion set
Preview of GFF3 Gene Annotations — 1-Based Inclusive Coordinates (.gff3)
gff3
681 B
Actual file preview for GFF3 Gene Annotations — 1-Based Inclusive Coordinates (.gff3)

GFF3 Gene Annotations — 1-Based Inclusive Coordinates (.gff3)

Seven features on a synthetic contig — two genes, an mRNA, two exons and two CDS records — linked by ID and Parent attributes across both strands. GFF3 coordinates are 1-based and inclusive, which is the fact its BED twin exists to contrast.

File
GFF3 · Bioinformatics
Use case
Scientific dataEditor testing· Paired fixture
Preview of Gravimetric Mass — TSV With Bracketed Units and Spaces in Headers (.tsv)
tsv
625 B
Actual file preview for Gravimetric Mass — TSV With Bracketed Units and Spaces in Headers (.tsv)

Gravimetric Mass — TSV With Bracketed Units and Spaces in Headers (.tsv)

Ten weighings as tab-separated values with headers that contain spaces, brackets and parentheses — 'u(mass) [g]' — the way balance software actually writes them. Column names like these break naive slug-based header handling long before the numbers become a problem.

File
TSV · Measurements · 10 rows
Use case
Scientific dataEditor testing+1· Conversion set
Preview of Gridded Air Temperature — CSV Ground Truth (.csv)
csv
2.5 KB
Actual file preview for Gridded Air Temperature — CSV Ground Truth (.csv)

Gridded Air Temperature — CSV Ground Truth (.csv)

Every value from the CF-1.8 NetCDF grid flattened to one row per cell, with the axis values spelled out in full. Diff a NetCDF-to-table export against this file to prove the reader walked the dimensions in (time, lat, lon) order and did not silently transpose the array.

File
CSV · Gridded · 120 rows
Use case
Scientific dataConversion testing+1· Paired fixture
Preview of GUM-Style Uncertainty Budget — Sources Combined in Quadrature (.csv)
csv
554 B
Actual file preview for GUM-Style Uncertainty Budget — Sources Combined in Quadrature (.csv)

GUM-Style Uncertainty Budget — Sources Combined in Quadrature (.csv)

A five-source uncertainty budget laid out the way the GUM prescribes: each source with its distribution, its divisor, its sensitivity coefficient and its contribution, then the combined and expanded values. Rectangular sources are divided by the square root of three, which is the step budget spreadsheets most often get wrong.

File
CSV · Measurements
Use case
Scientific dataCSV parsing+1· Conversion set
Preview of HDF5 Chunked + gzip + shuffle Filters (.h5)
h5
42.7 KB
Actual file preview for HDF5 Chunked + gzip + shuffle Filters (.h5)

HDF5 Chunked + gzip + shuffle Filters (.h5)

One array stored twice in the same file: chunked with the shuffle and gzip filters applied, and contiguous with no filters at all. Comparing the two proves a reader ran the HDF5 filter pipeline rather than reading raw chunk bytes.

File
H5 · Hdf5
Use case
Scientific dataSerialization testing+1· Conversion set
Preview of HDF5 Compound Record dtype — Mixed Field Types (.h5)
h5
6.3 KB
Actual file preview for HDF5 Compound Record dtype — Mixed Field Types (.h5)

HDF5 Compound Record dtype — Mixed Field Types (.h5)

A compound-dtype dataset mixing an integer key, two float measurements, a fixed-width byte string and a boolean flag in a single record. It is the fixture for readers that must map an HDF5 record type onto a native struct without reordering or repadding the fields.

File
H5 · Hdf5 · 10 records
Use case
Scientific dataSerialization testing+1· Conversion set