Search files, editable visual templates, and live browser targets from one registry-backed directory. Filtered query views stay crawlable for links but are deliberately noindex; the stable taxonomy pages below remain the canonical search surfaces.
Page 3 of 6; 24 results per page.
Eight levels of nested groups, each holding a dataset whose values equal its own depth. Any tree walk that caps recursion depth or flattens names silently loses the lower levels, and the depth-valued arrays make that immediately visible.
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.
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.
A three-group HDF5 file laid out the way a real bench run is — raw arrays, a processed derivative that names its source in a derived_from attribute, and a metadata group — with units on every dataset. It is the walk-the-tree fixture: a reader has to recurse rather than assume a flat namespace.
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.
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.
Fixed-width byte strings, variable-length UTF-8 strings and UTF-8 attribute text in one file, including Greek, CJK and combining diacritics. HDF5 hands fixed-width strings back as padded bytes and variable-length ones as decoded text, and conflating the two is where string handling usually breaks.
Four measured quantities where the uncertainty lives in dataset attributes rather than a parallel column, with the coverage factor spelled out so k=1 and k=2 values cannot be confused. It is the fixture for a pipeline that must propagate uncertainty it read from metadata.
A single-data-block CIF describing an idealised rock-salt lattice: cell parameters, space group, a symmetry-operation loop and an atom-site loop with fractional coordinates and occupancies. The '?' in the temperature field is CIF's marker for unknown, which is not the same as an empty value.
The float32 boundary values split into sign, 8-bit exponent and 23-bit mantissa alongside their decimal forms. Use it to check a single-precision encoder field by field rather than guessing which end of the number went wrong.
The single-precision counterpart of the float64 boundary array, including the 2^24 integer limit where consecutive whole numbers stop being representable. Widening float32 to float64 and back must preserve every one of these bit patterns.
Every value in the float64 boundary array decomposed into its shortest decimal representation, its C99 hexadecimal float form, and its raw sign, exponent and mantissa fields. It turns 'the numbers came back wrong' into a diff you can point at a single bit.
The same boundary values as strict RFC 8259 JSON, where non-finite numbers are null in the numeric field and text in the string field because the standard has no NaN or Infinity literal. It is the fixture for the encoder that emits bare NaN and produces JSON nothing else will parse.
The sixteen structurally distinct float64 values a numeric pipeline has to survive, in binary form: both zeros, both subnormal limits, the smallest normal, epsilon, the largest finite value, both infinities, a quiet NaN and the 2^53 integer boundary. Round-tripping this array is the minimum bar for any float64 codec.
Six large integers written both as JSON numbers and as strings, including the 2^53 boundary where consecutive integers stop being distinguishable in a double. A parser backed by doubles turns 9007199254740993 into 9007199254740992 and reports no error at all.
An intentionally corrupt DICOM-shaped file whose header, meta group and every non-pixel element are valid, and whose PixelData element declares a length the file does not contain. A viewer must report the short read rather than render a partial image padded with whatever it found.
An intentionally corrupt FASTQ whose first five records are complete and whose sixth ends after the plus line, leaving no quality string. A four-line-block reader must report an incomplete final record rather than pairing the sequence with an empty quality string.
An intentionally corrupt FITS file whose header is complete and whose data unit is cut short, leaving a total length that is not a multiple of the mandatory 2880-byte block. A reader must report the short read rather than hand back a half-filled array padded with whatever it found.
An intentionally corrupt HDF5 file cut to 1024 bytes, so the 8-byte signature and superblock survive while the object headers and B-trees they point at do not. Format sniffing will say HDF5 and opening must fail loudly, which is exactly the split this fixture measures.
An intentionally corrupt Matrix Market file whose banner and size line are perfectly valid and whose entry block stops seven lines short of the declared count. A reader that preallocates from the declared count and never checks ends up with seven silent zeros.
An intentionally corrupt molfile whose counts line declares twelve atoms while the atom block contains nine, so a parser reading by count consumes three bond lines as atoms. Everything else about the file is well formed, which is what makes the failure quiet.
An intentionally corrupt NetCDF file, cut to its first 512 bytes so the magic number and part of the header survive but the variable table and every data value do not. It is the fixture for the failure path where format detection succeeds and reading must not.
Six fictional laboratories reporting the same measurand, scored both by z-score against a fixed sigma and by En number against each lab's own claimed uncertainty. The two statistics disagree about which labs are acceptable, which is the point: En rewards an honest uncertainty claim and z does not.
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.
We use Google Analytics and show ads via Adsterra. Non-essential cookies and ad scripts run only after you allow the matching categories. See our cookie policy.
