osobhandClaude Opus 5.5
e94a52a88b
Elements of a virtual dataset that no mapping supplies (unmapped regions, a missing source file, a missing source dataset) read as 0 instead of the fill value libhdf5 returns — silent wrong data for any VDS created with a non-zero fillvalue (read-matrix cases 0471/0472: -1 and 7 read as 0). A missing source dataset was an error; libhdf5 reads it as fill. Move VDS assembly into a new vds module following H5Dvirtual.c: vds::read_virtual_dataset takes the dataset's fill value and a VdsFileResolver that can refuse a name, and reports how many elements were unmapped. Sources are read with their own fill value, and a source whose datatype differs from the virtual dataset's is an error (libhdf5 converts). File passes the dataset's fill value, resolves source names against the virtual file's directory, and refuses names that leave it with an error instead of reading them as fill. read_selection on a VDS goes through the same fill-aware path. The raw-read API (read_raw_data_full*) has no fill value, so it now errors for a VDS with unmapped elements instead of guessing zeros. Tests: vds_interop::vds_unmapped_regions_read_as_fill_value (external, same-file, missing file/dataset, sparse source with its own fill, int fill; earliest and latest format) and vds_source_outside_directory_is_an_error_not_fill, both against h5py; integration_test::v4_virtual_dataset_raw_api_refuses_to_guess_the_fill_value. Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
clawhdf5
Pure-Rust HDF5 reader/writer — no C dependencies.
Features
- Read and write HDF5 files entirely in Rust
- Memory-mapped I/O for large files (
mmapfeature, enabled by default) - Parallel chunk reads via Rayon (
parallelfeature) - Lazy dataset access for minimal memory usage
- h5py-compatible file output
Usage
use clawhdf5::File;
let file = File::open("data.h5").unwrap();
let dataset = file.dataset("/group/data").unwrap();
let values: Vec<f64> = dataset.read_1d().unwrap();
License
MIT