feat: write complex numbers, incl. HDF5 2.0 native complex (class 11)

- Datatype::Complex serializes class 11 version 5 byte-identically to
  libhdf5 2.2.0; containers holding it are written as version 5.
- DatasetBuilder::with_complex_f32/f64_data (h5py's {r, i} compound,
  default) and with_native_complex_f32/f64_data (class 11, opt-in);
  make_(native_)complex_f32/f64_type for attributes.
- Dataset::read_complex_f64/f32 read either form.
- Python create_dataset accepts complex64/complex128 (compound form).
- Parsing unchanged: class 11 still surfaces as {r, i}.
- Tests vs h5py 3.16 / libhdf5 2.0.0 and h5dump 2.2.0; docs.

Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
This commit is contained in:
osobh
2026-09-28 21:25:03 -05:00
co-authored by Claude Opus 5.5
parent bce07e9cb9
commit d0d5347cd9
21 changed files with 790 additions and 24 deletions
+23 -1
View File
@@ -161,6 +161,10 @@ pub(crate) enum DatasetData {
I64(Vec<i64>),
I32(Vec<i32>),
U8(Vec<u8>),
/// numpy `complex64`, `[re, im]` pairs, written as h5py does.
C64(Vec<[f32; 2]>),
/// numpy `complex128`, `[re, im]` pairs, written as h5py does.
C128(Vec<[f64; 2]>),
}
/// Specification for a dataset to be written.
@@ -281,6 +285,14 @@ pub(crate) fn apply_dataset_spec(
DatasetData::U8(v) => {
db.with_u8_data(v);
}
// h5py's compound `{r, i}`, not HDF5 2.0's native complex type: it
// is what h5py writes (3.16 included) and every libhdf5 can read it.
DatasetData::C64(v) => {
db.with_complex_f32_data(v);
}
DatasetData::C128(v) => {
db.with_complex_f64_data(v);
}
}
if !spec.shape.is_empty() {
db.with_shape(&spec.shape);
@@ -314,9 +326,19 @@ pub(crate) fn extract_numpy_data(
"int64" => DatasetData::I64(flat.extract::<Vec<i64>>()?),
"int32" => DatasetData::I32(flat.extract::<Vec<i32>>()?),
"uint8" => DatasetData::U8(flat.extract::<Vec<u8>>()?),
// A 1-D complex array viewed as floats is its (re, im) parts in order.
"complex64" => {
let parts: Vec<f32> = flat.call_method1("view", ("<f4",))?.extract()?;
DatasetData::C64(parts.as_chunks::<2>().0.to_vec())
}
"complex128" => {
let parts: Vec<f64> = flat.call_method1("view", ("<f8",))?.extract()?;
DatasetData::C128(parts.as_chunks::<2>().0.to_vec())
}
_ => {
return Err(PyErr::new::<pyo3::exceptions::PyTypeError, _>(format!(
"unsupported numpy dtype: {dtype_str}; expected float64, float32, int64, int32, or uint8"
"unsupported numpy dtype: {dtype_str}; expected float64, float32, int64, int32, \
uint8, complex64 or complex128"
)));
}
};