File size: 2,011 Bytes
b64b64f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 | """Lightweight NumPy/h5py reader for the T4 structural-dynamics pilot."""
from __future__ import annotations
import json
from pathlib import Path
import h5py
import numpy as np
DEFAULT_PATH = (
Path(__file__).resolve().parents[1]
/ "data"
/ "t4_structural_dynamics_pilot"
/ "pilot.h5"
)
def trajectory_ids(path: str | Path = DEFAULT_PATH) -> tuple[str, ...]:
with h5py.File(path, "r") as h5:
return tuple(sorted(h5["trajectories"]))
def load_trajectory(
trajectory_id: str,
path: str | Path = DEFAULT_PATH,
*,
include_fields: bool = True,
) -> dict[str, object]:
with h5py.File(path, "r") as h5:
group = h5[f"trajectories/{trajectory_id}"]
arrays = {
name: np.asarray(dataset)
for name, dataset in group.items()
if isinstance(dataset, h5py.Dataset)
}
if include_fields:
arrays["field_time_s"] = np.asarray(group["fields/time_s"])
arrays["displacement_m"] = np.asarray(group["fields/displacement_m"])
arrays["velocity_m_per_s"] = np.asarray(group["fields/velocity_m_per_s"])
arrays["acceleration_m_per_s2"] = np.asarray(
group["fields/acceleration_m_per_s2"]
)
arrays["reference_geometry_m"] = np.asarray(
h5["common/reference_geometry_m"]
)
arrays["topology"] = np.asarray(h5["common/topology"])
arrays["sensor_coordinates_m"] = np.asarray(
h5["common/sensor_coordinates_m"]
)
return {
"trajectory_id": trajectory_id,
"spec": json.loads(group.attrs["spec_json"]),
"attributes": {name: group.attrs[name] for name in group.attrs},
"arrays": arrays,
}
if __name__ == "__main__":
ids = trajectory_ids()
sample = load_trajectory(ids[0], include_fields=False)
print(ids)
print({name: value.shape for name, value in sample["arrays"].items()})
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