Parameters¶

Note

For the HDF5 data format and file I/O see Data. For pipeline operations see Pipeline.

Parameters in the file¶

Every zea HDF5 file stores all parameters needed to process the acquisition alongside the raw data. They are split into two groups:

Probe (probe/): Fixed for the whole acquisition — element geometry, center frequency, bandwidth, lens properties. Shared across all tracks. Defined by ProbeSpec.
Scan (scan/): Per-track transmit sequence — delays, apodizations, angles, waveforms, sound speed. Each track has its own ScanSpec.

See the Group reference table for the complete field listing.

zea.Parameters¶

load_parameters() merges the probe and scan groups into a single Parameters object and adds derived quantities (wavelength, n_tx, grid, xlims/zlims, selected_transmits):

with zea.File("data.hdf5") as f:
    parameters = f.load_parameters()             # single-track
    parameters = f.tracks[0].load_parameters()   # multi-track

Config¶

A config is a YAML file (loaded as Config) that specifies where the data lives, the pipeline to run, the device to use, and any parameter overrides.

>>> from zea import Config
>>> from zea.config import check_config

>>> config = Config.from_path("../configs/config_picmus_rf.yaml")
>>> config = check_config(config)   # fills defaults, validates
>>> config.pipeline.operations
['demodulate',
 {'name': 'downsample', 'params': {'factor': 4}},
 {'name': 'beamform', 'params': {'beamformer': 'delay_and_sum', 'enable_pfield': False, 'num_patches': 200}},
 'envelope_detect',
 'normalize',
 'log_compress']

>>> config.to_yaml("my_config.yaml")

Supported keys¶

data — where to find the file

Key	Default	Description
`path`	`null`	Full path to the HDF5 file. Supports local absolute paths, paths relative to the user data root (set in `users.yaml`), and Hugging Face Hub paths (`hf://org/repo/path/to/file.hdf5`).
`local`	`true`	Whether to use local data (`true`) or a network/NAS location (`false`).
`indices`	`null`	Which frames to load: `null` (default), `'all'`, a single `int`, or a list of positive ints.

parameters — override any field from the Group reference or pass custom keys straight through to the pipeline:

parameters:
  center_frequency: 5.0e6
  xlims: [-0.02, 0.02]
  grid_size_x: 512

pipeline — list of operations (see Pipeline):

Key	Default	Description
`operations`	`[identity]`	Ordered list of operations. Each entry is either an operation name (string) or a mapping with `name` and optional `params`.
`jit_options`	`'ops'`	JIT scope: `'ops'` (compile each op), `'pipeline'` (compile the whole pipeline), or `null` (disable JIT).
`with_batch_dim`	`true`	Whether operations expect a leading batch dimension.

Top-level keys

Key	Default	Description
`device`	`'auto:1'`	Target hardware: `cpu`, `gpu`, `cuda`, `gpu:0`, `auto:1` (auto-select; `-1` for last device).
`hide_devices`	`null`	Device indices to exclude from auto-selection (int or list of ints).
`git`	`null`	Git commit or branch recorded for reproducibility.

The top-level config is open: arbitrary extra sections (model:, etc.) are accepted and passed through unchanged.

API reference¶

zea.Config([dictionary, __parent__])

Config class.

zea.config.check_config(config, verbose=False)[source]: Check a config given dictionary