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experiment_acquisition#

zen_api_utils.experiment_acquisition #

Typed acquisition metadata extracted from a ZEN experiment.

Classes:

Functions:

AcquisitionDimensions dataclass #

AcquisitionDimensions(time_points: int, channels: int, z_planes: int, scenes: int, z_spacing: float = 1.0, tiles: int = 1, pixel_width: int | None = None, pixel_height: int | None = None)

Acquisition axes known before pixel streaming starts.

AcquisitionChannel dataclass #

AcquisitionChannel(name: str | None, pixel_type: str | None)

An active acquisition channel.

ExperimentAcquisition dataclass #

ExperimentAcquisition(experiment_name: str | None, dimensions: AcquisitionDimensions, channels_info: tuple[AcquisitionChannel, ...], positions: tuple[dict[str, object], ...], split_scenes_in_separate_files: bool)

Small typed snapshot of the acquisition settings used by streaming.

Attributes:

  • well_ids (tuple[str, ...]) –

    Unique sample-carrier well IDs in acquisition order.

  • well_count (int) –

    Number of sample-carrier wells used for acquisition.

  • position_count (int) –

    Number of active acquisition positions/scenes.

well_ids property #

well_ids: tuple[str, ...]

Unique sample-carrier well IDs in acquisition order.

well_count property #

well_count: int

Number of sample-carrier wells used for acquisition.

position_count property #

position_count: int

Number of active acquisition positions/scenes.

query_experiment_acquisition async #

query_experiment_acquisition(service: ExperimentServiceStub, experiment_id: str, experiment_name: str | None = None) -> ExperimentAcquisition

Export and parse a loaded experiment through the ZEN API.

load_experiment_acquisition async #

load_experiment_acquisition(service: ExperimentServiceStub, experiment_name: str) -> ExperimentAcquisition

Load an experiment by name, export it, and return its acquisition data.