omero_data.OmeroData

Dataclass to store all the data related to the omero project and plate.

Usage

Source

omero_data.OmeroData(
    well_pos_list=list(),
    image_input=str(),
    image_index=list(),
    screen_dataset=_DatasetWrapper(),
    plate_id=int(),
    plate_name=str(),
    plate=_PlateWrapper(),
    plate_data=pl.LazyFrame(),
    data_path=get_data_path(),
    csv_path=Path(),
    flatfield_masks=(lambda: np.empty((0,)))(),
    pixel_size=None,
    channel_data=dict(),
    intensities=dict(),
    crop_start=tuple(),
    crop_length=tuple(),
    well_list=list(),
    well_id_list=list(),
    well_metadata_list=list(),
    well_ifdata=pl.DataFrame(),
    well_image_index=list(),
    images=(lambda: np.empty((0,)))(),
    image_ids=list(),
    image_positions=list(),
    labels=(lambda: np.empty((0,)))(),
    label_stitched_mode=False,
    stitched_images=(lambda: np.empty((0,)))(),
    cropped_images=list(),
    cropped_labels=list(),
    cropped_cell_meta=list(),
    selected_images=list(),
    selected_labels=list(),
    selected_crops=list(),
    selected_classes=list(),
    selected_cell_meta=list(),
    session_file_path=None
)

Parameter Attributes

well_pos_list: list[str] = list()

image_input: str = str()

image_index: list[int] = list()

screen_dataset: _DatasetWrapper = _DatasetWrapper()

plate_id: int = int()

plate_name: str = str()

plate: _PlateWrapper = _PlateWrapper()

plate_data: pl.LazyFrame = pl.LazyFrame()

data_path: Path = get_data_path()

csv_path: Path = Path()

flatfield_masks: NDArray[Any] = (lambda: np.empty((0,)))()

pixel_size: Optional[tuple[float, float]] = None

channel_data: dict[str, Any] = dict()

intensities: dict[int, Any] = dict()

crop_start: tuple[int, …] = tuple()

crop_length: tuple[int, …] = tuple()

well_list: list[_WellWrapper] = list()

well_id_list: list[int] = list()

well_metadata_list: list[dict[str, Any]] = list()

well_ifdata: pl.DataFrame = pl.DataFrame()

well_image_index: list[int] = list()

images: NDArray[Any] = (lambda: np.empty((0,)))()

image_ids: list[int] = list()

image_positions: list[tuple[float, float] | None] = list()

labels: NDArray[Any] = (lambda: np.empty((0,)))()

label_stitched_mode: bool = False

stitched_images: NDArray[Any] = (lambda: np.empty((0,)))()

cropped_images: list[NDArray[Any]] = list()

cropped_labels: list[NDArray[Any]] = list()

cropped_cell_meta: list[dict[str, Any]] = list()

selected_images: list[NDArray[Any]] = list()

selected_labels: list[NDArray[Any]] = list()

selected_crops: list[NDArray[Any]] = list()

selected_classes: list[str] = list()

selected_cell_meta: list[dict[str, Any]] = list()

session_file_path: Optional[Path] = None

Methods

Name	Description
reset_well_and_image_data()	Resets the well and image data to their default states.

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reset_well_and_image_data()

Resets the well and image data to their default states.

Usage

Source

reset_well_and_image_data()