bioio.StandardMetadata

class bioio.StandardMetadata(binning: str | None = None, column: str | None = None, dimensions_present: Sequence[str] | None = None, image_size_c: int | None = None, image_size_t: int | None = None, image_size_x: int | None = None, image_size_y: int | None = None, image_size_z: int | None = None, imaged_by: str | None = None, imaging_datetime: datetime | None = None, objective: str | None = None, pixel_size_x: float | None = None, pixel_size_y: float | None = None, pixel_size_z: float | None = None, position_index: int | None = None, row: str | None = None, timelapse: bool | None = None, timelapse_interval: timedelta | None = None, total_time_duration: timedelta | None = None)[source]

A simple container for embedded metadata fields.

Attributes:
binning: Optional[str]

Binning configuration.

column: Optional[str]

Column information.

dimensions_present: Optional[Sequence[str]]

List or sequence of dimension names.

image_size_c: Optional[int]

Channel dimension size.

image_size_t: Optional[int]

Time dimension size.

image_size_x: Optional[int]

Spatial X dimension size.

image_size_y: Optional[int]

Spatial Y dimension size.

image_size_z: Optional[int]

Spatial Z dimension size.

imaged_by: Optional[str]

The experimentalist who produced this data.

imaging_date: Optional[str]

Date this file was imaged.

objective: Optional[str]

Objective.

pixel_size_x: Optional[float]

Physical pixel size along X.

pixel_size_y: Optional[float]

Physical pixel size along Y.

pixel_size_z: Optional[float]

Physical pixel size along Z.

position_index: Optional[int]

Position index, if applicable.

row: Optional[str]

Row information.

timelapse: Optional[bool]

Is the data a timelapse?

timelapse_interval: Optional[timedelta]

Average time interval between timepoints.

total_time_duration: Optional[timedelta]

Total time duration of imaging, measured from the beginning of the first time point to the beginning of the final time point.

FIELD_LABELS: dict[str, str]

Mapping of the above attribute names to readable labels.

__init__(binning: str | None = None, column: str | None = None, dimensions_present: Sequence[str] | None = None, image_size_c: int | None = None, image_size_t: int | None = None, image_size_x: int | None = None, image_size_y: int | None = None, image_size_z: int | None = None, imaged_by: str | None = None, imaging_datetime: datetime | None = None, objective: str | None = None, pixel_size_x: float | None = None, pixel_size_y: float | None = None, pixel_size_z: float | None = None, position_index: int | None = None, row: str | None = None, timelapse: bool | None = None, timelapse_interval: timedelta | None = None, total_time_duration: timedelta | None = None) None

Methods

__init__([binning, column, ...])

to_dict()

Convert the metadata into a dictionary using readable labels.

Attributes