autoemx.config.schema_models.frames module

Frames acquired on a sample (SampleLedger.frames): one record per frame, with its segmentation results.

autoemx.config.schema_models.frames.FramePurpose

searched for particles to measure by EDS, or by a particle size statistics measurement

Type:

Why a frame was acquired

alias of Literal[‘eds_search’, ‘size_stats’]

class autoemx.config.schema_models.frames.FrameRecord(*, frame_id: str, label: str, purpose: ~typing.Literal['eds_search', 'size_stats'], measurement_id: int | None = None, datetime: str | None = <factory>, center_mm: ~autoemx.config.schema_models.acquisition.Coordinate2D | None = None, frame_width_um: float, pixel_size_um: float, area_um2: float, search_window_um: ~typing.Tuple[float, float], image_file: str | None = None, segmentations: ~typing.List[~autoemx.config.schema_models.segmentation.FrameSegmentation] = <factory>)

Bases: BaseModel

A frame acquired on the sample: what the acquisition fixed (position of its centre on the stage, if known, frame width, pixel size, area and saved image), and the particles found in it by each segmentation (never replaced: segmenting it again adds a result).

frame_id is unique in the ledger and names the image file (<sample>_fr<frame_id>_particles); label is the label of the frame navigation (A0, A0_a0), as in AcquisitionDetails.frame_id of the spectra acquired in it. search_window_um are the particle diameters searched (particle area limits of the acquisition); measurement_id is the particle size statistics measurement that acquired it.

frame_id: str

label: str

purpose: Literal['eds_search', 'size_stats']

measurement_id: int | None

datetime: str | None

center_mm: Coordinate2D | None

frame_width_um: float

pixel_size_um: float

area_um2: float

search_window_um: Tuple[float, float]

image_file: str | None

segmentations: List[FrameSegmentation]

model_config = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod validate_positive(v: float) → float

validate_record() → FrameRecord

segmentation(segmentation_id: int | None) → FrameSegmentation | None

Result of a segmentation of the frame, or None if not segmented with it.

add_segmentation(result: FrameSegmentation) → None

Add the result of a segmentation (one per segmentation id).