QualityMetrics

class QualityMetrics(*, observation_set_type, observation_ids, describes_id=None, invalid=False, dut_label, observation_set_id, created_timestamp, end_timestamp, observations, calibration_set)

Bases: ObservationSetWithObservations

The content of the quality metric set stored in the database, with a list of observations and calibration set.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Module: iqm.station_control.interface.models.observation_set

Attributes

model_config	Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
calibration_set
observations	Observations belonging to the observation set.
dut_label	String representation of the DUT the observation set is associated with.
observation_set_id	Unique identifier of the observation set.
created_timestamp	Time when the object was created in the database.
end_timestamp	Time when the observation set was finalized.
observation_set_type	Indicates the type (i.e. purpose) of the observation set.
observation_ids	Database IDs of the observations belonging to the observation set.
describes_id	Unique identifier of the observation set this observation set describes.
invalid	Flag indicating if the object is invalid.

Methods

Parameters:

• observation_set_type (Literal['calibration-set', 'characterization-set', 'generic-set', 'quality-metric-set']) –

• observation_ids (list[int]) –

• describes_id (UUID | None) –

• invalid (bool) –

• dut_label (str | None) –

• observation_set_id (UUID) –

• created_timestamp (datetime) –

• end_timestamp (datetime | None) –

• observations (list[ObservationLite]) –

• calibration_set (ObservationSetData) –

model_config: ClassVar[ConfigDict] = {'extra': 'ignore', 'ser_json_inf_nan': 'constants', 'validate_assignment': True, 'validate_default': True}

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