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:
ObservationSetWithObservationsThe 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_setAttributes
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
calibration_setobservationsObservations belonging to the observation set.
dut_labelString representation of the DUT the observation set is associated with.
observation_set_idUnique identifier of the observation set.
created_timestampTime when the object was created in the database.
end_timestampTime when the observation set was finalized.
observation_set_typeIndicates the type (i.e. purpose) of the observation set.
observation_idsDatabase IDs of the observations belonging to the observation set.
describes_idUnique identifier of the observation set this observation set describes.
invalidFlag indicating if the set is invalid.
Methods
- Parameters:
observation_set_type (ObservationSetType)
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].