ObservationDefinition#

class ObservationDefinition(*, dut_field, value, unit, uncertainty=None, invalid=False, dut_label, source, tags=[])#

The content of the observation definition.

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.

Attributes

`model_config`	Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
`dut_label`	DUT label of the device the observation is about.
`source`	How the observation was made, e.g. experiment analysis or manual specification.
`tags`	Human-readable tags of the observation.
`dut_field`	Name of the property the observation is about.
`value`	Value of the observation.
`unit`	SI unit of the value.
`uncertainty`	Uncertainty of the observation value.
`invalid`	Flag indicating if the observation is invalid.

Methods

Parameters:

source: dict[str, Any]#: How the observation was made, e.g. experiment analysis or manual specification. source always has the key "type" whose str value determines the other contents of the dict. The currently supported source types are: - analysis_source - configuration_source - measurement_source - sequence_analysis_source - specification_source

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].

ObservationDefinition