m3resp.DerivedFeature#

class m3resp.DerivedFeature(*, feature_id=<factory>, source_signal_ids=<factory>, processing_run_id, feature_name, time_window_start=None, time_window_end=None, value=None, unit=None, quality_flag=None)[source]#

A quantitative result computed from one or more source streams (doc Sec 7.11).

Attributes

`model_config`	Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
`feature_id`
`source_signal_ids`
`processing_run_id`
`feature_name`
`time_window_start`
`time_window_end`
`value`
`unit`
`quality_flag`

Parameters:

feature_id (str)
source_signal_ids (list[str])
processing_run_id (str)
feature_name (str)
time_window_start (float | None)
time_window_end (float | None)
value (float | None)
unit (str | None)
quality_flag (Literal['valid', 'suspect', 'invalid', 'missing'] | None)

feature_id: str#

feature_name: str#

model_config = {'extra': 'forbid'}#: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

processing_run_id: str#

quality_flag: QualityFlag | None#

source_signal_ids: list[str]#

time_window_end: float | None#

time_window_start: float | None#

unit: str | None#

value: float | None#