rate_of_change

rate_of_change ¤

RateOfChangeEvents ¤

RateOfChangeEvents(
    dataframe: DataFrame,
    signal_uuid: str,
    *,
    event_uuid: str = "eng:rate_of_change",
    value_column: str = "value_double",
    time_column: str = "systime"
)

Bases: Base

Engineering: Rate of Change Events

Detect rapid changes and step jumps in a numeric signal.

Methods: - detect_rapid_change: Flag intervals where rate of change exceeds threshold. - rate_statistics: Per-window rate of change statistics. - detect_step_changes: Sudden value jumps within a short duration.

detect_rapid_change ¤

detect_rapid_change(
    threshold: float, window: str | None = None
) -> pd.DataFrame

Flag intervals where rate of change exceeds threshold.

Each run of consecutive samples whose absolute rate is at or above threshold becomes one interval.

Parameters:

Name	Type	Description	Default
`threshold`	`float`	Minimum absolute rate (units/second) to flag.	required
`window`	`str \| None`	Deprecated and not used: the rate is always computed between consecutive samples. Passing any value emits a `DeprecationWarning`. Filter the result on `duration_seconds` to drop short intervals.	`None`

Returns:

Type	Description
`DataFrame`	DataFrame with columns: start, end, duration_seconds, uuid,
`DataFrame`	source_uuid, max_rate, direction.

rate_statistics ¤

rate_statistics(window: str = '1h') -> pd.DataFrame

Per-window rate of change statistics.

Parameters:

Name	Type	Description	Default
`window`	`str`	Resample window.	`'1h'`

Returns:

Type	Description
`DataFrame`	DataFrame with columns: start, end, duration_seconds, mean_rate,
`DataFrame`	std_rate, max_rate, min_rate. `end` is `start` + `window`.

detect_step_changes ¤

detect_step_changes(
    min_delta: float, max_duration: str = "5s"
) -> pd.DataFrame

Detect sudden value jumps within a short duration.

Parameters:

Name	Type	Description	Default
`min_delta`	`float`	Minimum absolute value change to qualify.	required
`max_duration`	`str`	Maximum time window for the step to occur.	`'5s'`

Returns:

Type	Description
`DataFrame`	DataFrame with columns: systime, uuid, source_uuid, time, start,
`DataFrame`	end, value_before, value_after, delta, duration,
`DataFrame`	duration_seconds. `systime` and `end` equal `time` (the
`DataFrame`	instant after the jump; `time` is a deprecated twin), `start`
`DataFrame`	is the sample before the jump, and `duration_seconds` is the
`DataFrame`	float-seconds twin of the Timedelta `duration`.