signal_quality

signal_quality ¤

SignalQualityEvents ¤

SignalQualityEvents(
    dataframe: DataFrame,
    signal_uuid: str,
    *,
    event_uuid: str = "quality:signal",
    value_column: str = "value_double",
    time_column: str = "systime"
)

Bases: Base

Quality: Signal Quality Monitoring

Detect data quality issues in a numeric signal: missing data, irregular sampling, out-of-range values, and data completeness.

Methods: - detect_missing_data: Find gaps exceeding expected sampling frequency. - sampling_regularity: Inter-sample interval statistics per window. - detect_out_of_range: Flag values outside physical/expected bounds. - data_completeness: Percentage of expected samples received per window.

detect_missing_data ¤

detect_missing_data(
    expected_freq: str = "1s", tolerance_factor: float = 2.0
) -> pd.DataFrame

Find gaps where time between samples exceeds expected frequency.

Parameters:

Name	Type	Description	Default
`expected_freq`	`str`	Expected sampling frequency (e.g. '1s', '100ms').	`'1s'`
`tolerance_factor`	`float`	Multiplier on expected_freq to trigger a gap.	`2.0`

Returns:

Type	Description
`DataFrame`	DataFrame with columns: gap_start, gap_end, gap_duration,
`DataFrame`	expected_samples_missing.

sampling_regularity ¤

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

Inter-sample interval statistics per window.

Parameters:

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

Returns:

Type	Description
`DataFrame`	DataFrame with columns: window_start, mean_interval, std_interval,
`DataFrame`	min_interval, max_interval, regularity_score.

detect_out_of_range ¤

detect_out_of_range(
    min_value: float, max_value: float
) -> pd.DataFrame

Flag intervals where signal is outside expected range.

Parameters:

Name	Type	Description	Default
`min_value`	`float`	Minimum acceptable value.	required
`max_value`	`float`	Maximum acceptable value.	required

Returns:

Type	Description
`DataFrame`	DataFrame with columns: start_time, end_time, duration,
`DataFrame`	min_observed, max_observed, direction.

data_completeness ¤

data_completeness(
    window: str = "1h", expected_freq: str = "1s"
) -> pd.DataFrame

Percentage of expected samples actually received per window.

Parameters:

Name	Type	Description	Default
`window`	`str`	Resample window.	`'1h'`
`expected_freq`	`str`	Expected sampling frequency.	`'1s'`

Returns:

Type	Description
`DataFrame`	DataFrame with columns: window_start, expected_count,
`DataFrame`	actual_count, completeness_pct.