Time series processing tasks (dqa.tasks.time_series)#

ComputeTimestamps(start_name, output_name, ...)

Computes a timestamp data row for a given input data row.

ConstantValuesIntervals(timestamp_name, ...)

Returns a list of intervals in which a time series has a specified constant value.

FilterIntervalList(interval_start, interval_end)


IntervalCoverageScore(a_start, a_end, ...[, ...])

Returns the share of intervals in list a that are covered by intervals of list b to at least a certain threshold.

IntervalIndicator(interval_start, ...)

Computes an indicator function for a list of intervals that can be plotted.

IntervalListDifference(a_start, a_end, ...)

Computes the total length of the intervals of list a that is not contained in the intervals of list b.

MergeSmallTimeGaps(index_name, ...)

For measurements containing time series of one time index, this merges the time indices below a certain threshold while ignoring nan values.

PandasDataFrameTask([index_name, modify_index])

Abstract base class for a task that works on a pandas DataFrame.

PandasSeriesTask([index_name, modify_index])

Abstract base class for a task that works on a pandas Series.

ResampleByTime(sampling_time, ...[, kind])

Resamples a data row with known sampling time to a chosen new sampling time.

SortIntervals(interval_start, interval_end)

Sorts a list of intervals, removes intersections and fills gaps.

SplitByGaps(gap_dataset, gap_beginning, ...)

Splits up one measurement with time series into multiple ones by an additional list of gaps.

SplitByIntervals(timestamp_name, ...[, ...])

Splits time series up using a list of intervals.

SplitMeasurementsByTimeGap(timestamp_name, ...)

Applied to measurements consisting of time series with one common timestamp data row, this task splits up these time series into separate measurements whenever the gap between two consecutive entries exceeds a certain threshold.

WindowSplit(window_length[, overlap, ...])

Splits input arrays into windows of a fixed length.

WindowSplitBySamplingTime(window_length, ...)

Splits input arrays into windows whose length depends on the sampling time.