Package tsdb.iterator

Provides iterators for time series data processing.

See: Description

Interface Summary

Interface	Description
ApplyIterator.ApplyFunc
CollectingAggregator	Interface for collecting aggregators

Class Summary

Class	Description
AbstractAggregationIterator	Base class for aggregation iterators.
AbstractCollectingAggregator	Base class for collecting aggregators
ApplyIterator	Apply a function to every entry in input_iterator.
AverageIterator	This iterator outputs elements of average values of input_iterator values.
BadInterpolatedRemoveIterator	Processed all interpolated values and removes all values that are of low quality.
BaseAggregationIterator	BaseAggregationIterator aggregates input elements to aggregated output elements with base aggregation time intervals
DayAggregationIterator	Aggregate hour data to day data.
DayCollectingAggregator	collecting aggregator to day
DifferenceIterator	Calculates difference between input_iterator and compare_iterator, corrected by reference values
DifferentialIterator	Calculates difference between consecutive time stamps
ElementCopyIterator	Copies value data to different columns.
ElementCopyIterator.Action	Action defines one copy operation from one column to an other column for all entries in iterator.
EmpiricalIterator	This iterator checks values of input_iterator by comparing values to compare_iterator.
EvaluatingAggregationIterator	Evaluates collections from CollectingAggregator to statics: min, max, median, quantiles
InterpolationAverageLinearIterator	Interpolates missing data values in iterator with interpolated data from other iterators with avarege of multiple linear regressions.
LinearIterpolationIterator	Linear interpolates one-value-gaps based on previous and next value.
MaskIterator	Replaces data values with NaN-values based on TimeSeriesMask.
MergeIterator	Merges multiple iterators into one by time stamp.
MiddleIterator	This iterator outputs elements of average values of input_iterator values.
MinDiffIterator	This iterator outputs minimum difference elements of input_iterators to one target_iterator.
MonthAggregationIterator	Aggregate day data to month data.
MonthCollectingAggregator	collecting aggregator to month
NanGapIterator	This iterator fills gaps in input_iterator with NaN rows.
NanRemoveIterator	Sends only input elements to output that have at least one not NaN-value in data.
PeakSmoothIterator	This iterator fills manually inserted sensor data with averaged values.
ProjectionFillIterator	Transforms from input schema to ouput schema output schema does not need to be subset of input schema (with arbitrary order) If some parameter in output schema is not in input schema -> column will be filled with Na-values.
ProjectionIterator	converts input schema to output schema output schema needs to be subset of input schema (with arbitrary order)
SunshineIterator	fills sunshine columns with calculated values from Rn_300 column. 1: sunhine at this point in time 0: no sunshine at this point in time
SunshineOlivieriIterator
WeekAggregationIterator	Aggregate day data to week data.
WeekCollectingAggregator	collecting aggregator to week
YearAggregationIterator	Aggregate month data to year data.
YearCollectingAggregator	collecting aggregator to year

Enum Summary

Enum	Description
PeakSmoothIterator.FillType

Package tsdb.iterator Description

Provides iterators for time series data processing.

Graph nodes use this iterators for processing. So the preferred way to process time series data is to build a graph of processing nodes instead of directly using iterators.