aggregates data by summing the values
Accumulative
Input
- inputVariable
Output
- outputVariable
Description
This transformation performs an aggregation from an instantaneous time series to an aggregated time series. This procedure sums the values of the input timeseries that fall within the output interval. If one of the input values is missing or unreliable the output is missing. The table below shows an example of accumulating 6-hourly values to daily values using this method.
|
Original series |
Result |
Date/Time |
Value |
Value |
01-01-2007 00:00 |
1,00 |
|
01-01-2007 06:00 |
2,00 |
|
01-01-2007 12:00 |
3,00 |
|
01-01-2007 18:00 |
4,00 |
|
02-01-2007 00:00 |
5,00 |
14,00 |
02-01-2007 06:00 |
6,00 |
|
02-01-2007 12:00 |
NaN |
|
02-01-2007 18:00 |
8,00 |
|
03-01-2007 00:00 |
9,00 |
NaN |
03-01-2007 06:00 |
10,00 |
|
The figure below shows original 15 minute data and the aggregated hourly data using the accumulative function:
Configuration example
<transformation id="aggregation accumulative"> <aggregation> <accumulative> <inputVariable> <timeSeriesSet> <moduleInstanceId>ImportTelemetry</moduleInstanceId> <valueType>scalar</valueType> <parameterId>H.obs</parameterId> <locationSetId>hydgauges</locationSetId> <timeSeriesType>external historical</timeSeriesType> <timeStep unit="minute" multiplier="15"/> <relativeViewPeriod unit="day" startOverrulable="true" start="-7" end="0"/> <readWriteMode>read only</readWriteMode> <delay unit="minute" multiplier="0"/> </timeSeriesSet> </inputVariable> <outputVariable> <timeSeriesSet> <moduleInstanceId>Aggregate_Historic</moduleInstanceId> <valueType>scalar</valueType> <parameterId>accumulative</parameterId> <locationSetId>hydgauges</locationSetId> <timeSeriesType>external historical</timeSeriesType> <timeStep unit="hour" multiplier="1"/> <relativeViewPeriod unit="day" startOverrulable="true" start="-7" end="0"/> <readWriteMode>add originals</readWriteMode> <synchLevel>1</synchLevel> </timeSeriesSet> </outputVariable> </accumulative> </aggregation> </transformation>