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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 intervalare within the aggregation period. If no aggregation period is configured, then the aggregation period is equal to the period between the current output time and the previous output time. Alternatively the aggregation period can be configured in the time series set of the output variable. In that case the aggregation period is relative to the current output time and aggregation periods for different output times are allowed to overlap. Using overlapping aggregation periods it is possible to use this transformation to calculate a moving sum. 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 methodtransformation.
| 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 |
|
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