Available disaggregation transformations
- Accumulative — disaggregates data by dividing the values
- accumulativeReferencePattern — disaggregates data by dividing the values using a pattern of a time series with a smaller time step
- Closest time step — Disaggregates data by sampling the input values and copying the value from the closest time step.
- Instantaneous — disaggregates data by sampling the values and optionally interpolate linear
- MeanToInstantaneous — disaggregates data
- meanToMean — disaggregates data by sampling and repeating the input data
- weights — disaggregate by setting a weight for each output point
The graph below gives an overviews of the results of the different disaggregations available.