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Available disaggregation transformations

  • Accumulativedisaggregates data by dividing the values
  • accumulativeReferencePatterndisaggregates data by dividing the values using a pattern of a time series with a smaller time step
  • Closest time stepDisaggregates data by sampling the input values and copying the value from the closest time step.
  • Instantaneousdisaggregates data by sampling the values and optionally interpolate linear
  • MeanToInstantaneousdisaggregates data
  • meanToMeandisaggregates data by sampling and repeating the input data
  • weightsdisaggregate by setting a weight for each output point

The graph below gives an overviews of the results of the different disaggregations available.

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