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keywords: | transformation, spatial interpolation, inverse distance |
Description and usage
This transformation function calculates the output based on the weighted average of the closest input locations/grid cells. The weight of each input location/grid cell will be calculated by the inverse distance of each location.
This transformation can handle four types of input:
- scalar time series
- regular grid
- irregular grid
- longitudinal profile
The output can be a:
- scalar time series
- regular grid
- irregular grid
- longitudinal profile
If the time series is not a scalar time series the centre of the grid cell will be used when trying to find the closest input location/grid cell.
When a longitudinal profile is used the profile is considered to be a scattered grid.
The configurator has the possibility to configure a minimum and maximum value for the output. If the output exceeds the minimum or maximum value the output is truncated to that value.
It is also possible to maximize the search radius in which the transformation searches for the closest input location/grid cell. This can be done by setting the searchRadius in the configuration.
The weight of each input value in the output is computed by the inverse distance from the input location/grid cell to the output location/grid cell. The power to which the inverse distance is raised in this calcuation can be configured. It is also possible to configure the maximum total number of input values which are used to calculate the output. First the transformation will try to find the closest input locations/grid cells which should be used in the calculation. If one or more values in the input values of these time series are missing values, the transformation will not search for the next closest locations/grid cells but will ignore these values in the calculation. For each input polygon this transformation copies the value of the input polygon to all output points that are inside the input polygon. If an output point is not contained in any input polygon, then the output is a missing value.”
Input/Output time series
In this function one input time series and one output time series must be identified.
- inputVariable: a time series with input values. This can Thismust be a scalar time series , longitudinal profile or a time series with a regular/irregular gridwith polygons.
- outputVariable: a time series in which the output will be stored. This can be a scalar time series, longitudinal profile or a time series with a regular/irregular grid.
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