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Description and usage

This transformation function is used to fill inner gaps in a time series. The inner gaps are filled with linearly interpolated data values.

A gap is defined as a number of consecutive values that are unreliable or missing. An inner gap is defined as a gap for which there is at least one reliable or doubtful value before the gap and at least one reliable or doubtful value after the gap. This function fills only inner gaps.

Each inner gap is filled using linear interpolation between the value just before the gap and the value just after the gap.

calculate the average value of an input time series (grid or scalar) within the area of a polygon of the output time series.

This transformation can handle three types of input:

• scalar
• regular grid
• irregular grid

When the input is a scalar time series the average value for a certain polygon in the output will be calculated by finding the points in the input time series which are within the area of the polygon and calculate the average value of these points. When the input is a time series with a grid (regular or irregular) the transformation will determine which cells of the input time series have an overlap with the output polygon and the average value of these cells will be calculated. The average value will be a weighted average. The weight of each input cell wil be based on how much area of the input polygon covers a certain part of the output polygon.

The output time series can be a output time series with polygons or a regular grid.

The configurator has the possibility to configure a minimum or a maximum value for the output of the transformation. If the output exceeds the minimum or maximum value configured the output will truncated to the minimum or maximum value configuredThis function has an option to define the maximum length of the gaps that should be filled. Gaps that are equal to or smaller than the defined maximum gap length will be filled with interpolated values. Gaps that are larger than the defined maximum gap length will not be filled.

Input/Output time series

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• inputVariable: A time series with input values. This will typically contain inner gapscan be a scalar time series or time series with a regular/irregular grid.
• outputVariable: A time series in which the output will be stored. The output series will contain all input values and the inner gaps will be filledtime series can be a time series with polygons or with a regular grid.

Configuration

A basic configuration of the function is described below. This describes the main elements and attributes required and provides an example configuration.

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outputVariable
Required element defining the identifier of the output time series with output values. This Id must reference a valid output time series.maxGapLength

minimumValue

Optional element defining the minimum value of the output time series. If the output value is lower than the configured minimum value the output value will be equal to the configured minimum value.

maximumValue

Optional element defining the maximum value of the input time series. If the output value is higher than the configured maximum value the output value will be equal to the configured maximum value.  maximum length of gaps that should be filled. The length is equal to the number of time steps. Gaps equal to or smaller than maxGapLength will be filled with interpolated values. Gaps larger than maxGapLength will not be filled. If maxGapLength is not defined, then all gaps will be filled with interpolated values.

Example

<transformation id="interpolation serial linear">
	<interpolationSerial>
<interpolationSpatial>

	<average>

		<linear><minimumValue>0</minimumValue>

		<maximumValue>20000</maximumValue>

		<inputVariable>

				<variableId>input</variableId>

			</inputVariable>
			<maxGapLength>5</maxGapLength>
			<outputVariable>

				<variableId>output</variableId>

			</outputVariable>

		</linear>average>

</transformation>interpolationSpatial>

Common issues

None reported.

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