linearInterpolateFit#

swordfish.function.linearInterpolateFit()#

Perform linear interpolation/extrapolation on a set of points. Interpolation estimates unknown values that fall between known data points, while extrapolation estimates values beyond the existing data range.

Parameters:

  • X (Constant) – A numeric vector indicating the x-coordinates of the points for interpolation. Note that X must contain no less than two unique values with no null values.

  • Y (Constant) – A numeric vector indicating the y-coordinates of the points for interpolation. Note that Y must be of the same length as X with no null values.

  • fillValue (Constant, optional) –

    Specifies how to assign values for the x-coordinate of the points outside the existing data range. The following options are supported:

    • A numeric pair in the form (min, max), where min and max represent the values assigned when the x-coordinate of the point Xnew is smaller than the minimum of X or larger than the maximum of X, respectively. Specifically:

      • If Xnew < Xmin, it is assigned below.

      • If Xnew > Xmax, it is assigned above.

    • The string “extrapolate” (default), which indicates that extrapolation is performed.

  • sorted (Constant, optional) –

    A Boolean scalar indicating whether the input X is sorted in ascending order.

    • If set to true, X must be in ascending order.

    • If set to false (default), the function will sort X and adjust the order of Y accordingly.

Returns:

A dictionary containing the following keys:

  • modelName: A string indicating the model name, which is “linearInterpolate”.

  • sortedX: A DOUBLE vector indicating the input Xsorted in ascending order.

  • sortedY: A DOUBLE vector indicating the input Y sorted corresponding to sortedX.

  • fillValue: The input fillValue.

  • predict: The prediction function of the model, which returns linear interpolation results. It can be called using model.predict(X) or predict(model, X), where:

    • model: A dictionary indicating the output of linearInterpolateFit.

    • X: A numeric vector indicating the x-coordinates of the points to be predicted.

Return type:

Constant

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