Cubic Fitting Method (CUBSPL)
Returns either a derivative of a curve or an interpolated value from a curve or surface. The curve is fit exactly through a set of discrete data points using a standard cubic spline fitting method.
Format
CUBSPL (First Independent Variable, Second Independent Variable, Spline Name, Derivative Order)
Arguments
First Independent Variable | (Required) A real variable that represents the first independent variable of the spline. |
Second Independent Variable | (Optional) A real variable that represents the second independent variable of the spline. |
Spline Name | (Required) The name of the existing data element spline modeling entity that defines the set of discrete data points to be used for the interpolation. |
Derivative Order | (Optional) The order of the derivative to be taken at the interpolated point (integer). The legal values are: ■0 - returns the curve coordinate value ■1 - returns the first derivative ■2 - returns the second derivative Note: Derivative Order may not be specified when interpolating on a surface; that is, when the Second Independent Variable  0. |
Example
A spline, spline_1, is defined with discrete data as shown in the following table. The data is then used to generate the interpolation function using the Cubic spline fitting method. Since the spline defines a curve rather than a surface, the Second Independent Variable must be set to 0.
The following example returns the interpolated value of the spline of displacement over time, to define a motion function:
Motion = CUBSPL(TIME, 0, spline_1)
Independent variable (Time) | Dependent variable (Displacement) |
|---|---|
0 | 100 |
1 | 125 |
2 | 130 |
3 | 80 |
4 | 40 |
5 | 20 |
Spline Defined Based on Tabular Data
