Difference between revisions of "CubicInterp"
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[[Image:Cubicinterp-graph.png]] | [[Image:Cubicinterp-graph.png]] | ||
| − | = | + | A cubic interpolation can vary wildly from the actual values of the data points. In the above graph, all the ''r'' values are positive, yet the interpolation is as small as -22.5 around x=33. Even if the ''r'' values are monotonically increasing, this does not mean that the cubic interpolation will be monotonically increasing. The [[MonoCubicInterp]] function is a variation that provides a guarantee of monotonicity. |
| − | + | = Library = | |
| + | |||
| + | Array functions | ||
= See also = | = See also = | ||
Revision as of 02:57, 12 August 2008
CubicInterp(d,r,x,I)
Returns the natural cubic spline interpolated values of r along d, interpolating for values of X. The points (r,d) that get interpolated are indexed by I. The values of d must be ascending. The index I is optional when d and r have only one index is common; however, it is recommended that you explicitly specify I, since this will enable your expression to array-abstract if any dimension is ever added to d and r in the future.
Null values are allowed in d and r only in releases later than 4.1.1 (not including 4.1.1). Points having either d or r equal to null are ignored. When x is null, the result is null.
A cubic interpolation can vary wildly from the actual values of the data points. In the above graph, all the r values are positive, yet the interpolation is as small as -22.5 around x=33. Even if the r values are monotonically increasing, this does not mean that the cubic interpolation will be monotonically increasing. The MonoCubicInterp function is a variation that provides a guarantee of monotonicity.
Library
Array functions
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