AkimaSplineInterpolator (Apache Commons Math 4.0-SNAPSHOT)

java.lang.Object
- org.apache.commons.math4.legacy.analysis.interpolation.AkimaSplineInterpolator

All Implemented Interfaces:

UnivariateInterpolator
```
public class AkimaSplineInterpolator
extends Object
implements UnivariateInterpolator
```
Computes a cubic spline interpolation for the data set using the Akima algorithm, as originally formulated by Hiroshi Akima in his 1970 paper "A New Method of Interpolation and Smooth Curve Fitting Based on Local Procedures." J. ACM 17, 4 (October 1970), 589-602. DOI=10.1145/321607.321609 http://doi.acm.org/10.1145/321607.321609
This implementation is based on the Akima implementation in the CubicSpline class in the Math.NET Numerics library. The method referenced is "CubicSpline.InterpolateAkimaSorted".

When the argument to the constructor is true, the weights are modified in order to smooth out spurious oscillations.

The interpolate method returns a PolynomialSplineFunction consisting of n cubic polynomials, defined over the subintervals determined by the x values, x[0] < x[i] ... < x[n]. The Akima algorithm requires that n >= 5.

Constructor Summary

Constructors
Constructor Description

AkimaSplineInterpolator()
Uses the original Akima algorithm.

AkimaSplineInterpolator(boolean useModified)

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`PolynomialSplineFunction`	`interpolate(double[] xvals, double[] yvals)`	Computes an interpolating function for the data set.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
  - AkimaSplineInterpolator
```
public AkimaSplineInterpolator()
```
    Uses the original Akima algorithm.
  - AkimaSplineInterpolator
```
public AkimaSplineInterpolator(boolean useModified)
```
    Parameters:
    
    useModified - Whether to use the modified Akima interpolation.
- Method Detail
  - interpolate
```
public PolynomialSplineFunction interpolate(double[] xvals,
                                            double[] yvals)
                                     throws DimensionMismatchException,
                                            NumberIsTooSmallException,
                                            NonMonotonicSequenceException
```
    Computes an interpolating function for the data set.
    
    Specified by:
    
    interpolate in interface UnivariateInterpolator
    
    Parameters:
    
    xvals - the arguments for the interpolation points
    
    yvals - the values for the interpolation points
    
    Returns:
    
    a function which interpolates the data set
    
    Throws:
    
    DimensionMismatchException - if xvals and yvals have different sizes.
    
    NonMonotonicSequenceException - if xvals is not sorted in strict increasing order.
    
    NumberIsTooSmallException - if the size of xvals is smaller than 5.