fr.cnes.sirius.patrius.math.analysis.interpolation

Class DividedDifferenceInterpolator

java.lang.Object

fr.cnes.sirius.patrius.math.analysis.interpolation.DividedDifferenceInterpolator

All Implemented Interfaces:

UnivariateInterpolator, Serializable

public class DividedDifferenceInterpolator
extends Object
implements UnivariateInterpolator, Serializable

Implements the Divided Difference Algorithm for interpolation of real univariate functions. For reference, see Introduction to Numerical Analysis, ISBN 038795452X, chapter 2.

The actual code of Neville's evaluation is in PolynomialFunctionLagrangeForm, this class provides an easy-to-use interface to it.

Since:

1.2

Version:

$Id: DividedDifferenceInterpolator.java 18108 2017-10-04 06:45:27Z bignon $

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
DividedDifferenceInterpolator()

Method Summary

Modifier and Type	Method and Description
protected static double[]	computeDividedDifference(double[] x, double[] y) Return a copy of the divided difference array.
PolynomialFunctionNewtonForm	interpolate(double[] x, double[] y) Compute an interpolating function for the dataset.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

DividedDifferenceInterpolator

public DividedDifferenceInterpolator()

Method Detail

interpolate

public PolynomialFunctionNewtonForm interpolate(double[] x,
                                                double[] y)

Compute an interpolating function for the dataset.

Specified by:

interpolate in interface UnivariateInterpolator

Parameters:

x - Interpolating points array.

y - Interpolating values array.

Returns:

a function which interpolates the dataset.

Throws:

DimensionMismatchException - if the array lengths are different.

NumberIsTooSmallException - if the number of points is less than 2.

NonMonotonicSequenceException - if x is not sorted in strictly increasing order.

computeDividedDifference

protected static double[] computeDividedDifference(double[] x,
                                                   double[] y)

Return a copy of the divided difference array.

The divided difference array is defined recursively by

 f[x0] = f(x0)
 f[x0,x1,...,xk] = (f[x1,...,xk] - f[x0,...,x[k-1]]) / (xk - x0)
 

The computational complexity is O(N^2).

Parameters:

x - Interpolating points array.

y - Interpolating values array.

Returns:

a fresh copy of the divided difference array.

Throws:

DimensionMismatchException - if the array lengths are different.

NumberIsTooSmallException - if the number of points is less than 2.

NonMonotonicSequenceException - if x is not sorted in strictly increasing order.