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java.lang.Objectorg.apache.commons.math.analysis.DividedDifferenceInterpolator
public class DividedDifferenceInterpolator
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 evalution is in PolynomialFunctionLagrangeForm, this class provides an easy-to-use interface to it.
Field Summary | |
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private static long |
serialVersionUID
serializable version identifier |
Constructor Summary | |
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DividedDifferenceInterpolator()
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Method Summary | |
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protected static double[] |
computeDividedDifference(double[] x,
double[] y)
Returns a copy of the divided difference array. |
UnivariateRealFunction |
interpolate(double[] x,
double[] y)
Computes an interpolating function for the data set. |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Field Detail |
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private static final long serialVersionUID
Constructor Detail |
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public DividedDifferenceInterpolator()
Method Detail |
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public UnivariateRealFunction interpolate(double[] x, double[] y) throws DuplicateSampleAbscissaException
interpolate
in interface UnivariateRealInterpolator
x
- the interpolating points arrayy
- the interpolating values array
DuplicateSampleAbscissaException
- if arguments are invalidprotected static double[] computeDividedDifference(double[] x, double[] y) throws DuplicateSampleAbscissaException
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).
x
- the interpolating points arrayy
- the interpolating values array
DuplicateSampleAbscissaException
- if any abscissas coincide
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