JMSLTM Numerical Library 5.0.1

com.imsl.math
Class Spline2DInterpolate

java.lang.Object
  extended by com.imsl.math.Spline2D
      extended by com.imsl.math.Spline2DInterpolate
All Implemented Interfaces:
Serializable, Cloneable

public class Spline2DInterpolate
extends Spline2D

Computes a two-dimensional, tensor-product spline interpolant from two-dimensional, tensor-product data.

The class Spline2DInterpolate computes a tensor-product spline interpolant. The tensor-product spline interpolant to data {(x_i, y_j, f_{ij})}, where 0 le i le (n_x - 1) and 0 le j le (n_y - 1) has the form

sum_{m=0}^{n_y - 1} sum_{n=0}^{n_x-1} c_{nm}B_{n,k_x,t_x}(x) B_{m,k_y,t_y}(y)

where k_x and k_y are the orders of the splines. These numbers are defaulted to be 4, but can be set to any positive integer using xOrder and yOrder in the constructor. Likewise, t_x and t_y are the corresponding knot sequences (xKnots and yKnots). These default values are selected by Spline2DInterpolate. The algorithm requires that

t_x(k_x - 1) le x_i le t_x(n_x),,,,,,,,,,,,,,,0 le i le n_x -1

t_y(k_y - 1) le y_j le t_y(n_y - 1),,,,,,,,,,,0 le j le n_y -1

Tensor-product spline interpolants in two dimensions can be computed quite efficiently by solving (repeatedly) two univariate interpolation problems.

The computation is motivated by the following observations. It is necessary to solve the system of equations

sum_{m=0}^{n_y - 1} sum_{n=0}^{n_x-1} c_{nm}B_{n,k_x,t_x}(x_i) B_{m,k_y,t_y}(y_j) = f_{ij}

Setting

h_{mi} = sum_{n=0}^{n_x-1} c_{nm}B_{n,k_x,t_x}(x_i)

note that for each fixed i from 0 to n_x - 1, we have n_y linear equations in the same number of unknowns as can be seen below:

sum_{m=0}^{n_y - 1} h_{mi}B_{m,k_y,t_y}(y_j) = f_{ij}

sum_{m=0}^{n_y - 1} sum_{n=0}^{n_x-1} c_{nm}B_{n,k_x,t_x}(x_i) B_{m,k_y,t_y}(y_j) = f_{ij}

Setting

h_{mi} = sum_{n=0}^{n_x-1} c_{nm}B_{m,k_x,t_x}(x_i)

note that for each fixed i from 0 to n_x - 1, we have n_y - 1 linear equations in the same number of unknowns as can be seen below:

sum_{m=0}^{n_y - 1} h_{mi}B_{n,k_y,t_y}(y_j) = f_{ij}

The same matrix appears in all of the equations above:

bigl[ B_{m,k_y,t_y}(y_j)bigr],,,,,,,,,,, 0 le m,j le n_y - 1

Thus, only factor this matrix once and then apply this factorization to the n_x right-hand sides. Once this is done and h_{mi} is computed, then solve for the coefficients c_{nm} using the relation

sum_{n=0}^{n_x-1} c_{nm}B_{n,k_x,t_x}(x_i) = h_{mi}

for n from 0 to n_y - 1, which again involves one factorization and n_y solutions to the different right-hand sides. The class Spline2DInterpolate is based on the routine SPLI2D by de Boor (1978, p. 347).

See Also:
Example 1, Example 2, Example 3, Serialized Form

Constructor Summary
Spline2DInterpolate(double[] xData, double[] yData, double[][] fData)
          Constructor for Spline2DInterpolate.
Spline2DInterpolate(double[] xData, double[] yData, double[][] fData, int xOrder, int yOrder)
          Constructor for Spline2DInterpolate.
Spline2DInterpolate(double[] xData, double[] yData, double[][] fData, int xOrder, int yOrder, double[] xKnots, double[] yKnots)
          Constructor for Spline2DInterpolate.
 
Method Summary
 
Methods inherited from class com.imsl.math.Spline2D
derivative, derivative, getCoefficients, getXKnots, getYKnots, value, value
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Constructor Detail

Spline2DInterpolate

public Spline2DInterpolate(double[] xData,
                           double[] yData,
                           double[][] fData)
Constructor for Spline2DInterpolate.

Parameters:
xData - a double array containing the data points in the x-direction.
yData - a double array containing the data points in the y-direction.
fData - a double matrix of size xData.length by yData.length containing the values to be interpolated.

Spline2DInterpolate

public Spline2DInterpolate(double[] xData,
                           double[] yData,
                           double[][] fData,
                           int xOrder,
                           int yOrder)
Constructor for Spline2DInterpolate.

Parameters:
xData - a double array containing the data points in the x-direction.
yData - a double array containing the data points in the y-direction.
fData - a double matrix of size xData.length by yData.length containing the values to be interpolated.
xOrder - an int scalar value specifying the order of the spline in the x-direction. xOrder must be at least 1. Default: xOrder = 4, tensor-product cubic spline.
yOrder - an int scalar value specifying the order of the spline in the y-direction. yOrder must be at least 1. Default: yOrder = 4, tensor-product cubic spline.

Spline2DInterpolate

public Spline2DInterpolate(double[] xData,
                           double[] yData,
                           double[][] fData,
                           int xOrder,
                           int yOrder,
                           double[] xKnots,
                           double[] yKnots)
Constructor for Spline2DInterpolate.

Parameters:
xData - a double array containing the data points in the x-direction.
yData - a double array containing the data points in the y-direction.
fData - a double matrix of size xData.length by yData.length containing the values to be interpolated.
xOrder - an int scalar value specifying the order of the spline in the x-direction. xOrder must be at least 1. Default: xOrder = 4, tensor-product cubic spline.
yOrder - an int scalar value specifying the order of the spline in the y-direction. yOrder must be at least 1. Default: yOrder = 4, tensor-product cubic spline.
xKnots - a double array of size xData.length + xOrder specifying the knot sequences of the spline in the x-direction. Default knot sequences are selected by the class.
yKnots - a double array of size yData.length + yOrder specifying the knot sequences of the spline in the y-direction. Default knot sequences are selected by the class.

JMSLTM Numerical Library 5.0.1

Copyright © 1970-2008 Visual Numerics, Inc.
Built July 8 2008.