Cubic spline data interpolation

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Saturday, November 21, 2009

MATLAB Function Reference spline


Cubic spline data interpolation

Syntax

pp = spline(x,Y)
yy = spline(x,Y,xx)



Description


pp = spline(x,Y) returns the piecewise polynomial form of the cubic spline interpolant for later use with ppval and the spline utility unmkpp. x must be a vector. Y can be a scalar, a vector, or an array of any dimension, subject to the following conditions: If Y is a scalar or vector, it must have the same length as x. A scalar value for x or Y is expanded to have the same length as the other. See Exceptions (1) for an exception to this rule, in which the not-a-knot end conditions are used. If Y is an array that is not a vector, the size of Y must have the form [d1,d2,...,dk,n], where n is the length of x. The interpolation is performed for each d1-by-d2-by-...-dk value in Y. See Exceptions (2) for an exception to this rule.

yy = spline(x,Y,xx) is the same as yy = ppval(spline(x,Y),xx), thus providing, in yy, the values of the interpolant at xx. xx can be a scalar, a vector, or a multidimensional array.The sizes of xx and yy are related as follows: If Y is a scalar or vector, yy has the same size as xx. If Y is an array that is not a vector, If xx is a scalar or vector, size(yy) equals [d1, d2, ..., dk, length(xx)]. If xx is an array of size [m1,m2,...,mj], size(yy) equals [d1,d2,...,dk,m1,m2,...,mj].

Exceptions
If Y is a vector that contains two more values than x has entries, the first and last value in Y are used as the endslopes for the cubic spline. If Y is a vector, this means f(x) = Y(2:end-1) df(min(x)) = Y(1) df(max(x)) = Y(end) If Y is a matrix or an N-dimensional array with size(Y,N) equal to length(x)+2, the following hold: f(x(j)) matches the value Y(:,...,:,j+1) for j=1:length(x) Df(min(x)) matches Y(:,:,...:,1) Df(max(x)) matches Y(:,:,...:,end)

Note You can also perform spline interpolation using the interp1 function with the command interp1(x,y,xx,'spline'). Note that while spline performs interpolation on rows of an input matrix, interp1 performs interpolation on columns of an input matrix.

Examples


Example 1. This generates a sine curve, then samples the spline over a finer mesh.

x = 0:10;
y = sin(x);
xx = 0:.25:10;
yy = spline(x,y,xx);
plot(x,y,'o',xx,yy)





Example 2. This illustrates the use of clamped or complete spline interpolation where end slopes are prescribed. Zero slopes at the ends of an interpolant to the values of a certain distribution are enforced.

x = -4:4;
y = [0 .15 1.12 2.36 2.36 1.46 .49 .06 0];
cs = spline(x,[0 y 0]);
xx = linspace(-4,4,101);
plot(x,y,'o',xx,ppval(cs,xx),'-');





Example 3. The two vectors

t = 1900:10:1990;
p = [ 75.995 91.972 105.711 123.203 131.669 ...
150.697 179.323 203.212 226.505 249.633 ];



represent the census years from 1900 to 1990 and the corresponding United States population in millions of people. The expression

spline(t,p,2000)



uses the cubic spline to extrapolate and predict the population in the year 2000. The result is
ans =
270.6060



Example 4. The statements

x = pi*[0:.5:2];
y = [0 1 0 -1 0 1 0;
1 0 1 0 -1 0 1];
pp = spline(x,y);
yy = ppval(pp, linspace(0,2*pi,101));
plot(yy(1,:),yy(2,:),'-b',y(1,2:5),y(2,2:5),'or'), axis equal



generate the plot of a circle, with the five data points y(:,2),...,y(:,6) marked with o's. Note that this y contains two more values (i.e., two more columns) than does x, hence y(:,1) and y(:,end) are used as endslopes.



Example 5. The following code generates sine and cosine curves, then samples the splines over a finer mesh.

x = 0:.25:1;
Y = [sin(x); cos(x)];
xx = 0:.1:1;
YY = spline(x,Y,xx);
plot(x,Y(1,:),'o',xx,YY(1,:),'-'); hold on;
plot(x,Y(2,:),'o',xx,YY(2,:),':'); hold off;





Algorithm


A tridiagonal linear system (with, possibly, several right sides) is being solved for the information needed to describe the coefficients of the various cubic polynomials which make up the interpolating spline. spline uses the functions ppval, mkpp, and unmkpp. These routines form a small suite of functions for working with piecewise polynomials. For access to more advanced features, see the M-file help for these functions and the Spline Toolbox.

See Also


interp1, ppval, mkpp, pchip, unmkpp

References


[1] de Boor, C., A Practical Guide to Splines, Springer-Verlag, 1978.




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