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fnval

Evaluate spline function

Description

example

v = fnval(f,x) provides the value f(x) at the points in x of the spline function f whose description is contained in f.

If f is scalar-valued and univariate, the output v is obtained by replacing each entry of x by the value of f at that entry. This is the intent in all other cases, except that, for a d-valued m-variate function, d-vectors replaces m-vectors.

For a univariate f :

  • If f is scalar-valued, then v is of the same size as x.

  • If f is [d1,...,dr]-valued, and x has size [n1,...,ns], then v has size [d1,...,dr, n1,...,ns], with v(:,...,:, j1,...,js) the value of f at x(j1,...,js), – except that:

    • n1 is ignored if it is 1 and s is 2, i.e., if x is a row vector;

    • MATLAB® ignores any trailing singleton dimensions of x.

For an m-variate f with m>1, with f [d1,...,dr]-valued, x might be either an array, or else a cell array {x1,...,xm}.

  • If x is an array, of size [n1,...,ns], then n1 must equal m, and v has size [d1,...,dr, n2,...,ns], with v(:,...,:, j2,...,js) the value of f at x(:,j2,...,js), – except that:

    • d1, ..., dr is ignored in case f is scalar-valued, i.e., both r and n1 are 1;

    • MATLAB ignores any trailing singleton dimensions of x.

  • If x is a cell array, then it must be of the form {x1,...,xm}, with xj a vector, of length nj, and, in that case, v has size [d1,...,dr, n1,...,nm], with v(:,...,:, j1,...,jm) the value of f at (x1(j1), ..., xm(jm)), – except that d1, ..., dr is ignored in case f is scalar-valued, i.e., both r and n1 are 1.

If f has a jump discontinuity at x, then the value f(x +), i.e., the limit from the right, is returned, except when x equals the right end of the basic interval of the form; for such x, the value f(x–), i.e., the limit from the left, is returned.

fnval(x,f) is the same as fnval(f,x).

fnval(...,'l') treats f as continuous from the left. This means that if f has a jump discontinuity at x, then the value f(x–), i.e., the limit from the left, is returned, except when x equals the left end of the basic interval; for such x, the value f(x +) is returned.

If the function is multivariate, then the above statements concerning continuity from the left and right apply coordinate wise.

Examples

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This example shows how to interpolate some data and plot and evaluate the resulting functions.

Define some data.

x = [0.074 0.31 0.38 0.53 0.57 0.58 0.59 0.61 0.61 0.65 0.71 0.81 0.97];
y = [0.91 0.96 0.77 0.5 0.5 0.51 0.51 0.53 0.53 0.57 0.62 0.61 0.31]; 

Interpolate the data and plot the resulting function, f.

f = csapi( x, y )
f = struct with fields:
      form: 'pp'
    breaks: [1x12 double]
     coefs: [11x4 double]
    pieces: 11
     order: 4
       dim: 1

fnplt( f )

Find the value of the function f at x = 0.5.

fnval( f, 0.5 )
ans = 0.5294

Find the value of the function f at 0, 0.1, ..., 1.

fnval( f, 0:0.1:1 )
ans = 1×11

    0.3652    1.0220    1.1579    0.9859    0.7192    0.5294    0.5171    0.6134    0.6172    0.4837    0.2156

Create a function f2 that represents a surface.

x = 0.0001+(-4:0.2:4);
y = -3:0.2:3;
[yy, xx] = meshgrid( y, x );
r = pi*sqrt( xx.^2+yy.^2 );
z = sin( r )./r;
f2 = csapi( {x,y}, z ); 

Plot the function f2.

fnplt( f2 )
axis( [-5, 5, -5, 5, -0.5, 1] );

Find the value of the function f2 at x = -2 and y = 3.

fnval( f2, [-2; 3] )
ans = -0.0835

Input Arguments

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Spline function that you want to evaluate, specified as an object.

Points at which you want to evaluate the spline function f, specified as a vector, matrix or cell array.

Output Arguments

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Value f(x) at the points in x of the spline function f, returned as a scalar, vector, matrix or cell array.

Algorithms

For each entry of x, the function determines the relevant break-interval or knot-interval and assembles the relevant information. Depending on whether f is in ppform or in B-form, nested multiplication or the B-spline recurrence (see, e.g., [PGS; X.(3)]) are then used vector-fashion for the simultaneous evaluation at all entries of x. Evaluation of a multivariate polynomial spline function takes full advantage of the tensor product structure.

Evaluation of a rational spline follows up evaluation of the corresponding vector-valued spline by division of all but its last component by its last component.

Evaluation of a function in stform makes essential use of stcol, and tries to keep the matrices involved to reasonable size.

Introduced in R2006b