rbf_interp_1d

rbf_interp_1d, a MATLAB code which defines and evaluates radial basis function (RBF) interpolants to 1D data.

A radial basis interpolant is a useful, but expensive, technique for definining a smooth function which interpolates a set of function values specified at an arbitrary set of data points.

Given nd multidimensional points xd with function values fd, and a basis function phi(r), the form of the interpolant is

       f(x) = sum ( 1 <= i <= nd ) w(i) * phi(||x-xd(i)||)
      

        sum ( 1 <= i <= nd ) w(i) * phi(||xd(j)-xd(i)||) = fd(j)
      

Although the technique is generally applied in a multidimensional setting, in this directory we look specifically at the case involving 1D data. This allows us to easily plot and compare the various results.

Four families of radial basis functions are provided.

• phi1(r) = sqrt ( r^2 + r0^2 ) (multiquadric)
• phi2(r) = 1 / sqrt ( r^2 + r0^2 ) (inverse multiquadric)
• phi3(r) = r^2 * log ( r / r0 ) (thin plate spline)
• phi4(r) = exp ( -0.5 r^2 / r0^2 ) (gaussian)

RBF_INTERP_1D needs the R8LIB library. The test code also needs the TEST_INTERP library.

Licensing:

The computer code and data files described and made available on this web page are distributed under the MIT license

Languages:

rbf_interp_1d is available in a C version and a C++ version and a FORTRAN90 version and a MATLAB version and a Python version.

Related Data and Programs:

barycentric_interp_1d, a MATLAB code which defines and evaluates the barycentric Lagrange polynomial p(x) which interpolates a set of data, so that p(x(i)) = y(i). The barycentric approach means that very high degree polynomials can safely be used.

chebyshev_interp_1d, a MATLAB code which determines the combination of Chebyshev polynomials which interpolates a set of data, so that p(x(i)) = y(i).

divdif, a MATLAB code which uses divided differences to compute the polynomial interpolant to a given set of data.

hermite_interpolant, a MATLAB code which computes the Hermite interpolant, a polynomial that matches function values and derivatives.

lagrange_interp_1d, a MATLAB code which defines and evaluates the Lagrange polynomial p(x) which interpolates a set of data, so that p(x(i)) = y(i).

nearest_interp_1d, a MATLAB code which interpolates a set of data using a piecewise constant interpolant defined by the nearest neighbor criterion.

newton_interp_1d, a MATLAB code which finds a polynomial interpolant to data using Newton divided differences.

pwl_interp_1d, a MATLAB code which interpolates a set of data using a piecewise linear interpolant.

r8lib, a MATLAB code which contains many utility routines using double precision real (R8) arithmetic.

rbf_interp_1d_test

rbf_interp_2d, a MATLAB code which defines and evaluates radial basis function (RBF) interpolants to 2D data.

rbf_interp_nd, a MATLAB code which defines and evaluates radial basis function (RBF) interpolants to multidimensional data.

shepard_interp_1d, a MATLAB code which defines and evaluates Shepard interpolants to 1D data, which are based on inverse distance weighting.

test_interp, a MATLAB code which defines a number of test problems for interpolation, provided as a set of (x,y) data.

test_interp_1d, a MATLAB code which defines test problems for interpolation of data y(x), depending on a 2D argument.

vandermonde_interp_1d, a MATLAB code which finds a polynomial interpolant to a function of 1D data by setting up and solving a linear system for the polynomial coefficients, involving the Vandermonde matrix.

Reference:

1. Richard Franke,
   Scattered Data Interpolation: Tests of Some Methods,
   Mathematics of Computation,
   Volume 38, Number 157, January 1982, pages 181-200.
2. William Press, Brian Flannery, Saul Teukolsky, William Vetterling,
   Numerical Recipes in FORTRAN: The Art of Scientific Computing,
   Third Edition,
   Cambridge University Press, 2007,
   ISBN13: 978-0-521-88068-8,
   LC: QA297.N866.

Source Code:

• phi1.m, evaluates the multiquadric radial basis function.
• phi2.m, evaluates the inverse multiquadric radial basis function.
• phi3.m, evaluates the thin-plate spline radial basis function.
• phi4.m, evaluates the gaussian radial basis function.
• rbf_interp.m, evaluates a radial basis function interpolant.
• rbf_weight.m, computes weights for radial basis function interpolation.