CHEBYSHEV_INTERP_1D is a Python library which determines the combination of Chebyshev polynomials which interpolates a set of data, so that p(x(i)) = y(i).
CHEBYSHEV_INTERP_1D needs the R8LIB library. The test program needs the TEST_INTERP library.
The computer code and data files described and made available on this web page are distributed under the GNU LGPL license.
CHEBYSHEV_INTERP_1D is available in a C version and a C++ version and a FORTRAN90 version and a MATLAB version and a Python version.
BARYCENTRIC_INTERP_1D, a Python library 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.
LAGRANGE_INTERP_1D, a Python library 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 Python library which interpolates a set of data using a piecewise constant interpolant defined by the nearest neighbor criterion.
NEWTON_INTERP_1D, a Python library which finds a polynomial interpolant to data using Newton divided differences.
PWL_INTERP_1D, a Python library which interpolates a set of data using a piecewise linear interpolant.
RBF_INTERP_1D, a Python library which defines and evaluates radial basis function (RBF) interpolants to 1D data.
SHEPARD_INTERP_1D, a Python library which defines and evaluates Shepard interpolants to 1D data, which are based on inverse distance weighting.
TEST_INTERP, a Python library which defines a number of test problems for interpolation, provided as a set of (x,y) data.
TEST_INTERP_1D, a Python library which defines test problems for interpolation of data y(x), depending on a 2D argument.
VANDERMONDE_INTERP_1D, a Python library 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.
The program plots a piecewise linear interpolant to the original data, and the Chebyshev interpolant.
You can go up one level to the Python source codes.