pracma (version 1.9.3)

cubicspline: Interpolating Cubic Spline

Description

Computes the natural interpolation cubic spline.

Usage

cubicspline(x, y, xi = NULL, endp2nd = FALSE, der = c(0, 0))

Arguments

x, y

x- and y-coordinates of points to be interpolated.

xi

x-coordinates of points at which the interpolation is to be performed.

endp2nd

logical; if true, the derivatives at the endpoints are prescribed by der.

der

a two-components vector prescribing derivatives at endpoints.

Value

Returns either the interpolated values at the points xi or, if is.null(xi), the piecewise polynomial that represents the spline.

Details

cubicspline computes the values at xi of the natural interpolating cubic spline that interpolate the values y at the nodes x. The derivatives at the endpoints can be prescribed.

References

Quarteroni, Q., and F. Saleri (2006). Scientific Computing with Matlab and Octave. Springer-Verlag Berlin Heidelberg.

See Also

spline

Examples

##  Example: Average temperatures at different latitudes
x <- seq(-55, 65, by = 10)
y <- c(-3.25, -3.37, -3.35, -3.20, -3.12, -3.02, -3.02,
       -3.07, -3.17, -3.32, -3.30, -3.22, -3.10)
xs <- seq(-60, 70, by = 1)

# Generate a function for this
pp <- cubicspline(x, y)
ppfun <- function(xs) ppval(pp, xs)

## Not run: 
# # Plot with and without endpoint correction
# plot(x, y, col = "darkblue",
#            xlim = c(-60, 70), ylim = c(-3.5, -2.8),
#            xlab = "Latitude", ylab = "Temp. Difference",
#            main = "Earth Temperatures per Latitude")
# lines(spline(x, y), col = "darkgray")
# grid()
# 
# ys <- cubicspline(x, y, xs, endp2nd = TRUE)     # der = 0 at endpoints
# lines(xs, ys, col = "red")
# ys <- cubicspline(x, y, xs)                     # no endpoint condition
# lines(xs, ys, col = "darkred")
# ## End(Not run)