smoothr (version 1.0.1)

smooth_spline: Spline interpolation

Description

Spline interpolation uses stats::spline() to interpolate between existing vertices using piecewise cubic polynomials. The coordinates are interpolated independently. The curve will always pass through the vertices of the original feature.

Usage

smooth_spline(x, wrap = FALSE, vertex_factor = 5, n)

Value

A matrix with the coordinates of the smoothed curve.

Arguments

x

numeric matrix; matrix of coordinates.

wrap

logical; whether the coordinates should be wrapped at the ends, as for polygons and closed lines, to ensure a smooth edge.

vertex_factor

double; the proportional increase in the number of vertices in the smooth curve. For example, if the original curve has 100 points, a value of 2.5 will yield a new smoothed curve with 250 points. Ignored if n is specified.

n

integer; number of vertices in the smoothed curve.

Details

This function works on matrices of points and is generally not called directly. Instead, use smooth() with method = "spline" to apply this smoothing algorithm to spatial features.

References

The spline method was inspired by the following StackExchange answers:

• Create polygon from set of points distributed

• Smoothing polygons in contour map?

See Also

smooth()

Examples

# smooth_spline works on matrices of coordinates
# use the matrix of coordinates defining a polygon as an example
m <- jagged_polygons$geometry[[2]][[1]]
m_smooth <- smooth_spline(m, wrap = TRUE)
class(m)
class(m_smooth)
plot(m_smooth, type = "l", col = "red", axes = FALSE, xlab = NA, ylab = NA)
lines(m, col = "black")

# smooth is a wrapper for smooth_spline that works on spatial features
library(sf)
p <- jagged_polygons$geometry[[2]]
p_smooth <- smooth(p, method = "spline")
class(p)
class(p_smooth)
plot(p_smooth, border = "red")
plot(p, add = TRUE)