cp: Control Polygons

In dewittpe/cpr: Control Polygon Reduction

Control Polygons

Description

Generate the control polygon for a uni-variable B-spline

Usage

cp(x, ...)

## S3 method for class 'cpr_bs'
cp(x, theta, ...)

## S3 method for class 'formula'
cp(
  formula,
  data,
  method = stats::lm,
  method.args = list(),
  keep_fit = TRUE,
  check_rank = TRUE,
  ...
)

Arguments

x	a cpr_bs object
...	pass through
theta	a vector of (regression) coefficients, the ordinates of the control polygon.
formula	a formula that is appropriate for regression method being used.
data	a required data.frame
method	the regression method such as lm, glm, lmer, etc.
method.args	a list of additional arguments to pass to the regression method.
keep_fit	(logical, default value is TRUE). If TRUE the regression model fit is retained and returned in as the fit element. If FALSE the fit element with be NA.
check_rank	(logical, defaults to TRUE) if TRUE check that the design matrix is full rank.

Details

cp generates the control polygon for the given B-spline function.

Value

a cpr_cp object, this is a list with the element cp, a data.frame reporting the x and y coordinates of the control polygon. Additional elements include the knot sequence, polynomial order, and other meta data regarding the construction of the control polygon.

Examples

# Support
xvec <- runif(n = 500, min = 0, max = 6)
bknots <- c(0, 6)

# Define the basis matrix
bmat1 <- bsplines(x = xvec, iknots = c(1, 1.5, 2.3, 4, 4.5), bknots = bknots)
bmat2 <- bsplines(x = xvec, bknots = bknots)

# Define the control vertices ordinates
theta1 <- c(1, 0, 3.5, 4.2, 3.7, -0.5, -0.7, 2, 1.5)
theta2 <- c(1, 3.4, -2, 1.7)

# build the two control polygons
cp1 <- cp(bmat1, theta1)
cp2 <- cp(bmat2, theta2)

# black and white plot
plot(cp1)
plot(cp1, show_spline = TRUE)

# multiple control polygons
plot(cp1, cp2, show_spline = TRUE)
plot(cp1, cp2, color = TRUE)
plot(cp1, cp2, show_spline = TRUE, color = TRUE)

# via formula
DF  <- data.frame(x = xvec, y = sin((xvec - 2)/pi) + 1.4 * cos(xvec/pi))
cp3 <- cp(y ~ bsplines(x, bknots = bknots), data = DF)

# plot the spline and target data.
plot(cp3, show_cp = FALSE, show_spline = TRUE) +
  ggplot2::geom_line(mapping = ggplot2::aes(x = x, y = y, color = "Target"),
                     data = DF, linetype = 2)

dewittpe/cpr documentation built on Feb. 16, 2024, 1:11 p.m.