flexFitR (version 1.2.2)

plot_fn: Plot user-defined function

Description

This function plots a function over a specified interval and annotates the plot with the calculated Area Under the Curve (AUC) and parameter values. The aim of `plot_fn` is to allow users to play with different starting values in their functions before fitting any models.

Usage

plot_fn(
  fn = "fn_lin_plat",
  params = c(t1 = 34.9, t2 = 61.8, k = 100),
  interval = c(0, 100),
  n_points = 1000,
  auc = FALSE,
  x_auc_label = NULL,
  y_auc_label = NULL,
  auc_label_size = 4,
  param_label_size = 4,
  base_size = 12,
  color = "red",
  label_color = "grey30"
)

Value

A ggplot object representing the plot.

Arguments

fn

A character string representing the name of the function to be plotted. Default is "fn_lin_plat".

params

A named numeric vector of parameters to be passed to the function. Default is c(t1 = 34.9, t2 = 61.8, k = 100).

interval

A numeric vector of length 2 specifying the interval over which the function is to be plotted. Default is c(0, 100).

n_points

An integer specifying the number of points to be used for plotting. Default is 1000.

auc

Print AUC in the plot? Default is FALSE.

x_auc_label

A numeric value specifying the x-coordinate for the AUC label. Default is NULL.

y_auc_label

A numeric value specifying the y-coordinate for the AUC label. Default is NULL.

auc_label_size

A numeric value specifying the size of the AUC label text. Default is 3.

param_label_size

A numeric value specifying the size of the parameter label text. Default is 3.

base_size

A numeric value specifying the base size for the plot's theme. Default is 12.

color

A character string specifying the color for the plot lines and area fill. Default is "red".

label_color

A character string specifying the color for the labels. Default is "grey30".

Examples

# Example usage
plot_fn(
  fn = "fn_lin_plat",
  params = c(t1 = 34.9, t2 = 61.8, k = 100),
  interval = c(0, 100),
  n_points = 1000
)
plot_fn(
  fn = "fn_lin_pl_lin",
  params <- c(t1 = 38.7, t2 = 62, t3 = 90, k = 0.32, beta = -0.01),
  interval = c(0, 100),
  n_points = 1000,
  base_size = 12
)