Plot an object of class modeler — plot.modeler • flexFitR

Creates several plots for an object of class modeler.

Usage

# S3 method for class 'modeler'
plot(
  x,
  id = NULL,
  type = 1,
  label_size = 4,
  base_size = 14,
  linewidth = 0.5,
  color = "red",
  color_points = "black",
  parm = NULL,
  n_points = 1000,
  title = NULL,
  add_points = FALSE,
  add_ci = TRUE,
  color_ci = "blue",
  color_pi = "red",
  add_ribbon_ci = FALSE,
  add_ribbon_pi = FALSE,
  color_ribbon_ci = "blue",
  color_ribbon_pi = "red",
  ...
)

Arguments

x

An object of class modeler, typically the result of calling modeler().

id

An optional group ID to filter the data for plotting, useful for avoiding overcrowded plots.

type

Numeric value (1-6) to specify the type of plot to generate. Default is 1.

type = 1: Plot of raw data with fitted curves.
type = 2: Plot of coefficients with confidence intervals.
type = 3: Plot of fitted curves, colored by group.
type = 4: Plot of fitted curves with confidence intervals.
type = 5: Plot of first derivative with confidence intervals.
type = 6: Plot of second derivative with confidence intervals.

label_size

Numeric value for the size of labels. Default is 4.

base_size

Numeric value for the base font size in pts. Default is 14.

linewidth

Numeric value specifying size of line geoms. Default is 0.5.

color

Character string specifying the color for the fitted line when type = 1. Default is "red".

color_points

Character string specifying the color for the raw data points when type = 1. Default is "black".

parm

Character vector specifying the parameters to plot for type = 2. If NULL, all parameters are included.

n_points

Numeric value specifying the number of points for interpolation along the x-axis. Default is 2000.

title

Optional character string to add a title to the plot.

add_points

Logical value indicating whether to add raw observations to the plot for type = 3 and 4. Default is FALSE.

add_ci

Logical value indicating whether to add confidence intervals for type = 4, 5, 6. Default is TRUE.

color_ci

Character string specifying the color of the confidence interval when type = 4, 5, 6. Default is "blue".

color_pi

Character string specifying the color of the prediction interval when type = 4. Default is "red".

add_ribbon_ci

Logical value indicating whether to add a ribbon for confidence intervals in type = 4, 5, 6. Default is FALSE.

add_ribbon_pi

Logical value indicating whether to add a ribbon for prediction intervals in type = 4. Default is FALSE.

color_ribbon_ci

Character string specifying the color of the ribbon (ci). Default is "blue".

color_ribbon_pi

Character string specifying the color of the ribbon (pi). Default is "red".

...

Additional graphical parameters for future extensions.

Value

A ggplot object representing the specified plot.

Author

Johan Aparicio [aut]

Examples

library(flexFitR)
data(dt_potato)
# Example 1
mod_1 <- dt_potato |>
  modeler(
    x = DAP,
    y = Canopy,
    grp = Plot,
    fn = "fn_lin_plat",
    parameters = c(t1 = 45, t2 = 80, k = 0.9),
    subset = c(1:3)
  )
print(mod_1)
#> 
#> Call:
#> Canopy ~ fn_lin_plat(DAP, t1, t2, k) 
#> 
#> Residuals (`Standardized`):
#>      Min.   1st Qu.    Median      Mean   3rd Qu.      Max. 
#> -1.778920  0.000000  0.000000  0.093170  0.005382  2.236068 
#> 
#> Optimization Results `head()`:
#>  uid   t1   t2     k   sse
#>    1 38.5 61.7  99.8 0.449
#>    2 35.1 61.1 100.0 5.701
#>    3 33.7 60.0 100.0 3.759
#> 
#> Metrics:
#>  Groups      Timing Convergence Iterations
#>       3 0.4456 secs        100%   566 (id)
#> 
plot(mod_1, id = 1:2)

plot(mod_1, id = 1:3, type = 2, label_size = 10)