Plot Enhanced Correlated Fitness Surface

Usage

plot_correlated_fitness_enhanced(
  tps,
  trait_cols = NULL,
  original_data = NULL,
  fitness_col = NULL,
  bins = 12,
  point_alpha = 0.7,
  show_optimum = TRUE,
  show_groups = TRUE,
  group_lines = TRUE,
  uncertainty = c("none", "se", "band"),
  ...
)

Arguments

tps: Output list from correlated_fitness_surface().
trait_cols: Character vector of length 2. If NULL, inferred from grid.
original_data: Optional data frame of original data.
fitness_col: Optional character string specifying the fitness column for coloring points.
bins: Integer specifying the number of contour bins. Default is 12.
point_alpha: Numeric value for point transparency. Default is 0.7.
show_optimum: Logical; mark the highest kept cell, a gold diamond, or an open one when it is on the edge of the data. Default is TRUE.
show_groups: Logical; when the surface was fitted with a group, draw each group's mean and the highest point of the surface within that group's hull, filled when it is a peak of the surface and open when it is not. Default is TRUE.
group_lines: Logical; join each group's mean to its peak with a dashed line. Default is TRUE.
uncertainty: What to draw of the surface's standard error, which a GAM surface carries: "none" (the default), "se" for dashed contour lines of the standard error of the fitted fitness over the surface, or "band" for three panels, the lower bound, the fit and the upper bound, on one fill scale.
...: Additional arguments passed to ggplot2::labs().

Value

A ggplot object with enhanced visualizations.

Examples

prep <- prepare_selection_data(bumpus, "survival", c("total_length", "weight"))
surf <- correlated_fitness_surface(prep, "survival", c("total_length", "weight"), grid_n = 30)
#> Data type: binary; method: gam; n = 136; k = 29
#> GAM fitting with 136 observations
#>   Trying formula: main
#> Success with formula: main
#> Predictions range: 0.0472 to 0.703
#> Masked 424 of 900 grid points outside the data
plot_correlated_fitness_enhanced(surf, c("total_length", "weight"),
                                 original_data = prep, fitness_col = "survival")
#> Using provided traits: total_length, weight