Plot Pattern Causality Effect — plot.pc_effect • patterncausality

Generates a plot to visualize the effects of positive, negative, or dark causality. Displays the influence exerted versus influence received for each item. This function generates a scatter plot showing the influence exerted versus influence received for each item, colored by the difference between exerted and received influence.

Usage

# S3 method for class 'pc_effect'
plot(
  x,
  status = "positive",
  add_label = TRUE,
  point_size = 3,
  label_size = 3,
  ...
)

Arguments

x: A pc_effect object.
status: Status of the effect to plot ("positive", "negative", or "dark").
add_label: Logical, whether to add labels to the plot.
point_size: Numeric value for point size (default: 3).
label_size: Numeric value for label text size (default: 3).
...: Additional arguments passed to plotting functions.

Value

Invisibly returns the ggplot object.

Examples

# \donttest{
data(climate_indices)
dataset <- climate_indices[, -1]
pc_matrix_obj <- pcMatrix(dataset, E = 3, tau = 1, 
  metric = "euclidean", h = 1, weighted = TRUE, 
  verbose = FALSE)
effects <- pcEffect(pc_matrix_obj)
plot(effects, status = "positive")

# }