plot.pc_effect {patterncausality} | R Documentation |
Plot Pattern Causality Effect
Description
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 |
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
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")
[Package patterncausality version 0.2.1 Index]