Visualize Pattern Causality Matrix

The plotMatrix function generates a visual representation of a pattern causality matrix using different methods. It allows users to visualize the positive, negative, or dark causality effects in a specified matrix, providing insight into the relationships between items.

Usage

plotMatrix(pcmatrix, status, method)

Arguments

pcmatrix

A list containing three matrices (positive, negative, and dark) which represent the respective causality types for different items.

status

A character string specifying which causality matrix to plot. Must be one of "positive", "negative", or "dark".

method

A character string specifying the visualization method for the plot. Options include "circle", "square", "ellipse", "number", "shade", "color", and "pie".

Value

A visual plot of the selected causality matrix using the specified method. The plot provides a color-coded representation of the causality strengths between items.

Examples

# \donttest{
data(climate_indices)
dataset <- climate_indices[,-1]
pcmatrix <- pcMatrix(dataset, E = 3, tau = 1, metric = "euclidean", h = 1, weighted = TRUE)
#> CAUSE:  AO 
#> EFFECT:  AO 
#> EFFECT:  AAO 
#> EFFECT:  NAO 
#> EFFECT:  PNA 
#> CAUSE:  AAO 
#> EFFECT:  AO 
#> EFFECT:  AAO 
#> EFFECT:  NAO 
#> EFFECT:  PNA 
#> CAUSE:  NAO 
#> EFFECT:  AO 
#> EFFECT:  AAO 
#> EFFECT:  NAO 
#> EFFECT:  PNA 
#> CAUSE:  PNA 
#> EFFECT:  AO 
#> EFFECT:  AAO 
#> EFFECT:  NAO 
#> EFFECT:  PNA 
#> Calculation duration:  7.57771873474121
plotMatrix(pcmatrix, status = "positive", method = "color")

# }