# In this file contains S3 methods for the netPower objects.
#' @title .
#' @export
plot.netPowerCell <- function(object, ...) {
# Suppress qgraph warnings.
toggle_console_warnings('off')
# Dividing the canvas.
par(mfrow = c(1, 2))
true = qgraph::qgraph(
object$raw$true$weights,
title = 'True model',
...,
layout = 'spring', edge.labels = TRUE, edge.label.cex = 1, edge.label.bg = FALSE, edge.label.color = 'black'
)
qgraph::qgraph(
object$raw$estimated$weights,
title = paste0('Estimated model (SEN: ',
round(object$computed$sensitivity, 2), ' | SPE: ',
round(object$computed$specificity, 2), ' | COR: ',
round(object$computed$edge_correlation, 2), ')'
),
...,
layout = true$layout, edge.labels = TRUE, edge.label.cex = 1, edge.label.bg = FALSE, edge.label.color = 'black'
)
# Restoring the canvas.
par(mfrow = c(1, 2))
# Enable warnings.
toggle_console_warnings('on')
}
#' @title .
#' @export
print.netPowerCell <- function(object, ...) {
cat('\n', 'Simulation cell results: ', '\n')
cat('\t', ' ', rep('-', 50),
'\n',
'\t -> config:',
object$raw$config[1], 'participants |',
object$raw$config[2], 'nodes |',
ifelse(object$raw$config[3] == 1, 'random', ifelse(object$raw$config[3] == 2, 'small world', 'scale free')), 'architecture |',
object$raw$config[4], 'connectedness |',
ifelse(object$raw$config[5] == 1, 'ising', 'ggm'), 'model.',
'\n',
'\t', ' ', rep('-', 50),
'\n'
)
cat('\t -> sensitivity:', object$computed$sensitivity, '\n')
cat('\t -> specificity:', object$computed$specificity, '\n')
cat('\t -> type one error:', object$computed$type_one, '\n')
cat('\t -> type two error:', object$computed$type_two, '\n')
cat('\t -> edge correlation:', object$computed$edge_correlation, '\n')
cat('\t -> equal # nodes:', ifelse(object$computed$equal_size, 'yes', 'no'), '\n')
cat('Try plot(result) for a visual inspection.', '\n\n')
}
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