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#' Creates network objects out of the netfacs data
#'
#' Takes the results of the nefacs object for combinations of 2 elements and
#' turns them into a network object (class \code{\link{igraph}} and
#' \code{\link{tbl_graph}}) that can be used for further plotting and analyses
#'
#' @param netfacs.list list of multiple objects resulting from
#' \code{\link{netfacs}} function or the \code{\link{netfacs_multiple}}
#' function
#' @param link determines how nodes/elements are connected. 'unweighted' gives a
#' 1 to significant connections and 0 to all others; 'weighted' gives the
#' difference between observed and expected probability of co-occurrence;
#' 'raw' just uses the observed probability of co-occurrence; 'SRI' uses the
#' simple ratio index/affinity (probability of co-occurrence/ (probabilities
#' of each element and the combination))
#' @param min.count numeric value, suggesting how many times a combination
#' should at least occur to be displayed
#' @param min.prob numeric value, suggesting the probability at which a
#' combination should at least occur to be displayed
#' @param significance numeric value, determining the p-value below which
#' combinations are considered to be dissimilar enough from the null
#' distribution
#' @param ignore.element vector of elements that will not be considered for the
#' network, e.g. because they are too common or too rare or their
#' interpretation is not relevant here
#'
#' @return Function returns a network object where the nodes are the elements,
#' edges represent their co-occurrence, and the vertex and edge attributes
#' contain all additional information from the netfacs object
#'
#' @export
#'
#' @examples
#' data(emotions_set)
#' emo.faces <- netfacs_multiple(
#' data = emotions_set[[1]],
#' condition = emotions_set[[2]]$emotion,
#' ran.trials = 10, # only for example
#' combination.size = 2
#' )
#'
#' emo.nets <- multiple_netfacs_network(emo.faces)
multiple_netfacs_network <-
function(netfacs.list,
link = "unweighted",
significance = 0.01,
min.count = 1,
min.prob = 0,
ignore.element = NULL) {
multi.net <- lapply(netfacs.list, function(x) {
xx <- netfacs_network(
x,
link = link,
significance = significance,
min.count = min.count,
min.prob = min.prob,
ignore.element = ignore.element
)
return(xx)
})
names(multi.net) <- names(netfacs.list)
return(multi.net)
}
#' @rdname multiple_netfacs_network
#' @export
multiple.netfacs.network <-
function(netfacs.list,
link = "unweighted",
significance = 0.01,
min.count = 1,
min.prob = 0,
ignore.element = NULL) {
multiple_netfacs_network(netfacs.list,
link,
significance,
min.count,
min.prob,
ignore.element)
}
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