R/get_graph_stats.R

In abodein/netOmics: Multi-Omics (time-course) network-based integration and interpretation

#' Get graph statistics
#' 
#' For a given igraph or list of igraph objects, this function summarize 
#' the number of vertices/edges and other vertex attributes.
#' 
#' @param X an 'igraph' or 'list.igraph' object
#' 
#' @return 
#' It returns a long data.frame with number of nodes/edges, 
#' and the count of the different attributes 
#' (if X is a list of graph, each row describes a graph)
#' 
#' @examples
#' graph1 <- igraph::graph_from_data_frame(
#'     list(from = c('A', 'B', 'A', 'D', 'C', 'A', 'C'),
#'          to = c('B', 'C', 'D', 'E', 'D', 'F', 'G')), 
#'     directed = FALSE)
#' graph1 <- igraph::set_vertex_attr(graph = graph1, 
#'                                   name = 'type', 
#'                                   index = c('A','B','C'), 
#'                                   value = '1')
#' graph1 <- igraph::set_vertex_attr(graph = graph1, 
#'                                   name = 'type', 
#'                                   index = c('D','E'),
#'                                   value = '2')
#' graph1 <- igraph::set_vertex_attr(graph = graph1, 
#'                                   name = 'type', 
#'                                   index = c('F', 'G'),
#'                                   value = '-1')
#' 
#' get_graph_stats(graph1)
#' 
#' graph1.list <- list(graph1 = graph1, 
#'                     graph2 = graph1)
#' get_graph_stats(graph1.list)
#' 
#' @importFrom minet build.mim aracne
#' @importFrom magrittr %>%
#' @importFrom dplyr select all_of
#' @importFrom purrr imap_dfr
#' @importFrom igraph set_vertex_attr graph_from_adjacency_matrix
#' @export
get_graph_stats <- function(X) {
    
    X <- check_graph(X)
    
    if (is(X, "list") |
        is(X, "list.igraph")) {
        as.data.frame(
            lapply(X, function(x) .get_graph_stats_graph(x)),
            check.names = FALSE
        )
        stats <- as.data.frame(
            purrr::imap_dfr(X, ~.get_graph_stats_graph(.x)),
            check.names = FALSE
        )
        rownames(stats) <- names(X)
        
    } else {
        # X is not a list
        stats <- .get_graph_stats_graph(X)
    }
    class(stats) <- c("stats", "data.frame")
    return(stats)
}


#' @importFrom igraph degree ecount edge_density
.get_graph_stats_graph <- function(X) {
    node.c <- sum(igraph::degree(X) != 0)
    node.i <- sum(igraph::degree(X) == 0)
    edge <- igraph::ecount(X)
    edge.density <- igraph::edge_density(graph = X)
    res <- list(node.c = node.c, 
                node.i = node.i, 
                edge = edge, 
                edge.density = edge.density)
    
    if (any(names(vertex_attr(X)) !="name")) {
        item <- names(vertex_attr(X))[names(vertex_attr(X)) != "name"]
        vertex.attr.res <- as.data.frame(
            vertex_attr(X),
            check.names = FALSE
        ) %>%
          # tidyselect deprecation was:
            # dplyr::select(item)
            # Now:
            dplyr::select(dplyr::all_of(item))
        for (i in item) {
            tmp <- as.list(table(vertex.attr.res[[i]]))
            for (j in names(tmp)) {
                name_item <- paste(i, j, sep = ":")
                res[[name_item]] <- tmp[[j]]
            }
        }
    }
    return(as.data.frame(res, check.names = FALSE))
}