#' @title Networking analysis.

#' @description This function checks the connectivity degree and the betweenness

#'   centrality, which reflect the communication flow in the defined PPI

#'   networks

#' @export

#' @param data Protein-protein interaction data frame resulted from running the

#'   PPI function.

#' @param export if `TRUE`, exports the analysis table as a csv file

#' @param FileName suffix for the file name (if export = TRUE)

#' @importFrom igraph graph.data.frame as_adjacency_matrix distance_table

#'   average.path.length get.adjacency V E mean_distance betweenness

#' @importFrom NetIndices GenInd

#' @return A network analysis table

NetAnalysis <- function(

    data, export = FALSE, FileName = "NetworkAnalysisTable-1") {

  if (length(data[, 1]) < 1) {

    stop("No Protein-Protein Interactions")

  }

  df <- data[, -c(1, 2)]

  gg <- graph.data.frame(df)

  betweenness <- betweenness(gg)

  betweenness.table <- data.frame(betweenness)

  names <- rownames(betweenness.table)

  rownames(betweenness.table) <- NULL

  degree <- degree(gg)

  Duplicated <- data[duplicated(data), ]

  if (length(Duplicated[, 1]) > 0) {

    degree <- degree / 2

  }

  degree.table <- data.frame(degree)

  names <- rownames(degree.table)

  rownames(degree.table) <- NULL

  AnalysisTable <- cbind(names, degree.table, betweenness.table)

  if (export) {

    write.csv(AnalysisTable, file = paste0(FileName, ".csv"))

  }

  test.graph.adj <- get.adjacency(gg, sparse = FALSE)

  test.graph.properties <- GenInd(test.graph.adj)

  message("Number of nodes: ", test.graph.properties$N)

  message("Number of links: ", test.graph.properties$Ltot)

  message("Link Density: ", test.graph.properties$LD)

  message("The connectance of the graph: ", test.graph.properties$C)

  message("Mean Distences", mean_distance(gg))

  message("Average Path Length", average.path.length(gg), "\n")

  AnalysisTable <-

    AnalysisTable[order(AnalysisTable[, 2], decreasing = TRUE), ]

  return(AnalysisTable)

}