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server.R
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# By default, Shiny limits file uploads to 5MB per file. You can modify
# this limit by using the shiny.maxRequestSize option. For example,# adding options(shiny.maxRequestSize=30*1024^2) to the top of server.R
# would increase the limit to 30MB. From within R, inside the app
# source dir, start the app with: shiny::runApp(getwd()) From a shell,# start the app with: R -e 'shiny::runApp('~/appsourcedir')'
read_data <- function(datapath, type = c("txt"), header = T, sep = "\t", quote = "\"", weighted = F) ({
dataset1 <- read.table(datapath, header = header, sep = sep, quote = quote)
# if(weighted)
if (ncol(dataset1) == 2) {
dataset1$V3 <- 1
} else if (ncol(dataset1) > 3) {
dataset1 <- dataset1[, 1:3]
} else if (ncol(dataset1) != 3)
return(NULL)
colnames(dataset1) <- c("Source", "Target", "Weight")
# else colnames(dataset1) <- c('Source', 'Target')
return(dataset1)
})
convert_to_igraph <- function(dataset1) ({
directed_tf <- FALSE
weighted_tf <- FALSE
# colnames(dataset1) <- c("Source", "Target", "weight") #new
# print(dataset1)
if (attr(dataset1, "directed")) {
directed_tf <- attr(dataset1, "directed")
}
if (attr(dataset1, "weighted")) {
weighted_tf <- attr(dataset1, "weighted")
}
igraph <- graph.data.frame(dataset1, directed = directed_tf, vertices = NULL)
if (attr(dataset1, which = "weighted"))
E(igraph)$weight <- dataset1$Weight
if (attr(dataset1, which = "bipartite"))
V(igraph)$type <- V(igraph)$name %in% dataset1[, 1]
return(igraph)
})
EmptyDataset <- function(columns) {
dataset <- data.frame(V1 = integer())
lapply(columns[-1], function(x) dataset[, x] <<- integer())
colnames(dataset) <- columns
return(dataset)
}
ui_options <- c(ui_table_font_sz = "80%") #html size
options(shiny.error = browser) #debugging
pairs2 <- function(x, labels, panel = points, ..., lower.panel = panel, upper.panel = panel, diag.panel = NULL, text.panel = textPanel, label.pos = 0.5 +
has.diag/3, cex.labels = NULL, font.labels = 1, row1attop = TRUE, gap = 1) {
textPanel <- function(x = 0.5, y = 0.5, txt, cex, font) text(x, y, txt, cex = cex, font = font)
localAxis <- function(side, x, y, xpd, bg, col = NULL, main, oma, ...) {
if (side%%2 == 1)
Axis(x, side = side, xpd = NA, ...) else Axis(y, side = side, xpd = NA, ...)
}
localPlot <- function(..., main, oma, font.main, cex.main) plot(...)
localLowerPanel <- function(..., main, oma, font.main, cex.main) lower.panel(...)
localUpperPanel <- function(..., main, oma, font.main, cex.main) upper.panel(...)
localDiagPanel <- function(..., main, oma, font.main, cex.main) diag.panel(...)
dots <- list(...)
nmdots <- names(dots)
if (!is.matrix(x)) {
x <- as.data.frame(x)
for (i in seq_along(names(x))) {
if (is.factor(x[[i]]) || is.logical(x[[i]]))
x[[i]] <- as.numeric(x[[i]])
if (!is.numeric(unclass(x[[i]])))
stop("non-numeric argument to 'pairs'")
}
} else if (!is.numeric(x))
stop("non-numeric argument to 'pairs'")
panel <- match.fun(panel)
if ((has.lower <- !is.null(lower.panel)) && !missing(lower.panel))
lower.panel <- match.fun(lower.panel)
if ((has.upper <- !is.null(upper.panel)) && !missing(upper.panel))
upper.panel <- match.fun(upper.panel)
if ((has.diag <- !is.null(diag.panel)) && !missing(diag.panel))
diag.panel <- match.fun(diag.panel)
if (row1attop) {
tmp <- lower.panel
lower.panel <- upper.panel
upper.panel <- tmp
tmp <- has.lower
has.lower <- has.upper
has.upper <- tmp
}
nc <- ncol(x)
if (nc < 2)
stop("only one column in the argument to 'pairs'")
has.labs <- TRUE
if (missing(labels)) {
labels <- colnames(x)
if (is.null(labels))
labels <- paste("var", 1L:nc)
} else if (is.null(labels))
has.labs <- FALSE
oma <- if ("oma" %in% nmdots)
dots$oma else NULL
main <- if ("main" %in% nmdots)
dots$main else NULL
if (is.null(oma)) {
oma <- c(4, 4, 4, 4)
if (!is.null(main))
oma[3L] <- 6
}
opar <- par(mfrow = c(nc, nc), mar = rep.int(gap/2, 4), oma = oma)
on.exit(par(opar))
dev.hold()
on.exit(dev.flush(), add = TRUE)
for (i in if (row1attop)
1L:nc else nc:1L) for (j in 1L:nc) {
localPlot(x[, j], x[, i], xlab = "", ylab = "", axes = FALSE, type = "n", ...)
if (i == j || (i < j && has.lower) || (i > j && has.upper)) {
box()
# edited here... if (i == 1 && (!(j%%2) || !has.upper || !has.lower))
# localAxis(1 + 2 * row1attop, x[, j], x[, i], ...) draw x-axis
if (i == nc)
localAxis(1, x[, j], x[, i], ...)
# draw y-axis
if (j == 1)
localAxis(2, x[, j], x[, i], ...)
# if (j == nc && (i%%2 || !has.upper || !has.lower)) localAxis(4, x[, #
# j], x[, i], ...)
mfg <- par("mfg")
if (i == j) {
if (has.diag)
localDiagPanel(as.vector(x[, i]), ...)
if (has.labs) {
par(usr = c(0, 1, 0, 1))
if (is.null(cex.labels)) {
l.wid <- strwidth(labels, "user")
cex.labels <- max(0.8, min(2, 0.9/max(l.wid)))
}
text.panel(0.5, label.pos, labels[i], cex = cex.labels, font = font.labels)
}
} else if (i < j)
localLowerPanel(as.vector(x[, j]), as.vector(x[, i]), ...) else localUpperPanel(as.vector(x[, j]), as.vector(x[, i]), ...)
if (any(par("mfg") != mfg))
stop("the 'panel' function made a new plot")
} else par(new = FALSE)
}
if (!is.null(main)) {
font.main <- if ("font.main" %in% nmdots)
dots$font.main else par("font.main")
cex.main <- if ("cex.main" %in% nmdots)
dots$cex.main else par("cex.main")
mtext(main, 3, 3, TRUE, 0.5, cex = cex.main, font = font.main)
}
invisible(NULL)
}
panel.regression <- function(x, y, col = par("col"), bg = NA, pch = par("pch"), cex = 1, col.regres = "red", ...) {
points(x, y, pch = pch, col = col, bg = bg, cex = cex)
if (all(is.finite(x) & is.finite(y)))
abline(stats::lm(y ~ x), col = col.regres, ...)
}
scatterplotmatrix <- function(R, lowerPanelRegression, method = c("pearson", "kendall", "spearman"), ...) {
x = checkData(R, method = "matrix")
if (missing(method))
method = method[1]
panel.cor <- function(x, y, digits = 2, prefix = "", use = "complete", method, cex.cor, ...) {
usr <- par("usr")
on.exit(par(usr))
par(usr = c(0, 1, 0, 1))
r <- cor(x, y, use = use, method = method)
txt <- format(c(r, 0.123456789), digits = digits)[1]
txt <- paste(prefix, txt, sep = "")
if (missing(cex.cor))
cex <- 0.4/strwidth(txt)
test <- cor.test(x, y, method = method)
Signif <- symnum(test$p.value, corr = FALSE, na = FALSE, cutpoints = c(0, 0.001, 0.01, 0.05, 0.1, 1), symbols = c("***", "**", "*", ".", " "))
text(0.5, 0.5, txt, cex = cex * (abs(r) + 0.01)/2)
text(0.8, 0.8, Signif, cex = cex * (abs(r) + 0.01)/2, col = 2)
}
# f <- function(t) { dnorm(t, mean = mean(x), sd = sd.xts(x)) }
hist.panel = function(x, ...) {
par(new = TRUE)
hist(x, col = "#9dd4f2", border = "#3187b7", probability = TRUE, axes = FALSE, main = "", breaks = "FD")
# lines(density(x, na.rm = TRUE), col = 'red', lwd = 1)
}
if (lowerPanelRegression)
lowerPanel <- panel.regression else lowerPanel <- points
pairs2(x, gap = 0, lower.panel = lowerPanel, upper.panel = panel.cor, method = method, bg = "#c4e5f7", pch = 21, ...)
}
shinyServer(function(input, output, session) {
reactiveVars <- reactiveValues()
reactiveVars$StoredNetworks <- data.frame(id = character(), name = character(), stringsAsFactors = F)
reactiveVars$SelectedStoredNetworksIds <- c()
reactiveVars$layoutCoord <- NULL
reactiveVars$plotData <- NULL
reactiveVars$last_intersection_data <- NULL
session$onSessionEnded(function() {
snets <- isolate(StoredNets())
if (nrow(snets) > 0) {
unlink(c("*.rda", "*.zip"))
}
})
############ Read the files ################
loadNetworkFromFile <- function() {
dataset1 <- NULL
switch(input$uiLoadGraphOptionsInput, oF = {
if (!is.null(input$file1)) {
dataset1 <- read_data(input$file1$datapath)
}
}, oR_Barbasi = {
dataset1 <- data.frame(get.edgelist(barabasi.game(n = as.integer(input$oR_selected_size), power = 1, directed = F)))
}, oR_Erdos_Renyi = {
n <- as.integer(input$oR_selected_size)
dataset1 <- data.frame(get.edgelist(erdos.renyi.game(n = n, p.or.m = as.integer(n * log10(n)), type = "gnm", directed = F)))
}, oR_Watts_Strogatz = {
n <- as.integer(input$oR_selected_size)
dataset1 <- data.frame(get.edgelist(sample_smallworld(1, n, 2, 0.05)))
}, oR_Bipartite = {
n <- as.integer(input$oR_selected_size)
v <- sample(c(F, T), n, T)
v1 <- sample(which(v == F))
v2 <- sample(which(v == T))
e <- unlist(mapply(c, v1, v2, SIMPLIFY = T))
dataset1 <- data.frame(get.edgelist(make_bipartite_graph(v, e, directed = F)))
})
if (input$uiLoadGraphOptionsInput != "oF" && !is.null(dataset1)) {
# if(input$weighted1) {
if (!is.null(dataset1))
dataset1$X3 <- sample(1:10, nrow(dataset1), replace = T)
colnames(dataset1) <- c("Source", "Target", "Weight")
# } else { colnames(dataset1) <- c('Source', 'Target') }
}
return(dataset1)
}
random_igraph_sizes <- c(`50` = 50, `500` = 500, `1000` = 1000)
output$uiLoadGraphOptionsOutput <- renderUI({
if (is.null(input$uiLoadGraphOptionsInput))
return()
# Depending on input$input_type, we'll generate a different UI
# component and send it to the client.
if (input$uiLoadGraphOptionsInput == "oF") {
wellPanel(fileInput("file1", "1: Choose file to upload",
accept = c("text/csv", "text/comma-separated-values,text/plain", ".csv")),
checkboxInput(inputId = "directed1", "Directed", value = FALSE),
checkboxInput("bipartite1", "Bipartite", FALSE),
checkboxInput(inputId = "weighted1", "Weighted", value = FALSE))
} else {
div(list(div(wellPanel(checkboxInput(inputId = "directed1", label = "Directed", value = F)), class = "col-md-6"), div(wellPanel(checkboxInput(inputId = "weighted1", label = "Weighted", value = F)), class = "col-md-6"), div(wellPanel(radioButtons("oR_selected_size", label = "Number of nodes", choices = random_igraph_sizes)), class = "col-md-6")), class = "row")
}
})
StoredNets <- reactive({
return(reactiveVars$StoredNetworks)
})
SelectedStoredNets <- function() {
if (length(reactiveVars$SelectedStoredNetworksIds) > 0)
return(StoredNets()[which(reactiveVars$StoredNetworks$id %in%
reactiveVars$SelectedStoredNetworksIds), ]) else if (nrow(StoredNets()) == 0 || is.na(StoredNets()[1, ]))
return(NULL) else {
updateCheckboxGroupInput(session, "storedGraphsOutputMultipleSelectTopolopgy", "Selected network(s)", choices = getStoredNetsChoices(), selected = getStoredNetsChoices()[1])
return(StoredNets()[1, ])
}
}
StoredNetsEmpty <- function() {
return(nrow(reactiveVars$StoredNetworks) == 0)
}
getDatasetName <- function(id) {
sn <- StoredNets()
idi <- which(sn$id == id)
if (is.null(sn) || nrow(sn) == 0 || length(idi) == 0)
return(NULL)
return(sn[idi, ]$name)
}
fetchDataset <- function(nid) {
retVal <- NULL
if (length(nid) > 0) {
retVal <- readRDS(paste0(nid, ".rda"))
attr(retVal, "id") <- nid
}
return(retVal)
}
fetchFirstSelectedStoredDataset <- reactive({
ssn <- SelectedStoredNets()
if (!is.null(ssn) && nrow(ssn) > 0) {
return(fetchDataset(ssn[1, ]$id))
} else {
return(NULL)
}
})
fetchFirstSelectedStoredIgraph <- function() {
dataset <- fetchFirstSelectedStoredDataset()
if (is.null(dataset))
return(NULL) else return(convert_to_igraph(dataset))
}
fetchAllSelectedStoredDataset <- function() {
ssn <- SelectedStoredNets()
ids <- c()
if (!is.null(ssn) && nrow(ssn) > 0) {
ret <- list()
for (i in 1:nrow(ssn)) {
ret[[i]] <- fetchDataset(ssn[i, ]$id)
ids <- c(ids, ssn[i, ]$id)
}
names(ret) <- ids
return(ret)
} else {
return(NULL)
}
}
fetchMaxNSelectedStoredDataset <- function(N) {
ssn <- SelectedStoredNets()
if (!is.null(ssn) && nrow(ssn) > 0) {
ret <- list()
for (i in 1:nrow(ssn)) {
if (i > N)
break
ret[[i]] <- fetchDataset(ssn[i, ]$id)
}
return(ret)
} else {
return(NULL)
}
}
fetchMaxTwoSelectedStoredIgraphs <- function() {
datasets <- fetchMaxNSelectedStoredDataset(2)
if (is.null(datasets) || length(datasets) == 0)
return(NULL) else {
ret <- list()
for (i in length(datasets)) ret[[i]] <- convert_to_igraph(datasets[[i]])
return(ret)
}
}
doAddNetwork <- observeEvent(input$btnAddNetwork, {
dataset <- loadNetworkFromFile()
if (!is.null(dataset)) {
nid <- UUIDgenerate(T) #time-base UUID is generated
nn <- input$networkName
cnt <- 1 #count
while (nn %in% reactiveVars$StoredNetworks$name) { #reactiveVars: represents a single reactive variable.
cnt <- cnt + 1
nn <- paste(input$networkName, cnt) #paste: converts its arguments (via as.character) to character strings
}
df <- data.frame(id = nid, name = nn, stringsAsFactors = F)
if (nrow(dataset) > 10000) {
dataset <- dataset[1:10000, ]
}
attr(dataset, which = "directed") <- input$directed1
attr(dataset, which = 'weighted') <- input$weighted1
attr(dataset, which = "bipartite") <- input$bipartite1 || input$uiLoadGraphOptionsInput == "oR_Bipartite"
reactiveVars$StoredNetworks <- rbind(reactiveVars$StoredNetworks, df)
saveRDS(dataset, paste0(nid, ".rda"))
if (length(reactiveVars$SelectedStoredNetworksIds) == 0) {
reactiveVars$SelectedStoredNetworksIds <- c(nid)
}
} else createAlert(session, "tabUploadSideAlert", "fileUploadAlert", title = "ERROR !", style = "danger", content = paste0("An error occurred while trying to read your file. Please make sure that it is formatted according to the requirements."), append = FALSE)
})
doRemNetwork <- observeEvent(input$btnRemoveNetworks, {
if (!is.null(input$availableNetworks)) {
reactiveVars$StoredNetworks <- reactiveVars$StoredNetworks[-which(reactiveVars$StoredNetworks$id %in%
input$availableNetworks), ]
nr <- nrow(reactiveVars$StoredNetworks)
if (nr > 0)
reactiveVars$SelectedStoredNetworksIds <- reactiveVars$StoredNetworks[nr, ]$id
}
})
getStoredNetsChoices <- function() {
snets <- StoredNets()
if (nrow(snets) == 0)
return(NULL)
choices <- snets$id
names(choices) <- snets$name
return(choices)
}
# outputOptions(output, 'availableNetworks', suspendWhenHidden=FALSE)
output$uiStoredGraphsOutputRadio <- renderUI({
input$btnAddNetwork
input$btnRemoveNetworks
choices <- getStoredNetsChoices()
if (is.null(choices))
return()
return(list(br(), wellPanel(h4("Available networks"), checkboxGroupInput("availableNetworks", label = "", choices = choices)), div(div(actionButton("btnRemoveNetworks", "REMOVE", icon = icon("minus")), class = "col-md-5 centerBlock"), class = "row text-center")))
})
uploadTabSetSelectedNetwork <- observeEvent(input$storedGraphsOutputSelectUpload, {
reactiveVars$SelectedStoredNetworksIds <- c(input$storedGraphsOutputSelectUpload)
}, ignoreNULL = FALSE)
output$uiStoredGraphsOutputSelectUpload <- renderUI({
input$btnAddNetwork
input$btnRemoveNetworks
choices <- getStoredNetsChoices()
if (is.null(choices))
return()
return(selectInput("storedGraphsOutputSelectUpload", "Selected network", choices))
})
# topologyTabSetSelectedNetwork <-
# observeEvent(input$storedGraphsOutputSelectTopolopgy, {
# reactiveVars$SelectedStoredNetworksIds<-c(input$storedGraphsOutputSelectTopolopgy)
# }, ignoreNULL = FALSE)
topologyTableViewSetSelectedNetwork <- observeEvent({
input$storedGraphsOutputSelectTopolopgy
input$statisticsMethodsMainTabsetPanel
}, {
if (input$statisticsMethodsMainTabsetPanel == "tableView" && !(length(reactiveVars$SelectedStoredNetworksIds) ==
1 && reactiveVars$SelectedStoredNetworksIds == input$storedGraphsOutputSelectTopolopgy)) {
reactiveVars$SelectedStoredNetworksIds <- c(input$storedGraphsOutputSelectTopolopgy)
}
}, ignoreNULL = FALSE)
output$uiStoredGraphsOutputSelectTopolopgy <- renderUI({
input$btnAddNetwork
input$btnRemoveNetworks
choices <- getStoredNetsChoices()
if (is.null(choices))
return()
return(selectInput("storedGraphsOutputSelectTopolopgy", "Selected network", choices))
})
topologyPlotViewSetSelectedNetwork <- observeEvent({
input$storedGraphsOutputMultipleSelectTopolopgy
input$statisticsMethodsMainTabsetPanel
}, {
if (input$statisticsMethodsMainTabsetPanel == "plotView" && !(length(reactiveVars$SelectedStoredNetworksIds) ==
length(input$storedGraphsOutputMultipleSelectTopolopgy) &&
all(reactiveVars$SelectedStoredNetworksIds == input$storedGraphsOutputMultipleSelectTopolopgy))) {
reactiveVars$SelectedStoredNetworksIds <- c(input$storedGraphsOutputMultipleSelectTopolopgy)
}
}, ignoreNULL = FALSE)
output$uiStoredGraphsOutputMultipleSelectTopolopgy <- renderUI({
input$btnAddNetwork
input$btnRemoveNetworks
choices <- getStoredNetsChoices()
if (is.null(choices))
return()
return(checkboxGroupInput("storedGraphsOutputMultipleSelectTopolopgy", "Selected network(s)", choices))
})
##########Clustering############
# clusteringTableViewSetSelectedNetwork <- observeEvent({input$storedGraphsOutputSelectClustering; input$clusteringMethodsMainTabsetPanel}, {
# if(input$clusteringMethodsMainTabsetPanel == "tableView" && ! (length(reactiveVars$SelectedStoredNetworksIds) == 1 && reactiveVars$SelectedStoredNetworksIds == input$storedGraphsOutputSelectClustering)){
# reactiveVars$SelectedStoredNetworksIds<-c(input$storedGraphsOutputSelectClustering)
# }
# }, ignoreNULL = FALSE)
# output$uiStoredGraphsOutputSelectClustering <- renderUI({
# input$btnAddNetwork
# input$btnRemoveNetworks
# choices<-getStoredNetsChoices()
# if(is.null(choices)) return()
# return(selectInput("storedGraphsOutputSelectClustering", "Selected network", choices ))
# })
# clusteringPlotViewSetSelectedNetwork <- observeEvent({input$storedGraphsOutputMultipleSelectClustering; input$statisticsMethodsMainTabsetPanel}, {
# if(input$clusteringMethodsMainTabsetPanel == "plotView" && !(length(reactiveVars$SelectedStoredNetworksIds) == length(input$storedGraphsOutputMultipleSelectClustering) && all(reactiveVars$SelectedStoredNetworksIds == input$storedGraphsOutputMultipleSelectClustering))){
# reactiveVars$SelectedStoredNetworksIds<-c(input$storedGraphsOutputMultipleSelectClustering)
# }
# }, ignoreNULL = FALSE)
# output$uiStoredGraphsOutputMultipleSelectClustering <- renderUI({
# input$btnAddNetwork
# input$btnRemoveNetworks
# choices<-getStoredNetsChoices()
# if(is.null(choices)) return()
# return(checkboxGroupInput("storedGraphsOutputMultipleSelectClustering", "Selected network(s)", choices ))
# })
rankingTableViewSetSelectedNetwork <- observeEvent({
input$storedGraphsOutputSelectRanking
input$rankingMethodsMainTabsetPanel
}, {
if (input$rankingMethodsMainTabsetPanel == "tableView" && !(length(reactiveVars$SelectedStoredNetworksIds) ==
1 && reactiveVars$SelectedStoredNetworksIds == input$storedGraphsOutputSelectRanking)) {
reactiveVars$SelectedStoredNetworksIds <- c(input$storedGraphsOutputSelectRanking)
}
}, ignoreNULL = FALSE)
output$uiStoredGraphsOutputSelectRanking <- renderUI({
input$btnAddNetwork
input$btnRemoveNetworks
choices <- getStoredNetsChoices()
if (is.null(choices))
return()
return(selectInput("storedGraphsOutputSelectRanking", "Selected network", choices))
})
rankingPlotViewSetSelectedNetwork <- observeEvent({
input$storedGraphsOutputMultipleSelectRanking
input$rankingMethodsMainTabsetPanel
}, {
if (input$rankingMethodsMainTabsetPanel == "plotView" && !(length(reactiveVars$SelectedStoredNetworksIds) ==
length(input$storedGraphsOutputMultipleSelectRanking) && all(reactiveVars$SelectedStoredNetworksIds ==
input$storedGraphsOutputMultipleSelectRanking))) {
reactiveVars$SelectedStoredNetworksIds <- c(input$storedGraphsOutputMultipleSelectRanking)
}
}, ignoreNULL = FALSE)
output$uiStoredGraphsOutputMultipleSelectRanking <- renderUI({
input$btnAddNetwork
input$btnRemoveNetworks
choices <- getStoredNetsChoices()
if (is.null(choices))
return()
return(selectInput("storedGraphsOutputMultipleSelectRanking", "Selected network", choices))
})
layoutPlotViewSetSelectedNetwork <- observeEvent(input$storedGraphsOutputSelectLayouts, {
reactiveVars$SelectedStoredNetworksIds <- c(input$storedGraphsOutputSelectLayouts)
}, ignoreNULL = FALSE)
output$uiStoredGraphsOutputSelectLayouts <- renderUI({
input$btnAddNetwork
input$btnRemoveNetworks
choices <- getStoredNetsChoices()
if (is.null(choices))
return()
return(selectInput("storedGraphsOutputSelectLayouts", "Selected network", choices))
})
intersectionTabSetSelectedNetworks <- observeEvent({
input$storedGraphsOutputIntersectionSelect1
input$storedGraphsOutputIntersectionSelect2
}, {
reactiveVars$SelectedStoredNetworksIds <- c(input$storedGraphsOutputIntersectionSelect1, input$storedGraphsOutputIntersectionSelect2)
}, ignoreNULL = FALSE)
output$uiStoredGraphsOutputIntersectionSelect1 <- renderUI({
input$btnAddNetwork
input$btnRemoveNetworks
choices <- getStoredNetsChoices()
if (is.null(choices))
return()
return(selectInput("storedGraphsOutputIntersectionSelect1", "Selected first network", choices))
})
output$uiStoredGraphsOutputIntersectionSelect2 <- renderUI({
input$btnAddNetwork
input$btnRemoveNetworks
choices <- getStoredNetsChoices()
if (is.null(choices))
return()
return(selectInput("storedGraphsOutputIntersectionSelect2", "Selected second network", choices))
})
######## Basic Info ################
output$info_vertices1 <- renderText({
igraph <- fetchFirstSelectedStoredIgraph()
if (is.null(igraph))
return()
igraphName <- SelectedStoredNets()$name
paste("Number of nodes in", igraphName, ":", vcount(igraph))
})
output$info_edges1 <- renderText({
igraph <- fetchFirstSelectedStoredIgraph()
if (is.null(igraph))
return()
igraphName <- SelectedStoredNets()$name
paste("Number of intercations in", igraphName, ":", ecount(igraph))
})
##############################################
output$vertices1_label <- renderText({
igraph <- fetchFirstSelectedStoredIgraph()
if (is.null(igraph))
return()
igraphName <- SelectedStoredNets()$name
paste("Number of vertices in", igraphName, ":", vcount(igraph))
})
# Print the vertices
output$vertices1 <- renderPrint({
igraph <- fetchFirstSelectedStoredIgraph()
if (is.null(igraph))
return(invisible(""))
cat(sort(V(igraph)$name, decreasing = FALSE), sep = "\t")
})
output$edges1_label <- renderText({
igraph <- fetchFirstSelectedStoredIgraph()
if (is.null(igraph))
return()
igraphName <- SelectedStoredNets()$name
paste("Number of edges in", igraphName, ":", ecount(igraph))
})
output$edges1 <- renderPrint({
igraph <- fetchFirstSelectedStoredIgraph()
if (is.null(igraph))
return(invisible(""))
if (as.logical(is.directed(igraph))) {
edgesym <- "<U+2794>"
} else {
edgesym <- "<U+2015>"
}
cat(gsub("\\|", edgesym, attr(E(igraph), "vnames")), sep = "\t")
# get.edgelist(igraph) get.data.frame(igraph, what=c( 'edges'))
})
#################################################
output$diameter1 <- renderText({
igraph <- fetchFirstSelectedStoredIgraph()
if (is.null(igraph))
return()
diameter <- diameter(igraph)
paste("Diameter of Graph 1:", diameter)
# unique_vertices <- length(vertices)
})
################################################ https://rstudio.github.io/DT/shiny.html
################################################ http://rstudio.github.io/DT/functions.html
################################################ https://cran.r-project.org/web/packages/DT/DT.pdf Print the data in
################################################ Table format ####################
output$datasettab1 <- DT::renderDataTable({
dataset <- fetchFirstSelectedStoredDataset()
if (is.null(dataset))
dataset <- EmptyDataset(c("Source", "Target", "Weight"))
# if (nrow(dataset) == 0 || attr(dataset, 'weighted'))
if (nrow(dataset) == 0 || attr(dataset, 'weighted')){
return(datatable(dataset, rownames = FALSE) %>% formatStyle(colnames(dataset), fontSize = ui_options["ui_table_font_sz"]) %>% formatRound("Weight"))
} else return(datatable(dataset, rownames = FALSE, options=list(deferRender = TRUE,
scrollY = 500,
scroller = TRUE,pageLength = 500,columnDefs = list(list(visible=FALSE, targets=c(2))))) %>% formatStyle(colnames(dataset),
fontSize = ui_options["ui_table_font_sz"]) %>% formatRound("Weight"))
})
# output$datasettab2 <- DT::renderDataTable({
# dataset <- Dataset2()
# if (is.null(dataset))
# dataset <- EmptyDataset(c("Source", "Target", "Weight"))
# # if (attr(dataset, 'weighted'))
# return(datatable(dataset, rownames = FALSE) %>% formatStyle(colnames(dataset), fontSize = ui_options["ui_table_font_sz"]) %>% formatRound("Weight"))
# # else return( datatable(dataset, rownames = FALSE) %>%
# # formatStyle(colnames(dataset), fontSize =
# # ui_options['ui_table_font_sz']) )
# })
###############################################
############ Plot the graphs ########### output$tabVizIgraphForce <-
############ renderSimpleNetwork({
output$tabVizIgraphForce <- renderVisNetwork({
igraph <- fetchFirstSelectedStoredIgraph()
if (is.null(igraph))
return()
set.seed(123)
igraph_visn <- toVisNetworkData(igraph)
igraph_visn$edges$value <- E(igraph)$weight
if(is.directed(igraph)){
visNetwork(igraph_visn$nodes, igraph_visn$edges) %>%
visNodes(size = 25, shape = "ellipse") %>%
visEdges(arrows = 'to', smooth =T) %>%
visOptions(highlightNearest = TRUE,
nodesIdSelection = TRUE) %>%
visPhysics(enabled = F) %>%
visInteraction(
keyboard = TRUE,
navigationButtons = TRUE,
zoomView = TRUE,
multiselect = TRUE,
dragView = TRUE
)
}else{
visNetwork(igraph_visn$nodes, igraph_visn$edges) %>%
visNodes(size = 25, shape = "ellipse") %>%
visOptions(highlightNearest = TRUE,
nodesIdSelection = TRUE) %>%
visPhysics(enabled = F) %>%
visInteraction(
keyboard = TRUE,
navigationButtons = TRUE,
zoomView = TRUE,
multiselect = TRUE,
dragView = TRUE
)
}
})
rankingMethodsScatterPlot <- renderPlot({
igraph <- fetchFirstSelectedStoredIgraph()
if (is.null(igraph))
return()
})
################ Statistics ########
stat_dataset <- function(dataset, datasetName) {
res <- tryCatch({
columns <- c("Statistics", paste0("Value for ", datasetName))
if (is.null(dataset)) {
dataset <- EmptyDataset(columns)
} else {
igraph <- convert_to_igraph(dataset)
if (length(input$statistics) == 0) {
dataset <- EmptyDataset(columns)
} else {
dataset <- netstats(igraph, input$statistics)
colnames(dataset) <- columns
}
}
return(dataset)
}, warning = function(w) {
}, error = function(e) {
cat(paste0("ERROR while executing stat_dataset: ", e, "\n"))
return(NULL)
}, finally = {
})
return(res)
}
output$statres <- DT::renderDataTable({
dset <- fetchFirstSelectedStoredDataset()
stat_dataset(dset, getDatasetName(attr(dset, "id")))
}, options = list(paging = FALSE, dom = "t", rowCallback = JS("function(row, data) {", "var num = parseFloat(data[2]).toFixed(2);", "if(isNaN(num)){num = data[2];}", "$('td:eq(2)', row).html(num);", "}")))
########### Output Clustering#########
clustering_dataset <- function(dataset){
res <- tryCatch({
columns<-c("Node","Cluster No.")
if(is.null(dataset)){
dataset<-EmptyDataset(columns)
}else{
igraph<-convert_to_igraph(dataset)
if(length(input$statistics)==0){
dataset<-EmptyDataset(columns)
}else{
adjacency<-as_adjacency_matrix(igraph, type ="both")
loopsTF = F
if( is.bipartite(igraph) | is.directed(igraph)){
loopsTF = T
}
inflation_value = input$inflation
mcl_res <- mcl(x=adjacency, max.iter = 1000, addLoops = loopsTF, inflation = inflation_value, allow1 = T)
dataset <- data.frame(as.vector(V(igraph)),mcl_res$Cluster)
colnames(dataset)<-columns
}
}
return(dataset)
}, warning = function(w){
}, error = function(e){
cat(paste0("ERROR while executing clustering_dataset: ",e, "\n"))
return(NULL)
}, finally = {
})
return(res)
}
# output$clusteringres <- DT::renderDataTable({
# clustering_dataset(fetchFirstSelectedStoredDataset())
# }, options = list(paging = FALSE, dom = 't', rowCallback= JS(
# "function(row, data) {",
# "var num = parseFloat(data[2]).toFixed(2);",
# "if(isNaN(num)){num = data[2];}",
# "$('td:eq(2)', row).html(num);",
# "}"
# )))
################ Ranking ###########
rank_dataset <- function(dataset, rankingMethod, nodeRanking = T) {
res <- tryCatch({
if (nodeRanking) {
columns <- c("Node", "Rank")
} else {
columns <- c("Edge", "Rank")
}
if (is.null(dataset) || length(rankingMethod) == 0) {
dataset <- EmptyDataset(columns)
} else {
igraph <- convert_to_igraph(dataset)
if (length(rankingMethod) == 0) {
dataset <- EmptyDataset(columns)
} else {
dataset <- ranking(igraph, rankingMethod, nodeRanking)
colnames(dataset) <- columns
}
}
return(dataset[order(-dataset$Rank), ])
}, warning = function(w) {
}, error = function(e) {
cat(paste0("ERROR while executing rank_dataset: ", e, "\n"))
return(NULL)
}, finally = {
})
return(res)
}
output$rankeddatasettab1 <- DT::renderDataTable({
node_ranking_mode <- input$rankingTableViewTabsetPanel == "Node ranking"
if (node_ranking_mode)
ranking_method <- input$vrankingTableView else ranking_method <- input$erankingTableView
dataset <- fetchFirstSelectedStoredDataset()
if (length(ranking_method) == 1 && !(is.null(dataset) || nrow(dataset) ==
0)) {
dataset <- rank_dataset(dataset, ranking_method, node_ranking_mode)
ranking_method_name <- unlist(strsplit(ranking_method, "\t"))
ranking_method_name <- ranking_method_name[length(ranking_method_name)]
if (is.null(dataset) || nrow(dataset) == 0)
createAlert(session, "tabRankingMainAlert", "rankingAlert",
title = "ERROR !", style = "danger",
content = paste0("Our apologies, an error occured while calculating the '", ranking_method_name, "' ."),
append = FALSE) else return(datatable(dataset, rownames = FALSE) %>% formatStyle(colnames(dataset), fontSize = ui_options["ui_table_font_sz"]) %>% formatRound("Rank"))
}
})
# doRefreshPalette <- observeEvent(input$btnRefreshPalette, {
# ncolors <- length(colors)
# colors <<- randomColor(ncolors)
# })
output$statisticsMethodsBarPlot <- renderPlotly({
# input$btnRefreshPalette
datasets <- fetchAllSelectedStoredDataset()
if (length(datasets) == 0)
return()
stat_res <- NULL
for (dataset_i in 1:length(datasets)) {
dataset <- datasets[[dataset_i]]
datasetName <- getDatasetName(names(datasets)[dataset_i])
dataset_stat_res <- stat_dataset(dataset, "")
if (is.null(dataset_stat_res) || nrow(dataset_stat_res) ==
0)
next
if (is.null(stat_res)) {
stat_res <- dataset_stat_res
stat_res$network <- datasetName
} else {
dataset_stat_res$network <- datasetName
stat_res <- rbind(stat_res, dataset_stat_res)
}
}
if (is.null(stat_res))
return()
colnames(stat_res) <- c("statistic", "value", "network")
stat_res$value <- as.numeric(as.character(stat_res$value))
stat_res$network <- factor(stat_res$network)
ncolors <- length(levels(stat_res$network))
if (length(colors) < ncolors)
colors <<- randomColor(ncolors)
plot.settings <- list(superpose.polygon = list(col = colors[1:ncolors], border = "transparent"),
strip.border = list(col = "black"))
### plotly ###
rows_of_plots<- 0
plot_list = vector("list",length(unique(stat_res$statistic)))
for(i in 1:nrow(stat_res)){
data_i <- paste("data", i, sep = "")
fig_i <- paste("fig", i, sep = "")
data_i <- filter(stat_res, stat_res$statistic == stat_res$statistic[i])
if(length(unique(data_i$network)) == 1){
fig_i<- plot_ly(x = data_i$statistic,
y = data_i$value,
name = data_i$network,
color = data_i$network,
type = "bar", showlegend = T)
fig_i <- fig_i %>% layout(legend = list(orientation = 'h'))
}else {
fig_i<- plot_ly(x = data_i$statistic,
y = data_i$value,
name = data_i$network,
color = data_i$network,
type = "bar", showlegend = F)
}
plot_list[[i]] = fig_i
if(i == length(unique(stat_res$statistic))){
break
}
}
if(any(length(plot_list)==(1:3))==T){
rows_of_plots<- 1
}
if(any(length(plot_list)==(4:6))==T){
rows_of_plots<- 2
}
if(any(length(plot_list)==(7:9))==T){
rows_of_plots<- 3
}
if(any(length(plot_list)==(10:12))==T){
rows_of_plots<- 4
}
if(any(length(plot_list)==(13:15))==T){
rows_of_plots<- 5
}
if(any(length(plot_list)==(15:18))==T){
rows_of_plots<- 6
}
if(any(length(plot_list)==(19))==T){
rows_of_plots<- 7
}
withProgress(min = 0, max = 1, {
incProgress(message = "Processing data into plot",
detail = "This may take a while...",
amount = .5)
subplot(plot_list, nrows = rows_of_plots, which_layout = 1)
})
})
output$statisticsMethodsPlotRender <- renderUI({
plotlyOutput("statisticsMethodsBarPlot", height = paste0(as.integer(600 +
480 * (input$statisticsPlotPercentMagnify/100)), "px"))
})
doStatSelectAll <- observeEvent(input$btnStatSelectAll, {
updateCheckboxGroupInput(session, "statistics", selected = statistics)
})
doStatSelectNone <- observeEvent(input$btnStatSelectNone, {
updateCheckboxGroupInput(session, "statistics", selected = character(0))
})
# output$rankingMethodsScatterPlot <- renderPlotly({
output$rankingMethodsScatterPlot <- renderPlot({
node_ranking_mode <- input$rankingPlotViewTabsetPanel == "Node ranking"
ranking_methods <- NULL
p <- NULL
reactiveVars$plotData <- NULL
if (node_ranking_mode)
ranking_methods <- input$vrankingPlotView else ranking_methods <- input$erankingPlotView
if (!is.null(ranking_methods) && length(ranking_methods) > 1) {
datasets <- fetchMaxNSelectedStoredDataset(2)
if (!is.null(datasets) && length(datasets) > 0) {
ranking_methods_names <- unlist(strsplit(ranking_methods, "\t"))[seq(1, length(ranking_methods) * 2, 2)]
if (length(datasets) > 1) {
# p<-plot(length(datasets))
} else {
dataset <- rank_dataset(datasets[[1]], ranking_methods[1], node_ranking_mode)
if (is.null(dataset) || nrow(dataset) == 0)
createAlert(session, "tabRankingMainAlert", "rankingAlert", title = "ERROR !", style = "danger", content = paste0("Our apologies, an error occured while calculating the '", ranking_methods_names[1], "' ."), append = FALSE)
colnames(dataset)[length(colnames(dataset))] <- ranking_methods_names[1]
for (i in 2:length(ranking_methods)) {
dataset_i <- rank_dataset(datasets[[1]], ranking_methods[i], node_ranking_mode)
if (is.null(dataset_i) || nrow(dataset_i) == 0)
createAlert(session, "tabRankingMainAlert", "rankingAlert", title = "ERROR !", style = "danger", content = paste0("Our apologies, an error occured while calculating the '", ranking_methods_names[i], "' ."), append = FALSE) else {
dataset <- cbind(dataset, dataset_i$Rank)
colnames(dataset)[length(colnames(dataset))] <- ranking_methods_names[i]
}
}
p <- scatterplotmatrix(dataset[, -1], input$IsRankingRegressionEnabled)
reactiveVars$plotData<-dataset
}
}
}
if (!is.null(p)) {
# pp <- ggplotly(p) pp
} else {
return(NULL)
}
})
output$rankingMethodsScatterPlotRender <- renderUI({
plotOutput("rankingMethodsScatterPlot", height = paste0(as.integer(480 +
480 * (input$scatterPlotMatrixPercentMagnify/100)), "px"))
})
################ Testing Ranking Plots #############