Create ide.config object when loading rds settings file. Replace deprecated aes_string() function.

R/datafile.R

@@ -370,6 +370,7 @@ input_data_server <- function(input, output, session) {
         for(field in inputChoices.params) {
           rv$inputChoices[[field]] <- settings[[field]]
         }
+        ide.config <- NULL
       } else if(!is.null(input$readConfigFile) && has_extension(input$readConfigFile$datapath, 'toml') == TRUE) {
         # A TOML config file was uploaded
         ide.config <- read.config(file = input$readConfigFile$datapath)

R/explore_plot.R

@@ -81,7 +81,7 @@ plot_server <- function(input, output, session, rv) {
     }
     if(length(selectedCols) > 0 && length(selectedCols) <= 2) {
       colours <- "grey"
-      p <- ggplot(data = Dunselected, aes_string(x = selectedCols[1], y = selectedCols[2], key = "ide.id")) +
+      p <- ggplot(data = Dunselected, aes(x = .data[[selectedCols[1]]], y = .data[[selectedCols[2]]], key = .data[["ide.id"]])) +
         labs(x = eval(selectedCols[1]), y = eval(selectedCols[2])) +
         coord_cartesian(expand = TRUE)
       if(!is.null(rv$clusters)) {
@@ -118,7 +118,7 @@ plot_server <- function(input, output, session, rv) {
       if(!is.null(rv$selectedRows) && length(rv$selectedRows)>0) {
         # Selected points
         p <- p + geom_point(data = D[rv$selectedRows,],
-                            aes_string(x = selectedCols[1], y = selectedCols[2], key = "ide.id"),
+                            aes(x = .data[[selectedCols[1]]], y = .data[[selectedCols[2]]], key = .data[["ide.id"]]),
                             colour = "black")
       }
       ggplotly(p, dynamicTicks = TRUE, tooltip = "none", source = "scatterPlot") %>% 
@@ -165,7 +165,7 @@ plot_server <- function(input, output, session, rv) {
       } else {
         clusters <- NULL
       }
-      p <- ggplot(data = D, aes_string(x = selectedCols[1], fill = clusters, color = clusters))
+      p <- ggplot(data = D, aes(x = .data[[selectedCols[1]]], fill = clusters, color = clusters))
       # Heuristic to choose binning
       if(max(D[, get(selectedCols[1])], na.rm = TRUE)>10) { # use binwidth = 1
         p <- p + geom_histogram(position = "identity", binwidth = 1, aes(y = after_stat(count)), alpha = 0.5) +
@@ -175,7 +175,7 @@ plot_server <- function(input, output, session, rv) {
           scale_color_manual(name = "", values = colours) + scale_fill_manual(name = "", values = colours)
       }
     } else {
-      p <- ggplot(data = D, aes_string(x = selectedCols[1]))
+      p <- ggplot(data = D, aes(x = .data[[selectedCols[1]]]))
       if(max(D[, get(selectedCols[1])], na.rm = TRUE)>10) { # use binwidth = 1
         p <- p + geom_histogram(position = "identity", binwidth = 1, aes(y = after_stat(count)), color=colours, fill=colours)
       } else { # make 30 bins
@@ -217,11 +217,11 @@ plot_server <- function(input, output, session, rv) {
       if(any(levels(clusters)=="N/A")) {
         clusters <- relevel(clusters, "N/A") # Make N/A first level
       }
-      p <- ggplot(data = D, aes_string(x = "clusters", y = selectedCols[1])) +
+      p <- ggplot(data = D, aes(x = .data[["clusters"]], y = .data[[selectedCols[1]]])) +
         theme(axis.text.x=element_blank(), axis.title.x=element_blank(),  axis.ticks.x=element_blank())
       if(n.clusters<=8) {
         colours <- c("grey", brewer.pal(n = 8, name = "Set1"))
-        p <- p + geom_boxplot(aes_string(fill = "clusters", color = "clusters")) +
+        p <- p + geom_boxplot(aes(fill = .data[["clusters"]], color = .data[["clusters"]])) +
           scale_fill_manual(name = "", values = colours) +
           scale_color_manual(name = "", values = colours)
       } else if(n.clusters<=25) {
@@ -230,16 +230,16 @@ plot_server <- function(input, output, session, rv) {
                      "#FFCC99", "#94FFB5", "#8F7C00", "#9DCC00", "#C20088", "#003380", "#FFA405",
                      "#FFA8BB", "#426600", "#FF0010", "#5EF1F2", "#00998F", "#E0FF66", "#740AFF", 
                      "#990000", "#FFFF80", "#FFE100", "#FF5005")
-        p <- p + geom_boxplot(aes_string(fill = "clusters", color = "clusters")) +
+        p <- p + geom_boxplot(aes(fill = .data[["clusters"]], color = .data[["clusters"]])) +
           scale_fill_manual(name = "", values = colours) +
           scale_color_manual(name = "", values = colours)
       } else {
-        p <- p + geom_boxplot(aes_string(fill = "clusters", color = "clusters")) +
+        p <- p + geom_boxplot(aes(fill = .data[["clusters"]], color = .data[["clusters"]])) +
           scale_fill_manual(name = "", values = rep('#A4A4A4', n.clusters)) +
           scale_color_manual(name = "", values = rep('black', n.clusters))
       }
     } else {
-      p <- ggplot(data = D, aes_string(y = selectedCols[1])) +
+      p <- ggplot(data = D, aes(y = .data[[selectedCols[1]]])) +
         geom_boxplot(color=colours, fill=colours)
     }
     p <- p + theme(plot.title = element_blank(), legend.title = element_blank())