namespace trellis improvements

DESCRIPTION

@@ -28,8 +28,10 @@ Imports:
     dplyr,
     ggplot2,
     gridExtra,
+    methods,
     minerva,
     randomForest,
+    rlang,
     stats,
     tidyr
 Suggests: 

NAMESPACE

@@ -17,7 +17,6 @@ importFrom(dplyr,group_by)
 importFrom(dplyr,select)
 importFrom(dplyr,summarise)
 importFrom(ggplot2,aes)
-importFrom(ggplot2,aes_string)
 importFrom(ggplot2,element_text)
 importFrom(ggplot2,geom_line)
 importFrom(ggplot2,geom_point)
@@ -32,9 +31,11 @@ importFrom(ggplot2,xlim)
 importFrom(ggplot2,ylab)
 importFrom(ggplot2,ylim)
 importFrom(gridExtra,grid.arrange)
+importFrom(methods,is)
 importFrom(minerva,mine)
 importFrom(randomForest,importance)
 importFrom(randomForest,randomForest)
+importFrom(rlang,.data)
 importFrom(stats,cor)
 importFrom(stats,lm)
 importFrom(stats,model.frame)

R/ggvip.R

@@ -3,8 +3,9 @@
 #' @importFrom randomForest importance
 #' @importFrom dplyr %>% arrange desc filter between case_when
 #' @importFrom ggplot2 ggplot geom_point xlim xlab ylab ggtitle theme
-#'   aes_string element_text
+#'   aes element_text
 #' @importFrom gridExtra grid.arrange
+#' @importFrom rlang .data
 #' @description A ggplot of variable importance as measured by a Random Forest.
 #' @param x An object of class randomForest.
 #' @param scale For permutation based measures such as MSE or Accuracy, should
@@ -83,18 +84,18 @@ ggvip <- function(x, scale = FALSE, sqrt = TRUE, type = "both", num_var) {
     )
 
     g <- imp_frame %>%
-      ggplot(aes_string(
-        x = colnames(imp_frame)[1],
-        y = colnames(imp_frame)[2]
+      ggplot(aes(
+        x = .data[[colnames(imp_frame)[1]]],
+        y = .data[[colnames(imp_frame)[2]]]
       )) +
       geom_point() +
       scale_x_continuous(
         limits = c(0, newm),
         breaks = seq(0, newm, by = newm / div)
       ) +
       ylab(NULL) +
-      xlab(ifelse(sqrt == FALSE, colnames(imp_frame)[1],
-        paste0("sqrt(", colnames(imp_frame)[1], ")")
+      xlab(ifelse(sqrt, paste0("sqrt(", colnames(imp_frame)[1], ")"),
+                  colnames(imp_frame)[1]
       )) +
       ggtitle("VIP") +
       theme(plot.title = element_text(hjust = 0.5))
@@ -139,18 +140,19 @@ ggvip <- function(x, scale = FALSE, sqrt = TRUE, type = "both", num_var) {
     )), ]
 
     g1 <- imp_frame %>%
-      ggplot(aes_string(
-        x = colnames(imp_frame)[1],
-        y = colnames(imp_frame)[3]
+      ggplot(aes(
+        x = .data[[colnames(imp_frame)[1]]],
+        y = .data[[colnames(imp_frame)[3]]]
       )) +
       geom_point() +
       scale_x_continuous(
         limits = c(0, newm),
         breaks = seq(0, newm, by = newm / div)
       ) +
       ylab(NULL) +
-      xlab(ifelse(sqrt == FALSE, colnames(imp_frame)[1],
-        paste0("sqrt(", colnames(imp_frame)[1], ")")
+      xlab(ifelse(sqrt,
+                  paste0("sqrt(", colnames(imp_frame)[1], ")"),
+                  colnames(imp_frame)[1]
       ))
 
     imp_frame <- imp_frame[do.call(base::order, as.list(imp_frame[2])), ]
@@ -183,18 +185,18 @@ ggvip <- function(x, scale = FALSE, sqrt = TRUE, type = "both", num_var) {
     )), ]
 
     g2 <- imp_frame %>%
-      ggplot(aes_string(
-        x = colnames(imp_frame)[2],
-        y = colnames(imp_frame)[3]
+      ggplot(aes(
+        x = .data[[colnames(imp_frame)[2]]],
+        y = .data[[colnames(imp_frame)[3]]]
       )) +
       geom_point() +
       scale_x_continuous(
         limits = c(0, newm),
         breaks = seq(0, newm, by = newm / div)
       ) +
       ylab(NULL) +
-      xlab(ifelse(sqrt == FALSE, colnames(imp_frame)[2],
-        paste0("sqrt(", colnames(imp_frame)[2], ")")
+      xlab(ifelse(sqrt, paste0("sqrt(", colnames(imp_frame)[2], ")"),
+                  colnames(imp_frame)[2]
       ))
 
     l <- list()

R/mtry_compare.R

@@ -4,9 +4,11 @@
 #' @importFrom dplyr %>% arrange across ends_with desc filter select
 #'   summarise group_by case_when
 #' @importFrom ggplot2 ggplot geom_point geom_line ylab ggtitle theme
-#'   aes_string scale_x_continuous scale_y_continuous
+#'   aes scale_x_continuous scale_y_continuous
 #' @importFrom tidyr pivot_wider
 #' @importFrom stats model.frame na.omit quantile
+#' @importFrom methods is
+#' @importFrom rlang .data
 #' @description A list of data.frames and useful plots for user evaluations of
 #'   the randomForest hyperparameter mtry.
 #' @param formula an object of class "\link{formula}" (or one that can be
@@ -185,9 +187,9 @@ mtry_compare <- function(formula, data = NULL, scale = FALSE, sqrt = TRUE,
   )
 
   g1 <- sd %>%
-    ggplot(aes_string(
-      x = colnames(sd)[4], y = colnames(sd)[1],
-      color = colnames(sd)[3], group = colnames(sd)[3]
+    ggplot(aes(
+      x = .data[[colnames(sd)[4]]], y = .data[[colnames(sd)[1]]],
+      color = .data[[colnames(sd)[3]]], group = .data[[colnames(sd)[3]]]
     )) +
     geom_point() +
     geom_line() +
@@ -218,9 +220,9 @@ mtry_compare <- function(formula, data = NULL, scale = FALSE, sqrt = TRUE,
   )
 
   g2 <- sd %>%
-    ggplot(aes_string(
-      x = colnames(sd)[4], y = colnames(sd)[2],
-      color = colnames(sd)[3], group = colnames(sd)[3]
+    ggplot(aes(
+      x = .data[[colnames(sd)[4]]], y = .data[[colnames(sd)[2]]],
+      color = .data[[colnames(sd)[3]]], group = .data[[colnames(sd)[3]]]
     )) +
     geom_point() +
     geom_line() +
@@ -251,7 +253,8 @@ mtry_compare <- function(formula, data = NULL, scale = FALSE, sqrt = TRUE,
   )
 
   g_err <- err_df %>%
-    ggplot(aes_string(x = colnames(err_df)[1], y = colnames(err_df)[2])) +
+    ggplot(aes(x = .data[[colnames(err_df)[1]]],
+               y = .data[[colnames(err_df)[2]]])) +
     geom_point() +
     geom_line() +
     scale_x_continuous(limits = c(1, num_preds), breaks = mvec) +

R/robust_vifs.R

@@ -1,7 +1,8 @@
 #' Non-linear Variance Inflation Factors
 #' @name robust_vifs
 #' @importFrom stats lm model.frame
-#' @importFrom ggplot2 ggplot geom_point xlim ylim geom_line ggtitle geom_vline
+#' @importFrom ggplot2 ggplot geom_point xlim ylim aes
+#'   geom_line ggtitle geom_vline
 #' @importFrom dplyr %>% arrange desc
 #' @importFrom car vif
 #' @description A list of data.frames and useful plots for user evaluations of
@@ -78,7 +79,7 @@ robust_vifs <- function(formula, data, model = randomForest,
     vdf[k - 1, 5] <- r2
   }
 
-  if (log10 == TRUE) {
+  if (log10) {
     vdf$lm_vif <- log10(vdf$lm_vif)
     vdf$model_vif <- log10(vdf$model_vif)
     colnames(vdf)[c(2, 4)] <- c("Log10_lm_vif", "Log10_model_vif")