updated docs + boxplot

R/regression_plot.R

@@ -33,7 +33,7 @@ plot.tbl_regression <- function(x,
   # gtsummary:::check_scalar_logical(remove_reference_rows)
 
   df_coefs <- x$table_body
-  browser()
+
   if (isTRUE(remove_header_rows)) {
     df_coefs <- df_coefs |> dplyr::filter(!header_row %in% TRUE)
   }
@@ -48,22 +48,16 @@ plot.tbl_regression <- function(x,
   if (plot_ref == TRUE){
   df_coefs[df_coefs$var_type == "categorical" & is.na(df_coefs$reference_row),"estimate"] <- if (x$inputs$exponentiate) 1 else 0}
 
-  df_coefs |>
+  p <- df_coefs |>
     ggstats::ggcoef_plot(exponentiate = x$inputs$exponentiate, ...)
+
+  if (x$inputs$exponentiate){
+    p <- symmetrical_scale_x_log10(p)
+  }
+  p
 }
 
 
-# default_parsing(mtcars) |> lapply(class)
-#
-# purrr::imap(mtcars,\(.x,.i){
-#   if (.i %in% c("vs","am","gear","carb")){
-#     as.factor(.x)
-#   } else .x
-#   }) |> dplyr::bind_cols()
-#
-#
-
-
 #' Wrapper to pivot gtsummary table data to long for plotting
 #'
 #' @param list a custom regression models list
@@ -103,3 +97,47 @@ merge_long <- function(list, model.names) {
 
   l_merged
 }
+
+
+#' Easily round log scale limits for nice plots
+#'
+#' @param data data
+#' @param fun rounding function (floor/ceiling)
+#' @param ... ignored
+#'
+#' @returns numeric vector
+#' @export
+#'
+#' @examples
+#' limit_log(-.1,floor)
+#' limit_log(.1,ceiling)
+#' limit_log(-2.1,ceiling)
+#' limit_log(2.1,ceiling)
+limit_log <- function(data,fun,...){
+  fun(10^-floor(data)*10^data)/10^-floor(data)
+}
+
+#' Ensure symmetrical plot around 1 on a logarithmic x scale for ratio plots
+#'
+#' @param plot ggplot2 plot
+#' @param breaks breaks used and mirrored
+#' @param ... ignored
+#'
+#' @returns ggplot2 object
+#' @export
+#'
+symmetrical_scale_x_log10 <- function(plot,breaks=c(1,2,3,5,10),...){
+  rx <- ggplot2::layer_scales(plot)$x$get_limits()
+
+  x_min <- floor(10*rx[1])/10
+  x_max <- ceiling(10*rx[2])/10
+
+  rx_min <- limit_log(rx[1],floor)
+  rx_max <- limit_log(rx[2],ceiling)
+
+  max_abs_x <- max(abs(c(x_min,x_max)))
+
+  ticks <- log10(breaks)+(ceiling(max_abs_x)-1)
+  browser()
+  plot + ggplot2::scale_x_log10(limits=c(rx_min,rx_max),breaks=create_log_tics(10^ticks[ticks<=max_abs_x]))
+}