Gof trt boxplot fix

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: cqtkit
 Title: Comprehensive C-QT Analysis From Data to Deliverables
-Version: 1.0.0
+Version: 1.0.1
 Authors@R: c(
     person("Matt", "Smith", , "matthews@a2-ai.com", role = c("aut", "cre")),
     person("Devin", "Pastoor", , "devin@a2-ai.com", role = c("aut")),

NEWS.md

@@ -1,3 +1,12 @@
+# cqtkit 1.0.1
+
+### Fixed
+* Exposed the intended optional `legend_location` argument in `gof_residuals_trt_boxplots()`.
+* Updated `predict_with_observations_plot` to use `trt_col` to group data allowing for styling.
+* Updated `predict_with_observations_plot` and `predict_with_quantiles_plot` to keep default black color
+for prediction line when other colors supplied.
+* Updated `eda_quantiles_plot` with `plot_observations` to add individual data points to plot.
+
 # cqtkit 1.0.0
 
 * Initial public release.

R/compute.R

@@ -1512,11 +1512,21 @@ compute_contrast_observations <- function(
 
   if (is.null(control_predictors)) {
     # Simple case: no control group subtraction
-    observed_df <- tibble::tibble(
-      group = "Observations",
-      conc = data %>% dplyr::pull(!!conc),
-      dv = data %>% dplyr::pull(!!dv)
-    )
+    if (rlang::quo_is_null(trt)) {
+      # No treatment column provided, use default grouping
+      observed_df <- tibble::tibble(
+        group = "Observations",
+        conc = data %>% dplyr::pull(!!conc),
+        dv = data %>% dplyr::pull(!!dv)
+      )
+    } else {
+      # Use treatment column for grouping
+      observed_df <- tibble::tibble(
+        group = data %>% dplyr::pull(!!trt),
+        conc = data %>% dplyr::pull(!!conc),
+        dv = data %>% dplyr::pull(!!dv)
+      )
+    }
   } else {
     # Control group subtraction case
     trt_str <- rlang::as_name(trt)
@@ -1527,7 +1537,7 @@ compute_contrast_observations <- function(
       # Individual ID+time matching (crossover studies)
       treatment_df <- data %>%
         dplyr::filter(!!rlang::sym(trt_str) == !!treatment_value) %>%
-        dplyr::select(!!id, !!ntime, !!conc, treatment_dv = !!dv)
+        dplyr::select(!!id, !!ntime, !!conc, !!trt, treatment_dv = !!dv)
 
       control_df <- data %>%
         dplyr::filter(!!rlang::sym(trt_str) == !!control_value) %>%
@@ -1540,7 +1550,7 @@ compute_contrast_observations <- function(
         ) %>%
         dplyr::mutate(dv = .data$treatment_dv - .data$control_dv) %>%
         dplyr::transmute(
-          group = "Observations",
+          group = !!trt,
           conc = !!conc,
           dv
         )
@@ -1564,7 +1574,7 @@ compute_contrast_observations <- function(
         dplyr::left_join(control_means, by = rlang::as_name(ntime)) %>%
         dplyr::mutate(dv = !!dv - .data$control_mean_dv) %>%
         dplyr::transmute(
-          group = "Observations",
+          group = !!trt,
           conc = !!conc,
           dv
         )

R/eda.R

@@ -283,6 +283,7 @@ eda_qtc_comparison_plot <- function(
 #' @param xdata_col An unquoted column name for x data
 #' @param ydata_col An unquoted column name for y data
 #' @param trt_col An unquoted column name for treatment column to stratify the data by
+#' @param plot_observations A boolean to include the raw individual data points as background points, default FALSE
 #' @param conf_int Numeric confidence interval level (default: 0.9)
 #' @param error_bars A string for setting which errorbars are shown, CI, SE, SD
 #' @param style A named list of arguments passed to style_plot()
@@ -312,6 +313,7 @@ eda_quantiles_plot <- function(
   xdata_col,
   ydata_col,
   trt_col = NULL,
+  plot_observations = FALSE,
   conf_int = 0.90,
   error_bars = "CI",
   style = list()
@@ -347,15 +349,32 @@ eda_quantiles_plot <- function(
         group = .data$.trt_group,
         color = .data$.trt_group
       )
-    ) +
-    ggplot2::geom_point(
+    )
+
+  if (plot_observations) {
+    p <- p +
+      ggplot2::geom_point(
+        data = data,
+        ggplot2::aes(
+          x = !!xdata,
+          y = !!ydata,
+          color = !!trt,
+        ),
+        alpha = 0.25
+      )
+  }
+
+  p <- p +
+      ggplot2::geom_point(
       ggplot2::aes(
         shape = .data$.trt_group
       )
     ) +
     ggplot2::geom_smooth(method = "lm", formula = y ~ x, level = conf_int) +
     ggplot2::theme_bw()
 
+
+
   p <- add_error_bars_to_plot(obs, p, NULL, error_bars, conf_int)
   caption <- p$labels$caption
 

R/gof.R

@@ -688,6 +688,7 @@ gof_residuals_time_boxplots <- function(
 #' @param ntime_col An unquoted column name for nominal time since dose
 #' @param trt_col An unquoted column name for treatment group"
 #' @param residual_references Numeric vector of reference residual lines to add, default -2 and 2
+#' @param legend_location String for legend position (top, bottom, left, right)
 #' @param style A named list of arguments passed to style_plot()
 #'
 #' @return a ggarrange plot
@@ -715,12 +716,15 @@ gof_residuals_trt_boxplots <- function(
   ntime_col,
   trt_col = NULL,
   residual_references = c(-2, 2),
+  legend_location = c("top", "bottom", "left", "right", "none"),
   style = list()
 ) {
   checkmate::assertDataFrame(data)
   checkmate::assert(checkmate::check_class(fit, "lme"))
   checkmate::assert_numeric(residual_references, null.ok = TRUE)
 
+  legend_location <- match.arg(legend_location)
+
   dv <- rlang::enquo(dv_col)
   conc <- rlang::enquo(conc_col)
   time <- rlang::enquo(ntime_col)
@@ -772,10 +776,13 @@ gof_residuals_trt_boxplots <- function(
   trt_plot <- ggpubr::ggarrange(
     plotlist = trtg_plots,
     ncol = 1,
-    common.legend = TRUE
+    common.legend = TRUE,
+    legend = legend_location
   )
-  if (!is.null(style$title))
+
+  if (!is.null(style$title)) {
     trt_plot <- ggpubr::annotate_figure(trt_plot, top = style$title)
+  }
 
   return(trt_plot)
 }

R/predict.R

@@ -135,6 +135,8 @@ predict_with_observations_plot <- function(
   attr(p, "fill_colors") <- stats::setNames("grey", ci_label)
   # default open circle for line group
   attr(p, "secondary_shapes") <- stats::setNames(1, "Predictions")
+  # default black color for predictions line
+  attr(p, "prediction_colors") <- stats::setNames("black", "Predictions")
 
   # Add reference line(s)
   p <- add_horizontal_references(p, reference_threshold)
@@ -378,6 +380,8 @@ predict_with_quantiles_plot <- function(
   # Add attributes for styling
   attr(p, "fill_colors") <- stats::setNames("grey", ci_label)
   attr(p, "secondary_shapes") <- stats::setNames(1, "Predictions")
+  # default black color for predictions line
+  attr(p, "prediction_colors") <- stats::setNames("black", "Predictions")
 
   p <- add_horizontal_references(p, reference_threshold)
   p <- p + ggplot2::theme_bw() + ggplot2::labs(caption = caption)

R/style.R

@@ -385,7 +385,10 @@ style_plot <- function(
     p,
     aesthetic = "color",
     groups = color_groups,
-    default_map = attr(p, "reference_colors") %||% character(0),
+    default_map = c(
+      attr(p, "reference_colors") %||% character(0),
+      attr(p, "prediction_colors") %||% character(0)
+    ),
     user_values = colors,
     user_labels = labels,
     scale_fn = ggplot2::scale_color_manual