Fix estimate_density plotting error with vector input and group_by

R/plot.estimate_density.R

@@ -11,6 +11,22 @@ data_plot.estimate_density <- function(
   if (!"Parameter" %in% names(dataplot)) {
     dataplot$Parameter <- "Distribution"
   }
+
+  # Handle case where Parameter column exists but is empty or malformed
+  if ("Parameter" %in% names(dataplot)) {
+    # Check for various problematic conditions with descriptive variables
+    parameter_is_empty <- length(dataplot$Parameter) == 0
+    parameter_all_na <- all(is.na(dataplot$Parameter))
+    parameter_all_empty_strings <- all(dataplot$Parameter == "")
+    parameter_no_unique_values <- length(unique(dataplot$Parameter[!is.na(dataplot$Parameter)])) == 0
+
+    parameter_is_problematic <- parameter_is_empty || parameter_all_na || 
+                               parameter_all_empty_strings || parameter_no_unique_values
+
+    if (parameter_is_problematic) {
+      dataplot$Parameter <- rep("Distribution", nrow(dataplot))
+    }
+  }
 
   # add component and effects columns
   if (!is.null(data)) {
@@ -23,11 +39,25 @@ data_plot.estimate_density <- function(
 
   dataplot <- .fix_facet_names(dataplot)
 
-  dataplot$Parameter <- factor(dataplot$Parameter)
-  dataplot$Parameter <- factor(
-    dataplot$Parameter,
-    levels = rev(levels(dataplot$Parameter))
-  )
+  # Safely convert Parameter to factor, ensuring it has valid data
+  parameter_column_exists <- "Parameter" %in% names(dataplot)
+  parameter_has_data <- length(dataplot$Parameter) > 0
+  parameter_length_matches <- length(dataplot$Parameter) == nrow(dataplot)
+  parameter_not_all_na <- !all(is.na(dataplot$Parameter))
+
+  parameter_is_valid_for_factor <- parameter_column_exists && parameter_has_data && 
+                                   parameter_length_matches && parameter_not_all_na
+
+  if (parameter_is_valid_for_factor) {
+    dataplot$Parameter <- factor(dataplot$Parameter)
+    dataplot$Parameter <- factor(
+      dataplot$Parameter,
+      levels = rev(levels(dataplot$Parameter))
+    )
+  } else {
+    # If Parameter column is still problematic, set a default with correct length
+    dataplot$Parameter <- factor(rep("Distribution", nrow(dataplot)))
+  }
 
   # summary
   split_columns <- intersect(
@@ -250,6 +280,12 @@ plot.see_estimate_density <- function(
       p <- p + facet_wrap(~Component, scales = "free", ncol = n_columns)
     }
   }
+
+  # Handle Group column for grouped data (e.g., from group_by in estimate_density)
+  # Only add facets if not already faceting by other variables and if we have groups
+  if ("Group" %in% names(x) && is.null(n_columns)) {
+    p <- p + facet_wrap(~Group, scales = "free")
+  }
 
   p
 }

tests/testthat/test-plot.estimate_density.R

@@ -9,6 +9,25 @@ test_that("`plot.see_estimate_density()` works", {
 })
 
 
+test_that("`plot.see_estimate_density()` works with group_by and vector input", {
+  skip_if_not_installed("bayestestR")
+  skip_if_not_installed("vdiffr")
+
+  # Test case that was failing: vector input with group_by
+  df <- bayestestR::estimate_density(iris[c("Species", "Petal.Width")], group_by = "Species")
+
+  # This should not error
+  expect_no_error(p <- plot(df))
+  expect_s3_class(p, "gg")
+
+  # Visual snapshot test
+  vdiffr::expect_doppelganger(
+    title = "plot.estimate_density with group_by and vector input",
+    fig = plot(df)
+  )
+})
+
+
 test_that("`plot.see_estimate_density()`, adding prior layers works", {
   skip_if_not_installed("curl")
   skip_if_offline()