library(DiagrammeR)
library(dplyr)

add_stars <- function(p) {
  case_when(
    is.na(p)  ~ "",
    p < 0.001 ~ "***",
    p < 0.01  ~ "**",
    p < 0.05  ~ "*",
    TRUE      ~ ""
  )
}

selected_predictor <- "Apathy"
predictor_node <- selected_predictor
predictor_label <- "Apathy"

df_pred <- Path_Coefficients_Adjusted %>%
  filter(Predictor == selected_predictor) %>%
  mutate(
    Outcome_Node = paste0("Outcome_", Outcome),
    a_label = paste0(sprintf("%.2f", Path_A_Beta), add_stars(Path_A_p)),
    b_label = paste0(sprintf("%.2f", Path_B_Beta), add_stars(Path_B_p))
  )

mediator_labels <- df_pred %>%
  distinct(Mediator) %>%
  mutate(
    Mediator_Label = case_when(
      Mediator == "Active_Approach" ~ "Actively Approach",
      Mediator == "Withdrawal" ~ "Withdrawal",
      Mediator == "Social_Support" ~ "Seeking Social Support",
      Mediator == "Self_blame" ~ "Self-blame",
      Mediator == "Planning" ~ "Refocus on Planning",
      Mediator == "Reappraisal" ~ "Positive Reappraisal",
      TRUE ~ Mediator
    )
  )

outcome_labels <- df_pred %>%
  distinct(Outcome_Node, Outcome) %>%
  mutate(
    Outcome_Label = case_when(
      Outcome == "WEMWBS" ~ "Mental Wellbeing",
      Outcome == "GDS" ~ "Depression",
      Outcome == "GAD" ~ "Anxiety",
      TRUE ~ Outcome
    )
  )

a_edges <- df_pred %>%
  distinct(Predictor, Mediator, a_label) %>%
  mutate(edge = paste0(Predictor, " -> ", Mediator,
                       ' [label = "', a_label, '"];')) %>%
  pull(edge)

b_edges <- df_pred %>%
  distinct(Mediator, Outcome_Node, b_label) %>%
  mutate(edge = paste0(Mediator, " -> ", Outcome_Node,
                       ' [label = "', b_label, '"];')) %>%
  pull(edge)

all_edges <- paste(c(a_edges, b_edges), collapse = "\n  ")

predictor_node_def <- paste0(
  predictor_node,
  ' [label = "', predictor_label,
  '", shape = box, style = filled, fillcolor = lightblue]'
)

mediator_nodes <- paste0(
  mediator_labels$Mediator,
  ' [label = "', mediator_labels$Mediator_Label,
  '", shape = ellipse, style = filled, fillcolor = lightyellow]'
) %>% paste(collapse = "\n  ")

outcome_nodes <- paste0(
  outcome_labels$Outcome_Node,
  ' [label = "', outcome_labels$Outcome_Label,
  '", shape = box, style = filled, fillcolor = lightpink]'
) %>% paste(collapse = "\n  ")

# Graphviz settings
diagram_code <- paste0("
digraph mediation {

 graph [
   layout = dot,
   rankdir = LR,
   fontname = Helvetica,
   margin = 0,
   pad = 0.02,
   nodesep = 0.6,
   ranksep = 0.9
 ]

 node [fontname = Helvetica, fontsize = 10]
 edge [fontname = Helvetica, fontsize = 9]

 ", predictor_node_def, "
 ", mediator_nodes, "
 ", outcome_nodes, "

 ", all_edges, "
}
")

# Preview in RStudio viewer
grViz(diagram_code)

# EXPORT EPS TO DESKTOP
desktop_path <- file.path(
  path.expand("~"),
  "Desktop",
  "SETON_figure1.eps"
)

dot_file <- tempfile(fileext = ".dot")
writeLines(diagram_code, dot_file)

system2("dot", args = c("-Teps", dot_file, "-o", desktop_path))

cat("EPS saved to:", desktop_path)