WIP

swimlane POC

Author: gogonzo

R/tm_p_swimlane.R

@@ -0,0 +1,57 @@
+tm_p_swimlane <- function(label = "Swimlane Plot Module", dataname, id_var, avisit_var, shape_var, color_var) {
+  module(
+    label = label,
+    ui = ui_p_swimlane,
+    server = srv_p_swimlane,
+    datanames = "synthetic_data",
+    server_args = list(
+      dataname = dataname,
+      id_var = id_var,
+      avisit_var = avisit_var,
+      shape_var = shape_var,
+      color_var = color_var
+    )
+  )
+}
+
+ui_p_swimlane <- function(id) {
+  ns <- NS(id)
+  shiny::tagList(
+    teal.widgets::plot_with_settings_ui(ns("myplot")),
+    teal::ui_brush_filter(ns("brush_filter"))
+  )
+}
+
+srv_p_swimlane <- function(id, data, dataname, id_var, avisit_var, shape_var, color_var, filter_panel_api) {
+  moduleServer(id, function(input, output, session) {
+    output_q <- reactive({
+      within(data(),
+        {
+          p <- ggplot(dataname, aes(x = avisit_var, y = subjid)) +
+            ggtitle("Swimlane Efficacy Table") +
+            geom_line(linewidth = 0.5) +
+            geom_point(aes(shape = shape_var), size = 5) +
+            geom_point(aes(color = color_var), size = 2) +
+            scale_shape_manual(values = c("Drug A" = 1, "Drug B" = 2)) +
+            scale_color_manual(values = c("CR" = "#9b59b6", "PR" = "#3498db")) +
+            labs(x = "Study Day", y = "Subject ID")
+        },
+        dataname = as.name(dataname),
+        id_var = as.name(id_var),
+        avisit_var = as.name(avisit_var),
+        shape_var = as.name(shape_var),
+        color_var = as.name(color_var)
+      )
+    })
+
+    plot_r <- reactive(output_q()$p)
+    pws <- teal.widgets::plot_with_settings_srv(id = "myplot", plot_r = plot_r)
+
+    teal::srv_brush_filter(
+      "brush_filter",
+      brush = pws$brush,
+      dataset = reactive(teal.code::dev_suppress(output_q()$synthetic_data)),
+      filter_panel_api = filter_panel_api
+    )
+  })
+}

inst/swimlane_poc.R

@@ -0,0 +1,49 @@
+pkgload::load_all("teal")
+pkgload::load_all("teal.widgets")
+pkgload::load_all("teal.modules.general")
+
+
+# Example data
+data <- within(teal_data(), {
+  library(dplyr)
+  library(tidyr)
+
+  set.seed(123) # Setting a seed for reproducibility
+  # Define possible maximum study days
+  .possible_end_days <- c(50, 60, 70)
+
+  # Create sample data
+  synthetic_data <- tibble(subjid = c(1:15)) |>
+    rowwise() |>
+    mutate(
+      max_study_day = sample(.possible_end_days, 1),
+      study_day = list(seq(10, max_study_day, by = 10))
+    ) |>
+    unnest(study_day) |>
+    group_by(subjid) |>
+    mutate(
+      assigned_drug = sample(c("Drug A", "Drug B"), 1)
+    ) |>
+    ungroup() |>
+    mutate(
+      response_type = sample(c("CR", "PR"), n(), replace = TRUE),
+      subjid = reorder(as.character(subjid), max_study_day)
+    ) |>
+    select(-max_study_day)
+})
+
+app <- init(
+  data = data,
+  modules = modules(
+    tm_p_swimlane(
+      dataname = "synthetic_data",
+      id_var = "usubjid",
+      avisit_var = "study_day",
+      shape_var = "assigned_drug",
+      color_var = "response_type"
+    )
+  ),
+  title = "Swimlane Efficacy Plot"
+)
+
+shinyApp(app$ui, app$server)