Merge pull request #455 from UCD-SERG/update_graph_curve2

Add chain_color option to graph.curve.params() for customizing MCMC line color

Author: Kwan-Jenny

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: serocalculator
 Title: Estimating Infection Rates from Serological Data
-Version: 1.3.0.9057
+Version: 1.3.0.9058
 Authors@R: c(
     person("Peter", "Teunis", , "p.teunis@emory.edu", role = c("aut", "cph"),
            comment = "Author of the method and original code."),

NEWS.md

@@ -2,6 +2,7 @@
 
 ## New features
 
+* Added `chain_color` option to `graph.curve.params()` to control MCMC line color (#455)
 * Made `graph.curve.params()` the default sub-method for `autoplot.curve_params()` (#450)
 * Added `log_x` and `log_y` options to `graph.curve.params()` sub-method for 
 `autoplot.curve_params()` (#453)

R/graph.curve.params.R

@@ -14,6 +14,9 @@
 #' or linear scale (`FALSE`, default)?
 #' @param log_y should the Y-axis be on a logarithmic scale
 #' (default, `TRUE`) or linear scale (`FALSE`)?
+#' @param chain_color [logical]: if [TRUE] (default), MCMC chain lines
+#' are colored by chain.
+#' If [FALSE], all MCMC chain lines are black.
 #' @inheritParams plot_curve_params_one_ab
 #' @param ... not currently used
 #' @returns a [ggplot2::ggplot()] object showing the antibody dynamic
@@ -31,6 +34,7 @@ graph.curve.params <- function( # nolint: object_name_linter
   verbose = FALSE,
   quantiles = c(0.1, 0.5, 0.9),
   alpha_samples = 0.3,
+  chain_color = TRUE,
   log_x = FALSE,
   log_y = TRUE,
   n_curves = 100,
@@ -150,14 +154,13 @@ graph.curve.params <- function( # nolint: object_name_linter
         mutate(
           group = interaction(across(all_of(group_vars)))
         )
-
       plot1 <-
         plot1 +
         geom_line(
           data = sc_to_graph,
           alpha = alpha_samples,
           aes(
-            color = .data$chain |> factor(),
+            color = if (chain_color) .data$chain |> factor(),
             group = .data$group
           )
         )
@@ -201,10 +204,12 @@ graph.curve.params <- function( # nolint: object_name_linter
         linewidth = 0.75
       )
 
-    if (length(iters_to_graph) > 0) {
-      plot1 <- plot1 +
-        ggplot2::labs(col = "MCMC chain")
+    label <- if (length(iters_to_graph) > 0 && chain_color) {
+      "MCMC chain"
+    } else {
+      ""
     }
+    plot1 <- plot1 + ggplot2::labs(col = label)
   }
 
 

inst/examples/exm-graph.curve.params.R

@@ -13,3 +13,12 @@ plot2 <- graph.curve.params(
   quantiles = c(0.1, 0.5, 0.9)
 )
 print(plot2)
+
+# Plot with MCMC chains in black
+plot3 <- graph.curve.params(
+  curve,
+  n_curves = Inf,
+  quantiles = c(0.1, 0.5, 0.9),
+  chain_color = FALSE
+)
+print(plot3)

man/graph.curve.params.Rd

@@ -19,7 +19,7 @@ test_that(
     )
     plot2 |> vdiffr::expect_doppelganger(title = "curve-quantiles-and-samples")
 
-    # 3. Curves only, no quantiles
+    # 3. Test that disabling quantiles works correctly (curves only)
     plot3 <- graph.curve.params(
       curve,
       n_curves = Inf,
@@ -28,14 +28,22 @@ test_that(
 
     plot3 |> vdiffr::expect_doppelganger(title = "curve-samples")
 
-    # 4. Custom numeric quantiles only
+    # 4. Test that custom numeric quantiles are drawn correctly
     plot4 <- graph.curve.params(
       curve,
       n_curves = 0,
       quantiles = c(0.05, 0.55, 0.95)
     )
     plot4 |> vdiffr::expect_doppelganger(title = "curve-custom-quantiles")
 
+    # 5. Test that chain_color = FALSE works correctly
+    plot5 <- graph.curve.params(
+      curve,
+      n_curves = Inf,
+      quantiles = c(0.05, 0.55, 0.95),
+      chain_color = FALSE
+    )
+    plot5 |> vdiffr::expect_doppelganger(title = "curve-black-chains")
   }
 )
 
@@ -46,10 +54,11 @@ test_that(
       typhoid_curves_nostrat_100 |>
       dplyr::filter(antigen_iso %in% c("HlyE_IgA", "HlyE_IgG")) |>
       dplyr::mutate(.by = antigen_iso, chain = rep(1:2, times = n() / 2))
+
+    # Test that log_x argument works with samples only
     plot3 <- graph.curve.params(
       curve,
       n_curves = Inf,
-      show_quantiles = TRUE,
       log_x = TRUE
     )
     plot3 |>