add individual trajectories plot

R/biokinetics.R

@@ -475,7 +475,7 @@ biokinetics <- R6::R6Class(
     },
     #' @description Simulate individual trajectories from the model. This is
     #' computationally expensive and may take a while to run if n_draws is large.
-    #' @return A data.table. If summarise = TRUE columns are calendar_date, titre_type, me, lo, hi, time_shift.
+    #' @return A data.table. If summarise = TRUE columns are calendar_day, titre_type, me, lo, hi, time_shift.
     #' If summarise = FALSE, columns are pid, draw, time_since_last_exp, mu, titre_type, exposure_day, calendar_day, time_shift
     #' and a column for each covariate in the regression model. See the data vignette for details:
     #' \code{vignette("data", package = "epikinetics")}.

R/plot.R

@@ -118,6 +118,61 @@ plot.biokinetics_population_trajectories <- function(x, ..., data = NULL) {
            shape = guide_legend(title = "Censored"))
 }
 
+#' Plot method for "biokinetics_individual_trajectories" class
+#'
+#' @param x An object of class "biokinetics_individual_trajectories". These are
+#' generated by running biokinetics$simulate_individual_trajectories(). See
+#' \href{../../epikinetics/html/biokinetics.html#method-biokinetics-simulate_individaul_trajectories}{\code{biokinetics$simulate_individual_trajectories()}}
+#' @param \dots Further arguments passed to the method.
+#' @export
+plot.biokinetics_individual_trajectories <- function(x, ..., data = NULL,
+                                                     min_date = NULL,
+                                                     max_date = NULL) {
+
+  # Declare variables to suppress notes when compiling package
+  # https://github.com/Rdatatable/data.table/issues/850#issuecomment-259466153
+  calendar_day <- value <- me <- mu <- titre_type <- lo <- hi <- day <- pid <- NULL
+  if (is.null(min_date)) {
+    min_date <- min(x$calendar_day)
+  }
+  if (is.null(max_date)) {
+    max_date <- max(x$calendar_day)
+  }
+  if (attr(x, "summarised")) {
+    plot <- ggplot(x) +
+      geom_line(aes(x = calendar_day, y = me, group = titre_type, colour = titre_type)) +
+      geom_ribbon(aes(x = calendar_day,
+                      ymin = lo,
+                      ymax = hi,
+                      group = titre_type), alpha = 0.5)
+  } else {
+    plot <- ggplot(x) +
+      geom_line(aes(x = calendar_day, y = mu,
+                    colour = titre_type, group = pid), alpha = 0.1, linewidth = 0.1)
+  }
+  if (!is.null(data)) {
+    validate_required_cols(data, c("day", "value"))
+    plot <- plot +
+      geom_point(data = data,
+                 aes(x = day,
+                     y = value), size = 0.5, alpha = 0.5)
+  }
+  plot +
+    labs(x = "Date",
+         y = expression(paste("Titre (IC"[50], ")"))) +
+    geom_smooth(
+      aes(x = calendar_day,
+          y = me,
+          fill = titre_type,
+          colour = titre_type,
+          group = titre_type),
+      alpha = 0.5, span = 0.2) +
+    scale_x_date(date_labels = "%b %Y",
+                 limits = c(min_date, max_date)) +
+    guides(colour = guide_legend(title = "Titre type"),
+           fill = "none")
+}
+
 facet_formula <- function(covariates) {
   paste("~", paste(c("titre_type", covariates), collapse = "+"))
 }
@@ -126,8 +181,8 @@ add_censored_indicator <- function(data) {
   if (!("censored" %in% colnames(data))) {
     # censored is an optional column in input data
     # if not present, treat all points as uncensored
-    data[, censored:= FALSE]
+    data[, censored := FALSE]
   } else {
-    data[, censored:= censored != 0]
+    data[, censored := censored != 0]
   }
 }