--- a
+++ b/R/utils-graphics.R
@@ -0,0 +1,542 @@
+ 
+#' Theme for ggplot2
+#' @param base_size Legend title size, all other sizes scaled appropriately 
+#' to this
+#' @param base_family Font family
+#' 
+#' @import ggplot2
+#' 
+theme_bma <- function(
+  base_size = 10, 
+  base_family = get_base_family()
+) {
+
+  `%+replace%` <- ggplot2::`%+replace%`
+
+  base_family <- ifelse(is.null(base_family), get_base_family(), base_family)
+
+  ggplot2::theme_bw(base_size = base_size, base_family = base_family) %+replace%
+    ggplot2::theme(
+      text = ggplot2::element_text(family = base_family),
+      plot.title = ggplot2::element_text(
+        size = base_size + 6,
+        margin = margin(0, 0, 13, 0),
+        hjust = 0,
+        face = "bold"
+      ),
+      plot.title.position = "plot",
+      plot.subtitle = ggplot2::element_text(
+        size = base_size + 4,
+        margin = margin(0, 0, 13, 0),
+        hjust = 0
+      ),
+      axis.text = ggplot2::element_text(size = base_size - 1),
+      axis.title = ggplot2::element_text(size = base_size + 4),
+      axis.title.x = ggplot2::element_text(
+        margin = ggplot2::margin(t = base_size - 1)
+      ),
+      axis.title.y = ggplot2::element_text(
+        margin = ggplot2::margin(l = 0, r = base_size + 1), 
+        angle = 90
+      ),
+      legend.text = ggplot2::element_text(size = base_size),
+      legend.title = ggplot2::element_text(size = base_size + 2),
+      strip.background = ggplot2::element_rect(fill = "grey90")
+    )
+}
+
+
+#' Set base font family for ggplot2.
+#' 
+#' @return Character string of the name of a postscript font related to 
+#' Arial if available, otherwise "sans".
+#' 
+#' @importFrom grDevices postscriptFonts
+#' 
+get_base_family <- function() {
+  avail_fonts <- tryCatch(
+    grDevices::postscriptFonts(),
+    error = function(cond) NULL,
+    warning = function(cond) NULL
+  )
+
+  avail_fontnames <- names(avail_fonts)
+
+  if (any(grepl("Arial", avail_fontnames))) {
+    base_family <- avail_fontnames[grep("Arial", avail_fontnames)[1]]
+  } else {
+    base_family <- "sans"
+  }
+
+  return(base_family)
+}
+
+
+#' Generate arm closure summaries for batches
+#' 
+#' @param file_prefix Consistent beginning of filenames holding 
+#' arm closure data. Defaults to `closures`.
+#' @param run_time Specify a particular instance of `biomkrAccrual()`
+#' execution using a date-time format `yyyy-mm-dd-hh-mm-ss`. 
+#' Used to select which files will be summarised.
+#' @param output_path Directory where the input files are located
+#' and the output files will be written.
+#' @param keep_files Save data files and plots generated during the run. 
+#' Defaults to TRUE.
+#' 
+#' @export
+#' 
+#' @importFrom stats sd
+#' @importFrom utils read.csv write.csv
+#' 
+##### Nothing is calling this?
+get_arm_closures <- function(
+  file_prefix = "closures",
+  run_time = "2024-08-07-18-35-09",
+  output_path = "../biomkrAccrual_output_data/",
+  keep_files = TRUE
+) {
+  # What output files do we have?
+  filenames <- list.files(
+    output_path, 
+    pattern = paste0("^", file_prefix, "-", run_time, ".*.csv"), 
+    full.names = TRUE
+  )
+
+  # Read files
+  closures_ls <- lapply(filenames, read.csv)
+
+  # Summarise files
+  summ <- lapply(closures_ls, function(d) summary(d[, -1]))
+  name_types <- c("1", "2", "mixed", "unbalanced", "multirate", "multimix")
+  names(summ) <- c(
+    paste0("gamma_rate_closures_", name_types),
+    paste0("fixed_rate_closures_", name_types)
+  )
+
+  write.csv(
+    summ, 
+    paste0(output_path, "arm_closure_summary-", run_time, ".csv")
+  )
+
+  # Standard Deviations
+  sd_mx <- t(sapply(
+    closures_ls, 
+    function(a_df) {
+      sapply(
+        seq_len(ncol(a_df)),
+        function(i) stats::sd(a_df[i, ], na.rm = TRUE)
+      )
+    }
+  ))
+
+  sd_mx <- sd_mx[, -1]
+
+  colnames(sd_mx) <- paste0("T", 1:3, "_sd")
+  rownames(sd_mx) <- c(
+    paste0("gamma_rate_closures_", name_types),
+    paste0("fixed_rate_closures_", name_types)
+  )
+
+  write.csv(
+    as.data.frame(sd_mx), 
+    paste0(output_path, "arm_closures_sd", run_time, ".csv")
+  )
+
+  return(list(summ, sd_mx))
+}
+
+
+#' Plot predicted recruitment from file containing a CSV from
+#' a single run
+#' 
+#' @param file_prefix Consistent beginning of filenames holding 
+#' arm closure data. Defaults to `accrual`.
+#' @param plot_prefix Prefix for file name to identify plot type. 
+#' Defaults to `accrual_plot`.
+#' @param run_time Specify a particular instance of `biomkrAccrual()`
+#' execution using a date-time format `yyyy-mm-dd-hh-mm-ss`. 
+#' Used to select which files will be summarised.
+#' @param output_path Directory where the output files from the 
+#' `biomkrAccrual()` instance are located.
+#' @param figs_path Folder where figures generated during execution
+#' will be stored; defaults to the `figures` subdirectory in
+#' `output_path`.
+#' 
+#' @export
+#' 
+accrual_plot_from_file <- function(
+  file_prefix = "accrual",
+  plot_prefix = "accrual-from-file",
+  run_time = "2024-08-07-18-35-09",
+  output_path = "../biomkrAccrual_output_data/",
+  figs_path = paste0(output_path, "figures/")
+) {
+  # Validate input
+
+  checkmate::assert_directory_exists(
+    file.path(output_path), 
+    access = "rx"
+  )
+
+  input_file <- paste0(
+    output_path, file_prefix, "-", run_time, ".csv"
+  )
+
+  checkmate::assert_file_exists(file.path(input_file))
+
+  makeifnot_dir(figs_path, min_access = "rwx")
+
+  accrual_raw_df <- utils::read.csv(file.path(input_file))
+
+  # Get unique arm identifiers
+  arm_names <- unique(sapply(
+    strsplit(names(accrual_raw_df), "\\."), 
+    getElement,
+    1
+  ))
+
+  # Make dataframe of arm recruitment per week by summing site-arm columns
+  accrual_df <- as.data.frame(
+    lapply(
+      arm_names, 
+      function(n) rowSums(accrual_raw_df[startsWith(names(accrual_raw_df), n)])
+    ),
+    col.names = arm_names
+  )
+
+  # Convert to long format of class "accrualplotdata"
+  accrual_df <- accrual_to_long(accrual_df)
+
+  # Plot 
+  p <- plot(
+    accrual_df, 
+    plot_prefix = plot_prefix,
+    run_time = run_time
+  )
+
+  print(p)
+
+  ggplot2::ggsave(
+    paste0(figs_path, plot_prefix, "-", run_time, ".png"),
+    plot = p,
+    width = 12,
+    height = 8,
+    dpi = 400
+  )
+}
+
+
+#' Convert accrual data to long format dataframe of class
+#' `accrualplotformat`.
+#' 
+#' @param accrual_df Wide format accrual data.
+#' 
+#' @importFrom stats reshape
+#' 
+accrual_to_long <- function(accrual_df) {
+  # Convert to cumulative sums
+  accrual_df <- cumsum(accrual_df)
+
+  arm_names <- names(accrual_df)
+
+  # Add week information
+  accrual_df$Week <- seq_len(nrow(accrual_df))
+
+  # Convert to long format
+  accrual_df <- stats::reshape(
+    accrual_df,
+    direction = "long",
+    varying = list(arm_names),
+    timevar = "Arm",
+    times = arm_names,
+    v.names = "Recruitment",
+    idvar = "Week"
+  )
+
+  accrual_df$Arm <- factor(accrual_df$Arm)
+
+  # Define an S3 class so we can have a custom plot command
+  class(accrual_df) <- c("accrualplotdata", class(accrual_df))
+
+  return(accrual_df)
+}
+
+
+#' S3 method to plot predicted recruitment from a long format 
+#' dataframe of class "accrualplotdata".
+#' 
+#' @param data long format dataframe with columns "Week", 
+#' "Arm" and "Recruitment".
+#' @param plot_prefix Prefix for file name to identify plot type.
+#' Defaults to `accrual_plot`.
+#' @param run_time Specify a particular instance of `biomkrAccrual()`
+#' execution using a date-time format `yyyy-mm-dd-hh-mm-ss`.
+#' @param output_path = Directory where the output files from the 
+#' `biomkrAccrual()` instance are located.
+#' @param figs_path Folder where figures generated during execution
+#' will be stored; defaults to the `figures` subdirectory in
+#' `output_path`.
+#' @param target_arm_size Number of subjects required for each treatment arm.
+#' @param target_control Number of subjects required for control arm(s).
+#' @param target_interim Number of subjects required for treatment arm at 
+#' interim analysis.
+#' @param accrual_period Number of weeks in recruitment period.
+#' @param interim_period Number of weeks to recruit for interim analysis.
+#' 
+#' @import ggplot2
+#' @importFrom grDevices palette.colors
+#' @importFrom rlang .data
+#' 
+plot.accrualplotdata <- function(
+  data,
+  plot_prefix = "accrual_plot",
+  run_time = NULL,
+  output_path = "../biomkrAccrual_output_data/",
+  figs_path = paste0(output_path, "figures/"),
+  target_arm_size = NA_integer_,
+  target_control = NA_integer_,
+  target_interim = NA_integer_,
+  accrual_period = NA_integer_,
+  interim_period = NA_integer_
+) {
+  
+  accrual_df <- data
+  arm_names <- levels(accrual_df$Arm)
+
+  linetypes <- c(
+    "Interim arm" = 2, "Experimental arm" = 3, "Control arm" = 4,
+    "Interim accrual" = 5, "Total accrual" = 6
+  )
+
+  hline_y <- c(target_interim, target_arm_size, target_control)
+  vline_x <- c(interim_period, accrual_period)
+
+  p <- ggplot2::ggplot(
+    accrual_df, 
+    ggplot2::aes(
+      x = .data$Week, 
+      y = .data$Recruitment, 
+      group = .data$Arm, 
+      color = .data$Arm
+    )
+  ) +
+    ggplot2::geom_line(linewidth = 1) +
+    # Use colourblind friendly Okabe-Ito palette
+    ggplot2::scale_colour_manual(
+      values = grDevices::palette.colors(length(arm_names))
+    ) +
+    ggplot2::geom_vline(
+      xintercept = vline_x,
+      linewidth = 1,
+      linetype = 2:3,
+      color = "grey75"
+    ) +
+    ggplot2::geom_hline(
+      yintercept = hline_y,
+      linewidth = 1,
+      linetype = 4:6,
+      color = "grey65"
+    ) +
+    ggplot2::labs(
+      title = "Accrual plot"
+    ) +
+    theme_bma(base_size = 16)
+
+  return(p)
+}
+
+
+#' Plot distributions of recruitment to arms at given time.
+#' 
+#' @param data Matrix with columns for each recruitment arm, 
+#' including control.
+#' @param target Vector of targets for recruitment. First two
+#' should be those directly relevant to the subject of the graph.
+#' @param target_names Vector of target names, for labelling.
+#' @param target The adjust parameter from `ggplot2::geom_density`;
+#' higher values mean more smoothing. Defaults to 1.
+#' 
+#' @importFrom stats reshape
+#' @import ggplot2
+#' @importFrom grDevices palette.colors
+#' 
+#' @export
+#' 
+plot.armtotals <- function(
+  data,
+  target,
+  target_names,
+  target_week,
+  adjust = 1
+) {
+  data_df <- matrix_to_long(data)
+
+  # Which of the accrual targets are within the dataset
+  if (length(target) > 2) {
+    target_indices <- 
+      c(1:2, 2 + which(target[-c(1, 2)] <= max(data_df$Recruitment)))
+  } else {
+    target_indices <- seq_len(length(target))
+  }
+  target <- target[target_indices]
+  target_names <- target_names[target_indices]
+
+  p <- ggplot2::ggplot(
+    data = data_df
+  ) +
+    ggplot2::geom_density(
+      ggplot2::aes(
+        x = Recruitment, group = Arm, fill = Arm, col = Arm
+      ),
+      alpha = 0.4, adjust = 1
+    ) +
+    ggplot2::scale_fill_manual(
+      values = grDevices::palette.colors(length(unique(data_df$Arm))),
+      aesthetics = c("color", "fill")
+    ) +
+    ggplot2::geom_vline(
+      xintercept = target, 
+      linetype = "dashed",
+      linewidth = 1,
+      colour = "grey65"
+    ) +
+    ggplot2::labs(
+      y = "Probability density",
+      title = target_names[1],
+    ) +
+    theme_bma(base_size = 16)
+
+  p <- label_vlines(p, target, target_names)
+
+  return(p)
+}
+
+
+#' Adds labels for vlines to accrual plots
+#' 
+#' @param p Ggplot object.
+#' @param target Vector of x axis positions of vlines.
+#' @param target_names Vector of target names (excluding the
+#' word `target`).
+#' @param size Font size (in ggplot measure) for labels; 
+#' defaults to 6.
+#' 
+label_vlines <- function(
+  p,
+  target,
+  target_names,
+  size = 6
+) {
+  # Get height of y axis for this particular plot
+  label_y <- round(ggplot2::layer_scales(p)$y$range$range[2], 2)
+
+  # Get x range of plot
+  xrange <- round(ggplot2::layer_scales(p)$x$range$range, 2)
+
+  whisker <- diff(xrange) * .2
+
+  # There's more than one target.  Move labels for the one at the range end
+
+  # Add labels for vlines
+  abline_df <- data.frame(
+    x = target, 
+    y = label_y * 0.9, 
+    label = paste(target_names, "\ntarget")
+  )
+
+  p <- p +
+    ggplot2::geom_text(
+      data = abline_df,
+      ggplot2::aes(x = x, y = y, label = label),
+      size = size,
+      family = get_base_family()
+    )
+
+  return(p)
+}
+
+
+#' Plot single arm accrual plot
+#' 
+#' Bodge, fix later
+#' 
+#' 
+accrual_arm_plot <- function(
+  data_df,
+  arm_colours,
+  treatment_arms,
+  targets,
+  plot_id,
+  i
+) {
+  arm_names <- colnames(data_df)
+
+  if (length(unique(data_df[, i])) == 1) {
+    # BODGE - don't want to see this but need it to produce graph
+    arm_col <- "white"
+    alpha <- 0.0001
+  } else {
+    arm_col <- arm_colours[i]
+    alpha <- 0.4
+  }
+
+
+  p <- ggplot2::ggplot(
+    data = data_df
+  ) +
+    ggplot2::geom_density(
+      ggplot2::aes(x = .data[[arm_names[i]]]),
+      col = arm_col, fill = arm_col,
+      alpha = alpha, adjust = 1
+    ) 
+  
+  if (length(unique(data_df[, i])) == 1) {
+    p <- p +
+      ggplot2::geom_vline(
+        xintercept = unique(data_df[, i]),
+        linewidth = 2,
+        colour = arm_colours[i],
+        alpha = 0.4
+      )
+  }
+
+  p <- p + 
+    ggplot2::geom_vline(
+      xintercept = ifelse(
+        treatment_arms[i], 
+        targets[1], 
+        targets[2]
+      ), 
+      linetype = "dashed",
+      linewidth = 1,
+      colour = "grey75"
+    ) +
+    ggplot2::labs(
+      x = paste(
+        "No. virtual patients recruited at", 
+        "target week for",
+        tolower(plot_id)
+      ),
+      y = "Probability density",
+      title = paste(plot_id, "for", arm_names[i]),
+    ) +
+    ggplot2::scale_x_continuous(expand = expansion(mult = 0.07)) +
+    theme_bma(base_size = 16)
+
+  p <- label_vlines(
+    p, 
+    target = ifelse(
+      treatment_arms[i],
+      targets[1], 
+      targets[2]
+    ),
+    target_names = ifelse(
+      treatment_arms[i],
+      plot_id, 
+      paste0(plot_id, "\ncontrol")
+    )
+  )
+
+  return(p)
+}
\ No newline at end of file