R/xs_compare_plot_L1.R

In FluvialGeomorph/fluvgeo: A Package for Fluvial Geomorphic Analysis

#' @title Overplot multiple cross section profile surveys
#'
#' @description Produces a cross section profile plot for the specified cross
#' section for the input surveys.
#'
#' @export
#' @param stream              character; The name of the stream.
#' @param xs_number           integer; The cross section `Seq` number.
#' @param xs_pts_sf_list      list; a list of `sf` objects of cross
#'                            section points, one for each survey time period
#'                            to be graphed. Survey list items must be tagged
#'                            with the survey label to be used in the graph
#'                            legend.
#'
#' @return A ggplot2 object.
#'
#' @details This function is used to plot the cross section profile from a
#' series of \code{xs_points} data frames representing multiple surveys.
#'
#' @seealso The \code{xs_compre_plot} function requires a \code{xs_points}
#' dataframe. See the \code{sin_xs_points} package dataset for an example of
#' this format of cross section data produced by the \code{FluvialGeomorph}
#' ArcGIS toolbox.
#'
#' @importFrom sf st_drop_geometry
#' @importFrom purrr map
#' @importFrom dplyr filter bind_rows
#' @importFrom rlang .data
#' @importFrom ggplot2 ggplot
#'
xs_compare_plot_L1 <- function(stream, xs_number, xs_pts_sf_list) {
  # Extract data frames (for ggplot2) from the sf objects
  xs_pts_df <- purrr::map(xs_pts_sf_list, sf::st_drop_geometry)

  # Filter for the current reach and xs_number
  xs_current <- purrr::map(xs_pts_df,
                    ~dplyr::filter(.x, ReachName == stream & Seq == xs_number))

  # Combine surveys
  xs_pts <- dplyr::bind_rows(xs_current, .id = "Survey")

  # Define survey factor levels
  survey_levels <- sort(unique(as.character(xs_pts$Survey)),
                        decreasing = TRUE)
  xs_pts$Survey <- factor(xs_pts$Survey,
                          levels = survey_levels,
                          labels = survey_levels,
                          ordered = TRUE)

  # Define colors
  cols <- c("coral3", "darkslategray4", "darkolivegreen", "mediumpurple4")

  # Define minor break interval
  minor_breaks <- seq(floor(min(xs_pts$DEM_Z)),
                      ceiling(max(xs_pts$DEM_Z)), by = 1)

  # Draw the graph
  p <- ggplot(data = xs_pts,
              aes(x = .data$POINT_M * 3.28084,
                  y = .data$DEM_Z,
                  color = .data$Survey)) +
    geom_line(size = 1.25) +
    scale_y_continuous(minor_breaks = minor_breaks) +
    scale_color_manual(values = cols) +
    theme_bw() +
    theme(aspect.ratio = 2/5,
          legend.direction = "vertical",
          legend.position = c(0.07,0.2),
          legend.background = element_rect(fill = alpha('white', 0.6)),
          legend.title = element_blank(),
          panel.grid.major = element_line(colour = "grey", size = 0.1),
          plot.title = element_text(hjust = 0),
          ) +
    labs(title = paste("Cross Section ", as.character(xs_number)),
         x = "Station Distance (feet, from left descending bank, looking downstream)",
         y = "Elevation (NAVD88 feet)")
  return(p)
}