R/plot_annual_symbols.R

In bcgov/fasstr: Analyze, Summarize, and Visualize Daily Streamflow Data

# Copyright 2022 Province of British Columbia
# 
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# 
# http://www.apache.org/licenses/LICENSE-2.0
# 
# Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and limitations under the License.


#' @title Plot daily streamflow data symbols by year
#'
#' @description Plots data symbols for a daily data set by year, either by day of year, total days, or percent of year (see
#'     \code{plot_type} argument. A column of symbols is required, default \code{symbols = 'Symbol'}. For HYDAT data, symbols
#'     include: 'E' Estimate, 'A' Partial Day, 'B' Ice Conditions, 'D' Dry, and 'R' Revised. Other symbols or categories may be 
#'     used to colour points of plot. Returns a list of plots.
#'
#' @inheritParams plot_flow_data_symbols
#' @param plot_type Character. One of \code{c('dayofyear','count','percent'}. With 'dayofyear' plot (default), the day of year for
#'    each year of data are coloured by symbols or missing dates are colours for each flow day of year. For 'count' and
#'    'percent' plots, the total count or percent of all symbols or missing dates per year are displayed.
#'
#' @return A list of ggplot2 objects with the following for each station provided:
#'   \item{Annual_Symbols}{a plot that contains data symbols and missing dates}
#'   
#' @examples
#' # Run if HYDAT database has been downloaded (using tidyhydat::download_hydat())
#' if (file.exists(tidyhydat::hy_downloaded_db())) {
#' 
#' # Plot annual symbol counts from a data frame and data argument
#' flow_data <- tidyhydat::hy_daily_flows(station_number = "08NM116")
#' plot_annual_symbols(data = flow_data)
#' 
#' # Plot annual symbol counts using station_number argument with defaults
#' plot_annual_symbols(station_number = "08NM116")
#' 
#' # Plot annual symbol percentages using station_number argument and plot by annual counts
#' plot_annual_symbols(station_number = "08NM116",
#'                     plot_type = "count")
#'                   
#' }
#' @export

plot_annual_symbols <- function(data,
                                dates = Date,
                                values = Value,
                                groups = STATION_NUMBER,
                                symbols = Symbol,
                                station_number,
                                water_year_start = 1,
                                start_year,
                                end_year,
                                months = 1:12,
                                include_title = FALSE,
                                plot_type = "dayofyear"){           
  
  
  ## ARGUMENT CHECKS
  ## ---------------
  
  if (missing(data)) {
    data <- NULL
  }
  if (missing(station_number)) {
    station_number <- NULL
  }
  if (missing(start_year)) {
    start_year <- 0
  }
  if (missing(end_year)) {
    end_year <- 9999
  }
  
  water_year_checks(water_year_start)
  years_checks(start_year, end_year, exclude_years = NULL)
  logical_arg_check(include_title)
  months_checks(months)
  
  if (length(plot_type) > 1)        stop("Only one plot_type logical value can be listed.", call. = FALSE)
  if (!plot_type %in% c("dayofyear","count","percent"))       
    stop("plot_type argument must be one of 'dayofyear','count','percent'.", call. = FALSE)
  
  ## FLOW DATA CHECKS AND FORMATTING
  ## -------------------------------
  
  # Check if data is provided and import it
  flow_data <- flowdata_import(data = data, station_number = station_number)
  flow_data$Symbols_fasstr <- dplyr::pull(flow_data[as.character(substitute(symbols))])
  
  
  if (plot_type %in% c("count","percent")) {
    
    symbol_data <- screen_flow_data(data = flow_data,
                                    symbols = "Symbols_fasstr",
                                    water_year_start = water_year_start,
                                    start_year = start_year,
                                    end_year = end_year,
                                    months = months,
                                    include_symbols = TRUE)
    
    
    symbol_data <- symbol_data[,1:which(names(symbol_data)=="Minimum")-1]
    symbol_data <- tidyr::pivot_longer(symbol_data, cols = 5:ncol(symbol_data), names_to = "Symbol", values_to = "Count")
    symbol_data <- dplyr::ungroup(symbol_data)
    symbol_data <- dplyr::mutate(symbol_data,
                                 Percent = Count / n_days * 100,
                                 Symbol = sub("\\_.*", "", Symbol),
                                 Symbol = dplyr::case_when(Symbol == "n" ~ "Missing",
                                                           Symbol == "No" ~ "No Symbol",
                                                           TRUE ~ Symbol))
    
    y_title <- ifelse(plot_type == "count", paste0("Number of Days"),
                      ifelse(plot_type == "percent", paste0("Percent of Days"), NA))
    
    # Plot the data
    sym_plots <- dplyr::group_by(symbol_data, STATION_NUMBER)
    sym_plots <- tidyr::nest(sym_plots)
    sym_plots <- dplyr::mutate(
      sym_plots,
      plot = purrr::map2(
        data, STATION_NUMBER,
        ~ggplot2::ggplot(data = ., ggplot2::aes(x = Year, fill = Symbol)) +
          {if (plot_type == "count") ggplot2::geom_bar(mapping = ggplot2::aes(y = Count), position = "stack", stat = "identity", width=1, colour = "black") }+
          {if (plot_type == "percent") ggplot2::geom_bar(mapping = ggplot2::aes(y = Percent), position = "stack", stat = "identity", width=1, colour = "black") }+
          ggplot2::ylab(y_title)+
          {if (include_title & .y != "XXXXXXX") ggplot2::ggtitle(.y) } +
          ggplot2::xlab(ifelse(water_year_start ==1, "Year", "Water Year"))+
          ggplot2::theme_bw()+
          ggplot2::scale_y_continuous(expand = c(0,0))+
          ggplot2::scale_x_continuous(expand = c(0,0))+
          ggplot2::theme(panel.border = ggplot2::element_rect(colour = "black", fill = NA, size = 1),
                         legend.position = "right",
                         legend.spacing = ggplot2::unit(0, "cm"),
                         legend.text = ggplot2::element_text(size = 9),
                         panel.grid = ggplot2::element_line(size = .2),
                         axis.title = ggplot2::element_text(size = 12),
                         axis.text = ggplot2::element_text(size = 10),
                         plot.title = ggplot2::element_text(hjust = 1, size = 9, colour = "grey25")) +
          ggplot2::scale_fill_viridis_d(begin = 1, end = 0)
      ))
    
  } else {
    
    origin_date <- get_origin_date(water_year_start)
    
    symbol_data <- format_all_cols(data = flow_data,
                                   dates = as.character(substitute(dates)),
                                   values = as.character(substitute(values)),
                                   groups = as.character(substitute(groups)),
                                   symbols = as.character(substitute(symbols)),
                                   rm_other_cols = TRUE,
                                   keep_symbols = TRUE)
    
    symbol_data <- analysis_prep(symbol_data, water_year_start = water_year_start)
    
    symbol_data <- dplyr::mutate(symbol_data,
                                 Symbol = ifelse(is.na(Symbol), "No Symbol", Symbol),
                                 Symbol = ifelse(is.na(Value), "Missing", Symbol),
                                 AnalysisDate = as.Date(DayofYear, origin = origin_date))
    
    symbol_data <- dplyr::filter(symbol_data, 
                                 WaterYear >= start_year & WaterYear <= end_year,
                                 Month %in% months,
                                 DayofYear < 366)
    
    # Plot the data
    sym_plots <- dplyr::group_by(symbol_data, STATION_NUMBER)
    sym_plots <- tidyr::nest(sym_plots)
    sym_plots <- dplyr::mutate(
      sym_plots,
      plot = purrr::map2(
        data, STATION_NUMBER,
        ~ggplot2::ggplot(data = ., ggplot2::aes(x = AnalysisDate, y= WaterYear, fill = Symbol)) +
          ggplot2::geom_tile()+
          ggplot2::xlab("Day of Year")+
          {if (include_title & .y != "XXXXXXX") ggplot2::ggtitle(.y) } +
          ggplot2::ylab(ifelse(water_year_start ==1, "Year", "Water Year"))+
          ggplot2::theme_bw()+
          ggplot2::scale_x_date(date_labels = "%b", date_breaks = "1 month",
                                limits = as.Date(c(as.character(min(symbol_data$AnalysisDate, na.rm = TRUE)),
                                                   as.character(max(symbol_data$AnalysisDate, na.rm = TRUE)))),
                                expand = c(0,0)) +
          ggplot2::scale_y_continuous(expand = c(0,0), breaks = scales::pretty_breaks(7))+
          ggplot2::theme(panel.border = ggplot2::element_rect(colour = "black", fill = NA, size = 1),
                         legend.position = "right",
                         legend.spacing = ggplot2::unit(0, "cm"),
                         legend.text = ggplot2::element_text(size = 9),
                         panel.grid = ggplot2::element_line(size = .2),
                         axis.title = ggplot2::element_text(size = 12),
                         axis.text = ggplot2::element_text(size = 10),
                         plot.title = ggplot2::element_text(hjust = 1, size = 9, colour = "grey25")) +
          ggplot2::scale_fill_viridis_d(begin = 1, end = 0)
      ))
  }
  
  # Create a list of named plots extracted from the tibble
  plots <- sym_plots$plot
  if (nrow(sym_plots) == 1) {
    names(plots) <- "Annual_Symbols"
  } else {
    names(plots) <- paste0(sym_plots$STATION_NUMBER, "_Annual_Symbols")
  }
  
  plots
  
}