# Copyright 2019 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 annual timing of flows
#'
#' @description Plots the timing (day of year and date) of portions of total annual flow of daily flow
#' values from a daily streamflow data set. Calculates statistics from all values from complete years, unless specified.
#' Data calculated using \code{calc_annual_flow_timing()} function. Returns a list of plots.
#'
#' @inheritParams calc_annual_flow_timing
#' @inheritParams plot_annual_stats
#'
#' @return A list of ggplot2 objects with the following for each station provided:
#' \item{Annual_Flow_Timing}{a plot that contains each n-percent of total volumetric discharge}
#' Default plots on each object:
#' \item{DoY_25pct_TotalQ}{day of year of 25-percent of total volumetric discharge}
#' \item{DoY_33.3pct_TotalQ}{day of year of 33.3-percent of total volumetric discharge}
#' \item{DoY_50pct_TotalQ}{day of year of 50-percent of total volumetric discharge}
#' \item{DoY_75pct_TotalQ}{day of year of 75-percent of total volumetric discharge}
#'
#' @references
#' \itemize{
#' \item{Barnett, T.P., Pierce, D.W., Hidalgo, H.G., Bonfils, C., Santer, B.D., Das, T., Bala, G., Wood, A.W.,
#' Nozawa, T., Mirin, A.A., Cayan, D.R., Dettinger, M.D., 2008. Human-Induced Clanges in the Hydrology of
#' the Western United States. Science 319, 1080-1083.}
#' }
#'
#' @seealso \code{\link{calc_annual_flow_timing}}
#'
#' @examples
#' # Run if HYDAT database has been downloaded (using tidyhydat::download_hydat())
#' if (file.exists(tidyhydat::hy_downloaded_db())) {
#'
#' # Plot annual flow timing statistics with default percent totals
#' plot_annual_flow_timing(station_number = "08NM116")
#'
#' # Plot annual flow timing with custom percent totals
#' plot_annual_flow_timing(station_number = "08NM116",
#' percent_total = 50,
#' start_year = 1980)
#'
#' }
#' @export
plot_annual_flow_timing <- function(data,
dates = Date,
values = Value,
groups = STATION_NUMBER,
station_number,
percent_total = c(25,33.3,50,75),
water_year_start = 1,
start_year,
end_year,
exclude_years,
months = 1:12,
include_title = FALSE){
## ARGUMENT CHECKS
## others will be check in calc_ function
## ---------------
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
}
if (missing(exclude_years)) {
exclude_years <- NULL
}
logical_arg_check(include_title)
## FLOW DATA CHECKS AND FORMATTING
## -------------------------------
# Check if data is provided and import it
flow_data <- flowdata_import(data = data, station_number = station_number)
# Check and rename columns
flow_data <- format_all_cols(data = flow_data,
dates = as.character(substitute(dates)),
values = as.character(substitute(values)),
groups = as.character(substitute(groups)),
rm_other_cols = TRUE)
## CALC STATS
## ----------
timing_stats <- calc_annual_flow_timing(data = flow_data,
dates = Date,
values = Value,
percent_total = percent_total,
water_year_start = water_year_start,
start_year = start_year,
end_year = end_year,
exclude_years = exclude_years,
months = months)
timing_stats <- dplyr::filter(dplyr::group_by(timing_stats, STATION_NUMBER),
Year >= Year[min(which(!is.na(.data[[names(timing_stats)[3]]])))])
timing_stats <- dplyr::select(timing_stats, STATION_NUMBER, Year, dplyr::contains("TotalQ"), -dplyr::contains("Date"))
timing_stats <- tidyr::gather(timing_stats, Statistic, Value, -STATION_NUMBER, -Year)
timing_stats <- dplyr::mutate(timing_stats, Statistic = substr(Statistic, 5, nchar(Statistic)))
timing_stats <- dplyr::mutate(timing_stats, Statistic = paste0(gsub("pct_TotalQ", "", Statistic), " Percent"))
## PLOT STATS
## ---------
# Create plots for each STATION_NUMBER in a tibble (see: http://www.brodrigues.co/blog/2017-03-29-make-ggplot2-purrr/)
timing_plots <- dplyr::group_by(timing_stats, STATION_NUMBER)
timing_plots <- tidyr::nest(timing_plots)
timing_plots <- dplyr::mutate(
timing_plots,
plot = purrr::map2(
data, STATION_NUMBER,
~ggplot2::ggplot(data = ., ggplot2::aes(x = Year, y = Value, color = Statistic, fill = Statistic)) +
ggplot2::geom_line(alpha = 0.5, na.rm = TRUE) +
ggplot2::geom_point(na.rm = TRUE, shape = 21, colour = "black", size = 2) +
{if(length(percent_total) > 1) ggplot2::facet_wrap(~Statistic, scales = "free_y", ncol = 1, strip.position = "top")} +
ggplot2::scale_x_continuous(breaks = scales::pretty_breaks(n = 8))+
{if(length(unique(timing_stats$Year)) < 8) ggplot2::scale_x_continuous(breaks = unique(timing_stats$Year))}+
ggplot2::scale_y_continuous(breaks = scales::pretty_breaks(n = 6), expand = ggplot2::expansion(mult = c(0.1, 0.1)))+
ggplot2::ylab(ifelse(water_year_start == 1, "Day of Year", "Day of Water Year"))+
ggplot2::xlab(ifelse(water_year_start == 1, "Year", "Water Year"))+
ggplot2::scale_color_viridis_d()+
ggplot2::scale_fill_viridis_d()+
ggplot2::theme_bw() +
ggplot2::guides(colour = 'none', fill = "none") +
{if (include_title & .y != "XXXXXXX") ggplot2::ggtitle(paste(.y)) } +
ggplot2::theme(legend.position = "right",
legend.spacing = ggplot2::unit(0, "cm"),
legend.justification = "right",
legend.text = ggplot2::element_text(size = 9),
panel.border = ggplot2::element_rect(colour = "black", fill = NA, size = 1),
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"),
strip.background = ggplot2::element_blank(),
strip.text = ggplot2::element_text(hjust = 0, face = "bold", size = 10))
))
# Create a list of named plots extracted from the tibble
plots <- timing_plots$plot
if (nrow(timing_plots) == 1) {
names(plots) <- "Annual_Flow_Timing"
} else {
names(plots) <- paste0(timing_plots$STATION_NUMBER, "_Annual_Flow_Timing")
}
plots
}
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