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plot_annual_lowflows.R
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plot_annual_lowflows.R
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# 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 low flows and dates
#'
#' @description Plot annual n-day minimum values, and the day of year and date of occurrence of daily flow values from a daily
#' streamflow data set. Calculates statistics from all values, unless specified. Data calculated from \code{calc_annual_lowflows()}
#' function. Returns a list of plots.
#'
#' @inheritParams calc_annual_lowflows
#' @inheritParams plot_annual_stats
#'
#' @return A list of ggplot2 objects with the following for each station provided:
#' \item{Annual_Minimums}{ggplot2 object of annual minimums of selected n-day rolling means}
#' \item{Annual_Minimums_Days}{ggplot2 object of the day of years of annual minimums of selected n-day rolling means}
#'
#' @seealso \code{\link{calc_annual_lowflows}}
#'
#' @examples
#' # Run if HYDAT database has been downloaded (using tidyhydat::download_hydat())
#' if (file.exists(tidyhydat::hy_downloaded_db())) {
#'
#' # Plot annual 1, 3, 7, and 30-day (default) low flow statistics with default alignment
#' plot_annual_lowflows(station_number = "08NM116")
#'
#' # Plot annual custom 3 and 7-day low flow statistics with "center" alignment
#' plot_annual_lowflows(station_number = "08NM116",
#' roll_days = c(3,7),
#' roll_align = "center")
#'
#' }
#' @export
plot_annual_lowflows <- function(data,
dates = Date,
values = Value,
groups = STATION_NUMBER,
station_number,
roll_days = c(1, 3, 7, 30),
roll_align = "right",
water_year_start = 1,
start_year,
end_year,
exclude_years,
months = 1:12,
complete_years = FALSE,
ignore_missing = FALSE,
allowed_missing = ifelse(ignore_missing,100,0),
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
## ----------
lowflow_stats <- calc_annual_lowflows(data = flow_data,
roll_days = roll_days,
roll_align = roll_align,
water_year_start = water_year_start,
start_year = start_year,
end_year = end_year,
exclude_years = exclude_years,
months = months,
complete_years = complete_years,
ignore_missing = ignore_missing,
allowed_missing = allowed_missing)
# Remove all leading NA years
lowflow_stats <- dplyr::filter(dplyr::group_by(lowflow_stats, STATION_NUMBER),
Year >= Year[min(which(!is.na(.data[[names(lowflow_stats)[3]]])))])
# Gather data and plot the minimums day
lowflow_doy <- dplyr::select(lowflow_stats, STATION_NUMBER, Year, dplyr::contains("DoY"))
stat_levels <- names(lowflow_doy[-(1:2)])
stat_levels <- substr(stat_levels, 5, nchar(as.character(stat_levels)))
stat_levels <- paste0(gsub("_Day_DoY", "", stat_levels), " Day Minimum")
lowflow_doy <- tidyr::gather(lowflow_doy, Statistic, Value, -STATION_NUMBER, -Year)
lowflow_doy <- dplyr::mutate(lowflow_doy, Statistic = substr(Statistic, 5, nchar(as.character(Statistic))))
lowflow_doy <- dplyr::mutate(lowflow_doy, Statistic = paste0(gsub("_Day_DoY", "", Statistic), " Day Minimum"))
lowflow_doy <- dplyr::mutate(lowflow_doy, Statistic = factor(Statistic, levels = stat_levels))
# Gather data and plot the minimums values
lowflow_values <- dplyr::select(lowflow_stats, STATION_NUMBER, Year, dplyr::contains("Day"),
-dplyr::contains("DoY"), -dplyr::contains("Date"))
lowflow_values <- tidyr::gather(lowflow_values, Statistic, Value, -STATION_NUMBER, -Year)
lowflow_values <- dplyr::mutate(lowflow_values, Statistic = substr(Statistic, 5, nchar(Statistic)))
lowflow_values <- dplyr::mutate(lowflow_values, Statistic = paste0(gsub("_Day", "", Statistic), " Day Minimum"))
lowflow_values <- dplyr::mutate(lowflow_values, Statistic = factor(Statistic, levels = stat_levels))
## PLOT STATS
## ----------
# Create axis label based on input columns
y_axis_title <- ifelse(as.character(substitute(values)) == "Volume_m3", "Volume (cubic metres)", #expression(Volume~(m^3))
ifelse(as.character(substitute(values)) == "Yield_mm", "Yield (mm)",
"Discharge (cms)")) #expression(Discharge~(m^3/s))
# Create plots for each STATION_NUMBER in a tibble (see: http://www.brodrigues.co/blog/2017-03-29-make-ggplot2-purrr/)
doy_plots <- dplyr::group_by(lowflow_doy, STATION_NUMBER)
doy_plots <- tidyr::nest(doy_plots)
doy_plots <- dplyr::mutate(
doy_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) +
ggplot2::facet_wrap(~Statistic, ncol = 1, strip.position = "top")+
ggplot2::scale_x_continuous(breaks = scales::pretty_breaks(n = 8))+
{if(length(unique(lowflow_doy$Year)) < 8) ggplot2::scale_x_continuous(breaks = unique(lowflow_doy$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(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))
))
flow_plots <- dplyr::group_by(lowflow_values, STATION_NUMBER)
flow_plots <- tidyr::nest(flow_plots)
flow_plots <- dplyr::mutate(
flow_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) +
ggplot2::facet_wrap(~Statistic, ncol = 1, strip.position = "top")+
ggplot2::scale_x_continuous(breaks = scales::pretty_breaks(n = 8))+
{if(length(unique(lowflow_values$Year)) < 8) ggplot2::scale_x_continuous(breaks = unique(lowflow_values$Year))}+
ggplot2::scale_y_continuous(breaks = scales::pretty_breaks(n = 6),
labels = scales::label_number(scale_cut = append(scales::cut_short_scale(),1,1)),
expand = ggplot2::expansion(mult = c(0.1, 0.1))) +
ggplot2::ylab(y_axis_title)+
ggplot2::xlab("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(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_1 <- flow_plots$plot
plots_2 <- doy_plots$plot
if (nrow(flow_plots) == 1) {
names(plots_1) <- "Annual_Low_Flows"
names(plots_2) <- "Annual_Low_Flows_Dates"
} else {
names(plots_1) <- paste0(flow_plots$STATION_NUMBER, "_Annual_Low_Flows")
names(plots_2) <- paste0(doy_plots$STATION_NUMBER, "_Annual_Low_Flows_Dates")
}
# Add the plots to the plot list
plots <- c(plots_1, plots_2)
plots
}