Add plot_climate_annual function

DESCRIPTION

 Package: SWATdoctR
 Type: Package
 Title: Finding the right diagnoses and treatments for SWAT+ models
-Version: 0.1.0.9001
+Version: 0.1.0.9002
 Author: c(person("Svajunas", "Plunge",
              email = "svajunas_plunge@sggw.edu.pl",
              role = c("aut")),

NAMESPACE

 # Generated by roxygen2: do not edit by hand
 
+export(plot_climate_annual)
 export(run_swat_verification)
+import(ggplot2)
+import(patchwork)
 importFrom(data.table,fread)
 importFrom(dplyr,"%>%")
+importFrom(dplyr,filter)
+importFrom(dplyr,group_by)
+importFrom(dplyr,left_join)
+importFrom(dplyr,mutate)
+importFrom(dplyr,rename)
+importFrom(dplyr,select)
+importFrom(dplyr,summarise)
+importFrom(ggplot2,aes)
+importFrom(ggplot2,geom_text)
+importFrom(ggplot2,ggplot)
+importFrom(ggplot2,lims)
+importFrom(ggplot2,theme_void)
 importFrom(lubridate,int_end)
 importFrom(lubridate,int_start)
 importFrom(lubridate,interval)
@@ -20,4 +35,5 @@ importFrom(stringr,str_sub)
 importFrom(stringr,str_trim)
 importFrom(tibble,as_tibble)
 importFrom(tibble,tibble)
+importFrom(tidyr,pivot_longer)
 importFrom(vroom,vroom_lines)

R/plot_climate.R

+#' Plot annual overview of simulated climate variables of a SWAT+ simulation
+#'
+#' plot_climate_annual uses the simulated basin averages of pet, the different
+#' et fractions, precip, snofall, temperatures, and solar radiation to plot
+#' annual sums and averages.
+#' The aim of the function is to provide an overview of the simulated variables
+#' and help to identify potential issues with the model weather input data.
+#'
+#' @param sim_verify Simulation output of the function \code{run_swat_verification()}.
+#'   To plot the climate outputs at least the output option \code{outputs = 'wb'} must
+#'   be set in  \code{run_swat_verification()}.
+#'
+#' @return Returns a patchwork of ggplots for the annual values of the simulated
+#'   climate variables.
+#'
+#' @importFrom dplyr filter group_by left_join mutate rename select summarise %>%
+#' @importFrom lubridate ymd
+#' @importFrom tidyr pivot_longer
+#' @import ggplot2
+#' @import patchwork
+#' @export
+#'
+plot_climate_annual <- function(sim_verify) {
+  basin_wb <- sim_verify$basin_wb_day %>%
+    mutate(date = ymd(paste(yr, mon, day, sep = '-')),
+           rainfall = precip - snofall) %>%
+    select(date, yr, mon, day, jday, precip, rainfall, snofall, et, ecanopy, eplant, esoil, pet)
+  basin_pw <- sim_verify$basin_pw_day %>%
+    mutate(date = ymd(paste(yr, mon, day, sep = '-'))) %>%
+    select(date, yr, mon, day, jday, tmx, tmn, tmpav, solarad, wndspd, rhum)
+
+  clim_data <- left_join(basin_wb, basin_pw, by = c("jday", "mon", "day", "yr", "date")) %>%
+    pivot_longer(., cols = -c(date, yr, mon, day, jday))
+
+  clim_data_annual <- clim_data %>%
+    group_by(name, yr) %>%
+    summarise(value_sum = sum(value), value_mean = mean(value), .groups = 'drop')
+
+  y_lim <- clim_data_annual %>%
+    filter(name %in% c('pet', 'precip')) %>%
+    .$value_sum %>%
+    max(.)
+
+  et_tbl <- clim_data_annual %>%
+    filter(name %in% c('ecanopy', 'eplant', 'esoil')) %>%
+    select(name, yr, value_sum)
+
+  pet_tbl <- clim_data_annual %>%
+    filter(name == 'pet') %>%
+    select(name, yr, value_sum)
+
+  gg_et <- ggplot() +
+    geom_col(data = et_tbl, aes(x = yr, y = value_sum, fill = name)) +
+    geom_errorbarh(data = pet_tbl, aes(xmax = yr + 0.5, xmin = yr - 0.5, y = value_sum, height = 0, col = name), lwd = 1) +
+    scale_color_manual(values = 'black') +
+    scale_fill_manual(values = c('skyblue3', 'springgreen3', 'wheat3')) +
+    ylim(c(0, 1.1*y_lim)) +
+    # geom_step(data = pet_tbl, aes(x = yr, y = value_sum), direction = 'mid') +
+    labs(y = 'PET, ETa (mm)') +
+    theme_bw() +
+    theme(axis.text.x = element_blank(),
+          axis.title.x = element_blank(),
+          legend.title = element_blank(),
+          legend.box = "horizontal",
+          legend.direction = 'horizontal',
+          legend.justification=c(1,1),
+          legend.position=c(0.995,0.99),
+          legend.key = element_blank(),
+          legend.background = element_blank(),
+          legend.box.background = element_rect(colour = "black", fill =alpha('white', 0.6)))
+
+  pcp_tbl <- clim_data_annual %>%
+    filter(name %in% c('rainfall', 'snofall')) %>%
+    select(name, yr, value_sum)
+
+  gg_pcp <- ggplot() +
+    geom_col(data = pcp_tbl, aes(x = yr, y = value_sum, fill = name)) +
+    scale_fill_manual(values = c('dodgerblue4','slategray2')) +
+    # geom_step(data = pet_tbl, aes(x = yr, y = value_sum), direction = 'mid') +
+    labs(y = 'Precipitation (mm)') +
+    ylim(c(0, 1.1*y_lim)) +
+    theme_bw() +
+    theme(axis.text.x = element_blank(),
+          axis.title.x = element_blank(),
+          legend.title = element_blank(),
+          legend.box = "horizontal",
+          legend.direction = 'horizontal',
+          legend.justification=c(1,1),
+          legend.position=c(0.995,0.99),
+          legend.key = element_blank(),
+          legend.background = element_blank(),
+          legend.box.background = element_rect(colour = "black", fill =alpha('white', 0.6)))
+
+  tmp_tbl <- basin_pw %>%
+    select(yr, tmn, tmx, tmpav) %>%
+    group_by(yr) %>%
+    summarise(tmn_d = min(tmn),
+              tmx_d = max(tmx),
+              tmn_a = mean(tmn),
+              tmx_a = mean(tmx),
+              tmpav = mean(tmpav)) %>%
+    pivot_longer(cols = -yr)
+
+  gg_tmp <- ggplot() +
+    geom_errorbarh(data = tmp_tbl, aes(xmax = yr + 0.5, xmin = yr - 0.5, y = value, height = 0, col = name), lwd = 1) +
+    scale_color_manual(values = c('dodgerblue2', 'dodgerblue4', 'black', 'tomato1', 'tomato3')) +
+    # geom_step(data = pet_tbl, aes(x = yr, y = value_sum), direction = 'mid') +
+    labs(y = 'Temperature (°C)') +
+    theme_bw() +
+    theme(axis.text.x = element_blank(),
+          axis.title.x = element_blank(),
+          legend.title = element_blank(),
+          legend.box = "horizontal",
+          legend.direction = 'horizontal',
+          legend.justification=c(1,1),
+          legend.position=c(0.995,0.99),
+          legend.key = element_blank(),
+          legend.background = element_blank(),
+          legend.box.background = element_rect(colour = "black", fill =alpha('white', 0.6)))
+
+  slr_tbl <- clim_data_annual %>%
+    filter(name %in% c('solarad')) %>%
+    select(name, yr, value_sum)
+
+  gg_slr <- ggplot() +
+    geom_col(data = slr_tbl, aes(x = yr, y = value_sum, fill = name)) +
+    scale_fill_manual(values = 'tan3') +
+    # labs(y = expression("Another really really really really long y label here "~cm^3)) +
+    labs(y = expression(Solar~Radiation~(MJ~m^{-2})),
+         x = 'Year') +
+    theme_bw() +
+    theme(legend.title = element_blank(),
+          legend.box = "horizontal",
+          legend.direction = 'horizontal',
+          legend.justification=c(1,1),
+          legend.position=c(0.995,0.99),
+          legend.key = element_blank(),
+          legend.background = element_blank(),
+          legend.box.background = element_rect(colour = "black", fill =alpha('white', 0.6)))
+
+  gg_et_stat  <- plot_stat_text(clim_data_annual,
+                                vars = c('pet', 'et', 'ecanopy', 'eplant', 'esoil'),
+                                c(2,1,0,3,4), 'mm', T)
+  gg_pcp_stat <- plot_stat_text(clim_data_annual,
+                                vars = c('precip', 'rainfall', 'snofall'),
+                                c(5,4,3), 'mm', F)
+  gg_tmp_stat <- plot_stat_text(rename(clim_data, value_sum = value),
+                                vars = c('tmn', 'tmx', 'tmpav'),
+                                c(5,4,3), '°C', F)
+  gg_slr_stat <- plot_stat_text(clim_data_annual, vars = c('solarad'),
+                                c(5), 'MJ m^-2', F)
+
+  gg_et + gg_et_stat + gg_pcp + gg_pcp_stat + gg_tmp + gg_tmp_stat +
+    gg_slr + gg_slr_stat + plot_layout(ncol = 2, widths = c(0.85, 0.15))
+}
+
+#' Plot annual average values in tabular text form as a ggplot
+#' @param tbl Processed climate variable table
+#' @param vars Character vector which defines the variables to be printed
+#' @param pos Print positions of the variables and their values
+#' @param unit_add Character string which defines unit to be added to values
+#' @param add_title Boolean to define if title should be added to table
+#'
+#' @importFrom dplyr filter group_by mutate select summarise %>%
+#' @importFrom ggplot2 aes ggplot lims geom_text theme_void
+#'
+#' @keywords internal
+#'
+plot_stat_text <- function(tbl, vars, pos, unit_add, add_title) {
+  tbl_mean <- tbl %>%
+    filter(name %in% vars) %>%
+    select(name, yr, value_sum) %>%
+    group_by(name) %>%
+    summarise(value_sum = round(mean(value_sum))) %>%
+    mutate(value_sum = paste(value_sum, unit_add),
+           y = pos)
+
+  gg <- ggplot() +
+    theme_void() +
+    lims(x = c(0, 5), y = c(0,5)) +
+    geom_text(aes(x = 0, y = tbl_mean$y, label = paste0(tbl_mean$name, ':')), hjust = 0) +
+    geom_text(aes(x = 5, y = tbl_mean$y, label = tbl_mean$value_sum), hjust = 1)
+
+  if(add_title) {
+    gg <- gg + geom_text(aes(x = 0, y = 5, label = 'Average annual values:'), hjust = 0, size = 6)
+  }
+
+  return(gg)
+}

man/plot_climate_annual.Rd

+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/plot_climate.R
+\name{plot_climate_annual}
+\alias{plot_climate_annual}
+\title{Plot annual overview of simulated climate variables of a SWAT+ simulation}
+\usage{
+plot_climate_annual(sim_verify)
+}
+\arguments{
+\item{sim_verify}{Simulation output of the function \code{run_swat_verification()}.
+To plot the climate outputs at least the output option \code{outputs = 'wb'} must
+be set in  \code{run_swat_verification()}.}
+}
+\value{
+Returns a patchwork of ggplots for the annual values of the simulated
+  climate variables.
+}
+\description{
+plot_climate_annual uses the simulated basin averages of pet, the different
+et fractions, precip, snofall, temperatures, and solar radiation to plot
+annual sums and averages.
+The aim of the function is to provide an overview of the simulated variables
+and help to identify potential issues with the model weather input data.
+}

man/plot_stat_text.Rd

+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/plot_climate.R
+\name{plot_stat_text}
+\alias{plot_stat_text}
+\title{Plot annual average values in tabular text form as a ggplot}
+\usage{
+plot_stat_text(tbl, vars, pos, unit_add, add_title)
+}
+\arguments{
+\item{tbl}{Processed climate variable table}
+
+\item{vars}{Character vector which defines the variables to be printed}
+
+\item{pos}{Print positions of the variables and their values}
+
+\item{unit_add}{Character string which defines unit to be added to values}
+
+\item{add_title}{Boolean to define if title should be added to table}
+}
+\description{
+Plot annual average values in tabular text form as a ggplot
+}
+\keyword{internal}