From 595abd47e2ad0b18bd4d6a2c99171df1f5cd5f3b Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Christoph=20Sch=C3=BCrz?= <christoph.schuerz@ufz.de>
Date: Mon, 5 Dec 2022 15:43:24 +0100
Subject: [PATCH] Add plot_climate_annual function
---
DESCRIPTION | 2 +-
NAMESPACE | 16 ++++
R/plot_climate.R | 189 +++++++++++++++++++++++++++++++++++++
man/plot_climate_annual.Rd | 24 +++++
man/plot_stat_text.Rd | 23 +++++
5 files changed, 253 insertions(+), 1 deletion(-)
create mode 100644 R/plot_climate.R
create mode 100644 man/plot_climate_annual.Rd
create mode 100644 man/plot_stat_text.Rd
diff --git a/DESCRIPTION b/DESCRIPTION
index e574a0a..73fcbb3 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,7 +1,7 @@
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")),
diff --git a/NAMESPACE b/NAMESPACE
index 63274f7..8d9e2aa 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -1,8 +1,23 @@
# 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)
diff --git a/R/plot_climate.R b/R/plot_climate.R
new file mode 100644
index 0000000..dcd4dde
--- /dev/null
+++ b/R/plot_climate.R
@@ -0,0 +1,189 @@
+#' 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)
+}
diff --git a/man/plot_climate_annual.Rd b/man/plot_climate_annual.Rd
new file mode 100644
index 0000000..7dfbf7d
--- /dev/null
+++ b/man/plot_climate_annual.Rd
@@ -0,0 +1,24 @@
+% 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.
+}
diff --git a/man/plot_stat_text.Rd b/man/plot_stat_text.Rd
new file mode 100644
index 0000000..95c7d8a
--- /dev/null
+++ b/man/plot_stat_text.Rd
@@ -0,0 +1,23 @@
+% 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}
--
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