Code/04_plot_seed_black_white.R
In davan690/beech-publication-wr: Small mammal dynamics in NZ beech forests
# By grid plot
# Base plot code
# feb2020
#plot theme
source("./R/davidson_2019_theme.r")
# source("./R/figures/study-design-data.R")
# libraries needed
# source("./R/r-packages-needed.R", echo = FALSE)
# source("./R/theme_raw_fig3s.r", echo = FALSE)
# source("./R/davidson_2019_theme.r", echo = FALSE)
require(citr)
require(deSolve)
require(lubridate)
require(jagsUI)
require(cowplot)
require(Matrix)
require(ggthemes)
require(ggplot2)
require(gridExtra)
require(coda)
require(tidyverse)
require(reshape2)
require(knitr)
require(knitcitations)
require(jtools)
require(flextable)
require(rmarkdown)
require(tinytex)
require(citr)
require(stringr)
require(tidyverse)
# jitter everything the same is harrrrrd
location.move <- position_dodge(width = 30)
#import ploting data
plot.dat.all1 <- read_csv("./data/plot-all-data1.csv")
glimpse(plot.dat.all1)
## reduce dataset to only cols of interest
names(plot.dat.all1)
seed_mean_vall_con_year3 <- plot.dat.all1 %>%
select(cum.seed, Control, Valley, year, Date, Conditions) %>%
mutate(year = as.factor(year)) %>%
group_by(Control, Valley, Date, Conditions) %>%
summarise(N = mean(ifelse(cum.seed > 0, ifelse(cum.seed > 0, log(cum.seed), 0), 0)),
Rats = factor("ALL"),
sd.s = sd(ifelse(cum.seed > 0, log(cum.seed), 0), na.rm = TRUE),
se.s = sd(ifelse(cum.seed > 0, log(cum.seed), 0)) / sqrt(length(cum.seed)) * 1.96,
lcl.s = mean(ifelse(cum.seed > 0, log(cum.seed), 0)) - (sd(ifelse(cum.seed > 0, log(cum.seed), 0)) / sqrt(length(cum.seed)) *
1.96),
lcl_seed = exp(lcl.s),
ucl.s = mean(ifelse(cum.seed > 0, log(cum.seed), 0)) + (sd(ifelse(cum.seed > 0, log(cum.seed), 0)) / sqrt(length(cum.seed)) *
1.96),
ucl_seed = exp(ucl.s), mean_seed = exp(N)) %>%
ungroup()
#data to plot
# seed_mean_vall_con_year3$lcl_seed
# seed_mean_vall_con_year3$ucl_seed
# seed_mean_vall_con_year3$mean_seed
# summaries_Control, valley, year
seed_mean_vall_con_CON_year <- plot.dat.all1 %>%
select(cum.seed, Control, Valley, Conditions, year, Date) %>%
mutate(year = as.factor(year),
Conditions = as.factor(Conditions)) %>%
group_by(Control, Valley, Date,Conditions) %>%
summarise(N = mean(ifelse(cum.seed > 0, ifelse(cum.seed > 0, log(cum.seed), 0), 0)),
# Rats = factor("ALL"),
sd.s = sd(ifelse(cum.seed > 0, log(cum.seed), 0), na.rm = TRUE),
se.s = sd(ifelse(cum.seed > 0, log(cum.seed), 0)) / sqrt(length(cum.seed)) * 1.96,
lcl.s = mean(ifelse(cum.seed > 0, log(cum.seed), 0)) - (sd(ifelse(cum.seed > 0, log(cum.seed), 0)) / sqrt(length(cum.seed)) *
1.96),
lcl_seed = exp(lcl.s),
ucl.s = mean(ifelse(cum.seed > 0, log(cum.seed), 0)) + (sd(ifelse(cum.seed > 0, log(cum.seed), 0)) / sqrt(length(cum.seed)) *
1.96),
ucl_seed = exp(ucl.s), mean_seed = exp(N)) %>%
ungroup()
#data to plot
# seed_mean_vall_con_CON_year$lcl_seed
# seed_mean_vall_con_CON_year$ucl_seed
# seed_mean_vall_con_CON_year$mean_seed
#spliting dataset based on these levels
# levels(seed_mean_vall_con_CON_year$Conditions)
## -----------------------dataset of replicates with rats present ------------------
seed_mean_vall_con_COND_year_RATS <- seed_mean_vall_con_CON_year %>%
filter(Conditions == "rats.present") %>%
mutate(
gp.treat = factor(paste(Valley, Control)),
Rats = factor("RATS", levels = c("ALL,", "RATS","NO_RATS")),
)
## -----------------------dataset of replicates with rats removed ------------------
seed_mean_vall_con_COND_year_NO_RATS <- seed_mean_vall_con_CON_year %>%
filter(Conditions == "rats.removed") %>%
mutate(
gp.treat = factor(paste(Valley, Control)),
Rats = factor("NO_RATS", levels = c("ALL,", "RATS","NO_RATS"))
)
seed_mean_vall_con_COND_year1 <- bind_rows(seed_mean_vall_con_COND_year_NO_RATS,seed_mean_vall_con_COND_year_RATS)
##-------------------plot code all conditions
# names(seed_mean_vall_con_year3)
p1 <- ggplot(data = seed_mean_vall_con_year3, aes(y = mean_seed, x = Date)) +
geom_point(aes(shape = Valley, col = Control), alpha = 0.7,
size = 6) +
geom_errorbar(aes(ymin = lcl.s, ymax = ucl.s, width = 0), lwd = 0.4, col = "black", position = location.move, alpha = 0.7) +
facet_wrap(~Conditions, ncol = 1)
p1
#
#
# p2 <-
#
# ggplot(data = seed_mean_vall_con_COND_year1, aes(y = mean_seed, x = Date)) +
# geom_point(aes(shape = Valley, col = Control), alpha = 0.7,
# size = 6) +
# geom_errorbar(aes(ymin = lcl_seed, ymax = ucl_seed, width = 0))
#
# +
# facet_wrap(~Rats)
#
# p2
#
# #doesnt work!!
# p3 <- p2 +
# # Remove fill legend and replace the fill legend using the newly created size
# guides(
# col = "none",
# size = guide_legend(override.aes = list(
# shape = c(15,0),alpha = 1
# )),
# shape = guide_legend(override.aes = list(
# shape = c(24, 21), size = 4
# )),
# fill = guide_legend(override.aes = list(
# col = c("white", "black"),shape = c("square"),
# size = 4
# ))
# )
# p3
# +
# geom_rect(aes(xmin=ymd('2000-01-01'),xmax = ymd('2000-12-31'),ymin = -Inf,ymax = Inf), colour = "grey90", fill = "grey90") +
# geom_rect(aes(xmin=ymd('2002-01-01'),xmax = ymd('2002-12-31'),ymin = -Inf,ymax = Inf), colour = "grey90", fill = "grey90") +
# geom_rect(aes(xmin=ymd('2004-01-01'),xmax = ymd('2004-12-31'),ymin = -Inf,ymax = Inf), colour = "grey90", fill = "grey90") +
# xlab(expression(paste("Time", "(", italic(t), ")"))) +
# ylab(expression(paste("Available seed "," ", "(", italic(Seed[jt]), ")"))) +
# scale_color_manual(name = "Stoat Control",
# values = c("black", "white", "white")) +
#
# scale_shape_manual(name = "Ecosystem",
# values = c(24, 21)) +
#
# scale_size_manual(name = "Rat Control", values = c(2.5, 3, 2.5)) +
# # manually define the fill colours
#
# scale_fill_manual(name = "Stoat Control",
# values = c("white", "black", "white")) +
# theme_tufte() +
# theme_bw() +
# theme(strip.background = element_blank(),
# strip.text.y = element_blank(),
#
# plot.title = element_text(hjust = 0, size=24, family = "Times", color="black", margin = margin(t = 10, b = 10)),
# plot.subtitle=element_text(size=16, face="italic", color="black"),
#
# legend.position = "none",
# legend.key = element_blank(),
# legend.background = element_rect(fill="white", size=1),
# legend.key.size=unit(1,"cm"),
# legend.text = element_text(colour = "black", size =16, family = "Times"),
# legend.title = element_text(colour = "black", size =16, family = "Times"),
#
# panel.grid.major = element_blank(),
# panel.grid.minor = element_blank(),
# panel.spacing = unit(2, "lines"),
# panel.border = element_blank(),
#
# axis.title.y = element_text(colour = "black",size =20, family = "Times", angle = 90),
# axis.title.x = element_text(colour = "black", size =20, family = "Times"),
# axis.text.y=element_text(colour = "black",size = 20, family = "Times"),
# axis.text.x = element_text(colour = "black", size =20, family = "Times"),
#
# axis.ticks.x = element_line(size = 1),
# axis.ticks.y = element_line(size = 1),
# axis.line.x = element_line(size = 1),
# axis.line.y = element_line(size = 1),
#
# strip.text = element_text(face="bold",colour = "black",size =14, family = "Times"))
# p.design <- plot.dat.all1 %>%
# mutate(grid = as.numeric(factor(grid)))
#
# # glimpse(plot.dat.all1)
# # adding NA grid to plot
# bd.row <- p.design[1, ]
# bd.row$grid <- "blank"
# bd.row$grid <- "blank"
# bd.row$grid <- "blank"
# bd.row$grid <- "blank"
# bd.row$Date <- NA
#
# # bind row to plot data
# p.design145 <- rbind(p.design, bd.row)
# # glimpse(p.design145$grid)
#
# # labels
# rat.labs <- c("No", "Reduced")
#
# #re-factoring
# p.design1 <- p.design145 %>%
# mutate(grid = factor(grid, levels = c(
# "1", "2", "3", "4", "blank", "5", "6", "7", "8"
# )),
# Rats = factor(Rats, labels = rat.labs))
#
# ## ----conf-intervals-above-zero-------------------------------------------
# #making datasest
# p.design2 <- p.design1 %>%
# group_by(Control, Valley, Date) %>%
# summarise(N = mean(ifelse(cum.seed > 0, ifelse(cum.seed > 0, log(cum.seed), 0), 0)),
# Rats = factor("Full", levels = c("Full", "Reduced")),
# sd.s = sd(ifelse(cum.seed > 0, log(cum.seed), 0), na.rm = TRUE),
# se.s = sd(ifelse(cum.seed > 0, log(cum.seed), 0)) / sqrt(length(cum.seed)) * 1.96,
# lcl.s = mean(ifelse(cum.seed > 0, log(cum.seed), 0)) - (sd(ifelse(cum.seed > 0, log(cum.seed), 0)) / sqrt(length(cum.seed)) *
# 1.96),
# lcl.slog = exp(lcl.s),
# ucl.s = mean(ifelse(cum.seed > 0, log(cum.seed), 0)) + (sd(ifelse(cum.seed > 0, log(cum.seed), 0)) / sqrt(length(cum.seed)) *
# 1.96),
# ucl.slog = exp(ucl.s)) %>%
# ungroup() %>%
# mutate(cum.seed = exp(N),
# grid = factor(paste(Control, Valley)))
#
# ## ------------------------------------------------------------------------
# # fig.3.plot.seed.sum.final
#
# # plot
# plot.final.f3.1 <- ggplot(p.design2,
# aes(
# y = cum.seed,
# col = Rats,
# shape = Valley,
# fill = Control,
# x = Date
# )) +
# geom_rect(aes(xmin=ymd('2000-01-01'),xmax = ymd('2000-12-31'),ymin = -Inf,ymax = Inf), colour = "grey90", fill = "grey90") +
# geom_rect(aes(xmin=ymd('2002-01-01'),xmax = ymd('2002-12-31'),ymin = -Inf,ymax = Inf), colour = "grey90", fill = "grey90") +
# geom_rect(aes(xmin=ymd('2004-01-01'),xmax = ymd('2004-12-31'),ymin = -Inf,ymax = Inf), colour = "grey90", fill = "grey90") +
#
# geom_errorbar(aes(ymin = lcl.slog, ymax = ucl.slog, width = 0), lwd = 0.4,
# col = "black", position = location.move, alpha = 0.7) +
#
# geom_line(col = "grey50") +
# geom_point(aes(y = cum.seed,
# x = Date
# ),alpha = 0.7, size = 6, position = location.move, size = 0.95) +
# xlab(expression(paste("Time", "(", italic(t), ")"))) +
# ylab(expression(paste("Available seed "," ", "(", italic(Seed[jt]), ")"))) +
# scale_color_manual(name = "Stoat Control",
# values = c("black", "white", "white")) +
#
# scale_shape_manual(name = "Ecosystem",
# values = c(24, 21)) +
#
# scale_size_manual(name = "Rat Control", values = c(2.5, 3, 2.5)) +
# # manually define the fill colours
#
# scale_fill_manual(name = "Stoat Control",
# values = c("white", "black", "white")) +
#
#
#
#
# # Remove fill legend and replace the fill legend using the newly created size
# guides(
# col = "none",
# size = guide_legend(override.aes = list(
# shape = c(15,0),alpha = 1
# )),
# shape = guide_legend(override.aes = list(
# shape = c(24, 21), size = 4
# )),
# fill = guide_legend(override.aes = list(
# col = c("white", "black"),shape = c("square"),
# size = 4
# ))
# ) +
#
# theme_tufte() +
# theme_bw() +
# theme(strip.background = element_blank(),
# strip.text.y = element_blank(),
#
# plot.title = element_text(hjust = 0, size=24, family = "Times", color="black", margin = margin(t = 10, b = 10)),
# plot.subtitle=element_text(size=16, face="italic", color="black"),
#
# legend.position = "none",
# legend.key = element_blank(),
# legend.background = element_rect(fill="white", size=1),
# legend.key.size=unit(1,"cm"),
# legend.text = element_text(colour = "black", size =16, family = "Times"),
# legend.title = element_text(colour = "black", size =16, family = "Times"),
#
# panel.grid.major = element_blank(),
# panel.grid.minor = element_blank(),
# panel.spacing = unit(2, "lines"),
# panel.border = element_blank(),
#
# axis.title.y = element_text(colour = "black",size =20, family = "Times", angle = 90),
# axis.title.x = element_text(colour = "black", size =20, family = "Times"),
# axis.text.y=element_text(colour = "black",size = 20, family = "Times"),
# axis.text.x = element_text(colour = "black", size =20, family = "Times"),
#
# axis.ticks.x = element_line(size = 1),
# axis.ticks.y = element_line(size = 1),
# axis.line.x = element_line(size = 1),
# axis.line.y = element_line(size = 1),
#
# strip.text = element_text(face="bold",colour = "black",size =14, family = "Times"))
#
# plot.final.f3.1
# # export plot for example vignette
# jpeg("./figs/fig-3.1-study.jpeg")
# fig.2.plot.design
# dev.off()
davan690/beech-publication-wr documentation built on March 29, 2020, 11:09 a.m.
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# By grid plot
# Base plot code
# feb2020
#plot theme
source("./R/davidson_2019_theme.r")
# source("./R/figures/study-design-data.R")
# libraries needed
# source("./R/r-packages-needed.R", echo = FALSE)
# source("./R/theme_raw_fig3s.r", echo = FALSE)
# source("./R/davidson_2019_theme.r", echo = FALSE)
require(citr)
require(deSolve)
require(lubridate)
require(jagsUI)
require(cowplot)
require(Matrix)
require(ggthemes)
require(ggplot2)
require(gridExtra)
require(coda)
require(tidyverse)
require(reshape2)
require(knitr)
require(knitcitations)
require(jtools)
require(flextable)
require(rmarkdown)
require(tinytex)
require(citr)
require(stringr)
require(tidyverse)
# jitter everything the same is harrrrrd
location.move <- position_dodge(width = 30)
#import ploting data
plot.dat.all1 <- read_csv("./data/plot-all-data1.csv")
glimpse(plot.dat.all1)
## reduce dataset to only cols of interest
names(plot.dat.all1)
seed_mean_vall_con_year3 <- plot.dat.all1 %>%
select(cum.seed, Control, Valley, year, Date, Conditions) %>%
mutate(year = as.factor(year)) %>%
group_by(Control, Valley, Date, Conditions) %>%
summarise(N = mean(ifelse(cum.seed > 0, ifelse(cum.seed > 0, log(cum.seed), 0), 0)),
Rats = factor("ALL"),
sd.s = sd(ifelse(cum.seed > 0, log(cum.seed), 0), na.rm = TRUE),
se.s = sd(ifelse(cum.seed > 0, log(cum.seed), 0)) / sqrt(length(cum.seed)) * 1.96,
lcl.s = mean(ifelse(cum.seed > 0, log(cum.seed), 0)) - (sd(ifelse(cum.seed > 0, log(cum.seed), 0)) / sqrt(length(cum.seed)) *
1.96),
lcl_seed = exp(lcl.s),
ucl.s = mean(ifelse(cum.seed > 0, log(cum.seed), 0)) + (sd(ifelse(cum.seed > 0, log(cum.seed), 0)) / sqrt(length(cum.seed)) *
1.96),
ucl_seed = exp(ucl.s), mean_seed = exp(N)) %>%
ungroup()
#data to plot
# seed_mean_vall_con_year3$lcl_seed
# seed_mean_vall_con_year3$ucl_seed
# seed_mean_vall_con_year3$mean_seed
# summaries_Control, valley, year
seed_mean_vall_con_CON_year <- plot.dat.all1 %>%
select(cum.seed, Control, Valley, Conditions, year, Date) %>%
mutate(year = as.factor(year),
Conditions = as.factor(Conditions)) %>%
group_by(Control, Valley, Date,Conditions) %>%
summarise(N = mean(ifelse(cum.seed > 0, ifelse(cum.seed > 0, log(cum.seed), 0), 0)),
# Rats = factor("ALL"),
sd.s = sd(ifelse(cum.seed > 0, log(cum.seed), 0), na.rm = TRUE),
se.s = sd(ifelse(cum.seed > 0, log(cum.seed), 0)) / sqrt(length(cum.seed)) * 1.96,
lcl.s = mean(ifelse(cum.seed > 0, log(cum.seed), 0)) - (sd(ifelse(cum.seed > 0, log(cum.seed), 0)) / sqrt(length(cum.seed)) *
1.96),
lcl_seed = exp(lcl.s),
ucl.s = mean(ifelse(cum.seed > 0, log(cum.seed), 0)) + (sd(ifelse(cum.seed > 0, log(cum.seed), 0)) / sqrt(length(cum.seed)) *
1.96),
ucl_seed = exp(ucl.s), mean_seed = exp(N)) %>%
ungroup()
#data to plot
# seed_mean_vall_con_CON_year$lcl_seed
# seed_mean_vall_con_CON_year$ucl_seed
# seed_mean_vall_con_CON_year$mean_seed
#spliting dataset based on these levels
# levels(seed_mean_vall_con_CON_year$Conditions)
## -----------------------dataset of replicates with rats present ------------------
seed_mean_vall_con_COND_year_RATS <- seed_mean_vall_con_CON_year %>%
filter(Conditions == "rats.present") %>%
mutate(
gp.treat = factor(paste(Valley, Control)),
Rats = factor("RATS", levels = c("ALL,", "RATS","NO_RATS")),
)
## -----------------------dataset of replicates with rats removed ------------------
seed_mean_vall_con_COND_year_NO_RATS <- seed_mean_vall_con_CON_year %>%
filter(Conditions == "rats.removed") %>%
mutate(
gp.treat = factor(paste(Valley, Control)),
Rats = factor("NO_RATS", levels = c("ALL,", "RATS","NO_RATS"))
)
seed_mean_vall_con_COND_year1 <- bind_rows(seed_mean_vall_con_COND_year_NO_RATS,seed_mean_vall_con_COND_year_RATS)
##-------------------plot code all conditions
# names(seed_mean_vall_con_year3)
p1 <- ggplot(data = seed_mean_vall_con_year3, aes(y = mean_seed, x = Date)) +
geom_point(aes(shape = Valley, col = Control), alpha = 0.7,
size = 6) +
geom_errorbar(aes(ymin = lcl.s, ymax = ucl.s, width = 0), lwd = 0.4, col = "black", position = location.move, alpha = 0.7) +
facet_wrap(~Conditions, ncol = 1)
p1
#
#
# p2 <-
#
# ggplot(data = seed_mean_vall_con_COND_year1, aes(y = mean_seed, x = Date)) +
# geom_point(aes(shape = Valley, col = Control), alpha = 0.7,
# size = 6) +
# geom_errorbar(aes(ymin = lcl_seed, ymax = ucl_seed, width = 0))
#
# +
# facet_wrap(~Rats)
#
# p2
#
# #doesnt work!!
# p3 <- p2 +
# # Remove fill legend and replace the fill legend using the newly created size
# guides(
# col = "none",
# size = guide_legend(override.aes = list(
# shape = c(15,0),alpha = 1
# )),
# shape = guide_legend(override.aes = list(
# shape = c(24, 21), size = 4
# )),
# fill = guide_legend(override.aes = list(
# col = c("white", "black"),shape = c("square"),
# size = 4
# ))
# )
# p3
# +
# geom_rect(aes(xmin=ymd('2000-01-01'),xmax = ymd('2000-12-31'),ymin = -Inf,ymax = Inf), colour = "grey90", fill = "grey90") +
# geom_rect(aes(xmin=ymd('2002-01-01'),xmax = ymd('2002-12-31'),ymin = -Inf,ymax = Inf), colour = "grey90", fill = "grey90") +
# geom_rect(aes(xmin=ymd('2004-01-01'),xmax = ymd('2004-12-31'),ymin = -Inf,ymax = Inf), colour = "grey90", fill = "grey90") +
# xlab(expression(paste("Time", "(", italic(t), ")"))) +
# ylab(expression(paste("Available seed "," ", "(", italic(Seed[jt]), ")"))) +
# scale_color_manual(name = "Stoat Control",
# values = c("black", "white", "white")) +
#
# scale_shape_manual(name = "Ecosystem",
# values = c(24, 21)) +
#
# scale_size_manual(name = "Rat Control", values = c(2.5, 3, 2.5)) +
# # manually define the fill colours
#
# scale_fill_manual(name = "Stoat Control",
# values = c("white", "black", "white")) +
# theme_tufte() +
# theme_bw() +
# theme(strip.background = element_blank(),
# strip.text.y = element_blank(),
#
# plot.title = element_text(hjust = 0, size=24, family = "Times", color="black", margin = margin(t = 10, b = 10)),
# plot.subtitle=element_text(size=16, face="italic", color="black"),
#
# legend.position = "none",
# legend.key = element_blank(),
# legend.background = element_rect(fill="white", size=1),
# legend.key.size=unit(1,"cm"),
# legend.text = element_text(colour = "black", size =16, family = "Times"),
# legend.title = element_text(colour = "black", size =16, family = "Times"),
#
# panel.grid.major = element_blank(),
# panel.grid.minor = element_blank(),
# panel.spacing = unit(2, "lines"),
# panel.border = element_blank(),
#
# axis.title.y = element_text(colour = "black",size =20, family = "Times", angle = 90),
# axis.title.x = element_text(colour = "black", size =20, family = "Times"),
# axis.text.y=element_text(colour = "black",size = 20, family = "Times"),
# axis.text.x = element_text(colour = "black", size =20, family = "Times"),
#
# axis.ticks.x = element_line(size = 1),
# axis.ticks.y = element_line(size = 1),
# axis.line.x = element_line(size = 1),
# axis.line.y = element_line(size = 1),
#
# strip.text = element_text(face="bold",colour = "black",size =14, family = "Times"))
# p.design <- plot.dat.all1 %>%
# mutate(grid = as.numeric(factor(grid)))
#
# # glimpse(plot.dat.all1)
# # adding NA grid to plot
# bd.row <- p.design[1, ]
# bd.row$grid <- "blank"
# bd.row$grid <- "blank"
# bd.row$grid <- "blank"
# bd.row$grid <- "blank"
# bd.row$Date <- NA
#
# # bind row to plot data
# p.design145 <- rbind(p.design, bd.row)
# # glimpse(p.design145$grid)
#
# # labels
# rat.labs <- c("No", "Reduced")
#
# #re-factoring
# p.design1 <- p.design145 %>%
# mutate(grid = factor(grid, levels = c(
# "1", "2", "3", "4", "blank", "5", "6", "7", "8"
# )),
# Rats = factor(Rats, labels = rat.labs))
#
# ## ----conf-intervals-above-zero-------------------------------------------
# #making datasest
# p.design2 <- p.design1 %>%
# group_by(Control, Valley, Date) %>%
# summarise(N = mean(ifelse(cum.seed > 0, ifelse(cum.seed > 0, log(cum.seed), 0), 0)),
# Rats = factor("Full", levels = c("Full", "Reduced")),
# sd.s = sd(ifelse(cum.seed > 0, log(cum.seed), 0), na.rm = TRUE),
# se.s = sd(ifelse(cum.seed > 0, log(cum.seed), 0)) / sqrt(length(cum.seed)) * 1.96,
# lcl.s = mean(ifelse(cum.seed > 0, log(cum.seed), 0)) - (sd(ifelse(cum.seed > 0, log(cum.seed), 0)) / sqrt(length(cum.seed)) *
# 1.96),
# lcl.slog = exp(lcl.s),
# ucl.s = mean(ifelse(cum.seed > 0, log(cum.seed), 0)) + (sd(ifelse(cum.seed > 0, log(cum.seed), 0)) / sqrt(length(cum.seed)) *
# 1.96),
# ucl.slog = exp(ucl.s)) %>%
# ungroup() %>%
# mutate(cum.seed = exp(N),
# grid = factor(paste(Control, Valley)))
#
# ## ------------------------------------------------------------------------
# # fig.3.plot.seed.sum.final
#
# # plot
# plot.final.f3.1 <- ggplot(p.design2,
# aes(
# y = cum.seed,
# col = Rats,
# shape = Valley,
# fill = Control,
# x = Date
# )) +
# geom_rect(aes(xmin=ymd('2000-01-01'),xmax = ymd('2000-12-31'),ymin = -Inf,ymax = Inf), colour = "grey90", fill = "grey90") +
# geom_rect(aes(xmin=ymd('2002-01-01'),xmax = ymd('2002-12-31'),ymin = -Inf,ymax = Inf), colour = "grey90", fill = "grey90") +
# geom_rect(aes(xmin=ymd('2004-01-01'),xmax = ymd('2004-12-31'),ymin = -Inf,ymax = Inf), colour = "grey90", fill = "grey90") +
#
# geom_errorbar(aes(ymin = lcl.slog, ymax = ucl.slog, width = 0), lwd = 0.4,
# col = "black", position = location.move, alpha = 0.7) +
#
# geom_line(col = "grey50") +
# geom_point(aes(y = cum.seed,
# x = Date
# ),alpha = 0.7, size = 6, position = location.move, size = 0.95) +
# xlab(expression(paste("Time", "(", italic(t), ")"))) +
# ylab(expression(paste("Available seed "," ", "(", italic(Seed[jt]), ")"))) +
# scale_color_manual(name = "Stoat Control",
# values = c("black", "white", "white")) +
#
# scale_shape_manual(name = "Ecosystem",
# values = c(24, 21)) +
#
# scale_size_manual(name = "Rat Control", values = c(2.5, 3, 2.5)) +
# # manually define the fill colours
#
# scale_fill_manual(name = "Stoat Control",
# values = c("white", "black", "white")) +
#
#
#
#
# # Remove fill legend and replace the fill legend using the newly created size
# guides(
# col = "none",
# size = guide_legend(override.aes = list(
# shape = c(15,0),alpha = 1
# )),
# shape = guide_legend(override.aes = list(
# shape = c(24, 21), size = 4
# )),
# fill = guide_legend(override.aes = list(
# col = c("white", "black"),shape = c("square"),
# size = 4
# ))
# ) +
#
# theme_tufte() +
# theme_bw() +
# theme(strip.background = element_blank(),
# strip.text.y = element_blank(),
#
# plot.title = element_text(hjust = 0, size=24, family = "Times", color="black", margin = margin(t = 10, b = 10)),
# plot.subtitle=element_text(size=16, face="italic", color="black"),
#
# legend.position = "none",
# legend.key = element_blank(),
# legend.background = element_rect(fill="white", size=1),
# legend.key.size=unit(1,"cm"),
# legend.text = element_text(colour = "black", size =16, family = "Times"),
# legend.title = element_text(colour = "black", size =16, family = "Times"),
#
# panel.grid.major = element_blank(),
# panel.grid.minor = element_blank(),
# panel.spacing = unit(2, "lines"),
# panel.border = element_blank(),
#
# axis.title.y = element_text(colour = "black",size =20, family = "Times", angle = 90),
# axis.title.x = element_text(colour = "black", size =20, family = "Times"),
# axis.text.y=element_text(colour = "black",size = 20, family = "Times"),
# axis.text.x = element_text(colour = "black", size =20, family = "Times"),
#
# axis.ticks.x = element_line(size = 1),
# axis.ticks.y = element_line(size = 1),
# axis.line.x = element_line(size = 1),
# axis.line.y = element_line(size = 1),
#
# strip.text = element_text(face="bold",colour = "black",size =14, family = "Times"))
#
# plot.final.f3.1
# # export plot for example vignette
# jpeg("./figs/fig-3.1-study.jpeg")
# fig.2.plot.design
# dev.off()
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