R/figures/pd-plot-code.R
In davan690/beech-publication-wr: Small mammal dynamics in NZ beech forests
# data for lines ----------------------------------------------------------
# Feb - seed
#feb filtered (parameters)
# flip dataset
# source("./R/Davidson_2019_Model_wrangling.R")
out.para.feb <- para.plot.dat %>%
filter(month == "Feb") %>%
select(mean.b, Control, Valley, para) %>%
droplevels() %>%
spread(key = para, value = mean.b)
#this gives us 12 times lines to estimate from
# for each group I need to ....
#feb filtered (data)
out.dat1.feb <- out.full.136 %>%
filter(month == "Feb") %>%
mutate(lag.sjt = lag(log.seed),
lag.N = lag(N)) %>%
select(-var) %>%
droplevels()
out.dat1.feb2 <- out.full.136 %>%
filter(month == "Feb") %>%
mutate(lag.sjt = lag(log.seed),
lag.N = lag(N)) %>%
group_by(Control, Valley) %>%
summarise(
M.seed = mean(lag.sjt, na.rm = TRUE),
M.dens = mean(lag.N, na.rm = TRUE),
M.rat = mean(lag.rat.mna, na.rm = TRUE),
MAX.rat = max(lag.rat.mna, na.rm = TRUE),
MAX.seed = max(lag.sjt, na.rm = TRUE),
MAX.dens = max(lag.N, na.rm = TRUE),
MAX.r = max(mean.r, na.rm = TRUE),
min.seed = 0,
min.dens = 0,
min.rat = 0,
min.r = min(mean.r, na.rm = TRUE)) %>%
ungroup()
# #merge two datasets
feb.plot <- left_join(out.dat1.feb2 ,out.para.feb)
# predict estimates for seed lines
# seed.feb.plot1 <- feb.plot %>%
# mutate(pred.mean = b0 + (b.seed * M.seed) + (b.dens*M.dens) + (b.rat*M.rat),
# pred.min = b0 + (b.seed * min.seed) + (b.dens*min.dens) + (b.rat*min.rat),
# pred.max = b0 + (b.seed * MAX.seed) + (b.dens*MAX.dens) + (b.rat*MAX.rat))
feb.plot1 <- feb.plot %>%
mutate(pred.mean = Intercept + (Seed * M.seed) + (Density*M.dens) + (Rats*M.rat),
pred.min = Intercept + (Seed * M.seed) + (Density*min.dens) + (Rats*M.dens),
pred.max = Intercept + (Seed * M.seed) + (Density*MAX.dens) + (Rats*M.dens))
# # r2
# # plot(pred~mean.r, data = seed.feb.plot1)
#
#
# # data in tidyverse for ggplot2
out.dens.feb2 <- feb.plot1 %>%
gather(key = pred.fact, value = mean.r, pred.min:pred.max) %>%
mutate(lag.N = ifelse(pred.fact == "pred.min", min.dens, MAX.dens)) %>%
select(Valley, Control, mean.r, lag.N) %>%
mutate(treat = paste(Valley, Control),
lag.N = ifelse(lag.N>0, lag.N, 0.1))
#
# # dens-feb ----------------------------------------------------------------
# #spread
# dens.feb.plot1 <- feb.plot %>%
# mutate(pred.min = b0 + (b.dens * dat.mice.min),
# pred.max = (b0 + b.dens * dat.mice.max))
#
# #tidyverse
# out.dens.feb2 <- dens.feb.plot1 %>%
# gather(key = pred.fact, value = mean.r, pred.min:pred.max) %>%
# mutate(lag.sjt = ifelse(pred.fact == "pred.min", dat.mice.min, dat.mice.max)) %>%
# select(valley, control, mean.r, lag.sjt) %>%
# mutate(treat = paste(valley, control))
#
#
# # rat-feb -----------------------------------------------------------------
# #spread and predict
# rat.feb.plot1 <- feb.plot %>%
# mutate(pred.min = b0 + (b.dens * dat.rat.min),
# pred.max = (b0 + b.dens * dat.rat.max))
#
# #tidyverse
# out.rat.feb2 <- rat.feb.plot1 %>%
# gather(key = pred.fact, value = mean.r, pred.min:pred.max) %>%
# mutate(lag.sjt = ifelse(pred.fact == "pred.min", dat.rat.min, dat.rat.max)) %>%
# select(valley, control, mean.r, lag.sjt) %>%
# mutate(treat = paste(valley, control))
# data ----------------------
### Seed lines (feb)
pD.plot.3 <- out.full.136 %>%
filter(month == "Feb") %>%
mutate(lag.sjt = lag(log.seed),
lag.N = lag(N))
pd.plot.feb <- ggplot(pD.plot.3, aes(y = mean.r, x = lag.N)) +
geom_errorbar(aes(ymin = lcl.r, ymax = ucl.r), lwd = 0.75, alpha = 0.2, position=position_dodge(width=30), width = 0) +
geom_point(aes(colour = Valley,shape = Valley, fill = Control),
stroke = 1.5, size = 2, alpha = 0.7) +
# ggplot(out.seed.feb2, aes(y = mean.r, x = lag.sjt)) +
geom_line(data = out.dens.feb2, aes(y = mean.r, x = lag.N, group = treat),size = 0.75, alpha = 0.7) +
geom_point(data = out.dens.feb2, aes(y = mean.r, x = lag.N, shape = Valley, fill = Control, group = treat), size = 5) +
scale_color_manual(name = "Stoat Control",
values = c("white", "black", "white")) +
scale_shape_manual(name = "Ecosystem",
values = c(24, 21)) +
scale_size_manual(name = "Rat Control", values = c(2.5, 3, 2.5)) +
scale_fill_manual(
name = "Stoat Control",
values = c("cornflowerblue", "darkorange", "cornflowerblue")
) +
# 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("cornflowerblue", "darkorange"),shape = c("square"),
size = 4
))
) +
#
# # scale_colour_manual(name = "Stoat control",
# # labels = c("E-", "H+", "H-"),
# # values = c("black","black", "black")) +
# # scale_shape_manual(name = "Valley",
# # labels = c("E", "H"),
# # values = c(25,21)) +
# # scale_fill_manual(name = "Stoat control",
# # labels = c("E-", "H+", "H-"),
# # values = c("white","black", "white")) +
# xlab(expression(paste("Intake"," ", "Rate"," ","(",italic(S[jt]),")" ))) +
xlab(expression(paste("Mouse"," ", "Density"," ","(",italic(N[jt]),")" ))) +
# xlab(expression(atop(paste("Minimum"," ", "number"," "),paste("of", " ", "rats"," ","(",italic(R[jt]),")"))) )+
# xlab(expression(atop(paste("Minimum"," ", "number"," "),paste("of", " ", "rats"," ","(",italic(R[jt]),")"))) )+
ylab(expression(atop(paste("Rate"," ", "of"," ",
"increase"),paste(" ", "of"," ",
"mice"," ","(",italic(r[jt]),")"))) ) +
# scale_y_continuous(expand = c(0,0.01),breaks = seq(-4,4,1)) +
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"))
pd.plot.feb
# pD.plot.3$month
pd.plot <- ggplot(data = pD.plot.3, aes(y = mean.r, x = lag.N)) +
#error bars
geom_errorbar(aes(ymin = lcl.r, ymax = ucl.r),
lwd = 0.75,
alpha = 0.2,
position=position_dodge(width=30),
width = 0) +
#background points
geom_point(aes(colour = Control,
shape = Valley,
fill = Conditions),
stroke = 1.001, size = 2,
alpha = 0.2) +
geom_line(data = out.dens.feb2,
aes(y = mean.r, x = lag.N, group = treat),
size = 0.75,
alpha = 0.7) +
geom_point(data = out.dens.feb2, aes(y = mean.r, x = lag.N, shape = Valley, fill = Control, group = treat), size = 5)+
#Aesthics
scale_color_manual(name = "Rat removal",
values = c("white", "black", "white", "black")) +
scale_shape_manual(name = "Ecosystem",
values = c(24, 21)) +
scale_fill_manual(name = "Stoat control",
values = c("white", "black","white", "black")) +
guides(fill = "none",
col = guide_legend(override.aes = list(
shape = c(15,0), alpha = 0.2
)),
shape = guide_legend(override.aes = list(
shape = c(24, 21), alpha = 1, size = 4
))) +
xlab(expression(paste("Mouse"," ", "Density"," ","(",italic(N[jt]),")" ))) +
# xlab(expression(atop(paste("Minimum"," ", "number"," "),paste("of", " ", "rats"," ","(",italic(R[jt]),")"))) )+
# xlab(expression(atop(paste("Minimum"," ", "number"," "),paste("of", " ", "rats"," ","(",italic(R[jt]),")"))) )+
# xlab(expression(paste("Avaliable seed"," ", "(", italic(Seed[jt]), ")"))) +
ylab(expression(atop(paste("Rate"," ", "of"," ",
"increase"),paste(" ", "of"," ",
"mice"," ","(",italic(r[jt]),")"))) ) +
geom_hline(yintercept = 0, lty = 2, size = 0.5) +
#theme
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 = "right",
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"))
pd.plot
# Save plot
# export plot for example vignette
# png("C://Code/beech-publication-wr/figs/fig-51.png")
# pd.plot
# dev.off()
davan690/beech-publication-wr documentation built on March 29, 2020, 11:09 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
# data for lines ----------------------------------------------------------
# Feb - seed
#feb filtered (parameters)
# flip dataset
# source("./R/Davidson_2019_Model_wrangling.R")
out.para.feb <- para.plot.dat %>%
filter(month == "Feb") %>%
select(mean.b, Control, Valley, para) %>%
droplevels() %>%
spread(key = para, value = mean.b)
#this gives us 12 times lines to estimate from
# for each group I need to ....
#feb filtered (data)
out.dat1.feb <- out.full.136 %>%
filter(month == "Feb") %>%
mutate(lag.sjt = lag(log.seed),
lag.N = lag(N)) %>%
select(-var) %>%
droplevels()
out.dat1.feb2 <- out.full.136 %>%
filter(month == "Feb") %>%
mutate(lag.sjt = lag(log.seed),
lag.N = lag(N)) %>%
group_by(Control, Valley) %>%
summarise(
M.seed = mean(lag.sjt, na.rm = TRUE),
M.dens = mean(lag.N, na.rm = TRUE),
M.rat = mean(lag.rat.mna, na.rm = TRUE),
MAX.rat = max(lag.rat.mna, na.rm = TRUE),
MAX.seed = max(lag.sjt, na.rm = TRUE),
MAX.dens = max(lag.N, na.rm = TRUE),
MAX.r = max(mean.r, na.rm = TRUE),
min.seed = 0,
min.dens = 0,
min.rat = 0,
min.r = min(mean.r, na.rm = TRUE)) %>%
ungroup()
# #merge two datasets
feb.plot <- left_join(out.dat1.feb2 ,out.para.feb)
# predict estimates for seed lines
# seed.feb.plot1 <- feb.plot %>%
# mutate(pred.mean = b0 + (b.seed * M.seed) + (b.dens*M.dens) + (b.rat*M.rat),
# pred.min = b0 + (b.seed * min.seed) + (b.dens*min.dens) + (b.rat*min.rat),
# pred.max = b0 + (b.seed * MAX.seed) + (b.dens*MAX.dens) + (b.rat*MAX.rat))
feb.plot1 <- feb.plot %>%
mutate(pred.mean = Intercept + (Seed * M.seed) + (Density*M.dens) + (Rats*M.rat),
pred.min = Intercept + (Seed * M.seed) + (Density*min.dens) + (Rats*M.dens),
pred.max = Intercept + (Seed * M.seed) + (Density*MAX.dens) + (Rats*M.dens))
# # r2
# # plot(pred~mean.r, data = seed.feb.plot1)
#
#
# # data in tidyverse for ggplot2
out.dens.feb2 <- feb.plot1 %>%
gather(key = pred.fact, value = mean.r, pred.min:pred.max) %>%
mutate(lag.N = ifelse(pred.fact == "pred.min", min.dens, MAX.dens)) %>%
select(Valley, Control, mean.r, lag.N) %>%
mutate(treat = paste(Valley, Control),
lag.N = ifelse(lag.N>0, lag.N, 0.1))
#
# # dens-feb ----------------------------------------------------------------
# #spread
# dens.feb.plot1 <- feb.plot %>%
# mutate(pred.min = b0 + (b.dens * dat.mice.min),
# pred.max = (b0 + b.dens * dat.mice.max))
#
# #tidyverse
# out.dens.feb2 <- dens.feb.plot1 %>%
# gather(key = pred.fact, value = mean.r, pred.min:pred.max) %>%
# mutate(lag.sjt = ifelse(pred.fact == "pred.min", dat.mice.min, dat.mice.max)) %>%
# select(valley, control, mean.r, lag.sjt) %>%
# mutate(treat = paste(valley, control))
#
#
# # rat-feb -----------------------------------------------------------------
# #spread and predict
# rat.feb.plot1 <- feb.plot %>%
# mutate(pred.min = b0 + (b.dens * dat.rat.min),
# pred.max = (b0 + b.dens * dat.rat.max))
#
# #tidyverse
# out.rat.feb2 <- rat.feb.plot1 %>%
# gather(key = pred.fact, value = mean.r, pred.min:pred.max) %>%
# mutate(lag.sjt = ifelse(pred.fact == "pred.min", dat.rat.min, dat.rat.max)) %>%
# select(valley, control, mean.r, lag.sjt) %>%
# mutate(treat = paste(valley, control))
# data ----------------------
### Seed lines (feb)
pD.plot.3 <- out.full.136 %>%
filter(month == "Feb") %>%
mutate(lag.sjt = lag(log.seed),
lag.N = lag(N))
pd.plot.feb <- ggplot(pD.plot.3, aes(y = mean.r, x = lag.N)) +
geom_errorbar(aes(ymin = lcl.r, ymax = ucl.r), lwd = 0.75, alpha = 0.2, position=position_dodge(width=30), width = 0) +
geom_point(aes(colour = Valley,shape = Valley, fill = Control),
stroke = 1.5, size = 2, alpha = 0.7) +
# ggplot(out.seed.feb2, aes(y = mean.r, x = lag.sjt)) +
geom_line(data = out.dens.feb2, aes(y = mean.r, x = lag.N, group = treat),size = 0.75, alpha = 0.7) +
geom_point(data = out.dens.feb2, aes(y = mean.r, x = lag.N, shape = Valley, fill = Control, group = treat), size = 5) +
scale_color_manual(name = "Stoat Control",
values = c("white", "black", "white")) +
scale_shape_manual(name = "Ecosystem",
values = c(24, 21)) +
scale_size_manual(name = "Rat Control", values = c(2.5, 3, 2.5)) +
scale_fill_manual(
name = "Stoat Control",
values = c("cornflowerblue", "darkorange", "cornflowerblue")
) +
# 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("cornflowerblue", "darkorange"),shape = c("square"),
size = 4
))
) +
#
# # scale_colour_manual(name = "Stoat control",
# # labels = c("E-", "H+", "H-"),
# # values = c("black","black", "black")) +
# # scale_shape_manual(name = "Valley",
# # labels = c("E", "H"),
# # values = c(25,21)) +
# # scale_fill_manual(name = "Stoat control",
# # labels = c("E-", "H+", "H-"),
# # values = c("white","black", "white")) +
# xlab(expression(paste("Intake"," ", "Rate"," ","(",italic(S[jt]),")" ))) +
xlab(expression(paste("Mouse"," ", "Density"," ","(",italic(N[jt]),")" ))) +
# xlab(expression(atop(paste("Minimum"," ", "number"," "),paste("of", " ", "rats"," ","(",italic(R[jt]),")"))) )+
# xlab(expression(atop(paste("Minimum"," ", "number"," "),paste("of", " ", "rats"," ","(",italic(R[jt]),")"))) )+
ylab(expression(atop(paste("Rate"," ", "of"," ",
"increase"),paste(" ", "of"," ",
"mice"," ","(",italic(r[jt]),")"))) ) +
# scale_y_continuous(expand = c(0,0.01),breaks = seq(-4,4,1)) +
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"))
pd.plot.feb
# pD.plot.3$month
pd.plot <- ggplot(data = pD.plot.3, aes(y = mean.r, x = lag.N)) +
#error bars
geom_errorbar(aes(ymin = lcl.r, ymax = ucl.r),
lwd = 0.75,
alpha = 0.2,
position=position_dodge(width=30),
width = 0) +
#background points
geom_point(aes(colour = Control,
shape = Valley,
fill = Conditions),
stroke = 1.001, size = 2,
alpha = 0.2) +
geom_line(data = out.dens.feb2,
aes(y = mean.r, x = lag.N, group = treat),
size = 0.75,
alpha = 0.7) +
geom_point(data = out.dens.feb2, aes(y = mean.r, x = lag.N, shape = Valley, fill = Control, group = treat), size = 5)+
#Aesthics
scale_color_manual(name = "Rat removal",
values = c("white", "black", "white", "black")) +
scale_shape_manual(name = "Ecosystem",
values = c(24, 21)) +
scale_fill_manual(name = "Stoat control",
values = c("white", "black","white", "black")) +
guides(fill = "none",
col = guide_legend(override.aes = list(
shape = c(15,0), alpha = 0.2
)),
shape = guide_legend(override.aes = list(
shape = c(24, 21), alpha = 1, size = 4
))) +
xlab(expression(paste("Mouse"," ", "Density"," ","(",italic(N[jt]),")" ))) +
# xlab(expression(atop(paste("Minimum"," ", "number"," "),paste("of", " ", "rats"," ","(",italic(R[jt]),")"))) )+
# xlab(expression(atop(paste("Minimum"," ", "number"," "),paste("of", " ", "rats"," ","(",italic(R[jt]),")"))) )+
# xlab(expression(paste("Avaliable seed"," ", "(", italic(Seed[jt]), ")"))) +
ylab(expression(atop(paste("Rate"," ", "of"," ",
"increase"),paste(" ", "of"," ",
"mice"," ","(",italic(r[jt]),")"))) ) +
geom_hline(yintercept = 0, lty = 2, size = 0.5) +
#theme
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 = "right",
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"))
pd.plot
# Save plot
# export plot for example vignette
# png("C://Code/beech-publication-wr/figs/fig-51.png")
# pd.plot
# dev.off()
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