Primary Investigator: Althea ArchMiller
Collaborators: J. Fieberg, B. Dorazio, K. St. Clair
Description Create plots for the manuscript and for the appendices.
# Documentation-related
library(devtools)
library(knitr)
library(ezknitr)
# Analysis-related
library(ggplot2)
library(ggthemes)
library(gridExtra)
# Remove environment and set seed
remove(list=ls())
set.seed(4587)
Posteriors for Psi/Lambda
load("data/processed_results/psiPosts.Rdata")
load("data/processed_results/lambdaPosts.Rdata")
Population estimates
load("data/processed_results/popnEsts.Rdata")
load("data/processed_results/popnEstsJoint.Rdata")
Sightability curves for joint models and mHT
load("data/processed_results/sightCurve_Joint.Rdata")
load("data/processed_results/sightCurve_mHT.Rdata")
VOC posteriors for 2006
load("data/processed_results/vocPosts2006.Rdata")
Population estimates graph
pe11 <- ggplot(data = popn.ests[popn.ests$Method=="FE model"|
popn.ests$Method=="TS model",],
aes(x = Year, y = tauhat, colour=Method, shape=Method))+
geom_ribbon(data = popn.ests[popn.ests$Method=="mHT",],
aes(x = Year, ymin = tau.LL90, ymax = tau.UL90),
fill="#e8e8e8")+
geom_line(data = popn.ests[popn.ests$Method=="mHT",],
aes(y = tauhat), colour="#969696",size=1.1)+
geom_pointrange(aes(ymin=tau.LL90, ymax=tau.UL90),
position=position_dodge(0.2))+
geom_line(position=position_dodge(0.2))+
ylab(expression(hat(tau)[t]*" (90% CI)"))+
scale_x_continuous(breaks=seq(2005,2016,1), limits = c(2004.8, 2016.2))+
theme_tufte()+
theme(legend.position = c(0.8,0.8),
legend.title = element_blank())+
scale_color_manual(values = c("#ae017e", "#e8e8e8", "#2ca25f"))+
ggtitle("A")
Log change graph
lc <- ggplot(data = popn.ests[popn.ests$Method!="mHT",],
aes(x = Year, y = logdiff, colour=Method, shape=Method))+
geom_ribbon(data = popn.ests[popn.ests$Method=="mHT",],
aes(x = Year, ymin = logdiff.LL90, ymax = logdiff.UL90),
fill="#e8e8e8")+
geom_line(data = popn.ests[popn.ests$Method=="mHT",],
aes(y = logdiff), colour="#969696", size=1.1)+
geom_hline(aes(yintercept=0))+
geom_pointrange(aes(ymin=logdiff.LL90, ymax=logdiff.UL90),
position=position_dodge(0.2))+
geom_line(position=position_dodge(0.2))+
ylab(expression("log("*hat(tau)[t]*"/"*hat(tau)[t*-1]*") (90% CI)"))+
scale_x_continuous(breaks=seq(2005,2016,1),limits = c(2004.8, 2016.2))+
theme_tufte()+
theme(legend.position="none")+
scale_color_manual(values = c("#ae017e", "#e8e8e8", "#2ca25f"),
breaks = c("FEM", "TEM"))+
ggtitle("B")
Combine together
grid.arrange(pe11, lc, ncol=1)
## Warning: Removed 1 rows containing missing values (geom_path).
## Warning: Removed 2 rows containing missing values (geom_pointrange).
## Warning: Removed 2 rows containing missing values (geom_path).
pdf("manuscript/figures/popnLog11-1.pdf", width = 6, height = 4.5)
grid.arrange(pe11, lc, ncol=1)
## Warning: Removed 1 rows containing missing values (geom_path).
## Warning: Removed 2 rows containing missing values (geom_pointrange).
## Warning: Removed 2 rows containing missing values (geom_path).
dev.off()
## RStudioGD
## 2
ggplot(aes(x = as.factor(Year), y = Median, colour=Method, shape=Method),
data=psiPosteriors)+
geom_linerange(aes(ymin=LL, ymax=UL), position = position_dodge(0.3))+
geom_point(aes(y=Median), position = position_dodge(0.3))+
facet_grid(Strata~.)+
xlab("Year")+
ylab(expression("Mean "*psi['h,t']))+
scale_color_manual(breaks = c("FE model", "TS model"),
values = c("#ae017e", "#2ca25f"))+
theme_minimal()+
theme(legend.position = "bottom")
ggsave("manuscript/figures/psiPosts-1.png", width = 5, height = 5)
ggsave("manuscript/figures/psiPosts-1.pdf", width = 5, height = 5)
ggplot(aes(x = as.factor(Year), y = Median, colour=Method, shape=Method),
data=lambdaPosteriors)+
geom_linerange(aes(ymin=LL, ymax=UL), position = position_dodge(0.3))+
geom_point(aes(y=Median), position = position_dodge(0.3))+
facet_grid(Strata~.)+
xlab("Year")+
ylab(expression(lambda['h,t']))+
scale_color_manual(breaks = c("FE model", "TS model"),
values = c("#ae017e", "#2ca25f"))+
theme_minimal()+
theme(legend.position = "bottom")
ggsave("manuscript/figures/lambdaPosts-1.png", width = 5, height = 5)
ggsave("manuscript/figures/lambdaPosts-1.pdf", width = 5, height = 5)
Function to get legend
get_legend<-function(myggplot){
tmp <- ggplot_gtable(ggplot_build(myggplot))
leg <- which(sapply(tmp$grobs, function(x) x$name) == "guide-box")
legend <- tmp$grobs[[leg]]
return(legend)
}
Part 1: Sight model curves
sc <- ggplot(data = sightcurve.mHT,
aes(x = voc, y = g, colour=Method))+
geom_ribbon(aes(ymin = LL90, ymax = UL90), fill="#e8e8e8", color="#e8e8e8")+
geom_line(color="#969696", size = 1.1)+
geom_line(data = sightcurve.joint, aes(x=x, y=g, colour=Method))+
theme_tufte()+
theme(legend.position = "none")+
scale_color_manual(values = c("#2166ac","#67a9cf", "#78c679",
"#fc8d59","#b2182b"),
labels = c("2yrs", "3yrs", "4yrs", "5yrs", "11yrs"))+
ggtitle("A")+
ylab(expression(hat(g)['h,i,j,t']))+
xlab(expression(x['h,i,j,t']))
Part 2: Population estimates
pe <- ggplot(data = popn.ests[popn.ests$Method=="mHT"&popn.ests$Year>2005,],
aes(x = Year, y = tauhat))+
geom_ribbon(aes(x = Year, ymin = tau.LL90, ymax = tau.UL90),
colour="#e8e8e8", fill="#e8e8e8")+
geom_line(colour="#969696",size=1.1)+
geom_pointrange(data = popn.ests.joint,
aes(ymin=tauhat.LL90, ymax=tauhat.UL90, y=tauhat.median,
colour=Method, shape=Method),
position=position_dodge(0.2))+
geom_line(data = popn.ests.joint,
aes(y=tauhat.median, colour=Method),
position=position_dodge(0.2))+
ylab(expression(hat(tau)[t]*" (90% CI)"))+
scale_x_continuous(breaks=seq(2006,2016,2))+
theme_tufte()+
scale_color_manual(values = c("#2166ac","#67a9cf", "#78c679",
"#fc8d59","#b2182b"))+
ggtitle("B")+
theme(legend.position = c(0.8,0.8),
legend.justification = c(0.8,0.8),
legend.title = element_blank())
legend.pe <- get_legend(pe)
pe2 <- ggplot(data = popn.ests[popn.ests$Method=="mHT"&popn.ests$Year>2005,],
aes(x = Year, y = tauhat))+
geom_ribbon(aes(x = Year, ymin = tau.LL90, ymax = tau.UL90),
colour="#e8e8e8", fill="#e8e8e8")+
geom_line(colour="#969696",size=1.1)+
geom_pointrange(data = popn.ests.joint,
aes(ymin=tauhat.LL90, ymax=tauhat.UL90, y=tauhat.median,
colour=Method, shape=Method),
position=position_dodge(0.2))+
geom_line(data = popn.ests.joint,
aes(y=tauhat.median, colour=Method),
position=position_dodge(0.2))+
ylab(expression(hat(tau)[t]*" (90% CI)"))+
scale_x_continuous(breaks=seq(2006,2016,2))+
theme_tufte()+
scale_color_manual(values = c("#2166ac","#67a9cf", "#78c679",
"#fc8d59","#b2182b"))+
ggtitle("B")+
theme(legend.position = "none")
Part 3: VOC posteriors
vp <- ggplot(aes(x = voc, colour = Method),
data=voc.posts.yr2006)+
geom_density()+
theme_tufte()+
facet_grid(.~time)+
scale_color_manual(values = c("#2166ac","#67a9cf", "#78c679",
"#fc8d59","#b2182b"))+
ggtitle("C")+
xlab(expression(mu[2006]^x))+
theme(legend.position = "none")
Combine together
grid.arrange(sc, pe2, legend.pe, vp, ncol=3,
layout_matrix=rbind(c(1,2,3),c(4,4,4)),
widths=c(2.5,2.5,0.75))
pdf("manuscript/figures/detectSens-1.pdf", width = 6, height = 4.5)
grid.arrange(sc, pe2, legend.pe, vp, ncol=3,
layout_matrix=rbind(c(1,2,3),c(4,4,4)),
widths=c(2.5,2.5,0.5))
dev.off()
## RStudioGD
## 2
Mean precision (i.e., width of 90% CIs/CRIs) by method
popn.ests$range <- popn.ests$tau.UL90 - popn.ests$tau.LL90
summaryBy(range~Method, data=popn.ests, FUN = mean)
## Error in eval(expr, envir, enclos): could not find function "summaryBy"
Session Information
devtools::session_info()
## Session info -------------------------------------------------------------
## setting value
## version R version 3.3.2 (2016-10-31)
## system x86_64, darwin13.4.0
## ui RStudio (1.0.143)
## language (EN)
## collate en_US.UTF-8
## tz America/Chicago
## date 2018-01-02
## Packages -----------------------------------------------------------------
## package * version date source
## assertthat 0.2.0 2017-04-11 CRAN (R 3.3.2)
## base * 3.3.2 2016-10-31 local
## colorspace 1.3-2 2016-12-14 CRAN (R 3.3.2)
## datasets * 3.3.2 2016-10-31 local
## devtools * 1.13.3 2017-08-02 CRAN (R 3.3.2)
## digest 0.6.12 2017-01-27 CRAN (R 3.3.2)
## evaluate 0.10.1 2017-06-24 CRAN (R 3.3.2)
## ezknitr * 0.6 2016-09-16 CRAN (R 3.3.0)
## ggplot2 * 2.2.1 2016-12-30 CRAN (R 3.3.2)
## ggthemes * 3.4.0 2017-02-19 CRAN (R 3.3.2)
## graphics * 3.3.2 2016-10-31 local
## grDevices * 3.3.2 2016-10-31 local
## grid 3.3.2 2016-10-31 local
## gridExtra * 2.3 2017-09-09 CRAN (R 3.3.2)
## gtable 0.2.0 2016-02-26 CRAN (R 3.3.0)
## highr 0.6 2016-05-09 CRAN (R 3.3.0)
## knitr * 1.17 2017-08-10 CRAN (R 3.3.2)
## labeling 0.3 2014-08-23 CRAN (R 3.3.0)
## lazyeval 0.2.0 2016-06-12 CRAN (R 3.3.0)
## magrittr 1.5 2014-11-22 CRAN (R 3.3.0)
## markdown 0.8 2017-04-20 CRAN (R 3.3.2)
## memoise 1.1.0 2017-04-21 CRAN (R 3.3.2)
## methods * 3.3.2 2016-10-31 local
## mime 0.5 2016-07-07 CRAN (R 3.3.0)
## munsell 0.4.3 2016-02-13 CRAN (R 3.3.0)
## plyr 1.8.4 2016-06-08 CRAN (R 3.3.0)
## R.methodsS3 1.7.1 2016-02-16 CRAN (R 3.3.0)
## R.oo 1.21.0 2016-11-01 CRAN (R 3.3.0)
## R.utils 2.5.0 2016-11-07 CRAN (R 3.3.0)
## Rcpp 0.12.13 2017-09-28 CRAN (R 3.3.2)
## reshape2 1.4.2 2016-10-22 CRAN (R 3.3.0)
## rlang 0.1.2 2017-08-09 CRAN (R 3.3.2)
## rstudioapi 0.7 2017-09-07 CRAN (R 3.3.2)
## scales 0.5.0 2017-08-24 CRAN (R 3.3.2)
## stats * 3.3.2 2016-10-31 local
## stringi 1.1.5 2017-04-07 CRAN (R 3.3.2)
## stringr 1.2.0 2017-02-18 CRAN (R 3.3.2)
## tibble 1.3.4 2017-08-22 CRAN (R 3.3.2)
## tools 3.3.2 2016-10-31 local
## utils * 3.3.2 2016-10-31 local
## withr 2.0.0 2017-07-28 CRAN (R 3.3.2)
spun with: ezknitr::ezspin(“programs/ms_programs/g_plot_results.R”, out_dir = “output”, fig_dir = “figures”, keep_md = F)