Nothing
## ----setup, include=FALSE-----------------------------------------------------
knitr::opts_chunk$set(fig.width=10, fig.height=10, fig.asp = 0.618, out.width = "95%", fig.align = "center", fig.dpi = 150, collapse = FALSE, comment = "#")
options(rmarkdown.html_vignette.check_title = FALSE)
## ----message=FALSE, warning=FALSE---------------------------------------------
#Load packages
# simulate temperatures
library(eesim)
# modelling
library(dynamAedes)
# data manipulation and plotting
library(ggplot2)
Sys.setlocale("LC_TIME", "en_GB.UTF-8")
## ----warning=FALSE------------------------------------------------------------
ndays <- 365*1 #length of the time series in days
set.seed(123)
sim_temp <- create_sims(n_reps = 1,
n = ndays,
central = 16,
sd = 2,
exposure_type = "continuous",
exposure_trend = "cos1", exposure_amp = -1.0,
average_outcome = 12,
outcome_trend = "cos1",
outcome_amp = 0.8,
rr = 1.0055)
## ----warning=FALSE------------------------------------------------------------
hist(sim_temp[[1]]$x,
xlab="Temperature (°C)",
main="Histogram of simulated temperatures")
plot(sim_temp[[1]]$date,
sim_temp[[1]]$x,
main="Simulated temperatures seasonal trend",
xlab="Date", ylab="Temperature (°C)"
)
## ----warning=FALSE------------------------------------------------------------
## Define the day of introduction (July 1st is day 1)
str <- "2000-07-01"
## Define the end-day of life cycle (August 1st is the last day)
endr <- "2000-08-01"
## Define the number of eggs to be introduced
ie <- 1000
## Define the number of model iterations
it <- 1 # The higher the number of simulations the better
## Define the number of liters for the larval density-dependent mortality
habitat_liters <- 1
#Define latitude and longitude for the diapause process
myLat <- 42
myLon <- 7
## Define the number of parallel processes (for sequential iterations set nc=1)
cl <- 1
## ----warning=FALSE------------------------------------------------------------
df_temp <- data.frame("Date" = sim_temp[[1]]$date, "temp" = sim_temp[[1]]$x)
w <- t(as.integer(df_temp$temp*1000)[format(as.Date(str)+1,"%j"):format(as.Date(endr)+1,"%j")])
## ----message=FALSE, warning=FALSE---------------------------------------------
simout <- dynamAedes.m(species="albopictus",
scale="ws",
jhwv=habitat_liters,
temps.matrix=w,
startd=str,
endd=endr,
n.clusters=cl,
iter=it,
intro.eggs=ie,
compressed.output=TRUE,
lat=myLat,
long=myLon,
verbose=FALSE,
seeding=TRUE)
## ----warning=FALSE------------------------------------------------------------
summary(simout)
## ----warning=FALSE, message=FALSE, results='hide'-----------------------------
simout@n_iterations
## ----warning=FALSE, message=FALSE, results='hide'-----------------------------
simout@simulation
## ----warning=FALSE------------------------------------------------------------
length(simout@simulation[[1]])
## ----warning=FALSE------------------------------------------------------------
simout@simulation[[1]][[1]]
simout@simulation[[1]][[15]]
## ----message=FALSE, warning=FALSE---------------------------------------------
psi(input_sim = simout, eval_date = 30)
## ----message=FALSE, warning=FALSE---------------------------------------------
# Retrieve the maximum number of simulated days
dd <- max(simout)
# Compute the inter-quartile of abundances along the iterations
breaks=c(0.25,0.50,0.75)
ed=1:dd
outdf <- rbind(
adci(simout, eval_date=ed, breaks=breaks, stage="Eggs"),
adci(simout, eval_date=ed, breaks=breaks, stage="Juvenile"),
adci(simout, eval_date=ed, breaks=breaks, stage="Adults"),
adci(simout, eval_date=ed, breaks=breaks, stage="Dia"))
## ----message=FALSE, warning=FALSE---------------------------------------------
outdf$stage <- factor(outdf$stage, levels= c('Egg', 'DiapauseEgg', 'Juvenile', 'Adult'))
outdf$Date <- rep(seq.Date(as.Date(str), as.Date(endr) - 2, by="day"), 4)
ggplot(outdf, aes(x=Date, y=X50., group=factor(stage), col=factor(stage))) +
ggtitle("Ae. albopictus Interquantile range abundance") +
geom_ribbon(aes(ymin=X25., ymax=X75., fill=factor(stage)),
col="white",
alpha=0.2,
outline.type="full") +
geom_line(linewidth=0.8) +
labs(x="Date", y="Interquantile range abundance", col="Stage", fill="Stage") +
facet_wrap(~stage, scales = "free_y") +
theme_light() +
theme(legend.position="bottom",
text = element_text(size=16),
strip.text = element_text(face = "italic"))
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