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Rnetlogo_Win.R
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### RNetlogo Package ###
# --Windows Version--#
library(RNetLogo)
library(tidyverse)
nl.path <- "c:/Program Files/NetLogo 6.0.4/app"
NLStart(nl.path, gui=F, nl.obj=NULL, is3d=FALSE, nl.jarname='netlogo-6.0.4.jar')
model.path.win <- "d:/github/jasss/Gangnam_v6_macro.nlogo"
NLLoadModel(model.path.win)
new.col.names <- c( "riskpop", "d_sinsa", "d_nonhyun1", "d_nonhyun2",
"d_samsung1", "d_samsung2","d_daechi1","d_daechi4","d_yeoksam1",
"d_yeoksam2","d_dogok1","d_dogok2","d_gaepo1","d_gaepo4",
"d_ilwon","d_ilwon1","d_ilwon2","d_suseo", "d_ap","d_chungdam",
"d_daechi2","d_gaepo2","d_segok",
"a_u15","a_btw1564","a_ov65","e_high","e_low")
for (i in 1:10){
NLCommand("setup")
NLCommand (paste('set AC', 100))
NLCommand (paste('set Scenario', '"BAU"'))
NLCommand (paste('set scenario-percent', '"inc-sce"'))
NLCommand (paste('set PM10-parameters', 100))
simulation <- paste("model100",i, sep = ".")
assign(simulation, NLDoReportWhile("ticks < 8764" , "go",
c("%riskpop", "d_sinsa", "d_nonhyun1", "d_nonhyun2",
"d_samsung1", "d_samsung2","d_daechi1","d_daechi4","d_yeoksam1",
"d_yeoksam2","d_dogok1","d_dogok2","d_gaepo1","d_gaepo4",
"d_ilwon","d_ilwon1","d_ilwon2","d_suseo", "d_ap","d_chungdam",
"d_daechi2","d_gaepo2","d_segok",
"a_u15","a_btw1564","a_ov65","e_high","e_low"), df.col.names= new.col.names,as.data.frame = T, max.minutes=150)
)
simulation %>% mutate(ticks = 1:8764, iteration = i)
h <- paste("health100",i, sep = ".")
assign(h, NLGetAgentSet(c("who", "homename", "destinationName", "age", "health"), "people")) %>% mutate(iteration = i)
}
for (i in 1:10){
NLCommand("setup")
NLCommand (paste('set AC', 150))
NLCommand (paste('set Scenario', '"BAU"'))
NLCommand (paste('set scenario-percent', '"inc-sce"'))
NLCommand (paste('set PM10-parameters', 100))
simulation <- paste("model150",i, sep = ".")
assign(simulation, NLDoReportWhile("ticks < 8764" , "go",
c("%riskpop", "d_sinsa", "d_nonhyun1", "d_nonhyun2",
"d_samsung1", "d_samsung2","d_daechi1","d_daechi4","d_yeoksam1",
"d_yeoksam2","d_dogok1","d_dogok2","d_gaepo1","d_gaepo4",
"d_ilwon","d_ilwon1","d_ilwon2","d_suseo", "d_ap","d_chungdam",
"d_daechi2","d_gaepo2","d_segok",
"a_u15","a_btw1564","a_ov65","e_high","e_low"), df.col.names= new.col.names,as.data.frame = T, max.minutes=150)
)
simulation %>% mutate(ticks = 1:8764, iteration = i)
h <- paste("health100",i, sep = ".")
assign(h, NLGetAgentSet(c("who", "homename", "destinationName", "age", "health"), "people")) %>% mutate(iteration = i)
}
for (i in 1:10){
NLCommand("setup")
NLCommand (paste('set AC', 200))
NLCommand (paste('set Scenario', '"BAU"'))
NLCommand (paste('set scenario-percent', '"inc-sce"'))
NLCommand (paste('set PM10-parameters', 100))
simulation <- paste("model200",i, sep = ".")
assign(simulation, NLDoReportWhile("ticks < 8764" , "go",
c("%riskpop", "d_sinsa", "d_nonhyun1", "d_nonhyun2",
"d_samsung1", "d_samsung2","d_daechi1","d_daechi4","d_yeoksam1",
"d_yeoksam2","d_dogok1","d_dogok2","d_gaepo1","d_gaepo4",
"d_ilwon","d_ilwon1","d_ilwon2","d_suseo", "d_ap","d_chungdam",
"d_daechi2","d_gaepo2","d_segok",
"a_u15","a_btw1564","a_ov65","e_high","e_low"), df.col.names= new.col.names,as.data.frame = T, max.minutes=150)
)
simulation %>% mutate(ticks = 1:8764, iteration = i)
h <- paste("health100",i, sep = ".")
assign(h, NLGetAgentSet(c("who", "homename", "destinationName", "age", "health"), "people")) %>% mutate(iteration = i)
}
#save.image(file = "d:/github/jasss/jasss.Rdata")
model100 <- bind_rows(model100.1, model100.2, model100.3,model100.4,model100.5,model100.6,model100.7,model100.8,model100.9,model100.10) %>%
group_by(ticks) %>%
summarise_all(funs(mean))
#############################################
library(tidyverse)
library(reshape2)
library(gghighlight)
#risk <- total %>% select(riskpop,ticks)
#dong <- total %>% select(matches('d_'),ticks)
#age <- total %>% select(matches('a_'),ticks)
#edu <- total %>% select(matches('e_'),ticks)
#pm10 <- total %>% select(matches('pm10-'),ticks)
##
risk100 <- model100 %>%
select(riskpop,ticks) %>%
melt(id = "ticks", variable.name = "total", value.name = "percent")
risk100 %>%
ggplot(aes(ticks, percent, group = total)) +
geom_line(size = 1) +
ylim(0,20) +
theme_bw() +
theme(axis.text=element_text(size=20),
axis.title=element_text(size=15,face="bold")) +
xlab("ticks") +
ylab("Percent of risk population(%)")
##
dong100 <- model100 %>%
select(matches('d_'),ticks) %>%
melt(id = "ticks", variable.name = "dongs", value.name = "percent")
ggplot(dong100) +
geom_line(aes(ticks, percent, color = dongs), size = 1) +
gghighlight(max(percent) > 8,
label_params = list(size = 8)) +
ylim(0,20) +
theme_bw() +
theme(legend.position="bottom",
axis.text=element_text(size=20),
axis.title=element_text(size=15,face="bold")) +
xlab("Days") +
ylab("Percent of risk population(%)")
##
age100 <- model100 %>% select(matches('a_'),ticks) %>%
melt(id = "ticks", variable.name = "age", value.name = "percent")
age100 %>%
ggplot(aes(ticks, percent, group = age, color = age)) +
geom_line(size = 1)+
gghighlight(max(percent) > 0,
label_params = list(size = 8)) +
ylim(0,20) +
theme_bw() +
theme(axis.text=element_text(size=20),
axis.title=element_text(size=15,face="bold"),
legend.position="none") +
xlab("Days") +
ylab("Percent of risk population(%)")
edu100 <- model100 %>% select(matches('e_'),ticks) %>%
melt(id = "ticks", variable.name = "edu", value.name = "percent")
edu100 %>%
ggplot(aes(ticks, percent, group = edu, color = edu)) +
geom_line(size = 1)+
gghighlight(max(percent) > 0,
label_params = list(size = 8)) +
ylim(0,20) +
theme_bw() +
theme(axis.text=element_text(size=20),
axis.title=element_text(size=15,face="bold"),
legend.position="none") +
xlab("Days") +
ylab("Percent of risk population(%)")
options("scipen"=100, "digits"=4) ##Coz of decimal points
# health distribution: density plot!
healthy <- NLGetAgentSet(c("who", "homename", "destinationName", "age", "health"), "people")
health <- healthy %>% filter(destinationName != "others") # remove agents destinated to others
health$health[health$health <= 0] <- 0
ggplot(health, aes(health, fill = destinationName)) +
geom_density(alpha = 0.4) +
theme_bw() +
theme(legend.title = element_text(size=20, face="bold"),
legend.text = element_text(size=15),
legend.position = c(0.2, 0.8),
axis.text=element_text(size=20),
axis.title=element_text(size=15,face="bold")
)
#
healthzero <- health %>% filter(health==0)
ggplot(healthzero, aes(homename, fill = age)) +
geom_bar(stat = "count", position = "dodge")+
theme_bw()
healthzero %>%
count(homename, age) %>%
ggplot(aes(x = reorder(homename, n, sum), y = n, fill = age)) +
geom_col() +
xlab("") +
ylab("Counts") +
theme_bw() +
theme(legend.title = element_text(size=20, face="bold"),
legend.text = element_text(size=15),
legend.position = c(0.1, 0.9),
axis.text=element_text(size=13),
axis.text.x = element_text(angle = 90, hjust = 1),
axis.title=element_text(size=15,face="bold")
)