library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Abu_dhabi <- sunrise.set(24.476431,54.37051, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Abu_dhabi$sunrise
sunset <- Abu_dhabi$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Abu_dhabi["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Abu_dhabi["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Abu_dhabi["timestamp"] <- align.time(Abu_dhabi$sunrise, 60*10)
Abu_dhabi <- Abu_dhabi[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Abu_dhabi, aes(x=Abu_dhabi$timestamp)) + geom_line(aes(y=Abu_dhabi$sr)) + geom_line(aes(y=Abu_dhabi$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Abu_dhabi 2024", x = "Datum", y = "Zeit")
pdf("Abu_dhabi_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Abu_dhabi_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Abu_dhabi["Sonnenaufgang"] <- strftime(Abu_dhabi$sr, format="%H:%M")
Abu_dhabi["Sonnenuntergang"] <- strftime(Abu_dhabi$ss, format="%H:%M")
write.table(Abu_dhabi, file="Abu_dhabi_SaSu.csv", dec=',', sep=';', row.names=FALSE)