library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Dubai <- sunrise.set(25.271139,55.307485, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Dubai$sunrise
sunset <- Dubai$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Dubai["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Dubai["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Dubai["timestamp"] <- align.time(Dubai$sunrise, 60*10)
Dubai <- Dubai[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Dubai, aes(x=Dubai$timestamp)) + geom_line(aes(y=Dubai$sr)) + geom_line(aes(y=Dubai$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Dubai 2024", x = "Datum", y = "Zeit")
pdf("Dubai_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Dubai_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Dubai["Sonnenaufgang"] <- strftime(Dubai$sr, format="%H:%M")
Dubai["Sonnenuntergang"] <- strftime(Dubai$ss, format="%H:%M")
write.table(Dubai, file="Dubai_SaSu.csv", dec=',', sep=';', row.names=FALSE)