library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Al_ain <- sunrise.set(24.2075,55.7447222, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Al_ain$sunrise
sunset <- Al_ain$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Al_ain["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Al_ain["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Al_ain["timestamp"] <- align.time(Al_ain$sunrise, 60*10)
Al_ain <- Al_ain[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Al_ain, aes(x=Al_ain$timestamp)) + geom_line(aes(y=Al_ain$sr)) + geom_line(aes(y=Al_ain$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Al_ain 2024", x = "Datum", y = "Zeit")
pdf("Al_ain_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Al_ain_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Al_ain["Sonnenaufgang"] <- strftime(Al_ain$sr, format="%H:%M")
Al_ain["Sonnenuntergang"] <- strftime(Al_ain$ss, format="%H:%M")
write.table(Al_ain, file="Al_ain_SaSu.csv", dec=',', sep=';', row.names=FALSE)