library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Bengasi <- sunrise.set(32.1166667,20.0666667, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Bengasi$sunrise
sunset <- Bengasi$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Bengasi["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Bengasi["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Bengasi["timestamp"] <- align.time(Bengasi$sunrise, 60*10)
Bengasi <- Bengasi[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Bengasi, aes(x=Bengasi$timestamp)) + geom_line(aes(y=Bengasi$sr)) + geom_line(aes(y=Bengasi$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Bengasi 2023", x = "Datum", y = "Zeit")
pdf("Bengasi_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Bengasi_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Bengasi["Sonnenaufgang"] <- strftime(Bengasi$sr, format="%H:%M")
Bengasi["Sonnenuntergang"] <- strftime(Bengasi$ss, format="%H:%M")
write.table(Bengasi, file="Bengasi_SaSu.csv", dec=',', sep=';', row.names=FALSE)