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)