library(lubridate) library(ggplot2) library(StreamMetabolism) library(xts) library(reshape) library(scales) Grasberg <- sunrise.set(53.1813452,8.9863191, "2019/01/01", timezone="MET", num.days=370) sunrise <- Grasberg$sunrise sunset <- Grasberg$sunset sunrise <- strftime(sunrise, format="%R", tz="MET") sunset <- strftime(sunset, format="%R", tz="MET") Grasberg["sr"] <- as.POSIXct(sunrise, format = "%H:%M") Grasberg["ss"] <- as.POSIXct(sunset, format = "%H:%M") Grasberg["timestamp"] <- align.time(Grasberg$sunrise, 60*10) Grasberg <- Grasberg[c("timestamp", "sr", "ss")] locsrss <- ggplot(Grasberg, aes(x=Grasberg$timestamp)) + geom_line(aes(y=Grasberg$sr)) + geom_line(aes(y=Grasberg$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Grasberg 2019", x = "Datum", y = "Zeit") pdf("Grasberg_SA_SU.pdf", paper="a4r", width=11) locsrss dev.off() png(filename="Grasberg_SA_SU.png", width = 1400, height = 800, units = "px") locsrss dev.off() Grasberg["Sonnenaufgang"] <- strftime(Grasberg$sr, format="%H:%M") Grasberg["Sonnenuntergang"] <- strftime(Grasberg$ss, format="%H:%M") write.table(Grasberg, file="Grasberg_SaSu.csv", dec=',', sep=';', row.names=FALSE)