library(lubridate) library(ggplot2) library(StreamMetabolism) library(xts) library(reshape) library(scales) Elsteraue <- sunrise.set(51.075,12.2180556, "2022/01/01", timezone="MET", num.days=370) sunrise <- Elsteraue$sunrise sunset <- Elsteraue$sunset sunrise <- strftime(sunrise, format="%R", tz="MET") sunset <- strftime(sunset, format="%R", tz="MET") Elsteraue["sr"] <- as.POSIXct(sunrise, format = "%H:%M") Elsteraue["ss"] <- as.POSIXct(sunset, format = "%H:%M") Elsteraue["timestamp"] <- align.time(Elsteraue$sunrise, 60*10) Elsteraue <- Elsteraue[c("timestamp", "sr", "ss")] locsrss <- ggplot(Elsteraue, aes(x=Elsteraue$timestamp)) + geom_line(aes(y=Elsteraue$sr)) + geom_line(aes(y=Elsteraue$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Elsteraue 2022", x = "Datum", y = "Zeit") pdf("Elsteraue_SA_SU.pdf", paper="a4r", width=11) locsrss dev.off() png(filename="Elsteraue_SA_SU.png", width = 1400, height = 800, units = "px") locsrss dev.off() Elsteraue["Sonnenaufgang"] <- strftime(Elsteraue$sr, format="%H:%M") Elsteraue["Sonnenuntergang"] <- strftime(Elsteraue$ss, format="%H:%M") write.table(Elsteraue, file="Elsteraue_SaSu.csv", dec=',', sep=';', row.names=FALSE)