library(lubridate) library(ggplot2) library(StreamMetabolism) library(xts) library(reshape) library(scales) Blavand <- sunrise.set(55.5629035,8.1802254, "2023/01/01", timezone="MET", num.days=370) sunrise <- Blavand$sunrise sunset <- Blavand$sunset sunrise <- strftime(sunrise, format="%R", tz="MET") sunset <- strftime(sunset, format="%R", tz="MET") Blavand["sr"] <- as.POSIXct(sunrise, format = "%H:%M") Blavand["ss"] <- as.POSIXct(sunset, format = "%H:%M") Blavand["timestamp"] <- align.time(Blavand$sunrise, 60*10) Blavand <- Blavand[c("timestamp", "sr", "ss")] locsrss <- ggplot(Blavand, aes(x=Blavand$timestamp)) + geom_line(aes(y=Blavand$sr)) + geom_line(aes(y=Blavand$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Blavand 2023", x = "Datum", y = "Zeit") pdf("Blavand_SA_SU.pdf", paper="a4r", width=11) locsrss dev.off() png(filename="Blavand_SA_SU.png", width = 1400, height = 800, units = "px") locsrss dev.off() Blavand["Sonnenaufgang"] <- strftime(Blavand$sr, format="%H:%M") Blavand["Sonnenuntergang"] <- strftime(Blavand$ss, format="%H:%M") write.table(Blavand, file="Blavand_SaSu.csv", dec=',', sep=';', row.names=FALSE)