library(lubridate) library(ggplot2) library(StreamMetabolism) library(xts) library(reshape) library(scales) Avalus <- sunrise.set(62.60345318745799,23.5986328125, "2022/01/01", timezone="MET", num.days=370) sunrise <- Avalus$sunrise sunset <- Avalus$sunset sunrise <- strftime(sunrise, format="%R", tz="MET") sunset <- strftime(sunset, format="%R", tz="MET") Avalus["sr"] <- as.POSIXct(sunrise, format = "%H:%M") Avalus["ss"] <- as.POSIXct(sunset, format = "%H:%M") Avalus["timestamp"] <- align.time(Avalus$sunrise, 60*10) Avalus <- Avalus[c("timestamp", "sr", "ss")] locsrss <- ggplot(Avalus, aes(x=Avalus$timestamp)) + geom_line(aes(y=Avalus$sr)) + geom_line(aes(y=Avalus$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Avalus 2022", x = "Datum", y = "Zeit") pdf("Avalus_SA_SU.pdf", paper="a4r", width=11) locsrss dev.off() png(filename="Avalus_SA_SU.png", width = 1400, height = 800, units = "px") locsrss dev.off() Avalus["Sonnenaufgang"] <- strftime(Avalus$sr, format="%H:%M") Avalus["Sonnenuntergang"] <- strftime(Avalus$ss, format="%H:%M") write.table(Avalus, file="Avalus_SaSu.csv", dec=',', sep=';', row.names=FALSE)