library(lubridate) library(ggplot2) library(StreamMetabolism) library(xts) library(reshape) library(scales) DEwinterlingen <- sunrise.set(7.62,51.96, "2021/01/01", timezone="MET", num.days=370) sunrise <- DEwinterlingen$sunrise sunset <- DEwinterlingen$sunset sunrise <- strftime(sunrise, format="%R", tz="MET") sunset <- strftime(sunset, format="%R", tz="MET") DEwinterlingen["sr"] <- as.POSIXct(sunrise, format = "%H:%M") DEwinterlingen["ss"] <- as.POSIXct(sunset, format = "%H:%M") DEwinterlingen["timestamp"] <- align.time(DEwinterlingen$sunrise, 60*10) DEwinterlingen <- DEwinterlingen[c("timestamp", "sr", "ss")] locsrss <- ggplot(DEwinterlingen, aes(x=DEwinterlingen$timestamp)) + geom_line(aes(y=DEwinterlingen$sr)) + geom_line(aes(y=DEwinterlingen$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - DEwinterlingen 2021", x = "Datum", y = "Zeit") pdf("DEwinterlingen_SA_SU.pdf", paper="a4r", width=11) locsrss dev.off() png(filename="DEwinterlingen_SA_SU.png", width = 1400, height = 800, units = "px") locsrss dev.off() DEwinterlingen["Sonnenaufgang"] <- strftime(DEwinterlingen$sr, format="%H:%M") DEwinterlingen["Sonnenuntergang"] <- strftime(DEwinterlingen$ss, format="%H:%M") write.table(DEwinterlingen, file="DEwinterlingen_SaSu.csv", dec=',', sep=';', row.names=FALSE)