library(lubridate) library(ggplot2) library(StreamMetabolism) library(xts) library(reshape) library(scales) D_65185 <- sunrise.set(50.0752003,8.2397125, "2021/01/01", timezone="MET", num.days=370) sunrise <- D_65185$sunrise sunset <- D_65185$sunset sunrise <- strftime(sunrise, format="%R", tz="MET") sunset <- strftime(sunset, format="%R", tz="MET") D_65185["sr"] <- as.POSIXct(sunrise, format = "%H:%M") D_65185["ss"] <- as.POSIXct(sunset, format = "%H:%M") D_65185["timestamp"] <- align.time(D_65185$sunrise, 60*10) D_65185 <- D_65185[c("timestamp", "sr", "ss")] locsrss <- ggplot(D_65185, aes(x=D_65185$timestamp)) + geom_line(aes(y=D_65185$sr)) + geom_line(aes(y=D_65185$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - D_65185 2021", x = "Datum", y = "Zeit") pdf("D_65185_SA_SU.pdf", paper="a4r", width=11) locsrss dev.off() png(filename="D_65185_SA_SU.png", width = 1400, height = 800, units = "px") locsrss dev.off() D_65185["Sonnenaufgang"] <- strftime(D_65185$sr, format="%H:%M") D_65185["Sonnenuntergang"] <- strftime(D_65185$ss, format="%H:%M") write.table(D_65185, file="D_65185_SaSu.csv", dec=',', sep=';', row.names=FALSE)