library(lubridate) library(ggplot2) library(StreamMetabolism) library(xts) library(reshape) library(scales) 07338 <- sunrise.set(52.50286939999999,13.587696300000061, "2023/01/01", timezone="MET", num.days=370) sunrise <- 07338$sunrise sunset <- 07338$sunset sunrise <- strftime(sunrise, format="%R", tz="MET") sunset <- strftime(sunset, format="%R", tz="MET") 07338["sr"] <- as.POSIXct(sunrise, format = "%H:%M") 07338["ss"] <- as.POSIXct(sunset, format = "%H:%M") 07338["timestamp"] <- align.time(07338$sunrise, 60*10) 07338 <- 07338[c("timestamp", "sr", "ss")] locsrss <- ggplot(07338, aes(x=07338$timestamp)) + geom_line(aes(y=07338$sr)) + geom_line(aes(y=07338$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 07338 2023", x = "Datum", y = "Zeit") pdf("07338_SA_SU.pdf", paper="a4r", width=11) locsrss dev.off() png(filename="07338_SA_SU.png", width = 1400, height = 800, units = "px") locsrss dev.off() 07338["Sonnenaufgang"] <- strftime(07338$sr, format="%H:%M") 07338["Sonnenuntergang"] <- strftime(07338$ss, format="%H:%M") write.table(07338, file="07338_SaSu.csv", dec=',', sep=';', row.names=FALSE)