library(lubridate) library(ggplot2) library(StreamMetabolism) library(xts) library(reshape) library(scales) 26670 <- sunrise.set(53.2895011,7.7624034, "2022/01/01", timezone="MET", num.days=370) sunrise <- 26670$sunrise sunset <- 26670$sunset sunrise <- strftime(sunrise, format="%R", tz="MET") sunset <- strftime(sunset, format="%R", tz="MET") 26670["sr"] <- as.POSIXct(sunrise, format = "%H:%M") 26670["ss"] <- as.POSIXct(sunset, format = "%H:%M") 26670["timestamp"] <- align.time(26670$sunrise, 60*10) 26670 <- 26670[c("timestamp", "sr", "ss")] locsrss <- ggplot(26670, aes(x=26670$timestamp)) + geom_line(aes(y=26670$sr)) + geom_line(aes(y=26670$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 26670 2022", x = "Datum", y = "Zeit") pdf("26670_SA_SU.pdf", paper="a4r", width=11) locsrss dev.off() png(filename="26670_SA_SU.png", width = 1400, height = 800, units = "px") locsrss dev.off() 26670["Sonnenaufgang"] <- strftime(26670$sr, format="%H:%M") 26670["Sonnenuntergang"] <- strftime(26670$ss, format="%H:%M") write.table(26670, file="26670_SaSu.csv", dec=',', sep=';', row.names=FALSE)