library(lubridate) library(ggplot2) library(StreamMetabolism) library(xts) library(reshape) library(scales) 30916 <- sunrise.set(52.45293270000001,9.8519046, "2023/01/01", timezone="MET", num.days=370) sunrise <- 30916$sunrise sunset <- 30916$sunset sunrise <- strftime(sunrise, format="%R", tz="MET") sunset <- strftime(sunset, format="%R", tz="MET") 30916["sr"] <- as.POSIXct(sunrise, format = "%H:%M") 30916["ss"] <- as.POSIXct(sunset, format = "%H:%M") 30916["timestamp"] <- align.time(30916$sunrise, 60*10) 30916 <- 30916[c("timestamp", "sr", "ss")] locsrss <- ggplot(30916, aes(x=30916$timestamp)) + geom_line(aes(y=30916$sr)) + geom_line(aes(y=30916$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 30916 2023", x = "Datum", y = "Zeit") pdf("30916_SA_SU.pdf", paper="a4r", width=11) locsrss dev.off() png(filename="30916_SA_SU.png", width = 1400, height = 800, units = "px") locsrss dev.off() 30916["Sonnenaufgang"] <- strftime(30916$sr, format="%H:%M") 30916["Sonnenuntergang"] <- strftime(30916$ss, format="%H:%M") write.table(30916, file="30916_SaSu.csv", dec=',', sep=';', row.names=FALSE)