library(lubridate) library(ggplot2) library(StreamMetabolism) library(xts) library(reshape) library(scales) 64665 <- sunrise.set(49.7365976,8.585234, "2023/01/01", timezone="MET", num.days=370) sunrise <- 64665$sunrise sunset <- 64665$sunset sunrise <- strftime(sunrise, format="%R", tz="MET") sunset <- strftime(sunset, format="%R", tz="MET") 64665["sr"] <- as.POSIXct(sunrise, format = "%H:%M") 64665["ss"] <- as.POSIXct(sunset, format = "%H:%M") 64665["timestamp"] <- align.time(64665$sunrise, 60*10) 64665 <- 64665[c("timestamp", "sr", "ss")] locsrss <- ggplot(64665, aes(x=64665$timestamp)) + geom_line(aes(y=64665$sr)) + geom_line(aes(y=64665$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 64665 2023", x = "Datum", y = "Zeit") pdf("64665_SA_SU.pdf", paper="a4r", width=11) locsrss dev.off() png(filename="64665_SA_SU.png", width = 1400, height = 800, units = "px") locsrss dev.off() 64665["Sonnenaufgang"] <- strftime(64665$sr, format="%H:%M") 64665["Sonnenuntergang"] <- strftime(64665$ss, format="%H:%M") write.table(64665, file="64665_SaSu.csv", dec=',', sep=';', row.names=FALSE)