library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
21684 <- sunrise.set(53.58769713531905,9.427424084570248, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 21684$sunrise
sunset <- 21684$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
21684["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
21684["ss"] <- as.POSIXct(sunset, format = "%H:%M")
21684["timestamp"] <- align.time(21684$sunrise, 60*10)
21684 <- 21684[c("timestamp", "sr", "ss")]
locsrss <- ggplot(21684, aes(x=21684$timestamp)) + geom_line(aes(y=21684$sr)) + geom_line(aes(y=21684$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 21684 2024", x = "Datum", y = "Zeit")
pdf("21684_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="21684_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
21684["Sonnenaufgang"] <- strftime(21684$sr, format="%H:%M")
21684["Sonnenuntergang"] <- strftime(21684$ss, format="%H:%M")
write.table(21684, file="21684_SaSu.csv", dec=',', sep=';', row.names=FALSE)