library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Feulen <- sunrise.set(49.8560492,6.0411998, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Feulen$sunrise
sunset <- Feulen$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Feulen["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Feulen["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Feulen["timestamp"] <- align.time(Feulen$sunrise, 60*10)
Feulen <- Feulen[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Feulen, aes(x=Feulen$timestamp)) + geom_line(aes(y=Feulen$sr)) + geom_line(aes(y=Feulen$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Feulen 2024", x = "Datum", y = "Zeit")
pdf("Feulen_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Feulen_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Feulen["Sonnenaufgang"] <- strftime(Feulen$sr, format="%H:%M")
Feulen["Sonnenuntergang"] <- strftime(Feulen$ss, format="%H:%M")
write.table(Feulen, file="Feulen_SaSu.csv", dec=',', sep=';', row.names=FALSE)