library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Saabrücken <- sunrise.set(49.2401572,6.9969327, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Saabrücken$sunrise
sunset <- Saabrücken$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Saabrücken["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Saabrücken["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Saabrücken["timestamp"] <- align.time(Saabrücken$sunrise, 60*10)
Saabrücken <- Saabrücken[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Saabrücken, aes(x=Saabrücken$timestamp)) + geom_line(aes(y=Saabrücken$sr)) + geom_line(aes(y=Saabrücken$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Saabrücken 2024", x = "Datum", y = "Zeit")
pdf("Saabrücken_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Saabrücken_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Saabrücken["Sonnenaufgang"] <- strftime(Saabrücken$sr, format="%H:%M")
Saabrücken["Sonnenuntergang"] <- strftime(Saabrücken$ss, format="%H:%M")
write.table(Saabrücken, file="Saabrücken_SaSu.csv", dec=',', sep=';', row.names=FALSE)