library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Darmstadt <- sunrise.set(49.910094370092665,8.67114853507087, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Darmstadt$sunrise
sunset <- Darmstadt$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Darmstadt["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Darmstadt["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Darmstadt["timestamp"] <- align.time(Darmstadt$sunrise, 60*10)
Darmstadt <- Darmstadt[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Darmstadt, aes(x=Darmstadt$timestamp)) + geom_line(aes(y=Darmstadt$sr)) + geom_line(aes(y=Darmstadt$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Darmstadt 2024", x = "Datum", y = "Zeit")
pdf("Darmstadt_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Darmstadt_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Darmstadt["Sonnenaufgang"] <- strftime(Darmstadt$sr, format="%H:%M")
Darmstadt["Sonnenuntergang"] <- strftime(Darmstadt$ss, format="%H:%M")
write.table(Darmstadt, file="Darmstadt_SaSu.csv", dec=',', sep=';', row.names=FALSE)