library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Crauthem <- sunrise.set(49.5344813,6.144375, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Crauthem$sunrise
sunset <- Crauthem$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Crauthem["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Crauthem["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Crauthem["timestamp"] <- align.time(Crauthem$sunrise, 60*10)
Crauthem <- Crauthem[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Crauthem, aes(x=Crauthem$timestamp)) + geom_line(aes(y=Crauthem$sr)) + geom_line(aes(y=Crauthem$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Crauthem 2024", x = "Datum", y = "Zeit")
pdf("Crauthem_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Crauthem_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Crauthem["Sonnenaufgang"] <- strftime(Crauthem$sr, format="%H:%M")
Crauthem["Sonnenuntergang"] <- strftime(Crauthem$ss, format="%H:%M")
write.table(Crauthem, file="Crauthem_SaSu.csv", dec=',', sep=';', row.names=FALSE)