library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Eppstein <- sunrise.set(50.145296,8.3881459, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Eppstein$sunrise
sunset <- Eppstein$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Eppstein["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Eppstein["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Eppstein["timestamp"] <- align.time(Eppstein$sunrise, 60*10)
Eppstein <- Eppstein[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Eppstein, aes(x=Eppstein$timestamp)) + geom_line(aes(y=Eppstein$sr)) + geom_line(aes(y=Eppstein$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Eppstein 2024", x = "Datum", y = "Zeit")
pdf("Eppstein_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Eppstein_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Eppstein["Sonnenaufgang"] <- strftime(Eppstein$sr, format="%H:%M")
Eppstein["Sonnenuntergang"] <- strftime(Eppstein$ss, format="%H:%M")
write.table(Eppstein, file="Eppstein_SaSu.csv", dec=',', sep=';', row.names=FALSE)