library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Beckingen <- sunrise.set(49.3912643,6.7043943, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Beckingen$sunrise
sunset <- Beckingen$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Beckingen["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Beckingen["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Beckingen["timestamp"] <- align.time(Beckingen$sunrise, 60*10)
Beckingen <- Beckingen[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Beckingen, aes(x=Beckingen$timestamp)) + geom_line(aes(y=Beckingen$sr)) + geom_line(aes(y=Beckingen$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Beckingen 2024", x = "Datum", y = "Zeit")
pdf("Beckingen_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Beckingen_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Beckingen["Sonnenaufgang"] <- strftime(Beckingen$sr, format="%H:%M")
Beckingen["Sonnenuntergang"] <- strftime(Beckingen$ss, format="%H:%M")
write.table(Beckingen, file="Beckingen_SaSu.csv", dec=',', sep=';', row.names=FALSE)