library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Beierfeld_ <- sunrise.set(50.56504049999999,12.79205049999996, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Beierfeld_$sunrise
sunset <- Beierfeld_$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Beierfeld_["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Beierfeld_["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Beierfeld_["timestamp"] <- align.time(Beierfeld_$sunrise, 60*10)
Beierfeld_ <- Beierfeld_[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Beierfeld_, aes(x=Beierfeld_$timestamp)) + geom_line(aes(y=Beierfeld_$sr)) + geom_line(aes(y=Beierfeld_$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Beierfeld_ 2024", x = "Datum", y = "Zeit")
pdf("Beierfeld__SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Beierfeld__SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Beierfeld_["Sonnenaufgang"] <- strftime(Beierfeld_$sr, format="%H:%M")
Beierfeld_["Sonnenuntergang"] <- strftime(Beierfeld_$ss, format="%H:%M")
write.table(Beierfeld_, file="Beierfeld__SaSu.csv", dec=',', sep=';', row.names=FALSE)