library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Bisingen <- sunrise.set(48.3128279,8.917053, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Bisingen$sunrise
sunset <- Bisingen$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Bisingen["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Bisingen["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Bisingen["timestamp"] <- align.time(Bisingen$sunrise, 60*10)
Bisingen <- Bisingen[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Bisingen, aes(x=Bisingen$timestamp)) + geom_line(aes(y=Bisingen$sr)) + geom_line(aes(y=Bisingen$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Bisingen 2024", x = "Datum", y = "Zeit")
pdf("Bisingen_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Bisingen_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Bisingen["Sonnenaufgang"] <- strftime(Bisingen$sr, format="%H:%M")
Bisingen["Sonnenuntergang"] <- strftime(Bisingen$ss, format="%H:%M")
write.table(Bisingen, file="Bisingen_SaSu.csv", dec=',', sep=';', row.names=FALSE)