library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Bern <- sunrise.set(46.947999,7.448148, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Bern$sunrise
sunset <- Bern$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Bern["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Bern["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Bern["timestamp"] <- align.time(Bern$sunrise, 60*10)
Bern <- Bern[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Bern, aes(x=Bern$timestamp)) + geom_line(aes(y=Bern$sr)) + geom_line(aes(y=Bern$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Bern 2024", x = "Datum", y = "Zeit")
pdf("Bern_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Bern_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Bern["Sonnenaufgang"] <- strftime(Bern$sr, format="%H:%M")
Bern["Sonnenuntergang"] <- strftime(Bern$ss, format="%H:%M")
write.table(Bern, file="Bern_SaSu.csv", dec=',', sep=';', row.names=FALSE)