library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Aesch <- sunrise.set(47.3373128,8.438366599999994, "2019/01/01", timezone="MET", num.days=370)
sunrise <- Aesch$sunrise
sunset <- Aesch$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Aesch["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Aesch["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Aesch["timestamp"] <- align.time(Aesch$sunrise, 60*10)
Aesch <- Aesch[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Aesch, aes(x=Aesch$timestamp)) + geom_line(aes(y=Aesch$sr)) + geom_line(aes(y=Aesch$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Aesch 2019", x = "Datum", y = "Zeit")
pdf("Aesch_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Aesch_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Aesch["Sonnenaufgang"] <- strftime(Aesch$sr, format="%H:%M")
Aesch["Sonnenuntergang"] <- strftime(Aesch$ss, format="%H:%M")
write.table(Aesch, file="Aesch_SaSu.csv", dec=',', sep=';', row.names=FALSE)