library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Freilassing <- sunrise.set(47.8419982,12.9728226, "2019/01/01", timezone="MET", num.days=370)
sunrise <- Freilassing$sunrise
sunset <- Freilassing$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Freilassing["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Freilassing["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Freilassing["timestamp"] <- align.time(Freilassing$sunrise, 60*10)
Freilassing <- Freilassing[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Freilassing, aes(x=Freilassing$timestamp)) + geom_line(aes(y=Freilassing$sr)) + geom_line(aes(y=Freilassing$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Freilassing 2019", x = "Datum", y = "Zeit")
pdf("Freilassing_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Freilassing_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Freilassing["Sonnenaufgang"] <- strftime(Freilassing$sr, format="%H:%M")
Freilassing["Sonnenuntergang"] <- strftime(Freilassing$ss, format="%H:%M")
write.table(Freilassing, file="Freilassing_SaSu.csv", dec=',', sep=';', row.names=FALSE)