library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Grasberg <- sunrise.set(53.1813452,8.9863191, "2019/01/01", timezone="MET", num.days=370)
sunrise <- Grasberg$sunrise
sunset <- Grasberg$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Grasberg["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Grasberg["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Grasberg["timestamp"] <- align.time(Grasberg$sunrise, 60*10)
Grasberg <- Grasberg[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Grasberg, aes(x=Grasberg$timestamp)) + geom_line(aes(y=Grasberg$sr)) + geom_line(aes(y=Grasberg$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Grasberg 2019", x = "Datum", y = "Zeit")
pdf("Grasberg_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Grasberg_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Grasberg["Sonnenaufgang"] <- strftime(Grasberg$sr, format="%H:%M")
Grasberg["Sonnenuntergang"] <- strftime(Grasberg$ss, format="%H:%M")
write.table(Grasberg, file="Grasberg_SaSu.csv", dec=',', sep=';', row.names=FALSE)