library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Düsseldorf <- sunrise.set(51.2249429,6.7756524, "2019/01/01", timezone="MET", num.days=370)
sunrise <- Düsseldorf$sunrise
sunset <- Düsseldorf$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Düsseldorf["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Düsseldorf["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Düsseldorf["timestamp"] <- align.time(Düsseldorf$sunrise, 60*10)
Düsseldorf <- Düsseldorf[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Düsseldorf, aes(x=Düsseldorf$timestamp)) + geom_line(aes(y=Düsseldorf$sr)) + geom_line(aes(y=Düsseldorf$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Düsseldorf 2019", x = "Datum", y = "Zeit")
pdf("Düsseldorf_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Düsseldorf_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Düsseldorf["Sonnenaufgang"] <- strftime(Düsseldorf$sr, format="%H:%M")
Düsseldorf["Sonnenuntergang"] <- strftime(Düsseldorf$ss, format="%H:%M")
write.table(Düsseldorf, file="Düsseldorf_SaSu.csv", dec=',', sep=';', row.names=FALSE)