library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Köln <- sunrise.set(50.85654539343374,7.0819865162598035, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Köln$sunrise
sunset <- Köln$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Köln["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Köln["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Köln["timestamp"] <- align.time(Köln$sunrise, 60*10)
Köln <- Köln[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Köln, aes(x=Köln$timestamp)) + geom_line(aes(y=Köln$sr)) + geom_line(aes(y=Köln$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Köln 2024", x = "Datum", y = "Zeit")
pdf("Köln_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Köln_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Köln["Sonnenaufgang"] <- strftime(Köln$sr, format="%H:%M")
Köln["Sonnenuntergang"] <- strftime(Köln$ss, format="%H:%M")
write.table(Köln, file="Köln_SaSu.csv", dec=',', sep=';', row.names=FALSE)